From a729cf3a0cae979b58b9d44737cfb7a42f51d14d Mon Sep 17 00:00:00 2001 From: Pooja Babu Date: Tue, 26 Mar 2024 13:17:44 +0100 Subject: [PATCH] Modify jupyter notebooks --- .../nestml_active_dendrite_tutorial.ipynb | 222 +- .../nestml_izhikevich_tutorial.ipynb | 112 +- .../nestml_ou_noise_tutorial.ipynb | 1197 +--- ..._spike_frequency_adaptation_tutorial.ipynb | 945 ++-- .../stdp_dopa_synapse/stdp_dopa_synapse.ipynb | 1097 +++- doc/tutorials/stdp_windows/stdp_windows.ipynb | 4835 ++--------------- .../triplet_stdp_synapse.ipynb | 817 ++- pynestml/codegeneration/nest_builder.py | 4 +- .../nest_code_generator_utils.py | 7 +- 9 files changed, 2797 insertions(+), 6439 deletions(-) diff --git a/doc/tutorials/active_dendrite/nestml_active_dendrite_tutorial.ipynb b/doc/tutorials/active_dendrite/nestml_active_dendrite_tutorial.ipynb index d27f1ea35..b82c4cc12 100644 --- a/doc/tutorials/active_dendrite/nestml_active_dendrite_tutorial.ipynb +++ b/doc/tutorials/active_dendrite/nestml_active_dendrite_tutorial.ipynb @@ -18,31 +18,9 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 14, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " -- N E S T --\n", - " Copyright (C) 2004 The NEST Initiative\n", - "\n", - " Version: 3.6.0-post0.dev0\n", - " Built: Mar 21 2024 13:58:01\n", - "\n", - " This program is provided AS IS and comes with\n", - " NO WARRANTY. See the file LICENSE for details.\n", - "\n", - " Problems or suggestions?\n", - " Visit https://www.nest-simulator.org\n", - "\n", - " Type 'nest.help()' to find out more about NEST.\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib as mpl\n", @@ -51,7 +29,10 @@ "import numpy as np\n", "import os\n", "\n", - "from pynestml.codegeneration.nest_code_generator_utils import NESTCodeGeneratorUtils" + "from pynestml.codegeneration.nest_code_generator_utils import NESTCodeGeneratorUtils\n", + "\n", + "# Set the verbosity in NEST to ERROR\n", + "nest.set_verbosity(\"M_ERROR\")" ] }, { @@ -110,7 +91,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -179,38 +160,9 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 16, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING:root:PyGSL is not available. The stiffness test will be skipped.\n", - "WARNING:root:Error when importing: No module named 'pygsl'\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " -- N E S T --\n", - " Copyright (C) 2004 The NEST Initiative\n", - "\n", - " Version: 3.6.0-post0.dev0\n", - " Built: Mar 21 2024 13:58:01\n", - "\n", - " This program is provided AS IS and comes with\n", - " NO WARRANTY. See the file LICENSE for details.\n", - "\n", - " Problems or suggestions?\n", - " Visit https://www.nest-simulator.org\n", - "\n", - " Type 'nest.help()' to find out more about NEST.\n", - "\n" - ] - }, { "name": "stderr", "output_type": "stream", @@ -236,7 +188,7 @@ "-- Detecting CXX compile features - done\n", "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", - "\u001b[0mnestml__module Configuration Summary\u001b[0m\n", + "\u001b[0mactive_dend_module Configuration Summary\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", @@ -248,15 +200,15 @@ "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mYou can now build and install 'nestml__module' using\u001b[0m\n", + "\u001b[0mYou can now build and install 'active_dend_module' using\u001b[0m\n", "\u001b[0m make\u001b[0m\n", "\u001b[0m make install\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mThe library file libnestml__module.so will be installed to\u001b[0m\n", - "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_vsu363gm\u001b[0m\n", + "\u001b[0mThe library file libactive_dend_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_fq3h0jb8\u001b[0m\n", "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", - "\u001b[0m (nestml__module) Install (in SLI)\u001b[0m\n", - "\u001b[0m nest.Install(nestml__module) (in PyNEST)\u001b[0m\n", + "\u001b[0m (active_dend_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(active_dend_module) (in PyNEST)\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -268,12 +220,12 @@ " information run \"cmake --help-policy CMP0000\".\n", "This warning is for project developers. Use -Wno-dev to suppress it.\n", "\u001b[0m\n", - "-- Configuring done (0.8s)\n", + "-- Configuring done (0.7s)\n", "-- Generating done (0.0s)\n", "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/active_dendrite/target\n", - "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/nestml__module_module.dir/nestml__module.o\u001b[0m\n", - "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/nestml__module_module.dir/iaf_psc_exp_active_dendrite_nestml.o\u001b[0m\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/active_dendrite/target/nestml__module.cpp:31:\n", + "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/active_dend_module_module.dir/active_dend_module.o\u001b[0m\n", + "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/active_dend_module_module.dir/iaf_psc_exp_active_dendrite_nestml.o\u001b[0m\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/active_dendrite/target/active_dend_module.cpp:31:\n", "/Users/pooja/nestml/master/doc/tutorials/active_dendrite/target/iaf_psc_exp_active_dendrite_nestml.h:230:17: warning: 'iaf_psc_exp_active_dendrite_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", " inline double get_C_m() const\n", " ^\n", @@ -295,18 +247,19 @@ " ^\n", "1 warning generated.\n", "3 warnings generated.\n", - "[100%] \u001b[32m\u001b[1mLinking CXX shared module nestml__module.so\u001b[0m\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module active_dend_module.so\u001b[0m\n", "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", - "[100%] Built target nestml__module_module\n", - "[100%] Built target nestml__module_module\n", + "[100%] Built target active_dend_module_module\n", + "[100%] Built target active_dend_module_module\n", "\u001b[36mInstall the project...\u001b[0m\n", "-- Install configuration: \"\"\n", - "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_vsu363gm/nestml__module.so\n" + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_fq3h0jb8/active_dend_module.so\n" ] } ], "source": [ "module_name, neuron_name = NESTCodeGeneratorUtils.generate_code_for(nestml_active_dend_model,\n", + " module_name=\"active_dend_module\",\n", " logging_level=\"ERROR\") # try \"INFO\" or \"DEBUG\" for more debug information" ] }, @@ -321,7 +274,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -415,35 +368,14 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 18, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Mar 22 12:36:44 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 22 12:36:44 NodeManager::prepare_nodes [Info]: \n", - " Preparing 5 nodes for simulation.\n", - "\n", - "Mar 22 12:36:44 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 5\n", - " Simulation time (ms): 100\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 22 12:36:44 SimulationManager::run [Info]: \n", - " Simulation finished.\n" - ] - }, { "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/ipykernel_87886/1260340709.py:84: UserWarning:FigureCanvasAgg is non-interactive, and thus cannot be shown\n" + "/var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/ipykernel_65032/1260340709.py:84: UserWarning:FigureCanvasAgg is non-interactive, and thus cannot be shown\n" ] }, { @@ -474,35 +406,14 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 19, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Mar 22 12:36:50 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 22 12:36:50 NodeManager::prepare_nodes [Info]: \n", - " Preparing 5 nodes for simulation.\n", - "\n", - "Mar 22 12:36:50 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 5\n", - " Simulation time (ms): 100\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 22 12:36:50 SimulationManager::run [Info]: \n", - " Simulation finished.\n" - ] - }, { "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/ipykernel_87886/1260340709.py:84: UserWarning:FigureCanvasAgg is non-interactive, and thus cannot be shown\n" + "/var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/ipykernel_65032/1260340709.py:84: UserWarning:FigureCanvasAgg is non-interactive, and thus cannot be shown\n" ] }, { @@ -585,7 +496,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -661,30 +572,9 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 21, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " -- N E S T --\n", - " Copyright (C) 2004 The NEST Initiative\n", - "\n", - " Version: 3.6.0-post0.dev0\n", - " Built: Mar 21 2024 13:58:01\n", - "\n", - " This program is provided AS IS and comes with\n", - " NO WARRANTY. See the file LICENSE for details.\n", - "\n", - " Problems or suggestions?\n", - " Visit https://www.nest-simulator.org\n", - "\n", - " Type 'nest.help()' to find out more about NEST.\n", - "\n" - ] - }, { "name": "stderr", "output_type": "stream", @@ -710,7 +600,7 @@ "-- Detecting CXX compile features - done\n", "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", - "\u001b[0mnestml__module Configuration Summary\u001b[0m\n", + "\u001b[0mactive_dend_reset_module Configuration Summary\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", @@ -722,15 +612,15 @@ "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mYou can now build and install 'nestml__module' using\u001b[0m\n", + "\u001b[0mYou can now build and install 'active_dend_reset_module' using\u001b[0m\n", "\u001b[0m make\u001b[0m\n", "\u001b[0m make install\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mThe library file libnestml__module.so will be installed to\u001b[0m\n", - "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_zr3r7uem\u001b[0m\n", + "\u001b[0mThe library file libactive_dend_reset_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_qj4h6poj\u001b[0m\n", "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", - "\u001b[0m (nestml__module) Install (in SLI)\u001b[0m\n", - "\u001b[0m nest.Install(nestml__module) (in PyNEST)\u001b[0m\n", + "\u001b[0m (active_dend_reset_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(active_dend_reset_module) (in PyNEST)\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -745,9 +635,9 @@ "-- Configuring done (0.6s)\n", "-- Generating done (0.0s)\n", "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/active_dendrite/target\n", - "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/nestml__module_module.dir/iaf_psc_exp_active_dendrite_resetting_nestml.o\u001b[0m\n", - "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/nestml__module_module.dir/nestml__module.o\u001b[0m\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/active_dendrite/target/nestml__module.cpp:31:\n", + "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/active_dend_reset_module_module.dir/active_dend_reset_module.o\u001b[0m\n", + "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/active_dend_reset_module_module.dir/iaf_psc_exp_active_dendrite_resetting_nestml.o\u001b[0m\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/active_dendrite/target/active_dend_reset_module.cpp:31:\n", "/Users/pooja/nestml/master/doc/tutorials/active_dendrite/target/iaf_psc_exp_active_dendrite_resetting_nestml.h:242:17: warning: 'iaf_psc_exp_active_dendrite_resetting_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", " inline double get_C_m() const\n", " ^\n", @@ -769,18 +659,19 @@ " ^\n", "1 warning generated.\n", "3 warnings generated.\n", - "[100%] \u001b[32m\u001b[1mLinking CXX shared module nestml__module.so\u001b[0m\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module active_dend_reset_module.so\u001b[0m\n", "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", - "[100%] Built target nestml__module_module\n", - "[100%] Built target nestml__module_module\n", + "[100%] Built target active_dend_reset_module_module\n", + "[100%] Built target active_dend_reset_module_module\n", "\u001b[36mInstall the project...\u001b[0m\n", "-- Install configuration: \"\"\n", - "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_zr3r7uem/nestml__module.so\n" + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_qj4h6poj/active_dend_reset_module.so\n" ] } ], "source": [ "module_name, neuron_name = NESTCodeGeneratorUtils.generate_code_for(nestml_active_dend_reset_model,\n", + " module_name=\"active_dend_reset_module\",\n", " logging_level=\"ERROR\") # try \"INFO\" or \"DEBUG\" for more debug information" ] }, @@ -793,35 +684,14 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 22, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Mar 22 12:37:13 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 22 12:37:13 NodeManager::prepare_nodes [Info]: \n", - " Preparing 5 nodes for simulation.\n", - "\n", - "Mar 22 12:37:13 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 5\n", - " Simulation time (ms): 100\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 22 12:37:13 SimulationManager::run [Info]: \n", - " Simulation finished.\n" - ] - }, { "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/ipykernel_87886/1260340709.py:84: UserWarning:FigureCanvasAgg is non-interactive, and thus cannot be shown\n" + "/var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/ipykernel_65032/1260340709.py:84: UserWarning:FigureCanvasAgg is non-interactive, and thus cannot be shown\n" ] }, { diff --git a/doc/tutorials/izhikevich/nestml_izhikevich_tutorial.ipynb b/doc/tutorials/izhikevich/nestml_izhikevich_tutorial.ipynb index 01e229ca0..6db636d2b 100644 --- a/doc/tutorials/izhikevich/nestml_izhikevich_tutorial.ipynb +++ b/doc/tutorials/izhikevich/nestml_izhikevich_tutorial.ipynb @@ -34,7 +34,7 @@ " Copyright (C) 2004 The NEST Initiative\n", "\n", " Version: 3.6.0-post0.dev0\n", - " Built: Mar 21 2024 13:58:01\n", + " Built: Mar 26 2024 10:08:21\n", "\n", " This program is provided AS IS and comes with\n", " NO WARRANTY. See the file LICENSE for details.\n", @@ -48,7 +48,7 @@ } ], "source": [ - "%matplotlib inline\n", + "# %matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import nest\n", "import numpy as np\n", @@ -117,17 +117,9 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING:root:PyGSL is not available. The stiffness test will be skipped.\n", - "WARNING:root:Error when importing: No module named 'pygsl'\n" - ] - }, { "name": "stdout", "output_type": "stream", @@ -137,7 +129,7 @@ " Copyright (C) 2004 The NEST Initiative\n", "\n", " Version: 3.6.0-post0.dev0\n", - " Built: Mar 21 2024 13:58:01\n", + " Built: Mar 26 2024 10:08:21\n", "\n", " This program is provided AS IS and comes with\n", " NO WARRANTY. See the file LICENSE for details.\n", @@ -167,7 +159,7 @@ "-- Detecting CXX compile features - done\n", "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", - "\u001b[0mnestml__module Configuration Summary\u001b[0m\n", + "\u001b[0mizhikevich_module Configuration Summary\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", @@ -179,15 +171,15 @@ "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mYou can now build and install 'nestml__module' using\u001b[0m\n", + "\u001b[0mYou can now build and install 'izhikevich_module' using\u001b[0m\n", "\u001b[0m make\u001b[0m\n", "\u001b[0m make install\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mThe library file libnestml__module.so will be installed to\u001b[0m\n", - "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_vy0vybop\u001b[0m\n", + "\u001b[0mThe library file libizhikevich_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_c_3ls96l\u001b[0m\n", "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", - "\u001b[0m (nestml__module) Install (in SLI)\u001b[0m\n", - "\u001b[0m nest.Install(nestml__module) (in PyNEST)\u001b[0m\n", + "\u001b[0m (izhikevich_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(izhikevich_module) (in PyNEST)\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -199,11 +191,11 @@ " information run \"cmake --help-policy CMP0000\".\n", "This warning is for project developers. Use -Wno-dev to suppress it.\n", "\u001b[0m\n", - "-- Configuring done (1.2s)\n", + "-- Configuring done (0.7s)\n", "-- Generating done (0.0s)\n", "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/izhikevich/target\n", - "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/nestml__module_module.dir/izhikevich_tutorial_nestml.o\u001b[0m\n", - "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/nestml__module_module.dir/nestml__module.o\u001b[0m\n", + "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/izhikevich_module_module.dir/izhikevich_module.o\u001b[0m\n", + "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/izhikevich_module_module.dir/izhikevich_tutorial_nestml.o\u001b[0m\n", "/Users/pooja/nestml/master/doc/tutorials/izhikevich/target/izhikevich_tutorial_nestml.cpp:179:16: warning: unused variable '__resolution' [-Wunused-variable]\n", " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " ^\n", @@ -214,20 +206,21 @@ " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " ^\n", "3 warnings generated.\n", - "[100%] \u001b[32m\u001b[1mLinking CXX shared module nestml__module.so\u001b[0m\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module izhikevich_module.so\u001b[0m\n", "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", - "[100%] Built target nestml__module_module\n", - "[100%] Built target nestml__module_module\n", + "[100%] Built target izhikevich_module_module\n", + "[100%] Built target izhikevich_module_module\n", "\u001b[36mInstall the project...\u001b[0m\n", "-- Install configuration: \"\"\n", - "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_vy0vybop/nestml__module.so\n" + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_c_3ls96l/izhikevich_module.so\n" ] } ], "source": [ "# generate and build code\n", "module_name, neuron_model_name = \\\n", - " NESTCodeGeneratorUtils.generate_code_for(\"izhikevich_solution.nestml\")" + " NESTCodeGeneratorUtils.generate_code_for(\"izhikevich_solution.nestml\",\n", + " module_name=\"izhikevich_module\")" ] }, { @@ -249,14 +242,35 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Mar 26 14:32:10 Install [Info]: \n", + " loaded module izhikevich_module\n", + "\n", + "Mar 26 14:32:10 NodeManager::prepare_nodes [Info]: \n", + " Preparing 4 nodes for simulation.\n", + "\n", + "Mar 26 14:32:10 SimulationManager::start_updating_ [Info]: \n", + " Number of local nodes: 4\n", + " Simulation time (ms): 250\n", + " Number of OpenMP threads: 1\n", + " Not using MPI\n", + "\n", + "Mar 26 14:32:10 SimulationManager::run [Info]: \n", + " Simulation finished.\n" + ] + }, { "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/ipykernel_86106/1353168583.py:33: UserWarning:FigureCanvasAgg is non-interactive, and thus cannot be shown\n" + "/var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/ipykernel_60089/1245292433.py:33: UserWarning:FigureCanvasAgg is non-interactive, and thus cannot be shown\n" ] }, { @@ -271,7 +285,7 @@ } ], "source": [ - "nest.set_verbosity(\"M_WARNING\")\n", + "nest.set_verbosity(\"M_ALL\")\n", "nest.ResetKernel()\n", "\n", "# load dynamic library (NEST extension module) into NEST kernel\n", @@ -306,6 +320,39 @@ "fig.show()" ] }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Mar 26 14:32:18 Install [Info]: \n", + " loaded module izhikevich_module\n" + ] + }, + { + "data": { + "text/plain": [ + "('izhikevich_module',)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "nest.ResetKernel()\n", + "nest.Install(module_name)\n", + "# nest.Models()\n", + "os.environ[\"DYLD_LIBRARY_PATH\"]\n", + "nest.get(\"modules\")" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -336,6 +383,13 @@ "\n", "You should have received a copy of the GNU General Public License along with NEST. If not, see .\n" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/doc/tutorials/ornstein_uhlenbeck_noise/nestml_ou_noise_tutorial.ipynb b/doc/tutorials/ornstein_uhlenbeck_noise/nestml_ou_noise_tutorial.ipynb index 41d4f7854..6eb7155fa 100644 --- a/doc/tutorials/ornstein_uhlenbeck_noise/nestml_ou_noise_tutorial.ipynb +++ b/doc/tutorials/ornstein_uhlenbeck_noise/nestml_ou_noise_tutorial.ipynb @@ -11,31 +11,9 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 18, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " -- N E S T --\n", - " Copyright (C) 2004 The NEST Initiative\n", - "\n", - " Version: 3.6.0-post0.dev0\n", - " Built: Mar 21 2024 13:58:01\n", - "\n", - " This program is provided AS IS and comes with\n", - " NO WARRANTY. See the file LICENSE for details.\n", - "\n", - " Problems or suggestions?\n", - " Visit https://www.nest-simulator.org\n", - "\n", - " Type 'nest.help()' to find out more about NEST.\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib.pyplot as plt\n", @@ -43,7 +21,10 @@ "import numpy as np\n", "import os\n", "\n", - "from pynestml.codegeneration.nest_code_generator_utils import NESTCodeGeneratorUtils" + "from pynestml.codegeneration.nest_code_generator_utils import NESTCodeGeneratorUtils\n", + "\n", + "# Set the verbosity in NEST to ERROR\n", + "nest.set_verbosity(\"M_ERROR\")" ] }, { @@ -82,7 +63,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -116,36 +97,13 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 20, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "WARNING:root:PyGSL is not available. The stiffness test will be skipped.\n", - "WARNING:root:Error when importing: No module named 'pygsl'\n" - ] - }, { "name": "stdout", "output_type": "stream", "text": [ - "\n", - " -- N E S T --\n", - " Copyright (C) 2004 The NEST Initiative\n", - "\n", - " Version: 3.6.0-post0.dev0\n", - " Built: Mar 21 2024 13:58:01\n", - "\n", - " This program is provided AS IS and comes with\n", - " NO WARRANTY. See the file LICENSE for details.\n", - "\n", - " Problems or suggestions?\n", - " Visit https://www.nest-simulator.org\n", - "\n", - " Type 'nest.help()' to find out more about NEST.\n", - "\n", "[12,ornstein_uhlenbeck_noise_nestml, WARNING, [2:0;16:0]]: Input block not defined!\n", "[13,ornstein_uhlenbeck_noise_nestml, WARNING, [2:0;16:0]]: Output block not defined!\n", "[17,ornstein_uhlenbeck_noise_nestml, WARNING, [2:0;16:0]]: Input block not defined!\n", @@ -164,7 +122,7 @@ "-- Detecting CXX compile features - done\n", "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", - "\u001b[0mnestml__module Configuration Summary\u001b[0m\n", + "\u001b[0mnestml_ou_module Configuration Summary\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", @@ -176,15 +134,15 @@ "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mYou can now build and install 'nestml__module' using\u001b[0m\n", + "\u001b[0mYou can now build and install 'nestml_ou_module' using\u001b[0m\n", "\u001b[0m make\u001b[0m\n", "\u001b[0m make install\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mThe library file libnestml__module.so will be installed to\u001b[0m\n", - "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_oncyf8_r\u001b[0m\n", + "\u001b[0mThe library file libnestml_ou_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_kc4zffnq\u001b[0m\n", "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", - "\u001b[0m (nestml__module) Install (in SLI)\u001b[0m\n", - "\u001b[0m nest.Install(nestml__module) (in PyNEST)\u001b[0m\n", + "\u001b[0m (nestml_ou_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(nestml_ou_module) (in PyNEST)\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -196,11 +154,11 @@ " information run \"cmake --help-policy CMP0000\".\n", "This warning is for project developers. Use -Wno-dev to suppress it.\n", "\u001b[0m\n", - "-- Configuring done (4.6s)\n", + "-- Configuring done (0.7s)\n", "-- Generating done (0.0s)\n", "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/ornstein_uhlenbeck_noise/target\n", - "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/nestml__module_module.dir/nestml__module.o\u001b[0m\n", - "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/nestml__module_module.dir/ornstein_uhlenbeck_noise_nestml.o\u001b[0m\n", + "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/nestml_ou_module_module.dir/nestml_ou_module.o\u001b[0m\n", + "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/nestml_ou_module_module.dir/ornstein_uhlenbeck_noise_nestml.o\u001b[0m\n", "/Users/pooja/nestml/master/doc/tutorials/ornstein_uhlenbeck_noise/target/ornstein_uhlenbeck_noise_nestml.cpp:154:16: warning: unused variable '__resolution' [-Wunused-variable]\n", " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " ^\n", @@ -208,20 +166,21 @@ " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", " ^\n", "2 warnings generated.\n", - "[100%] \u001b[32m\u001b[1mLinking CXX shared module nestml__module.so\u001b[0m\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module nestml_ou_module.so\u001b[0m\n", "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", - "[100%] Built target nestml__module_module\n", - "[100%] Built target nestml__module_module\n", + "[100%] Built target nestml_ou_module_module\n", + "[100%] Built target nestml_ou_module_module\n", "\u001b[36mInstall the project...\u001b[0m\n", "-- Install configuration: \"\"\n", - "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_oncyf8_r/nestml__module.so\n" + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_kc4zffnq/nestml_ou_module.so\n" ] } ], "source": [ "# generate and build code\n", "module_name, neuron_model_name_adapt_curr = \\\n", - " NESTCodeGeneratorUtils.generate_code_for(nestml_ou_model)" + " NESTCodeGeneratorUtils.generate_code_for(nestml_ou_model,\n", + " module_name=\"nestml_ou_module\")" ] }, { @@ -235,11 +194,11 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ - "def evaluate_ou_process(neuron_model_name: str, h: float=.1, t_sim:float=100., neuron_parms=None, title=None, plot=True):\n", + "def evaluate_ou_process(neuron_model_name: str, module_name: str, h: float=.1, t_sim:float=100., neuron_parms=None, title=None, plot=True):\n", " \"\"\"\n", " h : float\n", " timestep in ms\n", @@ -291,46 +250,9 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 22, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Mar 25 14:53:59 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:53:59 correlation_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:53:59 correlomatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:53:59 correlospinmatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.1 to 1 ms\n", - "\n", - "Mar 25 14:53:59 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:53:59 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 1 ms.\n", - "\n", - "Mar 25 14:53:59 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:53:59 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 1000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:53:59 SimulationManager::run [Info]: \n", - " Simulation finished.\n" - ] - }, { "data": { "image/png": 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", @@ -344,6 +266,7 @@ ], "source": [ "timevec, U = evaluate_ou_process(neuron_model_name_adapt_curr,\n", + " module_name,\n", " h=1.,\n", " t_sim=1000.,\n", " neuron_parms={\"U\" : -2500.,\n", @@ -370,7 +293,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 23, "metadata": {}, "outputs": [ { @@ -378,1011 +301,111 @@ "output_type": "stream", "text": [ "For h = 0.01, tau_noise = 10.0, sigma_noise = 0.0\n", - "\n", - "Mar 25 14:53:59 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:53:59 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:53:59 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.01 ms.\n", - "\n", - "Mar 25 14:53:59 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:53:59 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:53:59 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 0.0\n", "Expected variance: 0.0\n", "For h = 0.01, tau_noise = 10.0, sigma_noise = 10.0\n", - "\n", - "Mar 25 14:54:00 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:00 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:00 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.01 ms.\n", - "\n", - "Mar 25 14:54:00 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:00 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:00 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 102.21030336065829\n", "Expected variance: 100.0\n", "For h = 0.01, tau_noise = 10.0, sigma_noise = 100.0\n", - "\n", - "Mar 25 14:54:00 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:00 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:00 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.01 ms.\n", - "\n", - "Mar 25 14:54:00 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:00 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:00 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 10221.030336065825\n", "Expected variance: 10000.0\n", "For h = 0.01, tau_noise = 10.0, sigma_noise = 1000.0\n", - "\n", - "Mar 25 14:54:00 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:00 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:00 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.01 ms.\n", - "\n", - "Mar 25 14:54:00 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:00 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:01 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 1022103.0336065828\n", "Expected variance: 1000000.0\n", "For h = 0.01, tau_noise = 100.0, sigma_noise = 0.0\n", - "\n", - "Mar 25 14:54:01 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:01 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:01 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.01 ms.\n", - "\n", - "Mar 25 14:54:01 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:01 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:01 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 0.0\n", "Expected variance: 0.0\n", "For h = 0.01, tau_noise = 100.0, sigma_noise = 10.0\n", - "\n", - "Mar 25 14:54:01 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:01 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:01 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.01 ms.\n", - "\n", - "Mar 25 14:54:01 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:01 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:02 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 114.93624532212093\n", "Expected variance: 100.0\n", "For h = 0.01, tau_noise = 100.0, sigma_noise = 100.0\n", - "\n", - "Mar 25 14:54:02 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:02 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:02 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.01 ms.\n", - "\n", - "Mar 25 14:54:02 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:02 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:02 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 11493.62453221208\n", "Expected variance: 10000.0\n", "For h = 0.01, tau_noise = 100.0, sigma_noise = 1000.0\n", - "\n", - "Mar 25 14:54:02 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:02 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:02 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.01 ms.\n", - "\n", - "Mar 25 14:54:02 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:02 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:02 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 1149362.453221211\n", "Expected variance: 1000000.0\n", "For h = 0.01, tau_noise = 1000.0, sigma_noise = 0.0\n", - "\n", - "Mar 25 14:54:03 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:03 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:03 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.01 ms.\n", - "\n", - "Mar 25 14:54:03 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:03 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:03 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 0.0\n", "Expected variance: 0.0\n", "For h = 0.01, tau_noise = 1000.0, sigma_noise = 10.0\n", - "\n", - "Mar 25 14:54:03 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:03 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:03 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.01 ms.\n", - "\n", - "Mar 25 14:54:03 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:03 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:03 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 94.22834590929104\n", "Expected variance: 100.0\n", "For h = 0.01, tau_noise = 1000.0, sigma_noise = 100.0\n", - "\n", - "Mar 25 14:54:03 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:03 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:03 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.01 ms.\n", - "\n", - "Mar 25 14:54:03 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:03 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:04 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 9422.834590928938\n", "Expected variance: 10000.0\n", "For h = 0.01, tau_noise = 1000.0, sigma_noise = 1000.0\n", - "\n", - "Mar 25 14:54:04 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:04 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:04 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.01 ms.\n", - "\n", - "Mar 25 14:54:04 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:04 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:04 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 942283.4590929038\n", "Expected variance: 1000000.0\n", "For h = 0.1, tau_noise = 10.0, sigma_noise = 0.0\n", - "\n", - "Mar 25 14:54:04 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:04 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:04 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.1 ms.\n", - "\n", - "Mar 25 14:54:04 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:04 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:04 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 0.0\n", "Expected variance: 0.0\n", "For h = 0.1, tau_noise = 10.0, sigma_noise = 10.0\n", - "\n", - "Mar 25 14:54:04 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:04 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:04 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.1 ms.\n", - "\n", - "Mar 25 14:54:04 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:04 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:04 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 99.44588939205474\n", "Expected variance: 100.0\n", "For h = 0.1, tau_noise = 10.0, sigma_noise = 100.0\n", - "\n", - "Mar 25 14:54:04 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:04 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:04 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.1 ms.\n", - "\n", - "Mar 25 14:54:04 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:04 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:04 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 9944.588939205476\n", "Expected variance: 10000.0\n", "For h = 0.1, tau_noise = 10.0, sigma_noise = 1000.0\n", - "\n", - "Mar 25 14:54:04 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:04 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:04 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.1 ms.\n", - "\n", - "Mar 25 14:54:04 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:04 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 994458.8939205472\n", "Expected variance: 1000000.0\n", "For h = 0.1, tau_noise = 100.0, sigma_noise = 0.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 0.0\n", "Expected variance: 0.0\n", "For h = 0.1, tau_noise = 100.0, sigma_noise = 10.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 96.98034018669549\n", "Expected variance: 100.0\n", "For h = 0.1, tau_noise = 100.0, sigma_noise = 100.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 9698.034018669543\n", "Expected variance: 10000.0\n", "For h = 0.1, tau_noise = 100.0, sigma_noise = 1000.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 969803.4018669543\n", "Expected variance: 1000000.0\n", "For h = 0.1, tau_noise = 1000.0, sigma_noise = 0.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 0.0\n", "Expected variance: 0.0\n", "For h = 0.1, tau_noise = 1000.0, sigma_noise = 10.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 137.92623396537726\n", "Expected variance: 100.0\n", "For h = 0.1, tau_noise = 1000.0, sigma_noise = 100.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 13792.623396537845\n", "Expected variance: 10000.0\n", "For h = 0.1, tau_noise = 1000.0, sigma_noise = 1000.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 0.1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 1379262.33965378\n", "Expected variance: 1000000.0\n", "For h = 1.0, tau_noise = 10.0, sigma_noise = 0.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 correlation_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlomatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlospinmatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.1 to 1 ms\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 0.0\n", "Expected variance: 0.0\n", "For h = 1.0, tau_noise = 10.0, sigma_noise = 10.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", "Actual variance: 102.32554029453819\n", "Expected variance: 100.0\n", "For h = 1.0, tau_noise = 10.0, sigma_noise = 100.0\n", - "\n", - "Mar 25 14:54:05 correlation_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlomatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlospinmatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.1 to 1 ms\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 correlation_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlomatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlospinmatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.1 to 1 ms\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 10232.554029453817\n", "Expected variance: 10000.0\n", "For h = 1.0, tau_noise = 10.0, sigma_noise = 1000.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 correlation_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlomatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlospinmatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.1 to 1 ms\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 1023255.4029453819\n", "Expected variance: 1000000.0\n", "For h = 1.0, tau_noise = 100.0, sigma_noise = 0.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", "Actual variance: 0.0\n", "Expected variance: 0.0\n", "For h = 1.0, tau_noise = 100.0, sigma_noise = 10.0\n", - "\n", - "Mar 25 14:54:05 correlation_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlomatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlospinmatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.1 to 1 ms\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 correlation_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlomatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlospinmatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.1 to 1 ms\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 102.5676581333639\n", "Expected variance: 100.0\n", "For h = 1.0, tau_noise = 100.0, sigma_noise = 100.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 correlation_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlomatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlospinmatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.1 to 1 ms\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 10256.76581333639\n", "Expected variance: 10000.0\n", "For h = 1.0, tau_noise = 100.0, sigma_noise = 1000.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 correlation_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlomatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlospinmatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.1 to 1 ms\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 1025676.581333639\n", "Expected variance: 1000000.0\n", "For h = 1.0, tau_noise = 1000.0, sigma_noise = 0.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 correlation_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlomatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlospinmatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.1 to 1 ms\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 0.0\n", "Expected variance: 0.0\n", "For h = 1.0, tau_noise = 1000.0, sigma_noise = 10.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 correlation_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlomatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlospinmatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.1 to 1 ms\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 65.70587968208686\n", "Expected variance: 100.0\n", "For h = 1.0, tau_noise = 1000.0, sigma_noise = 100.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 correlation_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlomatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlospinmatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.1 to 1 ms\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 6570.587968208678\n", "Expected variance: 10000.0\n", "For h = 1.0, tau_noise = 1000.0, sigma_noise = 1000.0\n", - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 correlation_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlomatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlospinmatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.1 to 1 ms\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "Actual variance: 657058.7968208689\n", "Expected variance: 1000000.0\n" ] @@ -1403,6 +426,7 @@ " print(\"For h = \" + str(_h) + \", tau_noise = \" + str(_tau_noise) + \", sigma_noise = \" + str(_sigma_noise))\n", " c = (_sigma_noise * np.sqrt(2 / _tau_noise))**2\n", " timevec, U = evaluate_ou_process(neuron_model_name_adapt_curr,\n", + " module_name,\n", " h=_h,\n", " t_sim=25000.,\n", " neuron_parms={\"U\" : 0.,\n", @@ -1434,46 +458,9 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 24, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Mar 25 14:54:05 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:54:05 correlation_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlomatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.5 to 5 ms\n", - "\n", - "Mar 25 14:54:05 correlospinmatrix_detector [Info]: \n", - " Default for delta_tau changed from 0.1 to 1 ms\n", - "\n", - "Mar 25 14:54:05 ornstein_uhlenbeck_noise_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 25 14:54:05 SimulationManager::set_status [Info]: \n", - " Temporal resolution changed from 0.1 to 1 ms.\n", - "\n", - "Mar 25 14:54:05 NodeManager::prepare_nodes [Info]: \n", - " Preparing 2 nodes for simulation.\n", - "\n", - "Mar 25 14:54:05 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 2\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:54:05 SimulationManager::run [Info]: \n", - " Simulation finished.\n" - ] - }, { "data": { "image/png": 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", @@ -1487,6 +474,7 @@ ], "source": [ "timevec, U = evaluate_ou_process(neuron_model_name_adapt_curr,\n", + " module_name,\n", " h=_h,\n", " t_sim=10000.,\n", " neuron_parms={\"U\" : 0.,\n", @@ -1498,7 +486,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 25, "metadata": {}, "outputs": [ { @@ -1538,7 +526,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 26, "metadata": {}, "outputs": [], "source": [ @@ -1588,28 +576,13 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "\n", - " -- N E S T --\n", - " Copyright (C) 2004 The NEST Initiative\n", - "\n", - " Version: 3.6.0-post0.dev0\n", - " Built: Mar 21 2024 13:58:01\n", - "\n", - " This program is provided AS IS and comes with\n", - " NO WARRANTY. See the file LICENSE for details.\n", - "\n", - " Problems or suggestions?\n", - " Visit https://www.nest-simulator.org\n", - "\n", - " Type 'nest.help()' to find out more about NEST.\n", - "\n", "[14,iaf_psc_exp_nestml, WARNING, [33:18;33:103]]: Implicit casting from (compatible) type 'pA' to 'real'.\n" ] }, @@ -1640,7 +613,7 @@ "-- Detecting CXX compile features - done\n", "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", - "\u001b[0mnestml__module Configuration Summary\u001b[0m\n", + "\u001b[0miaf_psc_exp_ou_module Configuration Summary\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", @@ -1652,15 +625,15 @@ "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mYou can now build and install 'nestml__module' using\u001b[0m\n", + "\u001b[0mYou can now build and install 'iaf_psc_exp_ou_module' using\u001b[0m\n", "\u001b[0m make\u001b[0m\n", "\u001b[0m make install\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mThe library file libnestml__module.so will be installed to\u001b[0m\n", - "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_k2k3kpkn\u001b[0m\n", + "\u001b[0mThe library file libiaf_psc_exp_ou_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_csdcfkxn\u001b[0m\n", "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", - "\u001b[0m (nestml__module) Install (in SLI)\u001b[0m\n", - "\u001b[0m nest.Install(nestml__module) (in PyNEST)\u001b[0m\n", + "\u001b[0m (iaf_psc_exp_ou_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(iaf_psc_exp_ou_module) (in PyNEST)\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -1675,9 +648,9 @@ "-- Configuring done (0.7s)\n", "-- Generating done (0.0s)\n", "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/ornstein_uhlenbeck_noise/target\n", - "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/nestml__module_module.dir/nestml__module.o\u001b[0m\n", - "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/nestml__module_module.dir/iaf_psc_exp_nestml.o\u001b[0m\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/ornstein_uhlenbeck_noise/target/nestml__module.cpp:31:\n", + "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/iaf_psc_exp_ou_module_module.dir/iaf_psc_exp_ou_module.o\u001b[0m\n", + "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/iaf_psc_exp_ou_module_module.dir/iaf_psc_exp_nestml.o\u001b[0m\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/ornstein_uhlenbeck_noise/target/iaf_psc_exp_ou_module.cpp:31:\n", "/Users/pooja/nestml/master/doc/tutorials/ornstein_uhlenbeck_noise/target/iaf_psc_exp_nestml.h:244:17: warning: 'iaf_psc_exp_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", " inline double get_C_m() const\n", " ^\n", @@ -1699,20 +672,21 @@ " ^\n", "1 warning generated.\n", "3 warnings generated.\n", - "[100%] \u001b[32m\u001b[1mLinking CXX shared module nestml__module.so\u001b[0m\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module iaf_psc_exp_ou_module.so\u001b[0m\n", "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", - "[100%] Built target nestml__module_module\n", - "[100%] Built target nestml__module_module\n", + "[100%] Built target iaf_psc_exp_ou_module_module\n", + "[100%] Built target iaf_psc_exp_ou_module_module\n", "\u001b[36mInstall the project...\u001b[0m\n", "-- Install configuration: \"\"\n", - "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_k2k3kpkn/nestml__module.so\n" + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_csdcfkxn/iaf_psc_exp_ou_module.so\n" ] } ], "source": [ "# generate and build code\n", - "module_name, neuron_model_name = \\\n", - " NESTCodeGeneratorUtils.generate_code_for(nestml_iaf_psc_exp_model)" + "module_name_ou, neuron_model_name = \\\n", + " NESTCodeGeneratorUtils.generate_code_for(nestml_iaf_psc_exp_model,\n", + " module_name=\"iaf_psc_exp_ou_module\")" ] }, { @@ -1724,7 +698,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 28, "metadata": {}, "outputs": [], "source": [ @@ -1786,30 +760,9 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 29, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Mar 25 14:55:20 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:55:20 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 25 14:55:20 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 300\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:55:20 SimulationManager::run [Info]: \n", - " Simulation finished.\n" - ] - }, { "data": { "image/png": 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", @@ -1822,7 +775,7 @@ } ], "source": [ - "spike_times = evaluate_neuron(neuron_model_name, module_name, mu=300, sigma=0.)" + "spike_times = evaluate_neuron(neuron_model_name, module_name_ou, mu=300, sigma=0.)" ] }, { @@ -1834,30 +787,9 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 30, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Mar 25 14:55:28 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:55:28 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 25 14:55:28 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 300\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:55:28 SimulationManager::run [Info]: \n", - " Simulation finished.\n" - ] - }, { "data": { "image/png": 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", @@ -1870,7 +802,7 @@ } ], "source": [ - "spike_times = evaluate_neuron(neuron_model_name, module_name, mu=300, sigma=200)\n", + "spike_times = evaluate_neuron(neuron_model_name, module_name_ou, mu=300, sigma=200)\n", "assert spike_times.size > 0" ] }, @@ -1883,28 +815,13 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 31, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "\n", - "Mar 25 14:55:49 Install [Info]: \n", - " loaded module nestml__module\n", - "\n", - "Mar 25 14:55:49 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 25 14:55:49 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 25000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 25 14:55:49 SimulationManager::run [Info]: \n", - " Simulation finished.\n", "265 spikes recorded\n", "Mean ISI: 94.38219696969698\n", "ISI std. dev.: 88.8518443884758\n" @@ -1923,7 +840,7 @@ ], "source": [ "spike_times = evaluate_neuron(neuron_model_name,\n", - " module_name,\n", + " module_name_ou,\n", " mu=300,\n", " sigma=200,\n", " t_sim=25000.,\n", diff --git a/doc/tutorials/spike_frequency_adaptation/nestml_spike_frequency_adaptation_tutorial.ipynb b/doc/tutorials/spike_frequency_adaptation/nestml_spike_frequency_adaptation_tutorial.ipynb index e4fd4b76c..dc8b15020 100644 --- a/doc/tutorials/spike_frequency_adaptation/nestml_spike_frequency_adaptation_tutorial.ipynb +++ b/doc/tutorials/spike_frequency_adaptation/nestml_spike_frequency_adaptation_tutorial.ipynb @@ -45,29 +45,7 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " -- N E S T --\n", - " Copyright (C) 2004 The NEST Initiative\n", - "\n", - " Version: 3.6.0-post0.dev0\n", - " Built: Mar 26 2024 10:08:21\n", - "\n", - " This program is provided AS IS and comes with\n", - " NO WARRANTY. See the file LICENSE for details.\n", - "\n", - " Problems or suggestions?\n", - " Visit https://www.nest-simulator.org\n", - "\n", - " Type 'nest.help()' to find out more about NEST.\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# %matplotlib inline\n", "\n", @@ -91,7 +69,10 @@ "import re\n", "import uuid\n", "\n", - "from pynestml.codegeneration.nest_code_generator_utils import NESTCodeGeneratorUtils" + "from pynestml.codegeneration.nest_code_generator_utils import NESTCodeGeneratorUtils\n", + "\n", + "# Set NEST verbosity to ERROR\n", + "nest.set_verbosity(\"M_ERROR\")" ] }, { @@ -139,34 +120,7 @@ "output_type": "stream", "text": [ "WARNING:root:PyGSL is not available. The stiffness test will be skipped.\n", - "WARNING:root:Error when importing: No module named 'pygsl'\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " -- N E S T --\n", - " Copyright (C) 2004 The NEST Initiative\n", - "\n", - " Version: 3.6.0-post0.dev0\n", - " Built: Mar 26 2024 10:08:21\n", - "\n", - " This program is provided AS IS and comes with\n", - " NO WARRANTY. See the file LICENSE for details.\n", - "\n", - " Problems or suggestions?\n", - " Visit https://www.nest-simulator.org\n", - "\n", - " Type 'nest.help()' to find out more about NEST.\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ + "WARNING:root:Error when importing: No module named 'pygsl'\n", "WARNING:root:Under certain conditions, the propagator matrix is singular (contains infinities).\n", "WARNING:root:List of all conditions that result in a singular propagator:\n", "WARNING:root:\ttau_m = tau_syn_exc\n", @@ -193,7 +147,7 @@ "-- Detecting CXX compile features - done\n", "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", - "\u001b[0mnestml_iaf_no_sfa_module Configuration Summary\u001b[0m\n", + "\u001b[0miaf_no_sfa_module Configuration Summary\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", @@ -205,15 +159,15 @@ "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mYou can now build and install 'nestml_iaf_no_sfa_module' using\u001b[0m\n", + "\u001b[0mYou can now build and install 'iaf_no_sfa_module' using\u001b[0m\n", "\u001b[0m make\u001b[0m\n", "\u001b[0m make install\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mThe library file libnestml_iaf_no_sfa_module.so will be installed to\u001b[0m\n", - "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_0481rk8n\u001b[0m\n", + "\u001b[0mThe library file libiaf_no_sfa_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_72q0gk1i\u001b[0m\n", "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", - "\u001b[0m (nestml_iaf_no_sfa_module) Install (in SLI)\u001b[0m\n", - "\u001b[0m nest.Install(nestml_iaf_no_sfa_module) (in PyNEST)\u001b[0m\n", + "\u001b[0m (iaf_no_sfa_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(iaf_no_sfa_module) (in PyNEST)\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -225,43 +179,43 @@ " information run \"cmake --help-policy CMP0000\".\n", "This warning is for project developers. Use -Wno-dev to suppress it.\n", "\u001b[0m\n", - "-- Configuring done (0.8s)\n", + "-- Configuring done (1.1s)\n", "-- Generating done (0.0s)\n", - "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target\n", - "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/nestml_iaf_no_sfa_module_module.dir/iaf_psc_alpha_nestml.o\u001b[0m\n", - "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/nestml_iaf_no_sfa_module_module.dir/nestml_iaf_no_sfa_module.o\u001b[0m\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/nestml_iaf_no_sfa_module.cpp:31:\n", - "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_nestml.h:295:17: warning: 'iaf_psc_alpha_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_no_sfa\n", + "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/iaf_no_sfa_module_module.dir/iaf_no_sfa_module.o\u001b[0m\n", + "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/iaf_no_sfa_module_module.dir/iaf_psc_alpha_nestml.o\u001b[0m\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_no_sfa/iaf_no_sfa_module.cpp:31:\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_no_sfa/iaf_psc_alpha_nestml.h:295:17: warning: 'iaf_psc_alpha_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", " inline double get_C_m() const\n", " ^\n", "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", " virtual double get_C_m( int comp );\n", " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_nestml.cpp:44:\n", - "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_nestml.h:295:17: warning: 'iaf_psc_alpha_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_no_sfa/iaf_psc_alpha_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_no_sfa/iaf_psc_alpha_nestml.h:295:17: warning: 'iaf_psc_alpha_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", " inline double get_C_m() const\n", " ^\n", "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", " virtual double get_C_m( int comp );\n", " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_nestml.cpp:192:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_no_sfa/iaf_psc_alpha_nestml.cpp:192:16: warning: unused variable '__resolution' [-Wunused-variable]\n", " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_nestml.cpp:382:10: warning: unused variable 'get_t' [-Wunused-variable]\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_no_sfa/iaf_psc_alpha_nestml.cpp:382:10: warning: unused variable 'get_t' [-Wunused-variable]\n", " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_nestml.cpp:376:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_no_sfa/iaf_psc_alpha_nestml.cpp:376:16: warning: unused variable '__resolution' [-Wunused-variable]\n", " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " ^\n", "1 warning generated.\n", "4 warnings generated.\n", - "[100%] \u001b[32m\u001b[1mLinking CXX shared module nestml_iaf_no_sfa_module.so\u001b[0m\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module iaf_no_sfa_module.so\u001b[0m\n", "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", - "[100%] Built target nestml_iaf_no_sfa_module_module\n", - "[100%] Built target nestml_iaf_no_sfa_module_module\n", + "[100%] Built target iaf_no_sfa_module_module\n", + "[100%] Built target iaf_no_sfa_module_module\n", "\u001b[36mInstall the project...\u001b[0m\n", "-- Install configuration: \"\"\n", - "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_0481rk8n/nestml_iaf_no_sfa_module.so\n" + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_72q0gk1i/iaf_no_sfa_module.so\n" ] } ], @@ -269,12 +223,13 @@ "# generate and build code\n", "module_name_no_sfa, neuron_model_name_no_sfa = \\\n", " NESTCodeGeneratorUtils.generate_code_for(nestml_neuron_model=\"models/iaf_psc_alpha.nestml\",\n", - " module_name=\"iaf_no_sfa\")" + " module_name=\"iaf_no_sfa_module\",\n", + " target_path=\"target_no_sfa\")" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -337,32 +292,11 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": { "scrolled": true }, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Mar 26 10:46:36 Install [Info]: \n", - " loaded module nestml_iaf_no_sfa_module\n", - "\n", - "Mar 26 10:46:36 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:46:36 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 300\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:46:36 SimulationManager::run [Info]: \n", - " Simulation finished.\n" - ] - }, { "data": { "text/plain": [ @@ -370,7 +304,7 @@ " 157. , 172.9, 188.8, 204.7, 220.6, 236.5, 252.4, 268.3, 284.2])" ] }, - "execution_count": 4, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, @@ -467,32 +401,11 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": { "scrolled": true }, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " -- N E S T --\n", - " Copyright (C) 2004 The NEST Initiative\n", - "\n", - " Version: 3.6.0-post0.dev0\n", - " Built: Mar 26 2024 10:08:21\n", - "\n", - " This program is provided AS IS and comes with\n", - " NO WARRANTY. See the file LICENSE for details.\n", - "\n", - " Problems or suggestions?\n", - " Visit https://www.nest-simulator.org\n", - "\n", - " Type 'nest.help()' to find out more about NEST.\n", - "\n" - ] - }, { "name": "stderr", "output_type": "stream", @@ -500,8 +413,8 @@ "WARNING:root:Under certain conditions, the propagator matrix is singular (contains infinities).\n", "WARNING:root:List of all conditions that result in a singular propagator:\n", "WARNING:root:\ttau_m = tau_sfa\n", - "WARNING:root:\ttau_m = tau_syn_inh\n", "WARNING:root:\ttau_m = tau_syn_exc\n", + "WARNING:root:\ttau_m = tau_syn_inh\n", "line 1:31 extraneous input '*' expecting {'integer', 'real', 'string', 'boolean', 'void', '(', ',', NAME, UNSIGNED_INTEGER}\n", "line 1:31 extraneous input '*' expecting {'integer', 'real', 'string', 'boolean', 'void', '(', ',', NAME, UNSIGNED_INTEGER}\n" ] @@ -524,7 +437,7 @@ "-- Detecting CXX compile features - done\n", "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", - "\u001b[0mnestml_iaf_adapt_curr_module Configuration Summary\u001b[0m\n", + "\u001b[0miaf_adapt_curr_module Configuration Summary\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", @@ -536,15 +449,15 @@ "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mYou can now build and install 'nestml_iaf_adapt_curr_module' using\u001b[0m\n", + "\u001b[0mYou can now build and install 'iaf_adapt_curr_module' using\u001b[0m\n", "\u001b[0m make\u001b[0m\n", "\u001b[0m make install\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mThe library file libnestml_iaf_adapt_curr_module.so will be installed to\u001b[0m\n", - "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_8rfw6ptq\u001b[0m\n", + "\u001b[0mThe library file libiaf_adapt_curr_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_r4il_31y\u001b[0m\n", "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", - "\u001b[0m (nestml_iaf_adapt_curr_module) Install (in SLI)\u001b[0m\n", - "\u001b[0m nest.Install(nestml_iaf_adapt_curr_module) (in PyNEST)\u001b[0m\n", + "\u001b[0m (iaf_adapt_curr_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(iaf_adapt_curr_module) (in PyNEST)\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -556,43 +469,43 @@ " information run \"cmake --help-policy CMP0000\".\n", "This warning is for project developers. Use -Wno-dev to suppress it.\n", "\u001b[0m\n", - "-- Configuring done (0.6s)\n", + "-- Configuring done (0.7s)\n", "-- Generating done (0.0s)\n", - "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target\n", - "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/nestml_iaf_adapt_curr_module_module.dir/nestml_iaf_adapt_curr_module.o\u001b[0m\n", - "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/nestml_iaf_adapt_curr_module_module.dir/iaf_psc_alpha_adapt_curr_nestml.o\u001b[0m\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/nestml_iaf_adapt_curr_module.cpp:31:\n", - "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_curr_nestml.h:313:17: warning: 'iaf_psc_alpha_adapt_curr_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_curr\n", + "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/iaf_adapt_curr_module_module.dir/iaf_adapt_curr_module.o\u001b[0m\n", + "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/iaf_adapt_curr_module_module.dir/iaf_psc_alpha_adapt_curr_nestml.o\u001b[0m\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_curr/iaf_adapt_curr_module.cpp:31:\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_curr/iaf_psc_alpha_adapt_curr_nestml.h:313:17: warning: 'iaf_psc_alpha_adapt_curr_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", " inline double get_C_m() const\n", " ^\n", "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", " virtual double get_C_m( int comp );\n", " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_curr_nestml.cpp:44:\n", - "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_curr_nestml.h:313:17: warning: 'iaf_psc_alpha_adapt_curr_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_curr/iaf_psc_alpha_adapt_curr_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_curr/iaf_psc_alpha_adapt_curr_nestml.h:313:17: warning: 'iaf_psc_alpha_adapt_curr_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", " inline double get_C_m() const\n", " ^\n", "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", " virtual double get_C_m( int comp );\n", " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_curr_nestml.cpp:198:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_curr/iaf_psc_alpha_adapt_curr_nestml.cpp:198:16: warning: unused variable '__resolution' [-Wunused-variable]\n", " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_curr_nestml.cpp:409:10: warning: unused variable 'get_t' [-Wunused-variable]\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_curr/iaf_psc_alpha_adapt_curr_nestml.cpp:409:10: warning: unused variable 'get_t' [-Wunused-variable]\n", " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_curr_nestml.cpp:403:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_curr/iaf_psc_alpha_adapt_curr_nestml.cpp:403:16: warning: unused variable '__resolution' [-Wunused-variable]\n", " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " ^\n", "1 warning generated.\n", "4 warnings generated.\n", - "[100%] \u001b[32m\u001b[1mLinking CXX shared module nestml_iaf_adapt_curr_module.so\u001b[0m\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module iaf_adapt_curr_module.so\u001b[0m\n", "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", - "[100%] Built target nestml_iaf_adapt_curr_module_module\n", - "[100%] Built target nestml_iaf_adapt_curr_module_module\n", + "[100%] Built target iaf_adapt_curr_module_module\n", + "[100%] Built target iaf_adapt_curr_module_module\n", "\u001b[36mInstall the project...\u001b[0m\n", "-- Install configuration: \"\"\n", - "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_8rfw6ptq/nestml_iaf_adapt_curr_module.so\n" + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_r4il_31y/iaf_adapt_curr_module.so\n" ] } ], @@ -600,42 +513,22 @@ "# generate and build code\n", "module_name_adapt_curr, neuron_model_name_adapt_curr = \\\n", " NESTCodeGeneratorUtils.generate_code_for(nestml_neuron_model=\"models/iaf_psc_alpha_adapt_curr.nestml\",\n", - " module_name=\"iaf_adapt_curr\")" + " module_name=\"iaf_adapt_curr_module\",\n", + " target_path=\"target_adapt_curr\")" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Mar 26 10:47:11 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:11 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:11 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 300\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:11 SimulationManager::run [Info]: \n", - " Simulation finished.\n" - ] - }, { "data": { "text/plain": [ "array([ 13.9, 39.4, 89.8, 154.8, 220.6, 286.4])" ] }, - "execution_count": 6, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, @@ -683,32 +576,11 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": { "scrolled": true }, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " -- N E S T --\n", - " Copyright (C) 2004 The NEST Initiative\n", - "\n", - " Version: 3.6.0-post0.dev0\n", - " Built: Mar 26 2024 10:08:21\n", - "\n", - " This program is provided AS IS and comes with\n", - " NO WARRANTY. See the file LICENSE for details.\n", - "\n", - " Problems or suggestions?\n", - " Visit https://www.nest-simulator.org\n", - "\n", - " Type 'nest.help()' to find out more about NEST.\n", - "\n" - ] - }, { "name": "stderr", "output_type": "stream", @@ -739,7 +611,7 @@ "-- Detecting CXX compile features - done\n", "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", - "\u001b[0mnestml_iaf_adapt_thresh_module Configuration Summary\u001b[0m\n", + "\u001b[0miaf_adapt_thresh_module Configuration Summary\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", @@ -751,15 +623,15 @@ "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mYou can now build and install 'nestml_iaf_adapt_thresh_module' using\u001b[0m\n", + "\u001b[0mYou can now build and install 'iaf_adapt_thresh_module' using\u001b[0m\n", "\u001b[0m make\u001b[0m\n", "\u001b[0m make install\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mThe library file libnestml_iaf_adapt_thresh_module.so will be installed to\u001b[0m\n", - "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_w7flhqq6\u001b[0m\n", + "\u001b[0mThe library file libiaf_adapt_thresh_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target__ct3q5va\u001b[0m\n", "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", - "\u001b[0m (nestml_iaf_adapt_thresh_module) Install (in SLI)\u001b[0m\n", - "\u001b[0m nest.Install(nestml_iaf_adapt_thresh_module) (in PyNEST)\u001b[0m\n", + "\u001b[0m (iaf_adapt_thresh_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(iaf_adapt_thresh_module) (in PyNEST)\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -771,43 +643,43 @@ " information run \"cmake --help-policy CMP0000\".\n", "This warning is for project developers. Use -Wno-dev to suppress it.\n", "\u001b[0m\n", - "-- Configuring done (0.7s)\n", + "-- Configuring done (0.9s)\n", "-- Generating done (0.0s)\n", - "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target\n", - "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/nestml_iaf_adapt_thresh_module_module.dir/nestml_iaf_adapt_thresh_module.o\u001b[0m\n", - "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/nestml_iaf_adapt_thresh_module_module.dir/iaf_psc_alpha_adapt_thresh_nestml.o\u001b[0m\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/nestml_iaf_adapt_thresh_module.cpp:31:\n", - "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_thresh_nestml.h:313:17: warning: 'iaf_psc_alpha_adapt_thresh_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_thresh\n", + "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/iaf_adapt_thresh_module_module.dir/iaf_adapt_thresh_module.o\u001b[0m\n", + "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/iaf_adapt_thresh_module_module.dir/iaf_psc_alpha_adapt_thresh_nestml.o\u001b[0m\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_thresh/iaf_adapt_thresh_module.cpp:31:\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_thresh/iaf_psc_alpha_adapt_thresh_nestml.h:313:17: warning: 'iaf_psc_alpha_adapt_thresh_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", " inline double get_C_m() const\n", " ^\n", "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", " virtual double get_C_m( int comp );\n", " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_thresh_nestml.cpp:44:\n", - "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_thresh_nestml.h:313:17: warning: 'iaf_psc_alpha_adapt_thresh_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_thresh/iaf_psc_alpha_adapt_thresh_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_thresh/iaf_psc_alpha_adapt_thresh_nestml.h:313:17: warning: 'iaf_psc_alpha_adapt_thresh_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", " inline double get_C_m() const\n", " ^\n", "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", " virtual double get_C_m( int comp );\n", " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_thresh_nestml.cpp:197:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_thresh/iaf_psc_alpha_adapt_thresh_nestml.cpp:197:16: warning: unused variable '__resolution' [-Wunused-variable]\n", " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_thresh_nestml.cpp:402:10: warning: unused variable 'get_t' [-Wunused-variable]\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_thresh/iaf_psc_alpha_adapt_thresh_nestml.cpp:402:10: warning: unused variable 'get_t' [-Wunused-variable]\n", " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_thresh_nestml.cpp:396:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target_adapt_thresh/iaf_psc_alpha_adapt_thresh_nestml.cpp:396:16: warning: unused variable '__resolution' [-Wunused-variable]\n", " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " ^\n", "1 warning generated.\n", "4 warnings generated.\n", - "[100%] \u001b[32m\u001b[1mLinking CXX shared module nestml_iaf_adapt_thresh_module.so\u001b[0m\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module iaf_adapt_thresh_module.so\u001b[0m\n", "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", - "[100%] Built target nestml_iaf_adapt_thresh_module_module\n", - "[100%] Built target nestml_iaf_adapt_thresh_module_module\n", + "[100%] Built target iaf_adapt_thresh_module_module\n", + "[100%] Built target iaf_adapt_thresh_module_module\n", "\u001b[36mInstall the project...\u001b[0m\n", "-- Install configuration: \"\"\n", - "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_w7flhqq6/nestml_iaf_adapt_thresh_module.so\n" + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target__ct3q5va/iaf_adapt_thresh_module.so\n" ] } ], @@ -815,42 +687,22 @@ "# generate and build code\n", "module_name_adapt_thresh, neuron_model_name_adapt_thresh = \\\n", " NESTCodeGeneratorUtils.generate_code_for(nestml_neuron_model=\"models/iaf_psc_alpha_adapt_thresh.nestml\",\n", - " module_name=\"iaf_adapt_thresh\")" + " module_name=\"iaf_adapt_thresh_module\",\n", + " target_path=\"target_adapt_thresh\")" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Mar 26 10:47:37 Install [Info]: \n", - " loaded module nestml_iaf_adapt_thresh_module\n", - "\n", - "Mar 26 10:47:37 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:37 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 300\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:37 SimulationManager::run [Info]: \n", - " Simulation finished.\n" - ] - }, { "data": { "text/plain": [ "array([ 13.9, 33.9, 58.6, 88.3, 122.2, 158.8, 196.7, 235.2, 273.9])" ] }, - "execution_count": 8, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, @@ -894,7 +746,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -929,7 +781,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -952,329 +804,18 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n", - "\n", - "Mar 26 10:47:38 Install [Info]: \n", - " loaded module nestml_iaf_adapt_curr_module\n", - "\n", - "Mar 26 10:47:38 NodeManager::prepare_nodes [Info]: \n", - " Preparing 3 nodes for simulation.\n", - "\n", - "Mar 26 10:47:38 SimulationManager::start_updating_ [Info]: \n", - " Number of local nodes: 3\n", - " Simulation time (ms): 10000\n", - " Number of OpenMP threads: 1\n", - " Not using MPI\n", - "\n", - "Mar 26 10:47:38 SimulationManager::run [Info]: \n", - " Simulation finished.\n" - ] - }, - { - "ename": "NESTErrors.DynamicModuleManagementError", - "evalue": "DynamicModuleManagementError in SLI function Install: Module 'nestml_iaf_no_sfa_module' could not be opened.\nThe dynamic loader returned the following error: 'file not found'.\n\nPlease check LD_LIBRARY_PATH (OSX: DYLD_LIBRARY_PATH)!", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNESTErrors.DynamicModuleManagementError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[11], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m I_stim_vec \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mlinspace(\u001b[38;5;241m10E-12\u001b[39m, \u001b[38;5;241m1E-9\u001b[39m, \u001b[38;5;241m20\u001b[39m) \u001b[38;5;66;03m# [A]\u001b[39;00m\n\u001b[1;32m 2\u001b[0m rate_vec_adapt \u001b[38;5;241m=\u001b[39m measure_fI_curve(I_stim_vec, neuron_model_name_adapt_curr, module_name_adapt_curr)\n\u001b[0;32m----> 3\u001b[0m rate_vec \u001b[38;5;241m=\u001b[39m \u001b[43mmeasure_fI_curve\u001b[49m\u001b[43m(\u001b[49m\u001b[43mI_stim_vec\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mneuron_model_name_no_sfa\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodule_name_no_sfa\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 4\u001b[0m rate_vec_thresh_adapt \u001b[38;5;241m=\u001b[39m measure_fI_curve(I_stim_vec, neuron_model_name_adapt_thresh, module_name_adapt_thresh)\n\u001b[1;32m 5\u001b[0m plot_fI_curve(I_stim_vec, {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNo adap\u001b[39m\u001b[38;5;124m\"\u001b[39m: rate_vec,\n\u001b[1;32m 6\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCurr adap\u001b[39m\u001b[38;5;124m\"\u001b[39m : rate_vec_adapt,\n\u001b[1;32m 7\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThr adap\u001b[39m\u001b[38;5;124m\"\u001b[39m : rate_vec_thresh_adapt})\n", - "Cell \u001b[0;32mIn[9], line 11\u001b[0m, in \u001b[0;36mmeasure_fI_curve\u001b[0;34m(I_stim_vec, neuron_model_name, module_name)\u001b[0m\n\u001b[1;32m 9\u001b[0m nest\u001b[38;5;241m.\u001b[39mResetKernel()\n\u001b[1;32m 10\u001b[0m \u001b[38;5;66;03m# try:\u001b[39;00m\n\u001b[0;32m---> 11\u001b[0m \u001b[43mnest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mInstall\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmodule_name\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 12\u001b[0m \u001b[38;5;66;03m# except Exception:\u001b[39;00m\n\u001b[1;32m 13\u001b[0m \u001b[38;5;66;03m# pass\u001b[39;00m\n\u001b[1;32m 15\u001b[0m neuron \u001b[38;5;241m=\u001b[39m nest\u001b[38;5;241m.\u001b[39mCreate(neuron_model_name)\n", - "File \u001b[0;32m~/conda/nestml_dev/lib/python3.11/site-packages/nest/ll_api.py:216\u001b[0m, in \u001b[0;36mstack_checker..stack_checker_func\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 213\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(f)\n\u001b[1;32m 214\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mstack_checker_func\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 215\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m get_debug():\n\u001b[0;32m--> 216\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mf\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 217\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 218\u001b[0m sr(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcount\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "File \u001b[0;32m~/conda/nestml_dev/lib/python3.11/site-packages/nest/lib/hl_api_simulation.py:332\u001b[0m, in \u001b[0;36mInstall\u001b[0;34m(module_name)\u001b[0m\n\u001b[1;32m 305\u001b[0m \u001b[38;5;129m@check_stack\u001b[39m\n\u001b[1;32m 306\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mInstall\u001b[39m(module_name):\n\u001b[1;32m 307\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Load a dynamically linked NEST module.\u001b[39;00m\n\u001b[1;32m 308\u001b[0m \n\u001b[1;32m 309\u001b[0m \u001b[38;5;124;03m Parameters\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 329\u001b[0m \n\u001b[1;32m 330\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 332\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43msr\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m(\u001b[39;49m\u001b[38;5;132;43;01m%s\u001b[39;49;00m\u001b[38;5;124;43m) Install\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m%\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mmodule_name\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/conda/nestml_dev/lib/python3.11/site-packages/nest/ll_api.py:103\u001b[0m, in \u001b[0;36mcatching_sli_run\u001b[0;34m(cmd)\u001b[0m\n\u001b[1;32m 100\u001b[0m engine\u001b[38;5;241m.\u001b[39mrun(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mclear\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 102\u001b[0m exceptionCls \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(kernel\u001b[38;5;241m.\u001b[39mNESTErrors, errorname)\n\u001b[0;32m--> 103\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m exceptionCls(commandname, message)\n", - "\u001b[0;31mNESTErrors.DynamicModuleManagementError\u001b[0m: DynamicModuleManagementError in SLI function Install: Module 'nestml_iaf_no_sfa_module' could not be opened.\nThe dynamic loader returned the following error: 'file not found'.\n\nPlease check LD_LIBRARY_PATH (OSX: DYLD_LIBRARY_PATH)!" - ] + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -1343,13 +884,113 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:root:Under certain conditions, the propagator matrix is singular (contains infinities).\n", + "WARNING:root:List of all conditions that result in a singular propagator:\n", + "WARNING:root:\ttau_m = tau_syn_inh\n", + "WARNING:root:\ttau_m = tau_syn_exc\n", + "line 1:31 extraneous input '*' expecting {'integer', 'real', 'string', 'boolean', 'void', '(', ',', NAME, UNSIGNED_INTEGER}\n", + "line 1:31 extraneous input '*' expecting {'integer', 'real', 'string', 'boolean', 'void', '(', ',', NAME, UNSIGNED_INTEGER}\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33mCMake Warning (dev) at CMakeLists.txt:93 (project):\n", + " cmake_minimum_required() should be called prior to this top-level project()\n", + " call. Please see the cmake-commands(7) manual for usage documentation of\n", + " both commands.\n", + "This warning is for project developers. Use -Wno-dev to suppress it.\n", + "\u001b[0m\n", + "-- The CXX compiler identification is AppleClang 15.0.0.15000309\n", + "-- Detecting CXX compiler ABI info\n", + "-- Detecting CXX compiler ABI info - done\n", + "-- Check for working CXX compiler: /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++ - skipped\n", + "-- Detecting CXX compile features\n", + "-- Detecting CXX compile features - done\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0madapt_thresh_OU_module Configuration Summary\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", + "\u001b[0mBuild static libs : OFF\u001b[0m\n", + "\u001b[0mC++ compiler flags : \u001b[0m\n", + "\u001b[0mNEST compiler flags : -std=c++17 -Wall -Xclang -fopenmp -O2\u001b[0m\n", + "\u001b[0mNEST include dirs : -I/Users/pooja/conda/nestml_dev/include/nest -I/usr/local/include -I/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX14.4.sdk/usr/include -I/usr/local/Cellar/gsl/2.7/include -I/Users/pooja/conda/nestml_dev/include\u001b[0m\n", + "\u001b[0mNEST libraries flags : -L/Users/pooja/conda/nestml_dev/lib/nest -lnest -lsli /usr/local/lib/libltdl.dylib /Users/pooja/conda/nestml_dev/lib/libreadline.dylib /Users/pooja/conda/nestml_dev/lib/libncurses.dylib /usr/local/Cellar/gsl/2.7/lib/libgsl.dylib /usr/local/Cellar/gsl/2.7/lib/libgslcblas.dylib /usr/local/lib/libomp.dylib\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mYou can now build and install 'adapt_thresh_OU_module' using\u001b[0m\n", + "\u001b[0m make\u001b[0m\n", + "\u001b[0m make install\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mThe library file libadapt_thresh_OU_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_y_58y7nj\u001b[0m\n", + "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", + "\u001b[0m (adapt_thresh_OU_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(adapt_thresh_OU_module) (in PyNEST)\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", + " No cmake_minimum_required command is present. A line of code such as\n", + "\n", + " cmake_minimum_required(VERSION 3.28)\n", + "\n", + " should be added at the top of the file. The version specified may be lower\n", + " if you wish to support older CMake versions for this project. For more\n", + " information run \"cmake --help-policy CMP0000\".\n", + "This warning is for project developers. Use -Wno-dev to suppress it.\n", + "\u001b[0m\n", + "-- Configuring done (0.8s)\n", + "-- Generating done (0.0s)\n", + "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target\n", + "[ 33%] \u001b[32mBuilding CXX object CMakeFiles/adapt_thresh_OU_module_module.dir/adapt_thresh_OU_module.o\u001b[0m\n", + "[ 66%] \u001b[32mBuilding CXX object CMakeFiles/adapt_thresh_OU_module_module.dir/iaf_psc_alpha_adapt_thresh_OU_nestml.o\u001b[0m\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/adapt_thresh_OU_module.cpp:31:\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_thresh_OU_nestml.h:333:17: warning: 'iaf_psc_alpha_adapt_thresh_OU_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_thresh_OU_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_thresh_OU_nestml.h:333:17: warning: 'iaf_psc_alpha_adapt_thresh_OU_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_thresh_OU_nestml.cpp:203:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/spike_frequency_adaptation/target/iaf_psc_alpha_adapt_thresh_OU_nestml.cpp:429:10: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " ^\n", + "1 warning generated.\n", + "3 warnings generated.\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module adapt_thresh_OU_module.so\u001b[0m\n", + "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", + "[100%] Built target adapt_thresh_OU_module_module\n", + "[100%] Built target adapt_thresh_OU_module_module\n", + "\u001b[36mInstall the project...\u001b[0m\n", + "-- Install configuration: \"\"\n", + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_y_58y7nj/adapt_thresh_OU_module.so\n" + ] + } + ], "source": [ "# generate and build code\n", - "module_name, neuron_model_name_adapt_thresh_ou = \\\n", - " NESTCodeGeneratorUtils.generate_code_for(\"models/iaf_psc_alpha_adapt_thresh_OU.nestml\")" + "module_name_ou, neuron_model_name_adapt_thresh_ou = \\\n", + " NESTCodeGeneratorUtils.generate_code_for(\"models/iaf_psc_alpha_adapt_thresh_OU.nestml\",\n", + " module_name=\"adapt_thresh_OU_module\")" ] }, { @@ -1361,12 +1002,43 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 16.1, 36.1, 60.8, 90.5, 124.4, 161. , 198.9, 237.4, 276.1])" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "evaluate_neuron(neuron_model_name_adapt_thresh_ou, module_name, stimulus_type=\"constant\", mu=500.)\n", - "evaluate_neuron(neuron_model_name_adapt_thresh_ou, module_name, stimulus_type=\"Ornstein-Uhlenbeck\", mu=500., sigma=0.)" + "evaluate_neuron(neuron_model_name_adapt_thresh_ou, module_name_ou, stimulus_type=\"constant\", mu=500.)\n", + "evaluate_neuron(neuron_model_name_adapt_thresh_ou, module_name_ou, stimulus_type=\"Ornstein-Uhlenbeck\", mu=500., sigma=0.)" ] }, { @@ -1378,12 +1050,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "spike_times = evaluate_neuron(neuron_model_name_adapt_thresh_ou,\n", - " module_name,\n", + " module_name_ou,\n", " stimulus_type=\"Ornstein-Uhlenbeck\",\n", " mu=500.,\n", " sigma=200.)" @@ -1398,12 +1081,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Mean: 35.32659574468086\n", + "Std. dev.: 15.105385180811849\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "spike_times = evaluate_neuron(neuron_model_name_adapt_thresh_ou,\n", - " module_name,\n", + " module_name_ou,\n", " stimulus_type=\"Ornstein-Uhlenbeck\",\n", " mu=500.,\n", " sigma=200.,\n", @@ -1453,9 +1155,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "For a Poisson process:\n", + "CV = 0.9392897672538981\n" + ] + } + ], "source": [ "mean_interval = 1.\n", "isi = np.random.exponential(mean_interval, 1000)\n", @@ -1465,9 +1176,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CV: 0.42759243743677944\n" + ] + } + ], "source": [ "CV = np.std(ISI) / np.mean(ISI)\n", "print(\"CV: \" + str(np.std(ISI) / np.mean(ISI)))" @@ -1482,7 +1201,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -1513,12 +1232,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "CV_reg, rate_reg = cv_across_curr(neuron_model_name_adapt_thresh_ou, module_name, {\"Delta_Theta\" : 0.})\n", - "CV_adapt, rate_adapt = cv_across_curr(neuron_model_name_adapt_thresh_ou, module_name, {\"Delta_Theta\" : 5.})\n", + "CV_reg, rate_reg = cv_across_curr(neuron_model_name_adapt_thresh_ou, module_name_ou, {\"Delta_Theta\" : 0.})\n", + "CV_adapt, rate_adapt = cv_across_curr(neuron_model_name_adapt_thresh_ou, module_name_ou, {\"Delta_Theta\" : 5.})\n", "\n", "fig, ax = plt.subplots()\n", "ax.scatter(rate_reg, CV_reg, label=\"non-adapt\")\n", @@ -1548,7 +1278,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ @@ -1588,9 +1318,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "spike_times = np.arange(0., 1000., 20.) \n", "_ = spike_train_autocorrelation(spike_times)" @@ -1605,9 +1346,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "spike_times = np.cumsum(np.random.exponential(10., 1000)) # cumsum turns ISIs into sequential spike times\n", "_ = spike_train_autocorrelation(spike_times)" @@ -1622,9 +1374,30 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "def autocorr(spike_times):\n", " ISI = np.diff(spike_times)\n", @@ -1643,7 +1416,7 @@ "mu = 500.\n", "for i, dth in enumerate(np.linspace(0., 10., N)):\n", " spike_times = evaluate_neuron(neuron_model_name_adapt_thresh_ou,\n", - " module_name,\n", + " module_name_ou,\n", " stimulus_type=\"Ornstein-Uhlenbeck\",\n", " mu=mu,\n", " sigma=500.,\n", diff --git a/doc/tutorials/stdp_dopa_synapse/stdp_dopa_synapse.ipynb b/doc/tutorials/stdp_dopa_synapse/stdp_dopa_synapse.ipynb index d3e055c5b..4531d5b66 100644 --- a/doc/tutorials/stdp_dopa_synapse/stdp_dopa_synapse.ipynb +++ b/doc/tutorials/stdp_dopa_synapse/stdp_dopa_synapse.ipynb @@ -86,7 +86,10 @@ "import random\n", "import re\n", "\n", - "from pynestml.codegeneration.nest_code_generator_utils import NESTCodeGeneratorUtils" + "from pynestml.codegeneration.nest_code_generator_utils import NESTCodeGeneratorUtils\n", + "\n", + "# Set the verbosity in NEST to ERROR\n", + "nest.set_verbosity(\"M_ERROR\")" ] }, { @@ -204,23 +207,358 @@ "tags": [] }, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:root:PyGSL is not available. The stiffness test will be skipped.\n", + "WARNING:root:Error when importing: No module named 'pygsl'\n" + ] + }, { "name": "stdout", "output_type": "stream", "text": [ - "[7,iaf_psc_deltadb67aa5d43e64530967cc637182cd89a_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", - "[8,iaf_psc_deltadb67aa5d43e64530967cc637182cd89a_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[13,neuromodulated_stdpdb67aa5d43e64530967cc637182cd89a_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", - "[22,iaf_psc_deltadb67aa5d43e64530967cc637182cd89a_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", - "[23,iaf_psc_deltadb67aa5d43e64530967cc637182cd89a_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[25,neuromodulated_stdpdb67aa5d43e64530967cc637182cd89a_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", - "[44,iaf_psc_deltadb67aa5d43e64530967cc637182cd89a_nestml__with_neuromodulated_stdpdb67aa5d43e64530967cc637182cd89a_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", - "[45,iaf_psc_deltadb67aa5d43e64530967cc637182cd89a_nestml__with_neuromodulated_stdpdb67aa5d43e64530967cc637182cd89a_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[49,neuromodulated_stdpdb67aa5d43e64530967cc637182cd89a_nestml__with_iaf_psc_deltadb67aa5d43e64530967cc637182cd89a_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", - "[56,iaf_psc_deltadb67aa5d43e64530967cc637182cd89a_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[60,iaf_psc_deltadb67aa5d43e64530967cc637182cd89a_nestml__with_neuromodulated_stdpdb67aa5d43e64530967cc637182cd89a_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[64,neuromodulated_stdpdb67aa5d43e64530967cc637182cd89a_nestml__with_iaf_psc_deltadb67aa5d43e64530967cc637182cd89a_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", - "[68,neuromodulated_stdpdb67aa5d43e64530967cc637182cd89a_nestml__with_iaf_psc_deltadb67aa5d43e64530967cc637182cd89a_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n" + "[13,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[14,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[19,neuromodulated_stdp_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[23,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[24,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[26,neuromodulated_stdp_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[30,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[31,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[35,neuromodulated_stdp_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[53,iaf_psc_delta_nestml__with_neuromodulated_stdp_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[54,iaf_psc_delta_nestml__with_neuromodulated_stdp_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[56,neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[63,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[67,iaf_psc_delta_nestml__with_neuromodulated_stdp_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[71,neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[75,neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "\u001b[33mCMake Warning (dev) at CMakeLists.txt:95 (project):\n", + " cmake_minimum_required() should be called prior to this top-level project()\n", + " call. Please see the cmake-commands(7) manual for usage documentation of\n", + " both commands.\n", + "This warning is for project developers. Use -Wno-dev to suppress it.\n", + "\u001b[0m\n", + "-- The CXX compiler identification is AppleClang 15.0.0.15000309\n", + "-- Detecting CXX compiler ABI info\n", + "-- Detecting CXX compiler ABI info - done\n", + "-- Check for working CXX compiler: /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++ - skipped\n", + "-- Detecting CXX compile features\n", + "-- Detecting CXX compile features - done\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0mstdp_dopa_module Configuration Summary\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", + "\u001b[0mBuild static libs : OFF\u001b[0m\n", + "\u001b[0mC++ compiler flags : \u001b[0m\n", + "\u001b[0mNEST compiler flags : -std=c++17 -Wall -Xclang -fopenmp -O2\u001b[0m\n", + "\u001b[0mNEST include dirs : -I/Users/pooja/conda/nestml_dev/include/nest -I/usr/local/include -I/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX14.4.sdk/usr/include -I/usr/local/Cellar/gsl/2.7/include -I/Users/pooja/conda/nestml_dev/include\u001b[0m\n", + "\u001b[0mNEST libraries flags : -L/Users/pooja/conda/nestml_dev/lib/nest -lnest -lsli /usr/local/lib/libltdl.dylib /Users/pooja/conda/nestml_dev/lib/libreadline.dylib /Users/pooja/conda/nestml_dev/lib/libncurses.dylib /usr/local/Cellar/gsl/2.7/lib/libgsl.dylib /usr/local/Cellar/gsl/2.7/lib/libgslcblas.dylib /usr/local/lib/libomp.dylib\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mYou can now build and install 'stdp_dopa_module' using\u001b[0m\n", + "\u001b[0m make\u001b[0m\n", + "\u001b[0m make install\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mThe library file libstdp_dopa_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_cl5dk_s8\u001b[0m\n", + "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", + "\u001b[0m (stdp_dopa_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(stdp_dopa_module) (in PyNEST)\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", + " No cmake_minimum_required command is present. A line of code such as\n", + "\n", + " cmake_minimum_required(VERSION 3.28)\n", + "\n", + " should be added at the top of the file. The version specified may be lower\n", + " if you wish to support older CMake versions for this project. For more\n", + " information run \"cmake --help-policy CMP0000\".\n", + "This warning is for project developers. Use -Wno-dev to suppress it.\n", + "\u001b[0m\n", + "-- Configuring done (0.7s)\n", + "-- Generating done (0.0s)\n", + "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target\n", + "[ 25%] \u001b[32mBuilding CXX object CMakeFiles/stdp_dopa_module_module.dir/stdp_dopa_module.o\u001b[0m\n", + "[ 50%] \u001b[32mBuilding CXX object CMakeFiles/stdp_dopa_module_module.dir/iaf_psc_delta_nestml.o\u001b[0m\n", + "[ 75%] \u001b[32mBuilding CXX object CMakeFiles/stdp_dopa_module_module.dir/iaf_psc_delta_nestml__with_neuromodulated_stdp_nestml.o\u001b[0m\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_nestml.h:267:17: warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_nestml__with_neuromodulated_stdp_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_nestml__with_neuromodulated_stdp_nestml.h:320:17: warning: 'iaf_psc_delta_nestml__with_neuromodulated_stdp_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_nestml__with_neuromodulated_stdp_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_nestml__with_neuromodulated_stdp_nestml.h:260:8: warning: 'register_stdp_connection' overrides a member function but is not marked 'override' [-Winconsistent-missing-override]\n", + " void register_stdp_connection( double t_first_read, double delay );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:482:16: note: overridden virtual function is here\n", + " virtual void register_stdp_connection( double, double );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/stdp_dopa_module.cpp:31:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_nestml.h:267:17: warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_nestml.cpp:171:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_nestml.cpp:289:10: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_nestml.cpp:283:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_nestml__with_neuromodulated_stdp_nestml.cpp:181:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_nestml__with_neuromodulated_stdp_nestml.cpp:318:10: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_nestml__with_neuromodulated_stdp_nestml.cpp:312:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/stdp_dopa_module.cpp:33:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_nestml__with_neuromodulated_stdp_nestml.h:320:17: warning: 'iaf_psc_delta_nestml__with_neuromodulated_stdp_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/stdp_dopa_module.cpp:33:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_delta_nestml__with_neuromodulated_stdp_nestml.h:260:8: warning: 'register_stdp_connection' overrides a member function but is not marked 'override' [-Winconsistent-missing-override]\n", + " void register_stdp_connection( double t_first_read, double delay );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:482:16: note: overridden virtual function is here\n", + " virtual void register_stdp_connection( double, double );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/stdp_dopa_module.cpp:36:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:517:18: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:705:12: warning: unused variable 'cd' [-Wunused-variable]\n", + " double cd;\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:859:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:876:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:1043:18: warning: unused variable '_tr_t' [-Wunused-variable]\n", + " const double _tr_t = start->t_;\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:1025:10: warning: unused variable 'timestep' [-Wunused-variable]\n", + " double timestep = 0;\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:519:10: warning: unused variable 'get_thread' [-Wunused-variable]\n", + " auto get_thread = [tid]()\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:668:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:590:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:615:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:646:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:979:8: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:585:9: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml::update_internal_state_' requested here\n", + " update_internal_state_(t_lastspike_, (start->t_ + __dendritic_delay) - t_lastspike_, cp);\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:668:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:500:7: warning: expression result unused [-Wunused-value]\n", + " dynamic_cast(t);\n", + " ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:316:14: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml::check_connection' requested here\n", + " connection.check_connection( src, tgt, receptor_type, get_common_properties() );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:668:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:519:10: warning: unused variable 'get_thread' [-Wunused-variable]\n", + " auto get_thread = [tid]()\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", + " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:668:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:590:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:615:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:646:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:979:8: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:585:9: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml::update_internal_state_' requested here\n", + " update_internal_state_(t_lastspike_, (start->t_ + __dendritic_delay) - t_lastspike_, cp);\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", + " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:668:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:500:7: warning: expression result unused [-Wunused-value]\n", + " dynamic_cast(t);\n", + " ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:316:14: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml::check_connection' requested here\n", + " connection.check_connection( src, tgt, receptor_type, get_common_properties() );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", + " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml.h:668:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< neuromodulated_stdp_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "4 warnings generated.\n", + "5 warnings generated.\n", + "21 warnings generated.\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module stdp_dopa_module.so\u001b[0m\n", + "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", + "[100%] Built target stdp_dopa_module_module\n", + "[100%] Built target stdp_dopa_module_module\n", + "\u001b[36mInstall the project...\u001b[0m\n", + "-- Install configuration: \"\"\n", + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_cl5dk_s8/stdp_dopa_module.so\n" ] } ], @@ -228,6 +566,7 @@ "# generate and build code\n", "module_name, neuron_model_name, synapse_model_name = NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_delta.nestml\",\n", " nestml_stdp_dopa_model,\n", + " module_name=\"stdp_dopa_module\",\n", " post_ports=[\"post_spikes\"],\n", " mod_ports=[\"mod_spikes\"])" ] @@ -261,6 +600,7 @@ "def run_network(pre_spike_time, post_spike_time, vt_spike_times,\n", " neuron_model_name,\n", " synapse_model_name,\n", + " module_name,\n", " resolution=.1, # [ms]\n", " delay=1., # [ms]\n", " lmbda=1E-6,\n", @@ -269,9 +609,6 @@ " fname_snip=\"\",\n", " debug=False):\n", "\n", - " #nest.set_verbosity(\"M_WARNING\")\n", - " nest.set_verbosity(\"M_ALL\")\n", - "\n", " nest.ResetKernel()\n", " \n", " # load dynamic library (NEST extension module) into NEST kernel\n", @@ -361,7 +698,7 @@ "metadata": {}, "outputs": [], "source": [ - "def run_vt_spike_timing_experiment(neuron_model_name, synapse_model_name, synapse_parameters=None):\n", + "def run_vt_spike_timing_experiment(neuron_model_name, synapse_model_name, module_name, synapse_parameters=None):\n", " sim_time = 10000. # [ms] -- make sure to simulate for much longer than the eligibility trace\n", " # time constant, which is typically the slowest time constant in \n", " # the system, PLUS the time of the latest vt spike\n", @@ -375,6 +712,7 @@ " dt, dw = run_network(pre_spike_time, post_spike_time, [vt_spike_time],\n", " neuron_model_name,\n", " synapse_model_name,\n", + " module_name,\n", " delay=delay, # [ms]\n", " synapse_parameters=synapse_parameters,\n", " sim_time=sim_time)\n", @@ -395,7 +733,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 6, @@ -404,14 +742,12 @@ }, { "data": { - "image/png": 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\n", 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o5rg7d+6gUaNGyM7ONgwn++6777B48WKsWLECXbp0gVarhaurK9q1a4e//vqr3PMeOXJE1nuEiosgAOjcuTMOHjyIu3fvGk2YcPz4ccPz1oCFkMIFBQU98CrPvVrUw+639EPl/rycgmsp2QheehhzgtrjhZ5+HCqnUObIBtVczAeJYTZIirXlw05tgzG9m2HhvkuS+wkAxvRuapGJEj788ENotVp88skncHd3L/P8+++/bzRzXP369eHu7o7Lly8jICAAOp0Oc+fOxfLly9GuXTvMmTMHiYmJ+PLLLyXPK9c9Qjk5OYiPj0dmZiYCAwMBACNHjsRnn32GlStXGtYRys/Px9q1axEYGGgVM8YBLIQUz1wfRl6uDlg/vieWRV7Bgt/+RUGhDu9uP4ujV1Lx0TMdUMfRtG5ksh7W9D8qsj7MB4lhNkiKNebjjYEtcepGBg5cTCoze1zx48FtfTBxYPVP/X3jxg0sXrwY//3vf8stggD9FOS//fYbdDqdYaY1f39/XLx4EQEBAdi8eTMaN25sWHT1zJkzGDx4cIXnNvc9QqYsWQPoJ9AYNGgQ5syZYyiEAgMDMWrUKMyaNQtJSUlo1aoV1q9fj7i4OKM1PeVWIxdUrU1CQ0PNdiwbGxUmDWqFLa/1Qv26+q7ZX84kIuirKJxNMG1eerIe5swG1TzMB4lhNkiKNebDTm2DFS93w7RH2xgWkC/m5eqAaY+2wYqXu1mkN+h///sfdDqd5H+nli1bIjc3F1euXDFsKy6ECgsLMW/ePMyfP9/w3JkzZ9CxY8dqbXd5PvvsM8yePRvLli0DoF+yZvbs2Zg9ezbS09PL7H//GkYbNmzA1KlTsXHjRkyZMgUajQa//PKLocCzBipBEKSGVJKIc+fOISAgAGfPnoW/f9WnVnxQsbGxaNWqldmPm5qVj9DvTuOPS/oFyuxtbTD7ifZ4KZBD5ZSiurJBNQPzQWKYDZJijnxcvXoVANCiRQtzNMmIRqvDibh0ZOYWwM3JHt2beVhs3aAHsWTJEhw5cgRDhgzBjh078PPPPwPQT4Dg6uqK9PR0uLi4yNxKaXl5eYbpsatLRdmp7Pdz608GSfrjjz+q5bj1XB2wblwPvD38IahtVCgo1GH2jrP47+aTuJunqZZzknlVVzaoZmA+SAyzQVKsPR92ahv0blkPwwN80btlPUUUQYC+RygmJgYffPABwsPDDdvv3dPPiFdQUPFaSXLLysqSuwmVpox0kCgPD49qO7aNjQpvDmyFrRN6oUFdfYW/K4ZD5ZSiOrNBysd8kBhmg6QwH9WjuBDq1q0bOnXqZNher149jB49Gn5+fujVq5eMLayYuafjtgQWQgpn7lWJy9OjmSd2v9UPgx7yBgBcT83BM0uPYMPROHBkpfWyRDZIuZgPEsNskBTmo3p4e3tDEAR89913ZZ5bv3497t27h2PHjsnQMtPZ29vL3YRKYyGkcHv37rXIeTxd7LF6bA+8M6KtfqicVof//XQOkzb/w6FyVspS2SBlYj5IDLNBUpgPEnP/ZAlKwMkSqshaJkvIycmBs7OzRc95Ii4Nk7ecRGJmHgDAz9MZi1/ogo6N3S3aDpImRzZIOZgPEsNskBRz5KM6J0sg+Wi12mofHsfJEsjIuHHjLH7O7s08sXtKPwxu6wMAiE/LwbPLjmDd4WscKmdF5MgGKQfzQWKYDZLCfJCYuLg4uZtQaewRqiJr6RGSk04n4Ouoq/h0z78o1OljNNy/AT4Z2RFuTlyAlYiIiMpijxBVFXuEyEhQUJBs57axUWFC/5b49vXeaOimn1Vuz7nbeOKrP3H6RoZs7SI9ObNB1o/5IDHMBklhPkjM5cuX5W5CpbEQUridO3fK3QR0a+qB3W/1wyPt9EPlbqTlYuTyI1gTxaFycrKGbJD1Yj5IDLNBUpgPEtO6dWu5m1BpLIQULiwsTO4mAADcne2xakx3vPd4O9jaqKDRCpj3y3m8vvFvZOZwVjk5WEs2yDoxHySG2SApzAeJuXnzptxNqDQWQgo3evRouZtgoFKp8J9+LfDdxN5o5O4EAPjt/B089uWfOMWhchZnTdkg68N8kBhmg6QwHyTG09NT7iZUGgshhYuJiZG7CWV09fPA7in98Gj7+gCAhIxcjFx2BF//eZVD5SzIGrNB1oP5IDHMBklhPkhMbm6u3E2oNBZCVC3cnO2w8uVumP1Ee9ipVSjUCZi/6wJe2/A3MnIK5G4eEREREdVyLIQUrkOHDnI3QZRKpcKrfZvj+4l90NhDP1Tu9wt38PiXUfgnPl3m1tV81pwNkh/zQWKYDZLCfJAYJycnuZtQaSyEFG7Lli1yN6FCnZu4Y9fkfhhaaqhcyPKjWPUHh8pVJyVkg+TDfJAYZoOkMB9Vc+HCBdja2kKlUiEtLU3u5lRZVlYW5syZg+HDh8PT0xMqlQrr1q0DAJOvKz8/HzNnzkTDhg3h5OSEwMBA7Nu3rxpbLY6FkMJ9+OGHcjfBJG7OdljxcjfMCSoZKvfB7gv4z/oTSM/mULnqoJRskDyYDxLDbJAUq8+HVgNc+xM4/7P+t9Y6Zq6dNWsWmjRpAgA4e/aszK2pupSUFMybNw8XLlxAp06djJ5r3LixSccYN24cFi5ciBdffBGLFi2CWq3GY489hqioqOposiQWQgqnpIXNVCoVxj/cHNsm9kETT3336f6LSXj8yz/x93UOlTM3JWWDLI/5IDHMBkmx2nxoNUDkp8DCdsD6J4DvXtb//ry9fruMBdGRI0ewa9curF27FoCyCyFfX18kJibi+vXriIiIMHrOlAVVo6OjsXXrVnz00UeIiIjAhAkTcODAATRt2hRvv/12dTVbFAshhVPiwmadmrjjl8n9MNy/AQDgVmYenltxFCsir0Cn41A5c1FiNshymA8Sw2yQFKvMh1YDbH0BOPgBkJ1i/FxWsn771hdlK4ZmzpyJcePGYeDAgXBzc1N0IeTg4IAGDRqU+5wpC6pu27YNarUaEyZMMGxzdHTEq6++iqNHj+LGjRtma6spWAgpXEhIiNxNqBI3Jzsse6kr3n/SH/ZqGxTqBHz060X8Z8MJpHGonFkoNRtkGcwHiWE2SIpV5iPqc+Dyb0UP7v8H1aLHl/cCUV9YsFF6P//8M06cOIE5c+YAANq1a1dtU5BrNBqkpKSY9KPT6cx+/itXrlS4z8mTJ9GmTRvUrVvXaHvPnj0BAKdOnTJ7u6SwEFK44hvUlEilUmFsn2b44Y0+8PN0BgAcKBoqdyJOuTcSWgslZ4OqH/NBYpgNkmJ1+dBqgOiVAFQV7KgC/lpp0V4hrVaLsLAwvPnmm4b7Z9q1a4dz585Vy/kOHz4Mb29vk37i4+PNfv5mzZpVuE9iYiJ8fX3LbC/eduvWLXM3S5KtRc/2gLKyshAREYHjx48jOjoa6enpWLt2LcaNG1fpY7322mv4+uuv8fjjj+OXX34xf2MtZMGCBZg9e7bczXggHRq74ZcpfTHrhxjsiklEYmYenlt5DNOHPoTX+7eAjU1FH25UnpqQDao+zAeJYTZISrXn49d3gNuV6DHJywCyk03YUQCykoCVAwFHd9OO3aADMOJj09tyn/Xr1yM+Ph6zZs0ybGvXrh3Wrl2LhIQENGrUqMrHLk+nTp1Mnn1NbHjbg7hz5w4aNmwouU9ubi4cHBzKbHd0dDQ8b0mKKoSKZ6rw8/NDp06dcOjQoSod58SJE1i3bp3hP7qSDRs2TO4mmEVdRzssfqELeh3zRPgvF1Cg1eGTPRdx/FoqFoZ0hqeLPQBAo9XhRFw6MnML4OZkj+7NPGCnZsdmeWpKNqh6MB8khtkgKdWej9sxwPVqnD3sjmXuz8nLy8OcOXPw/PPPIyMjAxkZGQBgGBIWExNjciEkCALq1KmDq1evwsfHR3Q/Dw8PPPLIIw/c9oKCgjJTYXt7e0OtVku+zs3NrcJjOzk5IT8/v8z2vLw8w/OWpKhCqHimigYNGuDEiRPo0aNHpY8hCAKmTJmCMWPGYP/+/dXQSstKSEiQuwlmo1Kp8HLvZuji54FJm//B9dQcHPo3GY8t+hMLQzrhxPV0bDgah5SsknuIvF0d8HLvpnhjYEsWRPepSdkg82M+SAyzQVKqPR8NKrlga15G5Yqb+gGV6xGqokWLFuHmzZtYtWoVVq1aVeb5s2fPYvjw4SYd69q1a3B2dpYsgoDyCxgxUoXNkSNHMGjQoDJtqGjoW0FBAVxcXCT38fX1LTdDiYmJAFBhj5K5KaoQkpqpwlQbN27E2bNn8eOPP9aIQig9veZNOx3QyA2/TO6Ld36Mwa4zibh9Nw8vfH0cQNkRwClZ+Vi47xJO3cjAipe7sRgqpSZmg8yH+SAxzAZJqfZ8VHYomlajnzI7OwVlJ0ooTQW4egMTDgFquwdoYMXS09Px8ccfY8KECXj00UfLPD927FijmePu3LmDRo0aITs72zBs7LvvvsPixYuxYsUKdOnSBVqtFq6urmjXrh3++uuvcs9bXgEjRqqwKW+InSnfv7VabYX7dO7cGQcPHsTdu3eNJkw4fvy44XlLUlQh9KDu3buHmTNnIiwsrFIFVVJSEpKTjcefxsbGmrt5VdK/f3+5m1At6jjaYfHoLujdoh7m/HwO2qJptUXmgsGBi0lYfugKJg+peOrG2qKmZoPMg/kgMcwGSbG6fKjtgJ4T9FNkSxKAHhOqvQgC9IvOarVafPLJJ3B3dy/z/Pvvv280c1z9+vXh7u6Oy5cvIyAgADqdDnPnzsXy5cvRrl07zJkzB4mJifjyyy8lz2uue4SqOsTO1dXV6HFOTg7i4+Ph5eUFLy8vAMDIkSPx2WefYeXKlZg+fToAID8/H2vXrkVgYKBh0VlLqVX/fD5v3jw4OTkhNDS0Uq9bunQpAgICjH6Cg4MBAFFRUYiMjERERATS0tIwduxYACULjoWGhiI2NhZr1qzB9u3bER0djfDwcOTk5BimoCzeNywsDDExMdi8eTM2b96MmJgYhIWFGe0TEhKCnJwchIeHIzo6GqGhoVizZg1iY2MN11W879ixY5GWloaIiAhERkZiz549WLJkCRISEjBx4kSjfSdOnIiEhAQsWbIEe/bskfWatm/fjjVr1uDKlSv469tFqONoCwjS6wupAHy19ww0Wp1VX5Ml36eQkJAad0018X2S65qWLFlS466pJr5PclzTF198UeOuqSa+T3Jd04QJEx74mk6dOgWtVouUlBSkp6cjOzsbt27dglarNUzBXLw4582bN5GTk4PU1FSkpqYiJycHN2/eNNrnSsMnIbQeCgAQ7hs7Uvw4u2FfoO9UXLt2DYWFhbh9+zbu3buHzMxMJCUloaCgANevXzc67vXr11FQUICkpCRkZmbi3r17uH37NgoLC3Ht2jWjfW/cuIG8vDycPn0aixcvxiuvvIKcnJxyr6lhw4a4cOECkpOTDdfUqlUrXLx4EZcvX8bmzZvh6emJhx9+GLdu3cI///yDFi1aICUlBXl5eYa1doqPV3xN+fn5CAwMRI8ePdCxY0f0798frVu3xiOPPIKmTZvikUceQevWrdG/f3/cvXvX5Gu6/3368ssv8X//939Ys2YNAP3aUjNmzEBYWBiuXbtmuKZdu3ahXbt2eP/99/Xv05Ur6N69O5544gnMmjULU6ZMwcKFCzFw4EDExcXh008/LXNN979POp0Of//9t2j2oqIqd3+ZShAq+IZppYrvETJ11rhLly4hICAAW7ZswbPPPgtAP81fQEBAhbPGifUIBQcH4+zZs/D396/ydZC0o1dSMXrVMZP33/JaL/RuWa8aW0REREQP4urVqwCAFi1amO+gWo1+naC/Vupnhyvm6qPvCeo71SK9QePHj8fmzZtx7do10ftdpk2bhoULF+LSpUuGRUjffPNNNGzYEO+88w7at2+PTZs2GdbW8ff3x5o1axAYGFjt7TdFs2bNDEXj/UoPuTt06BAGDRqEOXPmYO7cuYZ98vLyMHv2bGzatAnp6eno2LEjwsPDTZqIo6LsnDt3DgEBASZ/P681Q+Peeust9OnTx1AEVYaPj0+FN6jJJSgoyDpXeTaTzNzKLa5a2f1rspqeDXowzAeJYTZIitXmQ20HDJihL3jijwG56YCTB+DXyyIFULG1a9di7dq1kvssWLAACxYsMNrm7++PI0eOYMOGDWjbtq2hCCooKDAMmbMWcXFx5W6/fPmy0X1HAwcORHn9LY6OjoiIiEBEREQ1tdB0taIQOnDgAPbs2YMff/zR6M0rLCxEbm4u4uLi4OnpWWaVWyWwyg8jM3Jzsq/U/pfvZGFoe4FrD6HmZ4MeDPNBYpgNkmL1+VDbAc37yd2KSvP398eKFStw7Ngx/Pjjj4bt9+7dA2DajGxyK+7dUpJacY9Q8eq5zzzzDJo3b274SUhIwIEDB9C8eXPDOEelKR53W1N1b+YBL1f7CteLLrZg3yUMX/QHdpxMQKFWV61ts3Y1PRv0YJgPEsNskBTmo3r4+/sjJiYG3bp1Q6dOnQzb69Wrh9GjR8PPzw+9evWSsYUVK77HSElq5D1CiYmJyMzMRMuWLWFnZ4f4+Hj8888/ZY4xYcIENG3aFO+++y46dOiAli1bmnz+yo5BrC5paWnw9PSU7fyW8OX+y1i471KF+9nb2qCgsKT4aeLphNf7t8TIbo3haCe9CFhNVBuyQVXHfJAYZoOkmCMf1XKPEMmusLAQtrbVO9jM3PcIKa5HaPHixZg/f77RTBXz58/H/PnzkZmZCQCYNWsW2rVrZ1iwyc/PD8HBwWV+nJ2dUb9+fQQHB1eqCLImq1evlrsJ1e6NgS0xuK3+Hq37e4aKHw9u64NjswZj5vC28HLVD6e7kZaL93acRb9PD2JF5BVk5RdartFWoDZkg6qO+SAxzAZJYT5ITEpKitxNqDTF3SP02WefGc1U8eOPPxrGUr700ktwc3OTq2myKL6ZriazU9tgxcvdsPzQFWw4eh3JWfmG57xcHTCmd1NMHNgSdmobvDGwJcY/3Azfn7iB5ZFXkZCRi+R7+fjo14tYeugKxvZphvF9msHDpXL3HilRbcgGVR3zQWKYDZLCfJAYa7+HqTyKK4TEZqoobd26dVi3bp1ZjmXtcnNz5W6CRdipbTB5SGtMHNgSJ+LSkZlbADcne3Rv5gE7tXHHpqOdGi/3bobne/ph5+lbWHroCmKTspCZq8GX+y9j1R9X8UKgH17r1wIN3BxluqLqV1uyQVXDfJAYZoOkMB8kRqdT3r3ZiiuEyFjxIl21hZ3axuR1guzUNnima2MEd26EfRfuYOnBWJy+mYlcjRaro65hw9E4PNu1MSYOaIlmXsr7V4yK1LZsUOUwHySG2SApzAeJyc/Pr3inByQIAlQq880MrLh7hMhYcHCw3E2wejY2Kgzzb4Adkx7GplcD0aeokNJoBWz96wYGLziEyVtO4vytuzK31LyYDZLCfJAYZoOkmCMfKpUKhYWF5a4xQ8rl7u5erccXBAFarZaFEJUIDw+XuwmKoVKp0Le1Fza/1gvb3+yDR9vXBwDoBGDn6Vt47Ms/8cq6v3AiLk3mlpoHs0FSmA8Sw2yQFHPkw9XVFVqtFomJiSgsrF0TGdVkiYmJ1XbswsJCJCYmQqvVwtXV1WzHVez02XKzlumz6cH8e/selh2Kxc4zidDqSv4q9GzuiUmDWqF/ay+z/ssDERFRbVdYWIiEhATk5OQAAGxtbWFjY8P/31IZgiBAp9MZCmZnZ2c0atRIdJruGj99NhkLCgqSuwmK9lCDOvji+S44OG0gXgz0g72t/q9E9LU0jF0TjSe+isLuGOMiSSmYDZLCfJAYZoOkmCMftra28PPzQ6NGjVCnTh3Y2tqyCKoBoqKizH5MlUoFW1tb1KlTB40aNYKfn59Z1ypij1AVsUeoZkq6m4fVUdew6dh1ZBdoDdtbeLlg4sCWCO7cyFAsEREREZH1YI9QLTNx4kS5m1Cj+NR1xKzH2uHwO4MR+kgbuDvbAQCupmTj7W1nMDDiINYdvobcUkWStWI2SArzQWKYDZLCfJAYJWaDPUJVZC09QgkJCWjUqJFs56/psvMLsSU6Hl//eQ237+YZttdzsccrfZvjpV5N4eZkJ2MLxTEbJIX5IDHMBklhPkiMNWSDPUK1zI4dO+RuQo3m4mCL//Rrgci3B+LjZzqgWT1nAEBqdgEi9v6Lvh8fwCd7LiL5XvXPnV9ZzAZJYT5IDLNBUpgPEqPEbLAQUriWLVvK3YRawcFWjed7+mH/tIH4anQXtG1QBwBwL78Qyw5dQd9PDuB/P53FzfQcmVtagtkgKcwHiWE2SArzQWKUmA0WQgrn5OQkdxNqFbWNCkGdGuLXt/ph7bge6N7UAwCQX6jDhqPXMTDiEKZ9dxqxSfdkbimzQdKYDxLDbJAU5oPEKDEb1VII6XQ6aLXWfzN5TRAdHS13E2ollUqFQW19sO2NPvju9d4Y0MYbAFCoE/DDPzfx6Od/YOLGv3HmZoZsbWQ2SArzQWKYDZLCfJAYJWbDrJMlXL9+HRMmTEBKSgoEQUC9evWwdOlStG7d2lynsBrWMllCWloaPD09ZTs/lTibkIllh65g99lElP5b1a+1F94c2Aq9WnhadJ0EZoOkMB8khtkgKcwHibGGbMg6WcJzzz2H559/Hn///Tf++ecfjBs3Ds8++6w5T0H3CQ0NlbsJVCSgkRuWvNgVv//fAIzq1hi2Nvqi58/LKRi96hieWXYEv5+/A52FFmdlNkgK80FimA2SwnyQGCVmw2w9QoWFhXBwcEBSUhLq1asHALh37x7c3d2RmZkJV1dXc5zGalhLjxBZr4SMXKz64yq2/hWPPI3OsP2h+nXw5qCWeLyDL2zVvE2PiIiIyBxk6xGytbWFv78/vvrqK8O2//3vf2jfvn2NK4KsSVBQkNxNIBGN3J0w90l/HJ45GP8d1Ap1HG0BAP/euYe3tp7C4AWR2Hw8HvmF1XM/HbNBUpgPEsNskBTmg8QoMRtmvUfo33//xXPPPYcWLVogNTUV9+7dw7Zt29CiRQtzncJqsEeIKutungbfHIvH6qirSMkqMGz3qeOA1/q1wAuBfnBxsC33tRqtDifi0pGZWwA3J3t0b+YBO/YmERERERnIeo+Qt7c3GjdujNOnT6OgoAANGjRgb1A1U+J4zNqqrqMd3hjYElEzB2PeU/5o5K6fZjLpXj4+2H0BfT4+gM/3XUJ6dkmRpNHq8OX+y+j90X6MXnUMEzf9g9GrjqHPRwfw5f7L0Gh1YqdjNkgS80FimA2SwnyQGCVmw6w9QkOGDIGXlxc2bNgABwcH/N///R+OHTuGI0eOmOsUVsNaeoRiY2PRqlUr2c5PVafR6vDzqVtYFnkFsUlZhu3O9mq80NMP4/o0w+yfzuLgv8lQASj9F7X48eC2Pljxcrdye4eYDZLCfJAYZoOkMB8kxhqyIVuP0L1793Do0CEsX74cDg4OAID33nsPx48fR0FBQQWvpqr6448/5G4CVZGd2gbPdmuM36b2x/KXuqFjYzcAQE6BFl9HXcOAiEM4+G8yAOMiqPTjAxeTsPzQlXKPz2yQFOaDxDAbJIX5IDFKzIbZCqE6derAz88Pf//9t2HbX3/9hZYtW8Le3t5cp6H7eHh4yN0EekA2NioMD2iAnyY9jE2vBqJ3C/2si1oTOmtVADYcvV7uEDlmg6QwHySG2SApzAeJUWI2yr8zu4q2bt2K1157DU2bNgUAxMfHY8uWLeY8Bd2nUaNGcjeBzESlUqFvay/0be2FDUfj8L+fzlX4GgFAclY+TsSlo3fLekbPMRskhfkgMcwGSWE+SIwSs2HWyRICAwNx5swZLFu2DMuWLcPp06fRrVs3c56C7rN37165m0DVwKeOQ6X2T8nKK7ON2SApzAeJYTZICvNBYpSYDbNOllCbWMtkCTk5OXB2dpbt/FQ9jl5JxehVx0ze39HWBoPa+mBIu/oY9JA36rk6MBskifkgMcwGSWE+SIw1ZEPW6bPJ8saNGyd3E6gadG/mAS9Xe6hM3D+vUIdfz97G9O9Po8cHv2PksiMY+tZnuHznHvhvHVQefnaQGGaDpDAfJEaJ2WCPUBVZS48Q1Vxf7r+MhfsuVbjf4x18YatW4dC/ycjM1ZR53s/TGUPa+eDRdvXRo7knF2IlIiKiGok9QrVMUFCQ3E2gavLGwJYY3NYHAMr0DBU/HtzWB1883xmLnu+Cv997BFsn9MJr/ZqjhZeLYd/4tBysPRyHF74+jq7h+/Dfzf9gx8kEZORwWvvajJ8dJIbZICnMB4lRYjYU1SOUlZWFiIgIHD9+HNHR0UhPT8fatWtN6orbv38/vvnmG0RFReHmzZto0KABBg8ejPDwcPj6+la6LewRIkvQaHVYfugKNhy9juSsfMN2b1cHjOndFBMHthTt4bmanIX9F5Kw78Id/H09HVqd8V91tY0K3Zt64JF29TGknQ9aeLtW67UQERERVaca3SOUkpKCefPm4cKFC+jUqVOlXjtz5kwcOnQITz/9NL788ks8//zz+O6779ClSxfcvn27mlpc/cLCwuRuAlUjO7UNJg9pjSOzBmPLa72w/KWu2PJaLxyZNRiTh7SWHOb29ecf4rX+LfDd673x93uP4IvnOuOJjr6o46CfNV+rE3D8Who+2H0BgxdEYvCCQ/hw9wUcv5qKwnLWJaKahZ8dJIbZICnMB4lRYjbMto6QIAi4ceMGGjRoAHt7e+h0OkPPi7kWVPX19UViYiIaNGiAEydOoEePHia/duHChejbty9sbEq+OA4fPhwDBgzA4sWLMX/+fLO00dJGjx4tdxPIAuzUNmXWCapI6Wy4O9sjuEsjBHdphIJCHf6KS8PvF+5g/4UkxKflAACuJmdjZfJVrPzjKtyd7TCwjTeGtKuPAQ95o66jnVmvh+THzw4Sw2yQFOaDxCgxG2brEUpLS0Pz5s0RFRUFAEhOTjZ6bA4ODg5o0KBBlV7bv39/oyKoeJunpycuXLhgjubJIiYmRu4mkJUSy4a9rQ0ebuWFOUH+iJwxEPtC+2Pm8Lbo1tQDqqKbjzJyNNhx6hYmbzmJrvP24cWvj2FN1DXEp+ZY8AqoOvGzg8QwGySF+SAxSsyG2XqEAJSZptfabz/KyspCVlYWvLy8JPdLSkpCcnKy0bbY2NjqbBqRRahUKrSuXwet69fBGwNbIjUrHwf/Tcb+C3fwx6VkZBdoUagTcDg2FYdjUzHvl/No7eOKR9rXxyPtfNC5iQfUNqZO8k1ERERkPRR1j5C5ffHFFygoKMBzzz0nud/SpUsREBBg9BMcHAwAiIqKQmRkJCIiIpCWloaxY8cCKJk5IzQ0FLGxsVizZg22b9+O6OhohIeHIycnByEhIUb7hoWFISYmBps3b8bmzZsRExNjGG9ZvE9ISAhycnIQHh6O6OhoJCUlYc2aNYiNjUVoaKjRvmPHjkVaWhoiIiIQGRmJPXv2YMmSJUhISMDEiRON9p04cSISEhKwZMkS7NmzR9Zr2r59O6/JDNf066+/Vvqa9v78Awr+/QNvdrLHE5o/seGVnvBMPYtG7k6Gvw+Xk7Kw7NAVPLvsKDrM/gUTVv+JkGkfISu/kO+Tgq6pQ4cONe6aauL7JMc1tWrVqsZdU018n+S6pnPnztW4a6qJ75Mc1+Tg4CD7NVV2JJrZZo1LTU2Ft7c3fv/9dwwePBh37tyBr6+v4bG5Fd8jZOqscff7448/MGTIEDzzzDP49ttvJfcV6xEKDg6Wfda4sLAwfPjhh7Kdn6yXObMhCAIu3r6H/Rfu4PcLSTh1I6PMPvZqG/RqWQ+PtPPBkHb1jYonsj787CAxzAZJYT5IjDVko7KzxtXKQujixYt4+OGH4efnhz/++AN16tSp9Pk5fTbVZkn38nDwYhJ+v5CEqMspyNVoy+zTtkEdPNq+Poa0q4+OjdxgwyF0REREVI1q9PTZ5nDjxg0MHToUbm5u2L17d5WKIGuixMWryDKqMxs+dRzxXA8/rBrTHSf/9yjWjuuBFwL90KCuo2Gfi7fv4asDsQhechiBH+3HzG1n8Nu528gpKDTpHBqtDkevpGLP2UQcvZIKDaf0Nit+dpAYZoOkMB8kRonZMOtkCdYuNTUVQ4cORX5+Pvbv31+lhVStzc6dO+VuAlkpS2XD0U6NQW19MKitD4RgAedu3TVMzR2TkAkASL6Xj29P3MC3J27AoWjWuiHtfDCkbX00cHM0Op5Gq8OyQ1ew4WgcUrIKDNu9XR3wcu+meENiEVkyHT87SAyzQVKYDxKjxGzUyG8TiYmJuHjxIjQajWFbdnY2HnvsMSQkJGD37t1o3bq1jC00n+Kb1YjuJ0c2VCoVAhq5YeojbbBzcl8cmzUEHzwdgMFtfeBgq/+4yS/U4cDFJLy7/Sx6fbQfQV9F4YvfL+FsQiYKCrWYsOEEFu67hNRSRRAApGTlY+G+S3h949/sHTIDfnaQGGaDpDAfJEaJ2VBcj9DixYuRkZGBW7duAdBXnzdv3gQATJ48GW5ubpg1axbWr1+Pa9euoVmzZgCAF198EdHR0XjllVdw4cIFo7WDXF1dDbPAKc26devkbgJZKWvIRgM3R7wY2BQvBjZFTkEhDsemGiZcSMnKBwDEJGQiJiETX/x+Ga4OtsjK1w+du//mxeLHBy4mYfmhK5g8pGb8Y4ZcrCEfZJ2YDZLCfJAYJWZDcT1Cn332GWbPno1ly5YBAH788UfMnj0bs2fPRnp6uujrTp06BQBYs2YNXn75ZaOfqVOnWqDl1WPBggVyN4GslLVlw9neFo+2r4+Pn+2I6LAh2DHpYUwe3ArtfOsa9ikugqSoAGw4ep29Qg/I2vJB1oPZICnMB4lRYjbM1iPk5uaGgwcPonPnzgAAT09Po8fmEhcXV+E+69atK1OVmvI6JRo2bJjcTSArZc3ZsLFRoXMTd3Ru4o5pQx/CzfQcrI66hrWH4yp8rQAgOSsfG4/GYVT3JqjjaFft7a2JrDkfJC9mg6QwHyRGidkwWyFka2uLAQMGGB7b2dkZPabqkZCQIHcTyEopKRuNPZwR2NzTpEKo2LxfLmDeLxfQtJ4z/BvWhX9DN7RvWBf+DevCp45jxQeo5ZSUD7IsZoOkMB8kRonZUNw9QmRMajgg1W5Ky4abk32VXnc9NQfXU3OwO+a2YZt3HYei4khfIAU0dEMTTyeoVFzLqJjS8kGWw2yQFOaDxCgxGyyEFK5///5yN4GslNKy0b2ZB7xc7ZGaVVBmooTSVAA8XOzxwdMBuJh4D+du3cX5W5m4lZln2Cf5Xj4O/ZuMQ/8mG7bVcbBFu1LFkX/Dumjl41prp+JWWj7IcpgNksJ8kBglZsMs3wA8PT2xe/ducxyKKmnJkiVyN4GslNKyYae2wZjezSSLIEB/j9D4Ps0wIsAXoY+2wddju+PIrCE4OftRbHo1ELNGtMVTnRuilY8rbEp1AN3LL0T0tTSsPRyH6d+fxohFf8J/zl4EfRWFd344g41H4/D39XSTF3xVOqXlgyyH2SApzAeJUWI2VIIgVPS9o0I2NjbYtGkTXnjhhXKf/+eff3D06FFMmjTpQU9lNc6dO4eAgACcPXsW/v7+cjeHqEbQaHV4fePfOHAxCSoYT6Fd/HhwWx+seLmbST05OQWFuHhb32t0LiET527dxb+376FAYsY5GxXQwtvVaGidf8O6cHeu2tA9IiIisozKfj+v8tC4w4cPIzExEV27dgUAybH3Fy5cwJQpU2pUIWQtgoKCFLmSL1U/JWbDTm2DFS93w/JDV7Dh6HUkF601BABerg4Y07spJg5safJwNmd7W3T180BXPw/DNo1Wh9ikLH1xdEtfHF24dRf3iqbu1glAbFIWYpOy8NOpW4bXNXJ3MkzGUFwc+bo5Kva+IyXmgyyD2SApzAeJUWI2qtwjFB4ejjlz5hi+BLRu3RoPP/wwOnbsiI4dO6JTp07w9PQEAERERGD+/PnIzMw0X8tlxh4houql0epwIi4dmbkFcHOyR/dmHtV2P49OJ+BGeo5RcXTu1l0k38uXfJ2Hs52hKGpfVCA193KB2qbqxZElr5uIiKgmqez38wcaGnfp0iWcOHECL730EgICAnD37l3Ex8frD6xSwdfXF40bN8bp06cxaNCgGnUfkbUUQmPHjsX69etlOz9ZL2bjwSXdyyuajKGkQLqemiP5Gic7Ndr51jEUSP4N3dCmgSscbNWSr9NodVh26Ao2HI1DSlaBYbu3qwNe7t0Ub1SiJ8wUzAeJYTZICvNBYqwhGxYthIoFBgbinXfewdNPP427d+/izJkzhp/4+Hg0b94c7733Hnx9fR/0VFbDWgqhtLQ0Q88bUWnMRvW4m6fBhaIeo+IepNikLBTqxD9KbW1UaOXjWqo40vcgFS8Gq9HqMGHDCRz8N9ks90aZgvkgMcwGSWE+SIw1ZMNi9wiVdvz4ccOf69ati759+6Jv377mODRVYPXq1ZgxY4bczSArxGxUj7qOdghsUQ+BLeoZtuUXanHpdlapYXWZuJB4D7kaLQCgUCfg4u17uHj7Hn74p+RYxYvBZuZqcDg2FQDKzJpX/PjAxSQsP3QFk4e0Nst1MB8khtkgKcwHiVFiNriOkML17NlT7iaQlWI2LMfBVo0Ojd3QobGbYZtWJ+BaSjbO3cosGlqnL5DSczSGfYoXgzWFCsCGo3GVmixCCvNBYpgNksJ8kBglZoOFkMLl5ubK3QSyUsyGvNRFw+Fa+bjiqc6NAACCICAxM89oUoaT19ORkl1QwdH0PUPJWQUYEHEQrX3qoJGHExq5O6Fx0e9GHk7wqeNo8kQNzAeJYTZICvNBYpSYDRZCCnflyhW5m0BWitmwPiqVCg3dndDQ3QmPtq8PANhzNhETN/1TwStL3MrIw62MvHKfs1Or0MDNEY3dnQ2FUiMPJzQu+u3r5gR7W31vEvNBYpgNksJ8kBglZoOFkMIFBwfL3QSyUsyGMrg5VW6h1u5NPZCr0SIhIxcZpYbZAYBGK+BGWi5upJX/r3IqFeBTxwGN3J1Qz6kzPtlzsUyx5Gxv+f8tcMpw68LPDpLCfJAYJWaDhZDChYeHY/ny5XI3g6wQs6EM3Zt5wMvVHqlZBWUmSihNBf2islsm9DIUCdn5hUjIyEVCei5uFv9OzzFsS7pvHSRBAO7czcedu/rt+y5llDmPh7NdqWF3zoZCqXgYnpuTndkWkbX0lOFkGn52kBTmg8QoMRtmmT47Pj4e3t7ecHJyKvf53NxcJCcnw8/P70FPZTWsZfpsIlK+L/dfxsJ9lyrcb9qjbSo1a1x+oRaJGXlGxdLN9BwkpOciISMXtzPzJKf9Lo+Lvdp42F2pYqmxuxO8XB1gY8J9SnJMGU5ERDWbLNNnN2/eHBs3bsQLL7xQ7vM///wzXnjhBWi1WnOcjkoJCgrCzp075W4GWSFmQzneGNgSp25k4MDFJMmiYOLAlpU6roOtGs28XNDMy6XMc0FBQYj86WfcuVtSKCVk5OLmfb1K+YU6o9dlF2hx6U4WLt3JKvec9mobNHR3LCmWiu5XKp7UoYGbI+zUNlh26AoO/psMwHJThpNp+NlBUpgPEqPEbJilEKqoU0mj0cDGhv+iVx2UFjiyHGZDOezUNljxcjcsP3QFG45eR3JWyZA2L1cHjOnd1GzTZhcrzkfx5A09mpXdRxAEpGYXGIqkkmIpBzeL/nwvr9DoNQVaHeJScxAnMi24jQqoX8cByVkVz5SnnzL8utmvnaTxs4OkMB8kRonZqHIhdPfuXWRkZBgep6amIj4+vsx+GRkZ2Lp1K3x9fat6KpIwceJExY3HJMtgNpTFTm2DyUNaY+LAlhaZOMCUfKhUKni5OsDL1QGdmriXu8/dPI2+QCoulu4bfpdyX8GjE4DEu/nlHut++inD8xGy/ChaeLvC08UOHi728HDW/3i62Ou3OdvDzckOtgorlqx1kgh+dpAU5oPEKDEbVb5H6P3338e8efNM2lcQBMyfPx9hYWFVOZVVspZ7hBISEtCoUSPZzk/Wi9kgKZbKR17RDHele5Wir6UiOi7d7Odyc7KDp4s9PJz1xZGHi33R46JtpR57uuiLJ1PXXTIna58kgp8dJIX5IDHWkA2L3SM0dOhQuLq6QhAEvP322xg9ejS6du1qtI9KpYKLiwu6deuG7t27V/VUJGHHjh2YNGmS3M0gK8RskBRL5cPRTo2W3q5o6e1q2Hb0SipGrzpm8jGaejpDo9UhNbugzD1LpWXmapCZq8E1E4+rUhUVT0VFU3EB5eki9vjBi6f7J4koLSUrHwv3XcKpGxmyThLBzw6SwnyQGCVmo8qFUO/evdG7d28AQHZ2Np599lkEBASYrWFkmpYtK3fzNNUezAZJkTMflZ0y/PdpAwxFQW6BFmk5BUjPLkB6TgHSsvV/TsvRIKP4cU4B0rL1j1OzC1AgUjwJApCRo9Gvx5SSbVLbVSrA3amod8nZHu7O9oYhe55FQ/Y8Sg3ZKy6eimfSU8IkEdWZDWsdDkim4/9bSIwSs2GWyRLmzJljjsNQFYhNWU7EbJAUOfNhp7bBmN7NKpwyXAAwpndToy/KTvZqNLLXz0BnCkEQkKvRFhVMGqTnGBdQ6TkaQ2GVll2AjBwN0rILUKAVL57SczRIz9HgKkwrnmxUgLuzPdydbBEvstjt/dYcvobgLg3h5mwPF3tbiw7hq45sWPtwQDId/99CYpSYDbMtqJqXl4cffvgB//zzDzIzM6HTGf9PRKVSYfXq1eY6HRWJjo7GgAED5G4GWSFmg6TInY/qmjL8fiqVCs72tnC2t0VjD9NeIwgCcgq0ht6l9ByNoVAqLqTSszVlHosVTzoBSCt6vanSczTo9+khw2NHOxu4Ouivw8XBFi72av1vBzVcirc5FG0rs0/Z/ezVNqIL45o7G0oYDlidalovmNyfHWS9lJgNsyyoev36dQwaNAhxcXFwd3dHZmYmPD09kZGRAa1WCy8vL7i6uuLq1avmaLNVsJbJEtLS0uDp6Snb+cl6MRskxRryodHqyp0y3LuapgyvToIgILtAW6ZgSsvWGIbxXUi8i3/iM+RuKgDA1kYFFwfbouLKuKiyhRaedZ1FiqrSBVXJY2d7tWhhVV0LBlu7mtoLZupnR00rAKli1vD/FVkWVJ0xYwYyMzNx7NgxtGjRAj4+Pvj222/x8MMP48svv8TixYuxd+9ec5yK7hMaGor169fL3QyyQswGSbGGfFh6yvDqpFKp4FpUWDTxdC53n8pOEvGfvs3RwM0RWfmFyM4vRHaBVv87X/87p6AQWfmFyCnQGvbRmfhPm4U6wTC5hDmoVICzXdkeKCd7NY5eSTXpGF9HXUPP5h5wcbCDg60N7G1t4GCrhoOtDRzs9H+WY5a/qqjJvWAVfXbU1ALQVLWxACy+5vBPF2D229MUdc1m6RHy8vLCG2+8gfDwcKSlpcHLywv79u3DkCFDAACvvPIK7ty5g127dj1wg62FtfQIERGRMmi0OvT+aL/Jk0QcmTW4Ul8mBEFAfqFOXxzla4uKpLLFUvGfc/ILkZWvNdonO994f7GJJuRia6MqKoyKCqTiYsmu1J9LFU6GfcrZ3159/34VH8fUtapqcy9Y6QJQbMirEgvAitTGAtAar1mWHqGcnBw0a9YMAFC3bl2oVCpkZmYanu/duzemT5/+wOfJyspCREQEjh8/jujoaKSnp2Pt2rUYN26cSa/PyMjA22+/je3btyMnJwc9e/bEggULykz7rSRBQUGKXMmXqh+zQVKYD8t7kEkiTKFSqeBop4ajnRpwrXh/MUFBQYgqyoZGq0NOvhbZBca9UiVFlhY59/dYldonMTMXN0ycIMIUhToBhQVaZBdozXbMylAXF2IShZOd2gZHYk3rBVvxx1W4OdvB0VYNW7UKdmob2KlVsLWxMTy2tVHBttR2O7X+sa1N0fNqFexsbGBnW/K82DBFc5D67FDCrIjVoXQBaIdC9LK5BDdkIROu+DurjaJ7AMXUlGs2SyHk5+eHmzdv6g9oa4tGjRrh2LFjeOaZZwAA58+fh6Oj4wOfJyUlBfPmzYOfnx86deqEQ4cOmfxanU6Hxx9/HKdPn8aMGTPg5eWFpUuXYuDAgfj777/RurUy/0LyiwyJYTZICvMhD0tNEvEgSmfDTm0DN2cbuDnbVelYlR0OOGtEW7T0dkV+oQ75hVr9b03R7+JtGt19z5f6s8Q+eYVaPOgYGK1OP5FGToEWwIMPK8zKL8T/fjr3wMe5n9pGZVQolRRQ+qLJtpyiyt62bNFVev/iouzhNyOw4Ld/SxVr+udUKhVW/lFyL7gtCtG91JfjE7o2KCz62rk66hoCW3gahjvaqFRQ25T6UalgYwOjx2obFWxK/blkP/mHSy47dAV//puIyeqfMcZ2H7xVJZ0BSYIbNhY+imUXn8TyQ+41pgCsKddslkJo8ODB+OmnnwzTaI8bNw4fffQR0tPTodPpsHHjRowZM+aBz+Pr64vExEQ0aNAAJ06cQI8ePUx+7bZt23DkyBF8//33GDlyJAAgJCQEbdq0wZw5c7B58+YHbp8cQkND8fnnn8vdDLJCzAZJYT7kYae2wYqXu5U7SYSXlUwSYc5sVHbNqFf6Nq+2axcEAYU6oeLiSqNDgbb87aYUYEn38hGflmM4r1RBUF20OgHaomu1NFsU4g2pL8faJ5GRC4SsML1ArkiZgkkF2KptigosGAom2/uKKRuVvjg0FGJFBZitjU3RfpDYT388APjl1HWstFuIwepTZe7T80ImptltQ2ebK/i/yOkQoP8csFEBNioVVEW/bVSAjY2+N8+m1Db9Y1U5+5d+vqSdYs/b2FTueMXbVEWvVZd6XqvTYdPhWJOu+d0j78j+mSbFLH8T33nnHfz111/Iz8+Hg4MDwsLCcOvWLWzbtg1qtRovvPACFi5c+MDncXBwQIMGDar02m3btqF+/fqGXioA8Pb2RkhICDZt2mRou9IobQVfshxmg6QwH/Kx9kkizJmN6h4OWBkqVUnvhatD9RUixb1gphQEhbDFkhe6omNjN/2wP60OGq2AQl3Rb60OhToBGq0OhaW3F/0u3q4p2q/06/XbpY9VULxdK0Cjq+hYRa8v1KFQEMrtXbNFoUlfjl/XhJq1GCwu/OQyWb0Dg+1OAdCvG1Za8eMh6pN4WbMDC/c9bdnGVZPJ6h9NuuaTedtwIq4HeresZ9kGmshsQ+P8/PwMjx0dHfH111/j66+/NsfhzeLkyZPo2rUrbGyMP2R79uyJlStX4tKlS+jQoUO5r01KSkJycrLRttjY2Gpra2X88ccfaNWqldzNICvEbJAU5kN+dmobq/xyYO5slB4OaIdCdCt9L4GuDTSwlX04oDl1b+aB+i42+KjAhH8tt38HQ/3rW0UBbKo1a9Zg/Pjx0OoEo8Lq2LVUnN/yHgarTwGQ/nI8UbcTLo++gzb160CrE6ATBGh1QKFOZ/izTidAW9SLpysqdPTPldomCOXsBxP3u+94RX/W6VDufqWPpS36c6FOgEaTjzHCPuiEstdcmk4Axtj+huXaoCoUgQJUEGBj+NFBBQFq6GADAaqi38U/xo91UKlK/mxjdCyd+GuK/qxWFf+55HlbaPAf290QBP2MkRVd88ns/wGwvs86AFDO37wHlJiYCF9f3zLbi7fdunVL9LVLly5FQECA0U9wcDAAICoqCpGRkYiIiEBaWhrGjh0LQH8zIaAfYhAbG4s1a9Zg+/btiI6ORnh4OHJychASEmK0b1hYGGJiYrB582Zs3rwZMTExCAsLM9onJCQEOTk5CA8PR3R0NP7991+sWbMGsbGxCA0NNdp37NixSEtLQ0REBCIjI7Fnzx4sWbIECQkJmDhxotG+EydOREJCApYsWYI9e/bIek3bt2/nNZnhmrZv317jrqkmvk9yXZOHh0eNu6aa+D7JcU3Ozs5mvabr167C7fQ32PrQHzhi/19stZ+PFfZfYKv9fBxxmIxlPj9hpNdtrFy+rEa8T18sXIC5LttNKgimYSP27/vN6q+pdPaOHTuGW7du4b+T3oSjnRovjHoGHi72+HnxXIyz21fhFO46AXjF9lcMc7qMzMivoT79HRonHkTijvkY5noV/3wxHiPrXcephS9gdL0rKNwZhgFZe9Hy/HK0Ob8cw3N2od7+WZjsfRK6jS/h/7z/Qp0fXsG0uofQ9cR7GJu7Ec/c/gpBcZ9gms1W9D/xFj7z3oMe+1/GIu9fMCJ6AhbW3YIJ8WGYq1mEuXmfYWbye1jpsgqTY9/Ad/XX47/nx+Inn68xN2EifnD7Asty3sZmmznYZj8X63NDcbDep1iT8RqiG3yK7fkT4a3KlCyCit93H1UmztedghiH/+By3Tdx0fk1/Ov8H8S6TsBFh3G4Vuc/uGj/Eq65jMdlhxdxzellXHV8AXGOL+Ka40u44vgyLjuOwb+O43DRcTzOOb6KGMf/4IzjBJxyfB3/OE7ECcc38JfjJBx3/C+OOk7GYce3EOUwFX84hOKQwzQccJiO/Q4zsM/hbex1eAe/OszCLocw/OLwHn52mI0dDv/Djw5z8YPD+/jeYR622s/HFvsP8I39R9ho/zHW23+C1fYL4abKkSyCSl/zr59PMUv2TPnci4qKkm7UfcwyfbYciu8RMnXWOLVajddffx1Lly412n7gwAEMGTIE27dvNxQ39xPrEQoODpZ9+uzo6Gj07NlTtvOT9WI2SArzQWLMng2tBtj6AnD5NwhQQVXqbiHD49bDgOe/AdRVm5TBqmg1EBa2A7LLriFUmgAALj5Q/d95wMYW0GkBnUb/30tXWPS7vMeFJdu1BeLPlXlc3jELpI9fzmtys+/ByV5ddP5SrynM0/+Z6D6FIzfANuApi5xLlumzlcDJyQn5+flltufl5RmeF+Pj4wMfH59qa9uD2Lt3L7/MULmYDZLCfFgBrQaIPwbkpgNOHoBfL6soBMyejajPgcu/AYBREWT0+PJeIOoLYMAM853XFMVf4Avzi34X/VmbX2qb2G+R5zJvQpWdXOGpVQCQnQTMrw8I8kwHXhVOAJAtdyuqSKUGbNRlfz/Itvy7wK2Tpreh9TCgbkNAZVPOj0pkuwn72Kgf/BiSz6tL/px4Btj9fyZfsq2LZxXeLMuoNYVQ8Yxz9yve1rBhQ0s3ySymTZsmdxPISjEbJIX5kJFWoy8OolcCpb8wu/oAPV4D+obKWhCZNRtajf46y0wWfj8VcHw50C4IEHQVFCAmFiSm/LaGAsTSbbCx0+fLxg5Q25Y8Nmyz0/dQlbePjS0KBRvY2jsa76e2B+7dBs79aHo7+s8AfNrfV2jYlvpSX3qbGrCxkdhme1+RYlP+tupYX6myPYA1oeezYWcIkR+Zfs1+vSzUsMqrNYVQ586d8eeff0Kn0xlNmHD8+HE4OzujTZs2Mrau6saNG4fvvvtO7maQFWI2SArzIZNSw8Rw/1eIrGTg4AfAzROyDhMrNxuCoC8cCrKB/Hv63wVZQH6W/ndBVtnnCrKBtGvGxZ4oAchJAZYGVss1VR8VYOcE2DoAto76gkCnA+7eMP0QAc8Cni3KKUhsxYsWo0Kl+LG9xHNFj23UD1wMvBASgu++21j2Ca0GiPsTyE5BhUWvqzcwYKbyCwIAUNtB1XOC/u+uBBUA9JzAa7YyZimE4uPj4e3tLTq8LDc3F8nJyUYzy1WnxMREZGZmomXLlrCz0//HHzlyJLZt24Yff/zRsI5QSkoKvv/+ewQFBSly6mwA/CJDopgNksJ8yKTUMLGyXxbNOExMpyspRooLlXyxgqX4Of3j7x7LAVYOKrVv0T7W0HtyP5WNvgApLkRM/m2m19jYli0stBpgYTvTC4KnV1j1F8X7iX52qO30X3or+HIMCEAP6/5yXGl9Q/X/gHF5r/R9cH2nytdGc6sh12yWQqh58+bYuHEjXnjhhXKf//nnn/HCCy9Aq33wD9HFixcjIyPDMMvbzp07cfPmTQDA5MmT4ebmhlmzZmH9+vW4du0amjVrBkBfCPXq1Qvjx4/H+fPn4eXlhaVLl0Kr1eL9999/4HbJJSgoiCvEU7mYDZLCfMigMsPEji0BGnbSD+Eq3etiKFjulSpSih6XKmagyZE4fjVTqQEHV8C+jv5aKtM70nca4NvRhMJEohCRWw0vCCQ/O0p9OS6b86LHCvhyXGlqO30vbtQXUP21EshKMjylcvXWv899pyruvZZUQ67ZLLPG2djYYNOmTaKF0KZNmzB+/HhoNA8+m0izZs1w/fr1cp8rLnzGjRtXphACgPT0dMyYMQM7duxAbm4uevTogc8++wzdu3evdDsqOysFERGJsNJJA6pEpwXyMoGc1Pt+0oDE05W7h8JSbJ0Ae5ei4qX4577HDkXb7OuUeu7+x0U/tg4lxUlle0dCzyv3vS9NqwG2vlhxQVAT7he5n1aj79G878ux/h44ZXw5fiA16fPMVFZ0zZX9fl7lQuju3bvIyMgAoC9OFi1ahKeeKjs1XkZGBsLCwnDmzBnEx8dX5VRWyVoKobCwMHz44YeynZ+sF7NBUqwiH1Y+aQB0OiAvQ1/ElC5qctOMC5zSz+emQ/oL/4NSAQ5FxYehYCnvcTnFTHmP7V31956UYvZsRH5qQu8IgEHvWX7WuOpUQwsCk/NhRV+OyTKs4f8rFps++/PPP8e8efMAACqVClOnTsXUqVPL3VcQBMyfP7+qpyIJo0ePlrsJZKWYDZIiez4sPWmATgfkZ5YtanLuK2py7ytqBN2Dn7uYja1+XRZTDf8EaNrHuNixc672oWBmz0ZtHi41YIb+umpQQWByPtR2QPN+1dsYsiqy/3+lCqpcCA0dOhSurq4QBAFvv/02Ro8eja5duxrto1Kp4OLigm7dulVp+BlVLCYmBh06dJC7GWSFmA2SIns+HmTSAEEoNfwszcSemjTzFjVqe8C5HuDkCTh76v/sXK/sn51KPVbbA5+3N32YWI9XZfnCbPZslLqXoGzviHLuJaiyGlYQyP7ZQVZLidmociHUu3dv9O7dGwCQnZ2NZ599FgEBAWZrGBER1VAmTxoA4M8FwK1/7rvvJs28M5jZ2N1XxHiWKnLqlfrxKPmzvWvVemZq8E30kmpo7wgRKZtZZo2bM2eOOQ5DVaC0ypssh9kgKRbNR2E+kHkTyIgHMm8AcVEmri0DoDAX+He36eeysb2viLn/d72yPTkOdSw385gCholVazZqWO9IbcT/t5AYJWbD7AuqZmVlIT09HeXNwWCpdYRqky1btigyeFT9mA2SYtZ85N8DMm7oi5yM+JKCp3hb1p0HO37dRoBHM4memlK9NQ51rW865dIUMEyMnx0khfkgMUrMhlmmz87Ly8P777+P1atXIzU1VXQ/c6wjZC2sZdY4IqJqJQj6oWiZ8frCxqjIKdqWl1G9bRj7S83sReCsWkREZmWxWeNKe/PNN7F+/XoEBwejX79+8PDwMMdhyQRcFJHEMBsKZaEvx4Z86HRA1m3pHp3KLs5pYwe4NQLcmgDufvoftyaAexP9bxcf4MtOpk8a4NfrQS7VelnpMDF+dpAU5oPEKDEbZukRcnd3x3PPPYcVK1aYo02KwB4hIjKr6lpTp7AAuJtgXNiULnYyEwBdJRe7tnMuKWwMRU6pYse1PmCjlj5GbV1bhoiIqo0sPUIqlarM1NlkGSEhIfjuu+/kbgZZIWZDQR5kTZ2CnPuGqsWXKnhuAPcSUekFPh3di4qcpsY9Oe5NADc//b06D3ofjgImDait+NlBUpgPEqPEbJilR2jcuHHIzs7G999/b442KYK19Ajl5OTA2dlZtvOT9WI2FMTU3pHWQ4F6rUvuzcm8oZ9OurJc60NbtzHUHk1LFTmlenQc6lT+mFWh1YhMGuBjFZMG1Fb87CApzAeJsYZsWKRHKC0tzejx7NmzERISggkTJuD111+Hn58f1OqywyI8PT2rcjqSsGDBAsyePVvuZpAVYjYUojJr6lz+rdQipCJU6qL7c/zu68kpKnbqNgLsHPFheDhmT5A5H1xbxirxs4OkMB8kRonZqFIh5OXlBdV9wyIEQcDJkyexevVq0dfVpFnjrMWwYcPkbgJZKWbDSmkLgZR/gcQzwO0zwLU/TF9TB9BPRODRrOxwteLHdXwBdcUf7VaVDyudNKC2sqpskNVhPkiMErNRpULof//7X5lCiOSRkJAgdxPISjEbVqAgB7hzDrh9uqTwuXMe0OZX/ZgjVwPtn3rgpjEfJIbZICnMB4lRYjaqVAjNnTvXzM2gqkpPT5e7CWSlmA0Ly0nTFzrFBU/iGSD1MiDoxF+jttf34qRdMf08TuYZYsx8kBhmg6QwHyRGidkwy6xxJJ/+/fvL3QSyUsxGNREE/XTUpQue22f0ExdIcagLNOgANOgI+HbU//Z+SP/cwnYWX1OH+SAxzAZJYT5IjBKzYWOWg9jYQK1WS/64uLjgoYcewsSJE3HlSiX+9ZMkLVmyRO4mkJViNsxApwWSLwEx24DfZgMbngIiWgKf+wNbRwOHPgL+3VW2CHKtD7R6FOg3DRi1HphyEph5HRi/GxjxMdD5BaBBgP7eGLUd0HMCKp7iWtDPpGamSQSYDxLDbJAU5oPEKDEbZpk+e+7cufjpp59w7tw5jBgxAq1atQIAXL58GXv27EGHDh0wePBgxMbGYvfu3XB0dMQff/yBTp06PfAFyMVaps8mIjMpzAeSzhv39Nw5B2iypV/n0bykh8e3k/53nfqVO7dWA2x9seI1dcpbR4iIiIgAyLSgasOGDZGSkoKLFy+iRYsWRs/FxsZi4MCBaN++PSIiInD58mX07t0bYWFh2LVrlzlOX6sFBQVh586dcjeDrJDis6HVVN+Uynl3gTtngcRSkxgkXwR0heKvsbEFvNsaD21rEAA4uj14e9R2+iKn3DV1vKtlTR3F54OqDbNBUpgPEqPEbJilR6h169Z49dVX8c4775T7/EcffYS1a9fi0qVLAID33nsPS5YsUeRNVcXYI0RUTbQaIOpz/do6paeVdvUBerwG9A2tXEFw705RD89p/e/bMUDaVenX2DkD9QNK9fR0BLzbAXaOVbumyqjOApCIiKgGk6VH6ObNm7C1FT+Ura0tbtwoGUPfrFkz5Oc/wPSxZDB27FisX79e7maQFVJkNrQaYOsLRYuG3jdFf1YycPAD4OaJ8oeICQKQHldS8BT39GTdkT6nk2fZoW31WgI2ZReFtggLramjyHyQRTAbJIX5IDFKzIZZeoS6d++O9PR0HDlyBPXrG4+Nv337Nvr06QNPT0+cOHECABAWFoatW7fi6tUK/lXWillLj1BaWho8Pc0znS7VLIrMRuSn+mKnIgNnAe2C7pu5LQbIz5R+Xd3GxkWPb0egbiOgFq6Lpsh8kEUwGySF+SAx1pANWXqEPvvsM8MkCcHBwYbJEmJjY7Fjxw5oNBqsWbMGAJCXl4d169ZhxIgR5jh1rbd69WrMmDFD7maQFVJcNrQa/XC4MpMFlOPQR/ofUSrAq7Xx/Ty+nQBn/s+7mOLyQRbDbJAU5oPEKDEbZimEBg4ciCNHjmDOnDn48ccfkZubCwBwdHTEI488grlz56Jr166Gbbdu3TLHaQlAz5495W4CWSnFZSP+mPE9QaZS2wM+7Y0Lnvr+gL2L+dtYgyguH2QxzAZJYT5IjBKzYbYFVbt06YKff/4ZOp0OSUn6GY98fHxgY2OWpYpIRHHRSXQ/RWVDkwdcPVS51/ScAHQdq1+UlJMJVJqi8kEWxWyQFOaDxCgxG2YrhIrZ2NigQYMG5j4sieDitCTG6rORlQRc2gtc2gNcOVjxej33a/ekfvpqqhKrzwfJhtkgKcwHiVFiNqpUCMXHxwMA/Pz8jB5XpHh/Mp/g4GC5m0BWyuqyIQj6BUv//VX/k/A3KrwXqFwq/do6fr3M3cJaxeryQVaD2SApzAeJUWI2qjRurVmzZmjevDkKCgqMHlf086Dy8/Mxc+ZMNGzYEE5OTggMDMS+fftMeu3vv/+OQYMGwcvLC+7u7ujZsyc2btz4wG2SW3h4uNxNICtlFdkozAdi9wO7ZwBfdASW9QEOhAMJJ2AogpzrAZ1eAEI2AP2mm3BQQb/AKIfDPRCryAdZJWaDpDAfJEaJ2ajS9Nnr1q2DSqXCmDFjoFKpDI8rMnbs2Co1stjo0aOxbds2TJ06Fa1bt8a6devw119/4eDBg+jbt6/o637++WcEBwejd+/eGD16NFQqFb777jv88ccfWLhwIUJDQyvdFmuZPpvI6mSn6tcBuvQrEHsAKLhXdh/vtkCb4cBDI4DGPUrW7NFqgK0vApf3ouzscUWPWw8rfx0hIiIiqtUq+/3cLOsIWUJ0dDQCAwMRERGB6dP1/2qcl5eHgIAA+Pj44MiRI6KvHTp0KM6dO4erV6/CwcEBAFBYWIi2bdvCxcUFp0+frnR7rKUQCgoKws6dO2U7P1kvi2VDEICUS/rhbpf2ADeOA4LOeB8bW6BpH+Chx4A2wwDPFuLH02qAqC+Av1bq7yMq5uqj7wnqO5VFkBnws4PEMBskhfkgMdaQDVnWESqWn5+Pf/75B0lJSXj44Yfh5eVltmNv27YNarUaEyZMMGxzdHTEq6++irCwMNy4cQNNmjQp97V3796Fh4eHoQgCAFtbW7O2Ty5yB46sV7VmQ6sB4o+W3O+Tfq3sPo7uQOuhwEPDgZZDACd3046ttgMGzNAXPPHHgNx0wMlDf08QCyCz4WcHiWE2SArzQWKUmA2zzW395ZdfwtfXF3379sUzzzyDM2fOAABSUlLg5eVlWFC1qk6ePIk2bdqgbt26RtuL5yw/deqU6GsHDhyIc+fOYfbs2YiNjcWVK1cQHh6OEydO4O23336gdslt4sSJcjeBrJTZs5GbDpz5Htj2CvBpS2B9EHBsqXERVK8V0Pu/wLhdwIwrwLOrgIBnTS+CSlPbAc37Ae2f1P9mEWRW/OwgMcwGSWE+SIwSs2GWHqG1a9di6tSpeP755zF06FC88sorhue8vLwwePBgbN261Wh7ZSUmJsLX17fM9uJtUou0zp49G9euXcMHH3yA+fPnAwCcnZ3xww8/4Kmnnqrw3ElJSUhONl7oMTY2tjLNrzazZ8+WuwlkpcySjdQrJUPerh8BBK3x8yobwK93yf0+Xq0f/JxkEfzsIDHMBklhPkiMErNhlh6hBQsW4KmnnsLmzZsRFBRU5vlu3brh3LlzD3SO3Nxco6FtxRwdHQ3Pi3FwcECbNm0wcuRIbNmyBZs2bUL37t3x0ksv4dixYxWee+nSpQgICDD6KZ4iMCoqCpGRkYiIiEBaWpphQoji/w6hoaGIjY3FmjVrsH37dkRHRyM8PBw5OTkICQkx2jcsLAwxMTHYvHkzNm/ejJiYGISFhRntExISgpycHISHhyM6Ohrvv/8+1qxZg9jYWMOkD8X7jh07FmlpaYiIiEBkZCT27NmDJUuWICEhwVC1F+87ceJEJCQkYMmSJdizZ4+s17R9+3Zekxmu6eWXX670NW35ZiP2ff0+kr+ZiOQ5TYGvugK/vQvE/WkogvJgj1TfgfjLbwI2NZyH2H5fInTbNcCrNd8nBV3Tjh07atw11cT3SY5r+u6772rcNdXE90muawoNDa1x11QT3yc5rmnJkiWyX1NUVBQqwyyTJTg6OuLLL7/EhAkTkJqaCm9vb/z+++8YPHgwAGDVqlWYPHky8vLyqnyOgIAA1K9fH/v37zfafv78efj7+2P58uV4/fXXy33txIkTcezYMfzzzz+wsdHXfhqNBv7+/vDw8MDx48clzy3WIxQcHCz7ZAl79uzB8OHDZTs/WS+Ts5GXqZ/i+tIe/Wxvuell9/FoBrQZob/fx68PYGtv9vaSZfGzg8QwGySF+SAx1pANWSZLcHd3R0pKiujz58+fR4MGDR7oHL6+vkhISCizPTExEQDQsGHDcl9XUFCA1atX4+233zYUQQBgZ2eHESNGYPHixSgoKIC9vfgXOx8fH/j4+DxQ+6uLk5OT3E0gKyWZjfQ44N89+imu46IAXeF9O6iAJj2Lhrw9Bng/BJgwRT4pBz87SAyzQVKYDxKjxGyYZWjcY489hpUrVyIjI6PMc+fOncOqVavw5JNPPtA5OnfujEuXLuHu3btG24t7czp37lzu61JTU1FYWAitVlvmOY1GA51OV+5zShEdHS13E8hKGWVDpwVuRAO/vw8s6QUs6gTsmQlcPVRSBNm7Au2eBIKXATNigVd/A/r9H+DTlkVQDcTPDhLDbJAU5oPEKDEbZhkad+vWLQQGBkIQBAQFBWHlypV46aWXoNVq8cMPP8DX1xfR0dEPNF318ePH0atXL6N1hPLz8xEQEIB69eoZ7vWJj49HTk4O2rZtCwDQarXw8vKCj48PYmJiDD0/WVlZaNeuHVxdXXHhwoVKt8da1hFKS0uDp6enbOcnC9FqKj2VdNrtG/BMO6kf8nZpL5BTTq+tW5OiXp/hQLN+gG3Z+/CoZuJnB4lhNkgK80FirCEbsgyNa9iwIf7++2+EhYXh22+/hSAI2LhxI+rUqYPRo0fj448/fuA1ewIDAzFq1CjMmjULSUlJaNWqFdavX4+4uDisXr3asN+YMWMQGRmJ4vpOrVZj+vTpeO+999CrVy+MGTMGWq0Wq1evxs2bN7Fp06YHapfcQkNDsX79ermbQdVFqwGiPgeiVwLZpe5Tc/UBerwG9A01Logybxpmeatz+QCg0pU9ZqNuRff7jADq+7O3p5biZweJYTZICvNBYpSYDbP0CN0vOTkZOp0O3t7eRvflPKi8vDzMnj0bmzZtQnp6Ojp27Ijw8HAMGzbMsM/AgQONCqFimzdvxqJFi3Dp0iXk5+ejY8eOmDFjBp599tkqtcVaeoSoBtNqgK0v6CcwgApA6UwXPW49FOg/Hbi8T3/Pz52YssexcwZaDNL3+rQeBtSpb5n2ExEREVlQZb+fV7kQ6tu3L/r164eHH34YDz/8MDw8PKpyGMWylkIoKChIkSv5kgkiPwUOflC119bxxa9XgRFvLQKa9wfslHcDI1UvfnaQGGaDpDAfJMYasmGxQsjPzw83b96ESqWCSqVC27Zt0bdvX8NPs2bNqnJYxbCWQohqKK0GWNgOyE6BcU+QBN9OJVNc+3bmkDciIiKqVSr7/bzK49bi4+MRHx+Pb775BhMnToS9vT1Wr16NMWPGoGXLlmjSpAmef/55LF68GKdOnSozVI3Mo3gBKqph4o8V3RNk4t+bUeuB1/8ABs0CGnYBVCpmgyQxHySG2SApzAeJUWI2HmiyhMaNG+P555/H888/D0A/E9uRI0dw+PBhHD58GLt27cL3338PAKhbty7S08tZqJEeyKRJk+RuAlWH1NjK7a8q+28azAZJYT5IDLNBUpgPEqPEbJhvJgMArq6uGDp0KN5//31s3LgRK1asQK9evSAIQpn1f8g8/vjjD7mbQOaUEgv8NAnYNa1yr3Mqe48es0FSmA8Sw2yQFOaDxCgxG2aZPhsAzp49i6ioKENv0PXr1+Hg4IAuXbpg2rRpePjhh811Kiqltk1SUWMlngb+XAic/wkmD4cDAKgAV2/9ukL3YTZICvNBYpgNksJ8kBglZqPKhVBkZCQOHz6MqKgoHDt2DBkZGahfvz769OmDSZMmoU+fPujWrZthAVOqHo0aNZK7CfQgrh/RF0Cx+4y3t30CcPEG/l5bwQEEoMeEchdXZTZICvNBYpgNksJ8kBglZqPKhdCgQYNgZ2eHUaNG4auvvkLv3r3RokULc7aNTLB371707NlT7mZQZQgCEPs78OcCIP5oyXaVGugYAjw8FfBpq5857u4t4PJeiK8jNAzoO7Xc0zAbJIX5IDHMBklhPkiMErNR5emzO3XqhHPnzkEQBAQEBKBPnz7o27cv+vTpg+bNm5u7nVbHWqbPzsnJgbOzs2znp0rQafVD36IWArdLLXyqdgC6jgH6TAY8mhq/RqsBor4A/loJZCWVbHf10fcE9Z1abm8QwGyQNOaDxDAbJIX5IDHWkA2LTZ99+vRppKen49dff0VwcDAuX76MiRMnolWrVvD19cWzzz6LhQsX4tixY9BoNFU9DVVg3LhxcjeBKlJYAPyzAVjcA9g2vqQIsq+j7/2ZGgM8/lnZIgjQFzkDZgCh54GxvwAhG/W/Q8/rt4sUQQCzQdKYDxLDbJAU5oPEKDEbVe4RKo9Wq8WpU6dw+PBhwzTat27dgoODA7p3767I2STEWEuPEFmxgmzg7/XA0cXA3YSS7c71gF5vAD1eA5zcZWseERERUU1isR6h8qjVanTr1g1TpkzBu+++i1mzZqFXr17Iy8vD4cOHzXkqKhIUFCR3E+h+uelA5KfA5wHA3lklRVDdRsDwT4CpZ4H+M6q9CGI2SArzQWKYDZLCfJAYJWbDLNNn5+fn4/jx44iKijLMIpeZmQkAcHBwQL9+/dC3b19znIrus3PnTrmbQMXu3QGOLQH+Wg0UZJVsr9dKPwSu43OAreVmUWQ2SArzQWKYDZLCfJAYJWajyj1CP/30E2bMmIHevXvDzc0NgwYNwnvvvYe//voL/fr1w8cff4yoqChkZmYiMjISH3zwgTnbTUXCwsLkbgKlxwG//B/wRQfg8KKSIqhBR2DUOmBSNND1ZYsWQQCzQdKYDxLDbJAU5oPEKDEbVe4RevrppwEAzZs3x3PPPYe+ffuib9++aNeundkaRxUbPXq03E2ovZIuAFGfAzHbAEFbsr3pw0Df/wNaDQFUKtmax2yQFOaDxDAbJIX5IDFKzEaVC6Fvv/0Wffv2ha+vrznbQ5UUExODDh06yN2M2uXm3/o1gP7dZby99VB9AdS0tzztug+zQVKYDxLDbJAU5oPEKDEbVS6ERo0aZc52EFk3QQCuRQJ/LtT/NlAB/k8DfUMB346yNY+IiIiIKscskyWQfJRWeSuOTgf8u1u/CGrC3yXbbeyAzqP1kyDUaylb86QwGySF+SAxzAZJYT5IjBKzYdbps8nytmzZIncTaiZtIXD6W2BZb+DbF0uKIDtnoNebwFungSe/stoiCGA2SBrzQWKYDZLCfJAYJWbDrAuq1iZcULWG0uQBpzbpZ3/LiC/Z7ugG9HwdCJwIuNSTr31EREREVC5ZF1Qly1Pi4lVWKe8uEPWFfgrsXdNKiiAXH+DRefpFUAe/q6giiNkgKcwHiWE2SArzQWKUmA32CFURe4RqiOxU4PgyIHolkJdZst3dT3//T+cXATtH2ZpHRERERKZhj1AtExISIncTlCnzJvDrO8AXAcAfESVFkHc74OmVwOSTQI9XFV0EMRskhfkgMcwGSWE+SIwSs8EeoSqylh6hnJwcODs7y3Z+xUm9ol8E9fRWQKcp2d6oG9BvGtBmBGBTM/59gNkgKcwHiWE2SArzQWKsIRvsEaplFixYIHcTlCHxDPD9OGBxd+DkxpIiqPkAYMzPwH/2A20frzFFEMBskDTmg8QwGySF+SAxSswG1xFSuGHDhsndBOt2/Sjw5wIgdp/x9rZPAH3/D2jcTZ52WQCzQVKYDxLDbJAU5oPEKDEbLIQULiEhQe4mWJZWA8QfA3LTAScPwK8XoLYz3kcQgNjfgT8XAvFHSrar1ECHUUDfqYBPO4s2Ww61LhtUKcwHiWE2SArzQWKUmA0WQgqXnp4udxMsQ6vR39sTvRLITi7Z7uoD9HgN6BsKqGyA8z8BUQuB2zEl+6gdgC4vAQ9PATyaWbzpcqk12aAqYT5IDLNBUpgPEqPEbCjqhoj8/HzMnDkTDRs2hJOTEwIDA7Fv376KX1jk22+/Re/eveHi4gJ3d3f06dMHBw4cqMYWV7/+/fvL3YTqp9UAW18ADn4AZKcYP5eVrN++cgDwVXdg2/iSIsjeFXj4LWBqDPDEwlpVBAG1JBtUZcwHiWE2SArzQWKUmA1FFULjxo3DwoUL8eKLL2LRokVQq9V47LHHEBUVVeFr586di9GjR6NJkyZYuHAh5s+fj44dOyqyG6+0JUuWyN2E6hf1OXD5t6IH909yWPT4zjkg/ar+z06ewKD3gNCz+sVQ69S3VEutSq3IBlUZ80FimA2SwnyQGCVmQzHTZ0dHRyMwMBARERGYPn06ACAvLw8BAQHw8fHBkSNHRF977Ngx9OnTBwsWLEBoaKhZ2mMt02fXeFoNsLBdUU9QBVFV2QCPhgPdxwP2LhZpHhERERFZhxo7ffa2bdugVqsxYcIEwzZHR0e8+uqrOHr0KG7cuCH62i+++AINGjTAW2+9BUEQkJWVZYkmW0RQUJDcTahe8ceK7gkyoV4XdIBvJxZBRWp8NuiBMB8khtkgKcwHiVFiNhRTCJ08eRJt2rRB3bp1jbb37NkTAHDq1CnR1+7fvx89evTAl19+CW9vb9SpUwe+vr5YvHhxdTbZInbu3Cl3E6pXbiVvvKvs/jVYjc8GPRDmg8QwGySF+SAxSsyGYgqhxMRE+Pr6ltlevO3WrVvlvi49PR0pKSk4fPgwZs+ejXfeeQfffvstOnfujMmTJ2PFihUVnjspKQnnzp0z+omNjX2wCzKTsWPHyt2E6uXkUb3712A1Phv0QJgPEsNskBTmg8QoMRuKKYRyc3Ph4OBQZrujo6Ph+fIUD4NLTU3F119/jenTpyMkJAS7du1C+/btMX/+/ArPvXTpUgQEBBj9BAcHAwCioqIQGRmJiIgIpKWlGUJQ3D0YGhqK2NhYrFmzBtu3b0d0dDTCw8ORk5ODkJAQo33DwsIQExODzZs3Y/PmzYiJiUFYWJjRPiEhIcjJyUF4eDiio6MxZMgQrFmzBrGxsYb7n4r3HTt2LNLS0hAREYHIyEjs2bMHS5YsQUJCAiZOnGi078SJE5GQkIAlS5Zgz549sl7T9u3bDde0aunnAFQVvkcCVMjUOgJ+vaz+miz1Pjk7O9e4a6qJ75Nc1/T555/XuGuqie+THNf0wQcf1Lhrqonvk1zX5O/vX+OuqSa+T3Jc02uvvSb7NZkygVppipksISAgAPXr18f+/fuNtp8/fx7+/v5Yvnw5Xn/99TKvS0lJgbe3N+zs7JCbmwu1Wm14bt68eZgzZw6uX78OPz8/0XMnJSUhOTnZaFtsbCyCg4NlnywhIiICM2bMkO381UZbCBycr58xzlSD3gMG1MD/FlVUY7NBZsF8kBhmg6QwHyTGGrJR2ckSFLOgqq+vb7lTXScmJgIAGjZsWO7rPD094ejoCHd3d6MiCAB8fHwA6IfPSRVCPj4+hn2tTfE9UjVK5k1g26vAjWP6x3YuQL2WwO0z0PcOla7dix63Hgb0nWrxplqzGpkNMhvmg8QwGySF+SAxSsyGYobGde7cGZcuXcLdu3eNth8/ftzwfHlsbGzQuXNnJCcno6CgwOi54vuKvL29zd9gCxEbEqhYl34DlvcrKYLqBwCvRwKvHdD3+Lje9165euu3P/8NoLazfHutWI3LBpkV80FimA2SwnyQGCVmQzGF0MiRI6HVarFy5UrDtvz8fKxduxaBgYFo0qQJACA+Ph4XL140eu1zzz0HrVaL9evXG7bl5eXhm2++Qfv27UV7k5TgypUrcjfBPLQa4LfZwOZRQG6aflu38cB/fge8WuuLnAEzgNDzwNhfgJCN+t+h5/XbWQSVUWOyQdWC+SAxzAZJYT5IjBKzoZihcYGBgRg1ahRmzZqFpKQktGrVCuvXr0dcXBxWr15t2G/MmDGIjIxE6VufXn/9dXz99deYNGkSLl26BD8/P2zcuBHXr19X5FR/pRVP2qBoGTeAba8AN6P1j+1dgaBFQIeRZfdV2wHN+1m2fQpVI7JB1Yb5IDHMBklhPkiMErOhmB4hANiwYQOmTp2KjRs3YsqUKdBoNPjll1/Qv39/ydc5OTnhwIEDeOGFF7BmzRrMmDEDNjY22LVrF0aMGGGh1leP8PBwuZvwYP7dA6zoV1IE1e8AvP5H+UUQVYris0HVivkgMcwGSWE+SIwSs6GYWeOsTWVnpaD7aDXA/veBI1+VbOv+KjDsQ8DOUb52EREREZEiVfb7uaJ6hKis4jnUFSUjHlg7oqQIsq8DjFwLPLGQRZAZKTIbZDHMB4lhNkgK80FilJgN9ghVEXuEqujibmDHG0Behv5xg47AqHX66bGJiIiIiKqIPUK1TPHqulavsADY+y6wdXRJEdTjNeDVfSyCqoliskGyYD5IDLNBUpgPEqPEbLBHqIqspUcoISEBjRo1ku38Jkm/DmwbDyT8rX/sUBd48ivAP1jWZtV0isgGyYb5IDHMBklhPkiMNWSDPUK1zI4dO+RugrSLu/SzwhUXQb6d9AuksgiqdlafDZIV80FimA2SwnyQGCVmQzHrCFH5Wra00mFlhQXA73OAY0tLtvV8HRgaDtg6yNeuWsRqs0FWgfkgMcwGSWE+SIwSs8FCSOGcnJzkbkJZ6XHA9+OBW//oHzu4AU8tBto/KWuzahurzAZZDeaDxDAbJIX5IDFKzAaHxilcdHS03E0wdmEnsLx/SRHUsIt+KByLIIuzumyQVWE+SAyzQVKYDxKjxGxwsoQqspbJEtLS0uDp6Snb+Q0K84F9/wOOLy/ZFvgG8Oj7HAonE6vJBlkl5oPEMBskhfkgMdaQDU6WUMuEhobK3QQg7RqwemhJEeTgBjy3CRjxMYsgGVlFNshqMR8khtkgKcwHiVFiNtgjVEXW0iMku/M/AT/9F8i/q3/csCswai3g0UzWZhERERFR7cIeoVomKChInhMX5gO7ZwDfjSkpgnpNAl7ZyyLISsiWDVIE5oPEMBskhfkgMUrMBnuEqqhW9wilXQW+HwckntY/dnQDgpcBbR+XtVlEREREVHuxR6iWsfh4zHPbgRUDSoqgRt2B1/9kEWSFlDhWlyyH+SAxzAZJYT5IjBKzwXWEFG7SpEmWOZEmD/jtXeCvr0u29f4vMGQOYGtvmTZQpVgsG6RIzAeJYTZICvNBYpSYDfYIKdwff/xR/SdJvQKsfrSkCHJ0B0ZvBYZ9wCLIilkkG6RYzAeJYTZICvNBYpSYDfYIKZyHh0f1nuDsD8DPbwEF9/SPG/cARq4F3JtU73npgVV7NkjRmA8Sw2yQFOaDxCgxGyyEFK5Ro0bVc2BNHrB3FnBiTcm2PlOAIf8D1HbVc04yq2rLBtUIzAeJYTZICvNBYpSYDQ6NU7i9e/ea/6ApscDXj5QUQU4ewAvfAUPDWQQpSLVkg2oM5oPEMBskhfkgMUrMBqfPriJrmT47JycHzs7O5jtgzDZg51tAQZb+cZNAYOQawK2x+c5BFmH2bFCNwnyQGGaDpDAfJMYassHps2uZcePGmedAmlx9AfTDqyVF0MNTgXG7WAQplNmyQTUS80FimA2SwnyQGCVmgz1CVWQtPUJmkXJZv0DqnbP6x06ewNMrgDZDZW0WEREREZGp2CNUywQFBT3YAc58p18gtbgIatILmBjFIqgGeOBsUI3GfJAYZoOkMB8kRonZYI9QFSm+R0iTC/z6NvDPhpJtff8PGPQuoOZkgkRERESkLOwRqmXCwsIq/6LkS8CqISVFkHM94MUfgEfmsAiqQaqUDao1mA8Sw2yQFOaDxCgxG/zWq3CjR4+u3AtOfwv8EgposvWP/foAI1cDdRuav3Ekq0png2oV5oPEMBskhfkgMUrMBnuEFC4mJsa0HQtygJ8mAdsnFBVBKqDfdGDsThZBNZTJ2aBaifkgMcwGSWE+SIwSs6GoQig/Px8zZ85Ew4YN4eTkhMDAQOzbt6/Sx3n00UehUqnw3//+txpaaYWSLgKrBgMnN+kfO3sBL/0ADJnNoXBEREREVCspqhAaN24cFi5ciBdffBGLFi2CWq3GY489hqioKJOP8eOPP+Lo0aPV2ErL6tChg/QOp7YAqwYByRf0j5v21c8K12pI9TeOZFVhNqhWYz5IDLNBUpgPEqPEbCimEIqOjsbWrVvx0UcfISIiAhMmTMCBAwfQtGlTvP322yYdIy8vD9OmTcPMmTOrubWWs2XLlvKfKMgGdrwJ7JgIaHIAqID+M4AxPwF1fS3aRpKHaDaIwHyQOGaDpDAfJEaJ2VBMIbRt2zao1WpMmDDBsM3R0RGvvvoqjh49ihs3blR4jE8//RQ6nQ7Tp0+vzqZajlaDD18bAZz/Gbj2J6DV6LcXD4U79Y3+sYs38PJ2YPB7HApXi3z44YdyN4GsGPNBYpgNksJ8kBglZkMxhdDJkyfRpk0b1K1b12h7z549AQCnTp2SfH18fDw+/vhjfPLJJ3BycqquZlqGVgNEfgosbAesfwL47mX978/bA1tf1C+QmnxRv2+zfvqhcC0HydtmsjglLmxGlsN8kBhmg6QwHyRGidlQTPdAYmIifH3LDukq3nbr1i3J10+bNg1dunTB888/X+lzJyUlITk52WhbbGxspY9jFloNsPUF4PJvAFTGz2UlARd/KXk84B1gwNuAjdqiTSTrsHPnTrmbQFaM+SAxzAZJYT5IjBKzoZgeodzcXDg4OJTZ7ujoaHhezMGDB/HDDz/giy++qNK5ly5dioCAAKOf4OBgAEBUVBQiIyMRERGBtLQ0jB07FkBJVRwaGorY2FisWbMG27dvR3R0NMLDw5GTk4OQkBCjfcPCwhATE4PNmzdj8+bNiImJMSxOVbzPt5N7FRVBACCIN7rzixi77iLSMjIRERGByMhI7NmzB0uWLEFCQgImTpxodNyJEyciISEBS5YswZ49eyx6TSEhIcjJyUF4eDiio6Oxfft2rFmzBrGxsQgNDTXad+zYsUhLS+M1mXBNbdq0qXHXVBPfJ7muKSQkpMZdU018n+S4pmeeeabGXVNNfJ/kuqauXbvWuGuqie+THNc0bNgw2a+pMhOoAYBKEASJb9PWIyAgAPXr18f+/fuNtp8/fx7+/v5Yvnw5Xn/99TKvKywsRJcuXdC1a1esX7/esF2lUmHSpElYvHhxhecW6xEKDg7G2bNn4e/vX8WrqiStRj8cLjsFkkUQVICrNxB6HlDbWaZtZHVycnLg7OwsdzPISjEfJIbZICnMB4mxhmycO3cOAQEBJn8/V0yPkK+vLxITE8tsL97WsGH5i4Ju2LAB//77L15//XXExcUZfgDg3r17iIuLQ05OjuS5fXx84O/vb/TTqlWrB7ugqog/BmQnQ7oIgv75rCT9/lRrLViwQO4mkBVjPkgMs0FSmA8So8RsKKYQ6ty5My5duoS7d+8abT9+/Ljh+fLEx8dDo9Hg4YcfRvPmzQ0/gL5Iat68OX777bdyX2t1ctOrd3+qUYYNGyZ3E8iKMR8khtkgKcwHiVFiNhQzWcLIkSPx2WefYeXKlYbpr/Pz87F27VoEBgaiSZMmAPSFT05ODtq2bQsAeP7558stkp5++mk89thjeO211xAYGGix63ggTh7Vuz/VKAkJCXI3gawY80FimA2SwnyQGCVmQzGFUGBgIEaNGoVZs2YhKSkJrVq1wvr16xEXF4fVq1cb9hszZgwiIyNRfOtT27ZtDUXR/Zo3b26Y9EAR/Hrp1wQy9R4hv16WahlZofR09giSOOaDxDAbJIX5IDFKzIZihsYB+qFsU6dOxcaNGzFlyhRoNBr88ssv6N+/v9xNswy1HdBzAky6R6jHBE6UUMvVmr8XVCXMB4lhNkgK80FilJgNRRVCjo6OiIiIQGJiIvLy8hAdHV1mPOKhQ4dgykR4giCYNGOc1ekbCrQuvub71hEqftx6GNB3qgUbRdZoyZIlcjeBrBjzQWKYDZLCfJAYJWZDMdNnW5vKTs9nVloNEPUF8NdK/exwxVx99D1BfaeyN4iIiIiIapUaO302laK2AwbMAELPY9a/HYGQjcDYX/TrBg2YwSKIAJQsNEZUHuaDxDAbJIX5IDFKzAZ7hKpI1h4hIiIiIiIywh6hWmbs2LFyN4GsFLNBUpgPEsNskBTmg8QoMRvsEaoia+kRSktLg6enp2znJ+vFbJAU5oPEMBskhfkgMdaQDfYI1TKl11AiKo3ZICnMB4lhNkgK80FilJgNFkIK17NnT7mbQFaK2SApzAeJYTZICvNBYpSYDVu5G6BU+fn5AIDY2FhZ23Hx4kV4eXnJ2gayTswGSWE+SAyzQVKYDxJjDdko/l5e/D29IiyEqujGjRsAgODgYHkbQkREREREBjdu3EDXrl0r3I+TJVRRRkYGIiMj0aRJEzg4OMjShtjYWAQHB2PHjh1o1aqVLG0g68RskBTmg8QwGySF+SAx1pKN/Px83LhxAwMGDIC7u3uF+7NHqIrc3d3x1FNPyd0MAECrVq24lhGVi9kgKcwHiWE2SArzQWKsIRum9AQV42QJRERERERU67AQIiIiIiKiWoeFEBERERER1ToshBTM29sbc+bMgbe3t9xNISvDbJAU5oPEMBskhfkgMUrNBmeNIyIiIiKiWoc9QkREREREVOuwECIiIiIiolqHhRAREREREdU6LISIiIiIiKjWYSFERERERES1DgshBcrPz8fMmTPRsGFDODk5ITAwEPv27ZO7WWQGWVlZmDNnDoYPHw5PT0+oVCqsW7eu3H0vXLiA4cOHw9XVFZ6ennj55ZeRnJxcZj+dTodPP/0UzZs3h6OjIzp27IgtW7Y80DHJ8v766y/897//hb+/P1xcXODn54eQkBBcunSpzL7MRu1z7tw5jBo1Ci1atICzszO8vLzQv39/7Ny5s8y+zEft9sEHH0ClUiEgIKDMc0eOHEHfvn3h7OyMBg0aYMqUKcjKyiqzX2W+h5h6TLK8Q4cOQaVSlftz7Ngxo31rbDYEUpznn39esLW1FaZPny6sWLFC6N27t2Brayv8+eefcjeNHtC1a9cEAIKfn58wcOBAAYCwdu3aMvvduHFD8PLyElq2bCksWrRI+OCDDwQPDw+hU6dOQn5+vtG+77zzjgBAeO2114SVK1cKjz/+uABA2LJlS5WPSZb37LPPCg0aNBAmT54srFq1SggPDxfq168vuLi4CDExMYb9mI3aadeuXcKwYcOEuXPnCitXrhS++OILoV+/fgIAYcWKFYb9mI/a7caNG4Kzs7Pg4uIi+Pv7Gz138uRJwdHRUejSpYuwbNky4d133xUcHByE4cOHlzmOqd9DKnNMsryDBw8KAIQpU6YIGzduNPpJTk427FeTs8FCSGGOHz8uABAiIiIM23Jzc4WWLVsKvXv3lrFlZA55eXlCYmKiIAiC8Ndff4kWQm+88Ybg5OQkXL9+3bBt3759Zb703Lx5U7CzsxMmTZpk2KbT6YR+/foJjRs3FgoLCyt9TJLH4cOHy3ypvHTpkuDg4CC8+OKLhm3MBhUrLCwUOnXqJDz00EOGbcxH7fbcc88JgwcPFgYMGFCmEBoxYoTg6+srZGZmGratWrVKACDs3bvXsK0y30NMPSbJo7gQ+v777yX3q8nZYCGkMDNmzBDUarVRcARBED788EMBgBAfHy9Ty8jcpAohHx8fYdSoUWW2t2nTRhgyZIjh8ZIlSwQAwrlz54z227x5swDA6F9oTD0mWZeuXbsKXbt2NTxmNqi0J554Qqhfv77hMfNRe0VGRgpqtVo4c+ZMmUIoMzNTsLW1FWbMmGH0mvz8fMHV1VV49dVXDdtM/R5SmWOSPEoXQnfv3hU0Gk2ZfWp6NniPkMKcPHkSbdq0Qd26dY229+zZEwBw6tQpGVpFlpSQkICkpCR07969zHM9e/bEyZMnDY9PnjwJFxcXtGvXrsx+xc9X9phkPQRBwJ07d+Dl5QWA2SAgOzsbKSkpuHLlCj7//HP8+uuvGDJkCADmozbTarWYPHky/vOf/6BDhw5lno+JiUFhYWGZ99He3h6dO3cukw1TvodU5pgkr/Hjx6Nu3bpwdHTEoEGDcOLECcNzNT0bLIQUJjExEb6+vmW2F2+7deuWpZtEFpaYmAgAojlIS0tDfn6+Yd/69etDpVKV2Q8oyUtljknW45tvvkFCQgKee+45AMwGAdOmTYO3tzdatWqF6dOn4+mnn8bixYsBMB+12fLly3H9+nWEh4eX+3xF72Pp7xamfg+pzDFJHvb29nj22WexaNEi/PTTT5g/fz5iYmLQr18/QzFS07Nha7EzkVnk5ubCwcGhzHZHR0fD81SzFb/HFeXAwcHB5LxU5phkHS5evIhJkyahd+/eGDt2LABmg4CpU6di5MiRuHXrFr777jtotVoUFBQAYD5qq9TUVPzvf//D7Nmz4e3tXe4+Fb2Ppb9bmCsb/L4ivz59+qBPnz6Gx08++SRGjhyJjh07YtasWdizZ0+NzwZ7hBTGycmp3H9dy8vLMzxPNVvxe2xKDkzNS2WOSfK7ffs2Hn/8cbi5uWHbtm1Qq9UAmA0C2rZti0ceeQRjxozBL7/8gqysLAQFBUEQBOajlnrvvffg6emJyZMni+5T0ftY+j00VzaYC+vUqlUrPPXUUzh48CC0Wm2NzwYLIYXx9fU1dCmWVrytYcOGlm4SWVhxV7JYDjw9PQ3/yuLr64vbt29DEIQy+wEleanMMUlemZmZGDFiBDIyMrBnzx6jv/PMBt1v5MiR+Ouvv3Dp0iXmoxa6fPkyVq5ciSlTpuDWrVuIi4tDXFwc8vLyoNFoEBcXh7S0tArfx/s/Z0z5HlKZY5J1adKkCQoKCpCdnV3js8FCSGE6d+6MS5cu4e7du0bbjx8/bniearZGjRrB29vb6GbGYtHR0UYZ6Ny5M3JycnDhwgWj/e7PS2WOSfLJy8tDUFAQLl26hF9++QXt27c3ep7ZoPsVDzHJzMxkPmqhhIQE6HQ6TJkyBc2bNzf8HD9+HJcuXULz5s0xb948BAQEwNbWtsz7WFBQgFOnTpXJhinfQypzTLIuV69ehaOjI1xdXWt+Niw2Px2ZxbFjx8rM0Z6Xlye0atVKCAwMlLFlZG5S02dPnDhRcHJyMpou/ffffxcACMuWLTNsu3HjhuhaII0aNTJaC8TUY5I8CgsLhSeffFKwtbUVdu3aJbofs1E73blzp8y2goICoWvXroKTk5Nw7949QRCYj9omOTlZ2L59e5kff39/wc/PT9i+fbtw5swZQRAEYfjw4YKvr69w9+5dw+u//vprAYDw66+/GrZV5nuIqcckeSQlJZXZdurUKcHOzk548sknDdtqcjZYCCnQqFGjDPOvr1ixQujTp49ga2srREZGyt00MoOvvvpKCA8PF9544w0BgPDMM88I4eHhQnh4uJCRkSEIgiDEx8cL9erVE1q2bCl8+eWXwocffih4eHgIHTp0EPLy8oyON2PGDAGAMGHCBGHVqlWG1eG/+eYbo/0qc0yyvLfeeksAIAQFBZVZAXzjxo2G/ZiN2ik4OFgYPHiwMHfuXGHVqlVCeHi40LZtWwGAsGDBAsN+zAcJglDugqp///234ODgIHTp0kVYtmyZ8O677wqOjo7C0KFDy7ze1O8hlTkmWd6gQYOExx57TJg/f76wcuVKYerUqYKzs7Pg5uYmnD9/3rBfTc4GCyEFys3NFaZPny40aNBAcHBwEHr06CHs2bNH7maRmTRt2lQAUO7PtWvXDPudPXtWGDp0qODs7Cy4u7sLL774onD79u0yx9NqtcKHH34oNG3aVLC3txf8/f2FTZs2lXtuU49JljdgwADRXNzfuc9s1D5btmwRHnnkEaF+/fqCra2t4OHhITzyyCPCTz/9VGZf5oPKK4QEQRD+/PNPoU+fPoKjo6Pg7e0tTJo0yehf7ItV5nuIqccky1u0aJHQs2dPwdPTU7C1tRV8fX2Fl156Sbh8+XKZfWtqNlSCcN+dkERERERERDUcJ0sgIiIiIqJah4UQERERERHVOiyEiIiIiIio1mEhREREREREtQ4LISIiIiIiqnVYCBERERERUa3DQoiIiIiIiGodFkJERERERFTrsBAiIiIiIqJah4UQERERERHVOiyEiIis3Lhx49CsWTO5m1Eld+7cwciRI1GvXj2oVCp88cUXlXp9XFwcVCoV1q1bVy3tszaHDh2CSqXCoUOHDNsGDhyIgICAaj9n8c+JEyeq7VzlmTp1quHcrq6uFj03EdVutnI3gIioNlKpVCbtd/DgwWpuSfUKDQ3F3r17MWfOHDRo0ADdu3eXu0kkIiwsDO3atUOLFi0set6XX34Z3bt3x8qVK/HPP/9Y9NxEVLuxECIiksHGjRuNHm/YsAH79u0rs71du3ZYtWoVdDqdJZtnNgcOHMBTTz2F6dOny90URejfvz9yc3Nhb29v8XM/+uijGDhwoMXP261bN3Tr1g2///47CyEisigWQkREMnjppZeMHh87dgz79u0rs13pkpKS4O7uLnczFMPGxgaOjo5yN4OIqFbgPUJERFbu/nuEiu+b+eyzz7BkyRK0aNECzs7OGDp0KG7cuAFBEBAeHo7GjRvDyckJTz31FNLS0soc99dff0W/fv3g4uKCOnXq4PHHH8e5c+dMatPVq1cxatQoeHp6wtnZGb169cKuXbsMz69btw4qlQqCIGDJkiWGe0CkZGRkYNy4cXBzc4O7uzvGjh2LjIyMcvc9cOCAoe3u7u546qmncOHCBaN95s6dC5VKhYsXLyIkJAR169ZFvXr18NZbbyEvL89o37Vr12Lw4MHw8fGBg4MD2rdvj2XLlpn03+L27dsYP348GjduDAcHB/j6+uKpp55CXFycYZ9mzZrhiSeewG+//YbOnTvD0dER7du3x48//mh0rPLuESrPb7/9BmdnZ4wePRqFhYUAgIsXL2LkyJHw9PSEo6Mjunfvjp9//tmkaxAzbtw4uLq6Ij4+Hk888QRcXV3RqFEjLFmyBAAQExODwYMHw8XFBU2bNsXmzZuNXq/RaPD++++jdevWcHR0RL169dC3b1/s27fvgdpFRGQOLISIiBTqm2++wdKlSzF58mRMmzYNkZGRCAkJwXvvvYc9e/Zg5syZmDBhAnbu3FlmaNrGjRvx+OOPw9XVFZ988glmz56N8+fPo2/fvkZf4Mtz584d9OnTB3v37sWbb76JDz74AHl5eXjyySexfft2APohXsXD/B599FFs3LixzLC/0gRBwFNPPYWNGzfipZdewvz583Hz5k2MHTu2zL6///47hg0bhqSkJMydOxf/93//hyNHjuDhhx8ut+0hISHIy8vDRx99hMceewxffvklJkyYYLTPsmXL0LRpU4SFhWHBggVo0qQJ3nzzTcMXfinPPvsstm/fjvHjx2Pp0qWYMmUK7t27h/j4eKP9Ll++jOeeew4jRozARx99BFtbW4waNarSRcEvv/yCJ598EqNGjcKmTZtga2uLc+fOoVevXrhw4QLeeecdLFiwAC4uLggODja8J1Wl1WoxYsQINGnSBJ9++imaNWuG//73v1i3bh2GDx+O7t2745NPPkGdOnUwZswYXLt2zfDauXPn4v3338egQYOwePFivPvuu/Dz8+MQOCKyDgIREclu0qRJgthH8tixY4WmTZsaHl+7dk0AIHh7ewsZGRmG7bNmzRIACJ06dRI0Go1h++jRowV7e3shLy9PEARBuHfvnuDu7i689tprRue5ffu24ObmVmb7/aZOnSoAEP7880/Dtnv37gnNmzcXmjVrJmi1WsN2AMKkSZMqvP4dO3YIAIRPP/3UsK2wsFDo16+fAEBYu3atYXvnzp0FHx8fITU11bDt9OnTgo2NjTBmzBjDtjlz5ggAhCeffNLoXG+++aYAQDh9+rRhW05OTpk2DRs2TGjRooVku9PT0wUAQkREhOR+TZs2FQAIP/zwg2FbZmam4OvrK3Tp0sWw7eDBgwIA4eDBg4ZtAwYMEPz9/QVBEIQffvhBsLOzE1577TWj/85DhgwROnToYHiPBUEQdDqd0KdPH6F169aSbSvvnMXGjh0rABA+/PBDo2t2cnISVCqVsHXrVsP2ixcvCgCEOXPmGLZ16tRJePzxxyXPX/pcLi4uJu1LRGQO7BEiIlKoUaNGwc3NzfA4MDAQgP7+I1tbW6PtBQUFSEhIAADs27cPGRkZGD16NFJSUgw/arUagYGBFc5Ut3v3bvTs2RN9+/Y1bHN1dcWECRMQFxeH8+fPV/padu/eDVtbW7zxxhuGbWq1GpMnTzbaLzExEadOncK4cePg6elp2N6xY0c8+uij2L17d5ljT5o0yehx8TFL7+vk5GT4c2ZmJlJSUjBgwABcvXoVmZmZou12cnKCvb09Dh06hPT0dMlrbNiwIZ5++mnD47p162LMmDE4efIkbt++LflaANiyZQuee+45vP7661ixYgVsbPT/C09LS8OBAwcQEhKCe/fuGd7P1NRUDBs2DJcvXza891X1n//8x/Bnd3d3PPTQQ3BxcUFISIhh+0MPPQR3d3dcvXrVaN9z587h8uXLD3R+IqLqwEKIiEih/Pz8jB4XF0VNmjQpd3vxF/XiL6WDBw+Gt7e30c9vv/2GpKQkyfNev34dDz30UJnt7dq1MzxfWdevX4evr2+ZdWTuP0/xscXOn5KSguzsbKPtrVu3NnrcsmVL2NjYGA2jO3z4MB555BHDPUfe3t4ICwsDAMlCyMHBAZ988gl+/fVX1K9fH/3798enn35abmHTqlWrMvdJtWnTBgAqHI547do1vPTSS3j22Wfx1VdfGR0nNjYWgiBg9uzZZd7POXPmAECF76kUR0dHeHt7G21zc3ND48aNy1yPm5ubUUE4b948ZGRkoE2bNujQoQNmzJiBM2fOVLktRETmxFnjiIgUSq1WV2q7IAgAYJiKe+PGjWjQoEGZ/Ur3JtVE9395v3LlCoYMGYK2bdti4cKFaNKkCezt7bF79258/vnnFU5dPnXqVAQFBWHHjh3Yu3cvZs+ejY8++ggHDhxAly5dzNJmX19f+Pr6Yvfu3Thx4oTRekzF7Zs+fTqGDRtW7utbtWpV5XNXNWeA/l6xK1eu4KeffsJvv/2Gr7/+Gp9//jmWL19u1MtERCSHmv1/OyIiKqNly5YAAB8fHzzyyCOVfn3Tpk3x77//ltl+8eJFw/NVOeb+/fuRlZVl1Ct0/3mKjy12fi8vL7i4uBhtv3z5Mpo3b254HBsbC51OZ5iJb+fOncjPz8fPP/9s1MtWmcVsW7ZsiWnTpmHatGm4fPkyOnfujAULFmDTpk1G5xUEwagQu3TpEgAYzQpYHkdHR/zyyy8YPHgwhg8fjsjISPj7+wOAYQFUOzu7Kr2f1c3T0xPjx4/H+PHjkZWVhf79+2Pu3LkshIhIdhwaR0RUywwbNgx1/7+9+wtpeo3jOP4xplf5J3GzEtG0LEb+qa5iSkYabqUIgpjQhUqEYuKF0qBYCSHK8GqBVFBZQipGoQmmCRLRwLxI8EYhjIhiiBeGZqPinIuDO65p5aH00O/9uvvt9zy/58sGgy/P7/t9oqLU3Nysz58/h9yfnZ397nyHw6GxsTF5vd7AZ4uLi7p+/bqSk5NltVrXHZPD4dCXL1+CWlZ//fpVHo8naNyOHTuUlZWljo6OoNbak5OTGhoaksPhCHn2t53flp9pt9sl/buzsXInY35+Xrdu3fph3B8/fgxpxZ2amqrIyEj5/f6gz9+9exfUwe3Dhw+6c+eOsrKyVt2Z+1Z0dLQeP34si8Wi/Px8vXr1StI/CW1ubq6uXbum9+/fh8z70e/5O83NzQVdb926Vbt37w75bgBgM7AjBAAGExUVpfb2dp0+fVoHDx5UWVmZzGaz3rx5o4GBAdlsNl29enXN+U6nU/fu3ZPdblddXZ1iY2PV0dGhmZkZ3b9/P1DEvx6FhYWy2WxyOp16/fp14Iyd1epz3G637Ha7Dh8+rKqqKi0tLcnj8Sg6OlqXL18OGT8zM6OioiIVFBTI6/Wqs7NT5eXlyszMlCQdP35cERERKiws1NmzZ7WwsKAbN27IYrGsmlisND09rWPHjqm0tFRWq1Umk0kPHjyQz+dTWVlZ0Ni0tDRVVVXpxYsXio+P182bN+Xz+X4q4VoWFxen4eFhZWdnKy8vT8+ePQuc65Odna309HSdOXNGKSkp8vl88nq9evv2rSYmJn56jV/JarUqNzdXhw4dUmxsrMbHx9Xb26va2tpNiQcAViIRAgADKi8v186dO9XS0iK32y2/36+EhATl5OSooqLiu3Pj4+P1/PlznT9/Xh6PR58+fVJGRob6+/t14sSJ/xTPli1b1NfXp/r6enV2diosLExFRUVqa2sLqbPJy8vT4OCgLl26JJfLpfDwcB05ckStra1Br8At6+7ulsvlktPplMlkUm1trdxud+D+3r171dvbq4sXL6qhoUHbt29XdXW1zGazKisrvxt3YmKiTp06pZGREd29e1cmk0n79u1TT0+PSkpKgsbu2bNHHo9HjY2Nmpqa0q5du9Td3b1mXc9aEhIS9OTJE+Xk5Cg/P19Pnz6V1WrV+Pi4mpqadPv2bc3NzclisejAgQNyuVzrev6vVFdXp76+Pg0NDcnv9yspKUlXrlxRY2PjpsUEAMvC/lr5LgAAAH+I5cM8Z2dnFRcXt6mxJCcna//+/Xr06NGmxrGa0dFRHT16VA8fPpTNZlNMTMyGNsxYXFzU0tKSzp07p/7+fi0sLGzY2gCMjRohAACg4uJimc1mvXz5ckPXvXDhgsxms7q6ujZ0XQDg1TgAAAwsMzNTw8PDgevVzmj6nWpqanTy5ElJf37rdgD/L/zjAABgYNu2bdvUtttpaWmBg2UBYCNRIwQAAADAcKgRAgAAAGA4JEIAAAAADIdECAAAAIDhkAgBAAAAMBwSIQAAAACGQyIEAAAAwHBIhAAAAAAYDokQAAAAAMMhEQIAAABgOCRCAAAAAAznb4VjuGQjSg6gAAAAAElFTkSuQmCC", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -419,8 +755,9 @@ "fig, ax = plt.subplots()\n", "for A_vt in [1., -1.]:\n", " dt_vec, dw_vec, delay = run_vt_spike_timing_experiment(neuron_model_name,\n", - " synapse_model_name, \n", - " synapse_parameters={\"A_vt\": A_vt})\n", + " synapse_model_name,\n", + " module_name,\n", + " synapse_parameters={\"A_vt\": A_vt})\n", " ax.plot(dt_vec, dw_vec, marker='o', label=\"$A_{vt}$ = \" + str(A_vt))\n", "\n", "ax.set_xlabel(\"Time of dopa spike [ms]\")\n", @@ -566,9 +903,6 @@ "neg_dopa_spike_times = [8000, 9000, 10000]\n", "A_vt = [10., -10.]\n", "\n", - "\n", - "nest.set_verbosity(\"M_ALL\")\n", - "\n", "nest.ResetKernel()\n", "try:\n", " nest.Install(module_name)\n", @@ -738,19 +1072,17 @@ "name": "stderr", "output_type": "stream", "text": [ - ":23: UserWarning:Matplotlib is currently using module://matplotlib_inline.backend_inline, which is a non-GUI backend, so cannot show the figure.\n" + "/var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/ipykernel_69190/2151756254.py:23: UserWarning:FigureCanvasAgg is non-interactive, and thus cannot be shown\n" ] }, { "data": { - "image/png": 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\n", 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mSATzQiKYFxLBvJDScTJL5Kbk5GS5SyCFYWZIBPNCIpgXEsG8kNJxMkvkpm7dusldAikMM0MimBcSwbyQCOaFlI6TWSI39e/fX+4SSGGYGRLBvJAI5oVEMC+kdJzMErlp8+bNcpdACsPMkAjmhUQwLySCeSGl41fzOPDUj50mz6XX6xEQECB3GaQgzAyJYF5IBPNCIpgXcpWnzpF4ZZbITVOmTJG7BFIYZoZEMC8kgnkhEcwLKR2vzDrw1J86EBERERERycFT50i8MkvkpqCgILlLIIVhZkgE80IimBcSwbyQ0vHKrANP/akDERERERGRHDx1jsQrs0RuioiIkLsEUhhmhkQwLySCeSERzAspneIns3v37sW//vUvDBs2DB07dsSgQYMQEhKCEydOyF0atROTJk2SuwRSGGaGRDAvJIJ5IRHMCymd4iezn376KdauXYsHHngAX375JV5++WUkJydj9OjROHz4sNzlUTuQmZkpdwmkMMwMiWBeSATzQiKYF1I6H7kLcNd//vMfxMbGwtfX17rsqaeewogRIzB79mysWrVKxuqIiIiIiIioJSh+MnvXXXc1WHbddddh2LBhOHr0qAwVtTCTESjOArpdDXh5y11N+9JI348YMaLV9mX3+IVTgEoFdL/GtSw0tU3L9iST+TFXtym6T8v/uwwESnPMywGg6ARQeg7oOhC48rr6dR3bWFcDZO8EBt4BlOeat1OcVb8O4Pr2LfXZPtb1KuBMsnm5zxXA4PsAn/oflKGuxvx4577mbdj2lW1bgfrau17VoJYRXfTmbXl51/e7pZ6yXKBTb/PfKpifd+V19W2z3b6z8aoxAIdWA5IEDLwd6HWDeV+H1wL9RgNXXmuux9J3lm10vcq8zfI84Oq7ze22HS9LP1vaY+lj2752HDfbttv2ue3jtjVYxrDohH0djs+z7XPb8et+TdM1Sab6Pg7sV/9YRQEw6M76TDXVPtscdBngfGwcM+/YHsfjzTEjDn0+YthQ+wxm7wT63wZo9zZ+LDj2t2NWbLPs4+vacxobg+IsoHM/+2Nn4J3m+q76s/0xZNl+U7myLOvUFzj6KzDsMcDX33ldtse3ZUwB89+BA4CcPQ37yJKDigLzmHh5m7dRnF1/zHW/pn5dy/aayrNlPdt1HZ9vqfdS51rHc0lT2bKMR+AAcy469sKITqXA8QT7djgbs8a26fg60dh5zzGrztpkyeulcuB4vNoeM42NT2mOOXc5e+qPB9v9XOpc5MlE3+u58d6wyfcwfM9JCqD4yawzkiShoKDgkp+0VVhYiKKiIrtlGo2mJUtzj8kILH8QyEkzv0l9YRNPLq2lib6Pi4tr3gntpcbZZARixgPn1Ob/DxgDvJjQdBaa2qbj9lzdpmg7QjcAKx42/9+3E1BTYd6PyQTk7rPf95SNwLcT7Nv4/K/A59ean6fyMr9xuqIjUFtpXqf/beY3LefUl97+iwnmfy8bZ34D1BjfTsDbZ8xvjupqgE+vrt+fY72Wtg0YY55IWrbrpJa47VUYkfE/oNfQpvdvYds2x+3btqmuBpjVx/65fUcDeekAJPt6bPsOAHwCgDp9/TpvaoCVj5rbZLuu5fmOf1vG2HbcbB97YZN5mW3WHGvof5u5bZbxsvS/l3fDzE/ZCCx/yL4fXKmpMZZMNdW+FzaZc22bA8exAcz/tuzbtkZLv373iH09thmxPN+mb+LU3TFig8a8788Gm9d1rNu2L20z7uzYfv5XIGqIfd9f6jnOjknb3DfG9hgC7M8LznLlmAkA+PU14J0cYNVj9nU55sWRpW+c9ZHFFR2Bnn9quA1n614qz5d6fv/bzH87O3Ztz8eW/rHNg7Ns2eVaBcsxHre9CiMe6NCwDmfnKsdtWh5rLO+2bbHk3rGtljbZ5rWpHDger7bHTGPjY3mOZWxtlzs7ZziOnSe/dxJ9r+fme8NG38PwPScphOLvmXXm+++/h1arxVNPPdXkevPnz8fw4cPt/gQHBwMAUlNTkZSUhKioKOh0OoSGhgKo/z6u8PBwaDQaxMTEID4+Hmq1GpGRkdDr9QgJCbFbNyIiApmZmYiNjUVsbCwyMzOtnx5nWSckJAR6vR6RkZFQq9WIj49HTEwMNBoNwsPDzes++H9AThpC1xmgO7EHUTOnIykpCQkJCYiOjoZWq0VYWJjddsPCwqDVahEdHY2EhATPa9PFdUNDQ6HT6RAVFeWZbbrY9yE/6qE/vQeR09+0tunaa69t3jb9tAJJKTsRtbMauhN7EPrMRPs2/fPv0Bzag5j0GsQfrYU6bTcip7/ZdJuWfIXY31KRWWBExLdJQHFW/Tg9HgT9mTREJlVDrTUi/mgtYtanQrM/0b02vfgctEd2I1pdg4QdO5G0Zj6ifkiGziAhdI35h0hBUYlA7j6EJ1RBozOZ27R1J9S/LkXk9ynQ10oI+VEPnFMj6G9/BmoqELG9Cpn5tYjNrEXsgRJzm7ZXAdq95u0BCPm+EPpaCZHfp0C9N83cpvQaaHQmhC9NNrf/wf8DtHvNx5NBQtTOaiRl1SFBU4dodQ20ZSaE/VwEZO80tyl7J8Liz0NbZjK3SVOHpKw6RK1Oge7gJoR+nVjfJu3e+jal6erHKW4n9LUSNDoTUFuJoM+TzOO0vQqZBUZzmzJr69sEIChOD2j3ImReYn2b1Huct+lvfzaPk22bdquRoKm1bxOAoO/Mf4dtMJjbtKukvk07LkC3a2V9my6uG55QBU1+mXmcDhZDrTUicusF8zjN3WHuq4tjELG9Cpk5peY2/ZaKzJ2bEfHGv8xjGWeeNIfEFpnbZMnetl2I2bjL3KaEKqCmAkFj7wOKsxD6TVJ9m1J3IeG7eYiO32lu0waDuc4VheY2/VxkbtPaFCR8Nw9JqbvMx5NBQug6Q32/WtqkMyHmQJV5nM6UIjKpGvrKcnP2airM6+akIeKNfyFzy0rEHiipH6fvUurbdE5dP06rkqH+dam5TZZx+vU8cCTe2kfWcdpxwZy9xF2I/jnV3Kb489Y6Z43RmY+ntHWITtXVj9POauj0RnObaivr27Q0GZr9iYj5Jsp8PGmN5jbVSgiZl2iu4eKYWrO3aSdil3xlHqcVyXZ9FDIvEfpj283Zsz1HJK1B+JIku3UbHE9/lCD6o7fqzxHFWQj6bId5nGyPpz9KzG1K1DUcJ8mE8Ocn2J/3tEZExqZCn73XPE42NVjbdKjaPE75tebjyaaPQn7Um8dpm67hOSLBft0G47RjJ6I/j4T2jz0IW2jffuvxtLPYfpwMEkKjk83nKdvsHdpjHifL69P0N6E/vaf+vGc5nlYkI3P/7vrjactKh3GSrG3y91HVj5O6uL5N59Tm48nyPuJkGqJWp9S36aO3oD2y23w85aSZz5GNnffWpEJ3Mq1h9mzbtGS2/fH0yNj614jiLER8m2Qep/3F5nHatwsRU1+w66OQ2CLos/favz6l10CTX2Zuk2SyH6fSckS9NxVJG1abjyfH895nO4DiLM9+b2RzjIR+nQjd6YymX3Mvvj8J22Awv+Z+HinUpttuu815my5uN2J7FTL37TK/j2gP7/fYpkbbFBcXB0/U5r5n9tixY7j99tsxbNgwpKSkwNu78Z8iNXZlNjg42OO+QwkAf0ompyb6PigoCOvXr2+VfVkf55VZRV+ZDYrTY/3zPXlllldm7etu5MpsULwv1qfnt98rsyovXpkVuDIbFKfH+kkBDevglVllvHdq5Suzjb6H4XtOcuCp3zPbpiaz+fn5+POf/4za2lrs2bMH/fr1E96Gpw6UFe9fkE9r9j3vmW3T98za3QvGe2Z5z+wl7pl1eg8i75nlPbON3DNrd+7gPbO8Z7Y166A2zVPnSG1mMltaWor7778fZ8+eRUpKCoYOHXrpJznhqQNFniskJARr1qyRuwxSEGaGRDAvJIJ5IRHMC7nKU+dIbWIyW1VVhbFjx2L//v3Ytm0b7rzzzsvelqcOFHkuvV6PgIAAucsgBWFmSATzQiKYFxLBvJCrPHWOpPgPgDIajXjqqaewe/du/Pjjj25NZIkux5w5c+QugRSGmSERzAuJYF5IBPNCSqf4r+Z544038OuvvyIoKAg6nQ6rVq2ye3zy5MkyVUbtxbhx4+QugRSGmSERzAuJYF5IBPNCSqf4yWxGRgYAYP369U4/jY2TWWppWq1W7hJIYZgZEsG8kAjmhUQwL6R0ip/MJiYmyl0CtXPFxcVyl0AKw8yQCOaFRDAvJIJ5IaVT/D2zRHK799575S6BFIaZIRHMC4lgXkgE80JKx8kskZuio6PlLoEUhpkhEcwLiWBeSATzQkrXJr6apzl56sdOExERERERycFT50i8MkvkpqCgILlLIIVhZkgE80IimBcSwbyQ0vHKrANP/akDERERERGRHDx1jsQrs0RuCg0NlbsEUhhmhkQwLySCeSERzAspHa/MOvDUnzqQ59LpdOjevbvcZZCCMDMkgnkhEcwLiWBeyFWeOkfilVkiNy1btkzuEkhhmBkSwbyQCOaFRDAvpHSczBK5acyYMXKXQArDzJAI5oVEMC8kgnkhpeNklshNBoNB7hJIYZgZEsG8kAjmhUQwL6R0nMwSuenUqVNyl0AKw8yQCOaFRDAvJIJ5IaVT/GT2yJEjmDhxIq655hoEBATgyiuvxL333ov169fLXRq1E8HBwXKXQArDzJAI5oVEMC8kgnkhpVP8ZDY7Oxvl5eUIDQ3Fl19+iRkzZgAAHnnkESxevFjm6qg9iIyMlLsEUhhmhkQwLySCeSERzAspXZv8ah6j0YhbbrkFVVVVOHbsmNBzPfVjp4mIiIiIiOTgqXMkxV+Zdcbb2xsDBw5ESUmJW9sxmow4W3YWRpOxeQpTkOZoe3vpv6CgILlLaPcsWaupq1FE5tzJjOhx1V6Ow8ulhP5xNS9GkxFnSs/gTMkZl9rD87yyNdb3fE0iEcwLKZ2P3AU0l8rKShgMBpSWluLXX3/Fpk2b8NRTTzX5nMLCQhQVFdkt02g0AMwvElMSpiCjKAMje47Et+O/hbeXd4vV70mao+3tqf94f7a8bLMW4BMAfZ3e4zN3uZkRPa7a03F4OZTSP67kxWgyInRTKA6ePwgAuLnnzVgxfkWj7eF5Xtma6nu+JpEI5oWUrs1cmX3jjTfQs2dPXHvttXjzzTfx2GOP4ZtvvmnyOfPnz8fw4cPt/lhuhN+wfQN2puxE0W9F2HdmH56abJ4YW36CFR4eDo1Gg5iYGMTHx0OtViMyMhJ6vR4hISF260ZERCAzMxOxsbGIjY1FZmYmIiIi7NYJCQmBXq9HZGQk1Go14uPjERMTA41Gg/DwcLt1Q0NDodPpEBUVhaSkJCQkJCA6OhparRZhYWF264aFhUGr1SI6OhoJCQlISkpCVFQUdDodQkNDnbZp7oK5SE5Ihv60HluWboGmUCPcJm2FFr9+8CtM1SZsWboFG5M2ytqmlhyn+++/v821SUnjtD1tOxIWJAAAjkYdBQD8+sGv0BRqPLZNQ4YMuaxx0hRqsGXpFuhP65GckIy5C+Y22aYZH8/AzpSdKD9Uju1x27H/xH5mz6ZN2gotNn25CdUF1dixdgeWxS3zyDaFhYVdsk3aCi1+nf4rACAvNg/qw2rMXTC30XEaN2EcMooykP9TPvYc2IPo5dHCbdp5cCc2fbkJAPBLxC/QVmg98hzhidlzt0225z1L31vadNtttymyTW1xnJTQpnHjxrW5NrXFcfKENsXFxcETtZl7Zo8dO4Zz584hNzcXa9asga+vLxYsWIDevXs3+pzGrswGBwfj4KGDiMqJapc/ceZP7MVotVr0799f7jLaLSVemb3czPDKbPNSSv+4khdemW1fmup7viaRCOaFXOWp98y2mcmso7Fjx6KkpARpaWlQqVQuP892oG78043QVmjRv1P/dvcCbTQZ3W57c2xDCaKjo/Haa6/JXUa7Zslan4A+yNfne3zm3MmM6HHVXo7Dy6WE/nE1L0aTEWfLzwISMChw0CXbw/O8sjXW93xNIhHMC7nKUyezbebXjB09+eST2Lt3L06cOHHZ2/D28nbpDUFb1Bxtby/9Z/mVUZKPJWu+Pr6KyJw7mRE9rtrLcXi5lNA/rubF28sbg7sMxuCug11qD8/zytZY3/M1iUQwL6R0bXYyazAYAAClpaUyV0Jtnb+/v9wlkMIwMySCeSERzAuJYF5I6RQ/mS0sLGywrLa2Ft999x38/f0xdOhQGaqi9kStVstdAikMM0MimBcSwbyQCOaFlE7xX83zyiuvoKysDPfeey/69++P/Px8fP/99zh27BjmzJmDTp06yV0itXEvvfSS3CWQwjAzJIJ5IRHMC4lgXkjpFH9l9qmnnoKXlxcWLFiAV199FXPnzsWAAQPwyy+/4D//+Y/c5VE7YPk4cyJXMTMkgnkhEcwLiWBeSOna7KcZXy5P/aQuIiIiIiIiOXjqHEnxV2aJ5Gb5gmkiVzEzJIJ5IRHMC4lgXkjpeGXWgaf+1IGIiIiIiEgOnjpH4pVZIjfxfhMSxcyQCOaFRDAvJIJ5IaXjZJbITa+99prcJZDCMDMkgnkhEcwLiWBeSOk4mSVyU3JystwlkMIwMySCeSERzAuJYF5I6TiZJXJTt27d5C6BFIaZIRHMC4lgXkgE80JKx8kskZv69+8vdwmkMMwMiWBeSATzQiKYF1I6TmaJ3LR582a5SyCFYWZIBPNCIpgXEsG8kNLxq3kceOrHTpPn0uv1CAgIkLsMUhBmhkQwLySCeSERzAu5ylPnSLwyS+SmKVOmyF0CKQwzQyKYFxLBvJAI5oWUjldmHXjqTx2IiIiIiIjk4KlzJF6ZJXJTUFCQ3CWQwjAzJIJ5IRHMC4lgXkjp2uRk9uOPP4ZKpcLw4cPlLoXagfXr18tdAikMM0MimBcSwbyQCOaFlK7NTWbPnTuHWbNmoWPHjnKXQu1ERESE3CWQwjAzJIJ5IRHMC4lgXkjpfOQuoLm9+eabuOOOO2A0GnH+/Hm5y6F2YNKkSXKXQArDzJAI5oVEMC8kgnkhpWtTk9nk5GT89NNPSE9Px9SpU1t135LRiNpz53DFgAFQeXu36r5JXpmZmRgxYsRlPfdyc9OceVNKdiWjETXZ2QBU8L1qkEfWatuXABr0q+Xxg+npuCEw0Lpe9enTqCsoRMCY26Dy9kbtuXPw6dsXtefOwVRTi7rCQvj07gWVlzdU3t7wvWoQTDU1KE/YjE7/9zeYLlzAFQMGwFRTg7LfNqHD8GHocO211hoct3VFv77wGzwYABr0qW0bJKMRhn374X/rLVB5e6MmOxuS0QSVtzd8+vZBVXqG08euGNAftefOOd2ud69eds9rqr9MNTWo3JMGQELHO+5odH3Hdtj+31KLqaYWtfn5ACT4Dhhgbb/tPp2Nn2PfeV/ZA8bzF6x9aNtHXr6+DbZhqcOnbx8Y9h+AV/duMJ6/AJ/eveB1hW+DvnJ8TlV6Bg6eOI7rO3ZssI6lvy3LLPXWZGejRptrbavvoEHWfdjuz/HfdXl58OnbF3V5eXZ9UpOdbe0/lZcKAbfdhrq8PLsaO4waibq8PEhGk/V4sM2Cs9wAgF69Fz59etv1ZYdRI2EsLLSrxXE8LDXXZGejNi8fV/Tra9fOxnLg2GfOzimNjaFtPzse186Oo+rTp621WdqnV++Fd88r4XWFr9PzmOV5tucDx2OrLi8P3r16wbD/gLXvbOs8dPAghg8datcGSy2W84hlfGxrMNXUWPvfMr7OzgvO/u9MY+dsy34aO2Ys5wnH9lnG31kmbJc1dU7zxNcNubnzHobIE7SZyazRaMTUqVPx97//3eWDsrCwEEVFRXbLNBqN8L4loxHZk5+DIT0d/qNG4apVK3nCpEu63Nw0Z96Ukl3JaETWs5NRlZEBAPAfNRJXrVrlUbXa9mWHkSOhUgGG9AxrvwKwPp5fXY1Tfn7oMHIkJMmE6oOHzBsJ8EeH628wtzMgANDrne7L96YRqDl8BDCZgHffvbjsJtRkZgIXP6De76ab4OXtBUO682353XwzVCqgKuMgAHOfDlqxAmdDp8CQng6/m29GjeYkpEo9EBAAv+uuQ/XBg/Ub8PIy79/ZYwH+gN7gdLu2z+tw/fWoyshw2l+S0Yjjt98BGMzbgb8/OtxwQ4P1O4wcCUCytqPDyJsB1LfLthbH9nt5qaz7HLTiW2uNtttvehxuQu0pDaRKPVQdO+K61BTkvPiSdRu2dUGlso6NHZv6GtR+sa/yyspwOjDQ+ToXl6lU5rbA37++zyxsl9n2h82/VR0DrO2QKiutfZL9fKj1uLOybYtlPF1on936/v7m/1+sy7YvLetYaml0PPw7AIYqp+28VA4cH7ecUwDYHceO2bL0s+1x7XhuGrRiBbKee97umPC96SbUaE7a1eB4HpOMRpx55tn65wX4w++66+22Yxkn2/52PJaLunVF9saN1uPD7hzjwFKDZDTixJ13QaqstNu24/HreKw09rrR2Dnbdj/OjhnrODu0z3KsOsuE7TLb8XJWu6e+xhHR5Wsz98wuXLgQ2dnZiIyMdPk58+fPx/Dhw+3+BAcHAwBSU1ORlJSEqKgo6HQ6hIaGAqj/1Lfw8HBoNBrExMTgp6VLkbZrFxacPw/d/v2Y+OijdutGREQgMzMTsbGxiI2NRWZmpvUeBcs6ISEh0Ov1iIyMhFqtRnx8PGJiYqDRaBAeHm63bmhoKHQ6HaKiopCUlISEhARER0dDq9UiLCzMbt2wsDBotVpER0cjISHB5TbFx8dDrVYjMjISer0eISEhbFMjbdJoNJfVptpz5/DC+l8BAO9s2oSsfftcatO/X34Zx9LSsLa0BOuTk7Frw4bLblPtuXMI27gBBpMJc7duxa4NGzxynGrPncOLG8wfUjGvqAgH9+zByuhoj8re8yEhMKSn45/nclCVkYH3N29Gdk0NViXuwE9Ll2LXhg2Yu3UrDCYT4gsLAAAvbliP6oOHMK+oCCeqq7AhPx8/JSfhRHUV5mVnAwD+eS7H3Ee5WhhMJiw4fx770tTYVlqKtaUlyK6pwezCAtQcOoR/5pwFALybl4uC9HR8s3079ur1SCkqRGxxMQpqa/FBfj4A4KWNG1CVcRAf5OejoLYWy37fgV+/iUbyzp1YpruAggMH8N+LP9z754njqD54ELMLC5BdU4O1pSXYVlqKQwYDFpw9i5L0dITnauvr1RusbfoxKQkrZn2Cg3t2Y15REWAyXVxHj1d/2wiDyYR527YhbddubCsvx6rEHTiamoppzz0PGAzW9r97+hTy9+/HMt0FpOzahS2pqYgtLkb23r34b8Jm676rMg7ivwmbUVBbi9jiYqQUFWGvXo9lugsoMRrxbl6utf2G9AzMLizAsbQ0LPrgQ6xPTsYhgwHztm2Dbv8Bc5v0emsN1nEqK8WGslIc3qvG3CzzOL16/BjKEzZbj6d527ZBvXsPtpWXm8epuhqzL467tU15uSgpr8Ay3QXs1euxdedOxOxIrB+ni311vZ+vdZxidiRi686ddm0K37QJhvQM83YNBvtxKi/HIZ0OC86fh8FkQrhlTB3GaX1eHjaUleK47gLmFRXBkJ6Oh//6V1RlZNhl75DBgG1lZfXZy88zb88meyVGo7VNKUVF9tmzjL/BgA/OnLGO0/bdu6AuOm9uU20t3s3LhVRZ2eB4WpuXa26TwYAFOefMbbJk7+QJ6zgdSkvDT8nJ2FBWevF4OmvX96/+9huKD6Rb27Q+OQVL5s7F0dRUvL85wXp8VmUctLYp+vffkbxzF1IqK7Ds99+RtW8fXn7+eVRlZFi3+86mBJzalIDliYlIqaywjlNhejrePXXKrob3N2/G0dRU63lv14YN+GL79vo26Q14aeMGu+xZxulElXnsbI9lyzipjx2zHk/fJyXixN59zrNnNOKb7dux/aef8Os30fj+3DnzOOXlWdc1pGfgHyFPIUutRmxxMbakpmDLkqX4Zvs2lBiNeP23jag9d67BuXzJ3LnYkJJiHqfz56HbfwATH30Uhn378erxYwCAuVlZ2LNoMX5MSsSGslIcStuDWVu22uUpPFeLkvR0zN26DYcMBmzNz8fa0hIcV6vx/ubN1mMPAMI3/Yb8/Qes2duSmoov3o1AllqND/LzzZkeN+6S5/L29t6osLCwzbWpLY6TJ7QpLi4OnqhNfM/shQsXcP311yMiIgJvvPEGAOD+++/H+fPncfjw4Uaf19iV2eDgYKHvUFLK1S1qGREREZg1a5bw83hl1nVt7crsFyUleL1r1+a5MmtdxiuzQNu8MjvvfBHCr+zpfB3wyqyzdrbnK7Nfe6nw9s0388osr8y65HLfw1D746nfM9smJrOvvvoqtm3bhiNHjsDX1xeAa5NZZy53oHhPBl0O3jPrurZ0z6zjPV68Z5b3zDZ1z6zjPYyWdXjPLO+ZdXbPrGOdlnMM75n17Nc4Ik/HyWwLOXnyJG688UZ88cUXdl/8/PTTT6O4uBibN29GYGAgunfv7tL2PHWgyHMFBQXxe9pICDNDIpgXEsG8kAjmhVzlqXMkxU9mExMT8Ze//KXJdf7973/jiy++cGl7njpQREREREREcvDUOZLiPwBq+PDhiI+Pb/Bn2LBhGDRoEOLj4/HSSy/JXSa1YZab8IlcxcyQCOaFRDAvJIJ5IaVz+8rs0aNHcerUKZSXl6Nz58649tprceONNzZXfZette+ZpfZLr9cjICBA7jJIQZgZEsG8kAjmhUQwL+QqT50jXfaV2UWLFmHQoEEYPnw4Hn30UUyePBmPPvoohg0bhsGDB2Pp0qXNWSeRx5ozZ47cJZDCMDMkgnkhEcwLiWBeSOl8LudJb775JubOnYvu3bvjxRdfxPDhw9GpUydUVFQgMzMT69atwyuvvIKTJ0/i008/be6aXZKYmCjLfqn9GXfxe+uIXMXMkAjmhUQwLySCeSGlE57MqtVqzJ07F4899hi+++47dOzYscE6X375JSZPnozPP/8cEydOxK233tosxRJ5Iq1WK3cJpDDMDIlgXkgE80IimBdSOuFfM162bBn69u2L2NhYpxNZAOjYsSPi4uLQu3dvLFu2zO0iiTxZcXGx3CWQwjAzJIJ5IRHMC4lgXkjphCezu3fvxsSJE+Hn59fkeh06dMDEiROxc+fOyy6OSAnuvfdeuUsghWFmSATzQiKYFxLBvJDSCU9mc3Jy8Kc//cmldYcOHYqcnBzhooiUJDo6Wu4SSGGYGRLBvJAI5oVEMC+kdMKT2bKyMnTu3NmldTt16oTy8nLhooiUZN68eXKXQArDzJAI5oVEMC8kgnkhpROezEqSBJVKJbQ+UVsWFBQkdwmkMMwMiWBeSATzQiKYF1I6lSQ42/Ty8sKoUaPQv3//S66r1WqRkZEBo9F42QW2Nk/9QmAiIiIiIiI5eOocSfjK7KBBg6DT6ZCZmXnJPzqdDoMGDWqJuok8RmhoqNwlkMIwMySCeSERzAuJYF5I6YSvzLZ1nvpTB/JcOp0O3bt3l7sMUhBmhkQwLySCeSERzAu5ylPnSMJXZonIHr9LmUQxMySCeSERzAuJYF5I6TiZJXLTmDFj5C6BFIaZIRHMC4lgXkgE80JK5yP6hJtuuklofZVKhYMHD4ruhkgxDAaD3CWQwjAzJIJ5IRHMC4lgXkjphCez3bt3F/pqntaQmJiIv/zlL04f2717N+64445Wrojak1OnTsldAikMM0MimBcSwbyQCOaFlE54MpuYmNgCZTSPadOm4bbbbrNbdu2118pUDbUXwcHBcpdACsPMkAjmhUQwLySCeSGla1P3zN5zzz2YPHmy3Z8rr7xS7rKojYuMjJS7BFIYZoZEMC8kgnkhEcwLKZ3wlVlPV15eDn9/f/j4tLmmNclkklB23oDAK/3h5eVZvwbe1i1cuFDuEjyOszxalgV09UPBqVL0HtIFFboqSCYJXl4qdOkVAAB26/QcHIiiM2Xoe11X+Ph4WbdTUqi3Pq/zlf4oO2+Asc4EQ2kN+lzX1bpdC8t6JYV6VF6oQkB3P/h4e8G/qx9O7y9Ez6sD0a13AMrOG6ACrOvqi6vR74Zu1n1b1NWZkHu8GB27+6FLz/rndezeAfknS9Cxux869/BvtJ2WzJhMEnT5lXb7qaszIe9kSYM2W9brc11XlJ03oPJCFTpd2cG6n77XdYWXlwolhXrU1hihy6nAkNt6w8fHCyWFeqgAuz4OvNIfJpOEvJMldv1s2YalHyxtc3yus3936t4BFboqdOrewa4vHf9trDOh8kIV4KNCv+u6QV9SjU7dO0CXX4kL2eXWup1t33FbzvLjmDvbvHTpFWBtd1MZdGyjl5fKui3LWDv2u7HOBH1xdYNxsR1H236yjIElS517+CP/ZAn8u/rCS2Xen6G0Bt98M7/B8eXYpqb6yDablm1btmMorbHLuCXb/l194ePthS69Ahq03bbvLceXpQbbdSp0VXbHu2WcLcdhpys7WI8fx+PXkjln+3bMmH9XP5xJL8JVN1+JC9nl6HtdVwCwjrG+pPqSObLNuO3xYhkfv8ArUFVSYz13NNbnlpptj1vbc47tPmzHz9LO87kVuJBdjsG39IK+pNouU7bnGmd907F7B+QdL8Y7r0WiSFtuHWfb3NiOt+Vc03tIF5SdN9idh2xrt+zbklkvL5Xdcy3j5eyYtBxrjmPibIxt+woSYCitQa8hXVB4qhQdu/uhW++ODV5PnB2njhp7f+TsXNse8T0MKV2bmvG98MILqKiogLe3N+655x5ERUXh1ltvbXT9wsJCFBUV2S3TaDQtXWazM5kkxM85gPxTpegzpAsee2M0J7StKCgoCOvXr5e7DI/hLI8ArMugAuDk2617D+4MlUqF/NNlDda5ws8bL865B15eKvz8+X4UnC6zPubj64W6GtMl6/K+QgVjbeNfq227Hdt1Lfu2fbO/7D/J1nUb3X8j7exzTSCWJ3+IX3/9FWuj9qHwTLl1P89/+md8985O1FYb7dpsu15j+/Hx9UL3/h3t1vt95TH0urozCrPMy2z7uNfgzijO1aO22mjXB7bbsG2b7XN7XxMIFdDg31f4eaO22mj3vMb+7Vi/lw9gqquvu/fgQBScsd9+U9uyrc82d4556XV1JxTnGeza7WwbtvvtM6QLHg0fhXVzD9Rvq4l+t33cdhwtx4Cln3oN7gydtvKS+V20+T0cOJlqnWQ4tsm27kv2txOWGgHYZRsw5/XR/4y2a7uz7fYe3BkAUGCT59pqY/1xcPFvx+OwqRqd7dtZxhx5X6GCl5eX3f5dyZFjG3pd3Qm6XL3T/TTW532uCcRjb94CAE6PW8d92Lbz58/3oSirwrxw5bEG+3Tcj2PfWCzcNB1hD37stG+Ahucax8emRN2NX+YdsKvd0u99hnRB0L9H4tu3Uhs813FMbI81uzGxYWlH/Jz9jZ/jLup9TSAev9i3lmPJ8Th1fP/T2PujujoTYt5IsTvXttcJLd/DkNK1iSPX19cXTzzxBL788kv88ssv+Oijj5CZmYl77rkH6enpjT5v/vz5GD58uN0fy70DqampSEpKQlRUFHQ6HUJDQwGYD3oACA8Ph0ajQUxMDOLj46FWqxEZGQm9Xo+QkBC7dSMiIpCZmYnY2FjExsYiMzMTERERduuEhIRAr9cjMjISarUa8fHxiImJgUajQXh4uN26oaGh0Ol0iIqKQlJSEn5e8wtW/7ICJZVFmLf8A5SdN1jXDQsLg1arRXR0NBISEhTTpoSEBERHR0Or1SIsLMxuXU9r02OPPdbm2uTOOD00fgLyT5UiLnkejh3SYM5nX+DnNb8gJSUZ2zJWo9JQhu92zAZgftMFAGt3zcfhjGOI/201Dp5JRVbBMWzavxI1tVVYtnUmaquNGP9/D6HsvAFL4uZCe+E09p7cjr0ntyM7T4Nf05babW/Z1pmoqa3Cpv0rkVV4DAfPpCI18zcUlWqxdtd8u3W/2zEblVVlSFDH4WTuQfxxVo3f0+NRUlmEuOR51n1bxik99Q9sP/Az/jirxsncg0hQx6Gyykmbds5HUakWu49tMrep0Nyms8cLcYW3L8rOGzBz/jQAwK9pS5GVexJzPpiPXYe3QHvhNNYmL0LeyRI8NH4CCs+UO23T7mObUFRiblNdjcm6PUubtmWsxs5dqfjjrBpJh9fh+OHTmPfthwCAmfOnobbaiLjkeSipLELS4XU4pNmDnTtTzeNUVYaYzbOsbSo4U47oVbNRVKrFut9WY/P235BVeAzf/hiNs8cLreO0cNN01NWY8GvaUmgvnMbuI1ux9+R2aC+cxs8pixuOU425TadzbdpUqsX87839+WH0VOSfNvdvaVkJtmWsxsncgzik2YOkw+us41RwphwfRE8FAMxb/gGOZZ7CnM++wI7EbTiZe9Daps+Xv2et05I9yzht+X0T9uxRY9P+lcg5XoiPF70JAPjgm38h72SJffZO1Lep8Ex5w+ztM4/TvmNJ+GJ2NDL2Hkb0yk8AAF+v+y8A4POY6XZtsoyTpU2Wvnpl3EeY8uxL0Gq1TtsUFTMd+afLrH1vaVPKoY122bMcT7ZjYMnegnlLsWDe0gbHU/7pMgQ//Dhyjhdas7f/eLJ1nCzH04fzp6HgTLk1e5vSYs1tyr7Ypgpzm4y1knXfccnzcL64AEmH11mPJ0ubvtsxG/mnyzD+/x5Cwekya5uSD27AwTOp0Jz7o9E2xacuQVbuSbtxWhI3166PLOO0fvcK6/G0btMaHM44Zm3TzAX/Rl2Nye54sozTmvUrcSzzFOKS56GuxmTd97xvP7RmLzFpe4M2FZwpx4cXj1NLm+J/W43lC1Zhr3pfk+OUnaexnvf2783A6/98AwUX22Sbvat63Wh/jnA479VWG/Fk0FMoKS1ukL0iXT6ee+oFu0zHJc9DkS4fSYfX4fcdW/HD0l+wKS22wXnPNnu7j23C1h0JOJlzBJv2r4RBb8DCDe83aNP+vRlYMG8pNm5ZB+2F002ey9P2qBH73WrM/2ohMg/8gbW75qPgdJn1uP9s6bvIPqm1e32a89kXOHZIg7jkecg/VYqHxk8AAEx59iVrmw6e3I342I2Kfc11933Eiy++2Oba1BbHyRPaFBcXB0+kkiSp8UsVCqbRaHDTTTfh3nvvRUJCgtN1GrsyGxwcjMOHD2PYsGGtUarbeGVWXmFhYfw1HRu8MntRE1dmt5xaggULFrb4lVkAirwya94fr8xarNn5Bbanr+OVWbSjK7NOuHplNi55HibdG97odnhllldmbfE9DLnqyJEjGD58uMfNkdrsZBYAJk2ahJ9//hl6vR7e3t4uPcdTB+pSeM+sfLRaLfr37y93GR6F98w2fc9sXl4u+vfvz3tmec+sS/fMSp30uOqqgXbHF++Z5T2zjd0zm1uQi2v/NJj3zNq0m/fMNo7vYchVnjpHatOT2bfffhtRUVEoLS1FYGCgS8/x1IEizxUdHY3XXntN7jJIQZgZEsG8kAjmhUQwL+QqT50jufWjKEmSsGjRIowZMwZXXnklvL29G/yR81OFT58+jQ4dOqBTp06y1UBt35AhQ+QugRSGmSERzAuJYF5IBPNCSufWTPPtt9/G3LlzMXLkSEyePBndunVrrrqEFBUVoWfPnnbLDh48iF9//RUPPvggvLza76+PUMvz9/eXuwRSGGaGRDAvJIJ5IRHMCymdW5PZFStW4IknnsCaNWuaq57L8tRTT8Hf3x933XUXevXqhT/++AOLFy9GQEAAZs+eLWtt1Pap1Wrcd999cpdBCsLMkAjmhUQwLySCeSGlc2syazAY8Le//a25arlswcHB+P777zF37lyUlZWhZ8+eePzxx/H+++/j2muvlbs8auNeeukluUsghWFmSATzQiKYFxLBvJDSufX7tw888AD27t3bXLVctmnTpiEtLQ0XLlxAbW0tcnNzsXLlSk5kqVVYvpuLyFXMDIlgXkgE80IimBdSOrc+zTg3Nxfjxo3DpEmT8Morr6BHjx7NWZssPPWTuoiIiIiIiOTgqXMkt67M3nDDDTh9+jRmzJiBXr16oWPHjggMDLT706VLl+aqlcgjBQUFyV0CKQwzQyKYFxLBvJAI5oWUzq17Zp944gmoVA2/oJqoPVm/fr3cJZDCMDMkgnkhEcwLiWBeSOncmsx+++23zVQGkXKFh4dj3rx5cpdBCsLMkAjmhUQwLySCeSGl4xewErnptddek7sEUhhmhkQwLySCeSERzAspnduT2bKyMnz44YcYM2YMevfujd69e2PMmDGYOXMmysrKmqNGIo+WnJwsdwmkMMwMiWBeSATzQiKYF1I6tyazubm5GDVqFD788ENUVFTgz3/+M/785z+jsrISH3zwAUaPHo28vLzmqpXII3Xr1k3uEkhhmBkSwbyQCOaFRDAvpHRu3TP7zjvvID8/Hxs2bMBDDz1k99imTZswceJE/Pe//8WKFSvcKpLIk/Xv31/uEkhhmBkSwbyQCOaFRDAvpHRuXZlNSEjA66+/3mAiCwAPPvggpk2bht9++82dXRB5vM2bN8tdAikMM0MimBcSwbyQCOaFlM6tyWxlZSV69+7d6ON9+vRBZWWlO7sg8nhvvPGG3CWQwjAzJIJ5IRHMC4lgXkjp3JrMDh06FHFxcaipqWnwWG1tLeLi4jB06FB3dkHk8aZMmSJ3CaQwzAyJYF5IBPNCIpgXUjq3JrPvvPMO0tLSMGbMGCxevBiJiYlITEzEokWLMGbMGKjVavz3v/9trlqbdODAATzyyCPo3r07AgICMHz4cHz11Vetsm9q39asWSN3CaQwzAyJYF5IBPNCIpgXUjq3JrMTJ05ETEwM8vPzERYWhgceeAAPPPAAXn31VeTl5SEmJgZPPvlkc9XaqC1btuDOO+9EYWEhZsyYgS+//BIPP/wwzp071+L7JgoKCpK7BFIYZoZEMC8kgnkhEcwLKZ1KkiTpcp4oSRLKy8vh6+sLHx8f7Nu3D9nZ2QCAq666Crfeeit8fNz6sGSXlJWV4frrr8ddd92Fn376CV5e7n117pEjRzB8+HAcPnwYw4YNa6YqiYiIiIiIlMlT50iXPfOrqalB9+7d8dVXX8HHxwd33HEHnnrqKTz11FO44447WmUiCwCxsbEoKCjAxx9/DC8vL1RWVsJkMrXKvh2ZTEYU5+fCZDLKsv/2wBP7OCIiQu4SWoQn9nVbIWdmOK7K01bPMc2lLWS6Odvgal7aQr+R+3h+IaW77Bmnn58f+vTpAz8/v+asR9i2bdsQGBgIrVaL4OBgnDhxAh07dsRzzz2HefPmoUOHDo0+t7CwEEVFRXbLNBrNZdVhMhmx+oP/Ivf4UfS74U946oPZ8PLyvqxtkXOe2seTJk2Su4Rm56l93VbIlRmOqzK1xXNMc2kLmW7uNriSl7bQb9Q8eH4hpXPrd3KnTJmC7777zumnGbeWkydPoq6uDo8++ijGjRuHtWvX4sUXX8TChQvxwgsvNPnc+fPnY/jw4XZ/goODAQCpqalISkpCVFQUdDodQkNDAdTfWxAeHg6NRoOYmBjEx8fj980JWPHzr6ipM2L28u9RWlhgXTciIgKZmZmIjY1FbGwsMjMzrT8Js6wTEhICvV6PyMhIqNVqxMfHIyYmBhqNBuHh4XbrhoaGQqfTISoqCklJSUhISEB0dDS0Wi3CwsLs1g0LC4NWq0V0dDQSEhKE2qRWqxEZGQm9Xo+QkBC7deVo00PjxyP3+FH8tC8TR9PTMefTTz2iTV9//XWbG6foL7/EoX378Ev6H8g9fhQPjR+v+DZ50vH0j3/8Q5Y2HT2Yga++N3/YR+TS71BaWMBxUkCbMjMz21ybmmuc8rKyMHv593aZVlqbor/8Epu378DZCyVY8fOvyMvKcmucZs6ceck2Pfv009AcOogdx04hJSUVa3/4od0cT2yTfZtiYmLaXJva4jh5Qpvi4uLgiS77nlkAWL16NSIjI1FdXY0pU6bg6quvhr+/f4P1Hn/8cbeKbMqQIUNw+vRphIWFYcGCBdblYWFhWLRoEU6cOIHrrrvO6XMbuzIbHBws/Pvg/Clny/PUPo6NjcUzzzwjdxnNylP7uq2QKzMcV2Vqi+eY5tIWMt3cbXAlL22h36h58PxCrvLUe2bdmsy68mFLKpUKRmPL3Y8xfPhwHDlyBElJSbj33nuty5OTk3HfffdhxYoVeP75513enjsDZTIZUVpYgC69evNFoYV4Yh9nZmZixIgRcpfR7Dyxr9sKOTPDcVWetnqOaS5tIdPN2QZX89IW+o3cx/MLucpTJ7NufUrTjh07mquOy9avXz8cOXIEvXv3tlveq1cvAEBxcXGr1eLl5Y1uffq12v7aI0/s47i4uDb5QuCJfd1WyJkZjqvytNVzTHNpC5luzja4mpe20G/kPp5fSOncmszed999zVXHZbvllluwdetWaLVa3HDDDdblubm5AICePXvKVRq1E7NmzZK7BFIYZoZEMC8kgnkhEcwLKZ17X8rqASw3QC9btsxu+dKlS+Hj44P7779fhqqoPeEXjpMoZoZEMC8kgnkhEcwLKZ1bV2b/+te/XnIdlUqF7du3u7ObJo0aNQovvvgiYmJiUFdXh/vuuw+JiYn48ccf8e6776JfP/4KDbWs9evXy10CKQwzQyKYFxLBvJAI5oWUzq0rsyaTCZIk2f2pq6vDqVOnkJiYiHPnzsFkMjVXrY1auHAhPvjgA6SlpeH1119Heno65s2bx1+doFZh+e0AIlcxMySCeSERzAuJYF5I6dz6NOOmbNiwAS+//DI2btyIUaNGtcQuWoSnflIXeS69Xo+AgAC5yyAFYWZIBPNCIpgXEsG8kKs8dY7UYvfMPvzww5g8eTJef/31ltoFkUeYM2eO3CWQwjAzJIJ5IRHMC4lgXkjpWvQDoIYMGYK9e/e25C6IZDdu3Di5SyCFYWZIBPNCIpgXEsG8kNK12GS2rq4Oa9aswZVXXtlSuyDyCFqtVu4SSGGYGRLBvJAI5oVEMC+kdG59mvGLL77odHlJSQn27NmD/Px8zJ07151dEHm84uJiuUsghWFmSATzQiKYFxLBvJDSuTWZ/f3336FSqeyWqVQqdOvWDXfffTf+/ve/Y+zYsW4VSOTp7r33XrlLIIVhZkgE80IimBcSwbyQ0rn1a8ZZWVk4c+aM3Z/Tp09j//79WLNmDSey1C5ER0fLXQIpDDNDIpgXEsG8kAjmhZSuxb6aR6k89WOniYiIiIiI5OCpcyS3PwCqrKwMs2fPxrhx4zBq1Cio1WoAgE6nw9y5c6HRaNwuksiTBQUFyV0CKQwzQyKYFxLBvJAI5oWUzq17Zs+dO4f77rsPOTk5uO6663Ds2DFUVFQAALp3745FixYhOzsbX375ZbMUS+SJ1q9fL3cJpDDMDIlgXkgE80IimBdSOreuzL711lsoLy9HRkYGkpKS4Pgby8HBwdi2bZtbBRJ5utDQULlLIIVhZkgE80IimBcSwbyQ0rk1md2yZQumTZuGoUOHNvhUYwC45pprkJOT484uiDzevHnz5C6BFIaZIRHMC4lgXkgE80JK59Zk1mAwoGfPno0+Xl5e7s7miRRh2bJlcpdACsPMkAjmhUQwLySCeSGlc2syO3ToUCQnJzf6+Lp16zBq1Ch3duGSKVOmQKVSNfpHq9W2eA3Ufo0ZM0buEkhhmBkSwbyQCOaFRDAvpHRufQDU66+/jtDQUNx0002YOHEiAMBkMkGj0eDDDz/E7t27sXbt2mYptCmvvPIK/va3v9ktkyQJYWFhuPrqq9G/f/8Wr4HaL4PBIHcJpDDMDIlgXkgE80IimBdSOrcms5MnT0Z2djbee+89TJ8+HQAwfvx4SJIELy8vzJo1C8HBwc1RZ5PuvPNO3HnnnXbLUlNTodfr8eyzz7b4/ql9O3XqlNwlkMIwMySCeSERzAuJYF5I6dyazALA9OnT8dxzz2Ht2rXQaDQwmUwYMmQIHn/8cVxzzTXNUeNliY2NhUqlwjPPPCNbDU2RTBKMuip4d+8AlVfDD88i5QgODhYeT08Z/+aow1PaoiSt8UM+ajuYFxIhkheev4nnF1I6tyezADBo0CCEh4c3x6aaRW1tLdasWYO77roLV199daPrFRYWoqioyG6ZRqNp4erMLx5Fiw6hJrsMvlcFoucrN/FFRMFmzpyJyJH/dHk8PWX8m6MOT2mL0kRGRmLhwoVyl0EKwbyQCFfzwvM3ATy/kPK59QFQnmrz5s24cOHCJX/FeP78+Rg+fLjdH8tPqFJTU5GUlISoqCjodDrr93AFBQUBAMLDw6HRaBATE4P4+Hio1WpERkZCr9cjJCTEbt2IiAhkZmYiNjYWsbGxyEjdh5nffQ4AeHbOP2HUVSEkJAR6vR6RkZFQq9WIj49HTEwMNBqN9QcFlu2FhoZCp9MhKioKSUlJSEhIQHR0NLRaLcLCwuzWDQsLg1arRXR0NBISElqsTZmZmYiIiLBbp7206daho3A84w98sP1r1GSXIejBCU226eyRU3hj8f/sxl+WNj04ATXZZXh13fso1RRi5vT3hcfptx9/xeL4b5FXXoQ3Fv8PRl2Vx46TJ2VPp9O1uTa1xXHylDYtXLiwzbWpLY6Tp7Spf//+LrWp6FQuvlqzCLvPZmDzjq34OuoLj21TWxwnT2nTuHHj2lyb2uI4eUKb4uLi4IlUkiRJIk+46aabxHagUuHgwYNCz3HXM888g59++gl5eXno0aNHo+s1dmU2ODgYhw8fxrBhw1qkPv40tG0JejgIyyZ8xCuzzLLLgoKCsH79ernLIIVgXkiEq3nh+ZsAnl/IdUeOHMHw4cNbdI50OYQns/fffz9Uqkuf7PLz83H8+HGoVCoYjcbLLlBURUUFevfujb/+9a+XdXC21kDxPpW2hffMyt8WIiISw/M3EbnKUyezwr9mnJiYiB07djT6Jy4uDiNHjkR2dja8vb2tl8xby7p16xTxKcYqLxV8rvTni0cbEBYWJjyenjL+zVGHp7RFSSy/dkTkCuaFRIjkhedv4vmFlE74ymxjCgoKMHv2bCxevBi1tbWYPHkypk+fjiFDhjTH5l324IMPIjU1FQUFBQgICBB+vqf+1IE8l1ar5XcZkxBmhkQwLySCeSERzAu5ylPnSG5/AFR+fj7Cw8NxzTXXIDo6Gk899RSOHTuGmJiYVp/IFhUVYdu2bXjssccuayJLdDnWrVsndwmkMMwMiWBeSATzQiKYF1K6y/5qnvz8fMyePRtLlixBbW0tnnvuObz33nsYPHhwc9YnZPXq1airq/P4XzGmtqW1f2hDysfMkAjmhUQwLySCeSGlE57M5uXlWSexdXV1eP755zF9+nRZJ7EW33//PXr16oW//e1vcpdC7Yi/v7/cJZDCMDMkgnkhEcwLiWBeSOmEJ7NDhgxBdXU1Ro4ciYiICAwePBjFxcUoLi5u9DmjR492q0hX7d69u1X2Q2RLrVbjvvvuk7sMUhBmhkQwLySCeSERzAspnfAHQHl51d9me6mv6JEkqdW/msddnnpzM3kunU6H7t27y10GKQgzQyKYFxLBvJAI5oVc5alzJOErs8uXL2+JOogUKzw8HCtWrJC7DFIQZoZEMC8kgnkhEcwLKV2zfTVPW+GpP3UgIiIiIiKSg6fOkdz+ah6i9i4oKEjuEkhhmBkSwbyQCOaFRDAvpHS8MuvAU3/qQEREREREJAdPnSPxyiyRm8LDw+UugRSGmSERzAuJYF5IBPNCSsfJLJGbXnvtNblLIIVhZkgE80IimBcSwbyQ0nEyS+Sm5ORkuUsghWFmSATzQiKYFxLBvJDScTJL5KZu3brJXQIpDDNDIpgXEsG8kAjmhZSOk1kiN/Xv31/uEkhhmBkSwbyQCOaFRDAvpHSczBK5afPmzXKXQArDzJAI5oVEMC8kgnkhpeNX8zjw1I+dJs+l1+sREBAgdxmkIMwMiWBeSATzQiKYF3KVp86R2sSV2ZMnT+Lpp5/GgAEDEBAQgBtvvBEzZ86EXq+XuzRqB6ZMmSJ3CaQwzAyJYF5IBPNCIpgXUjrFX5nNycnBTTfdhC5duiAsLAzdu3fH7t278e233+KRRx7BL7/8IrQ9T/2pAxERERERkRw8dY6k+CuzK1euRElJCTZu3Ij//ve/ePnll7F8+XI8//zz+PXXX1FcXCx3idTGBQUFyV0CKQwzQyKYFxLBvJAI5oWUTvGT2bKyMgBA79697Zb37dsXXl5e8PX1laMsAmAymXDhwgWYTKYW3W5L7cdV69evd7pc7rrIczWWGXKuvR9LSshLex8jT2AZA9HfSKP2TQnnF6KmKH4ye//99wMAXnrpJWRkZCAnJwerV6/GggULMG3aNHTs2LHR5xYWFuLIkSN2fzQaTStV3raZTCYsX74cX3/9NZYvX95sb3Act1tXV9ci+xERERFxyTr5Bo9sOcsMOcdjyfPzwjGSn+0YBAUFcQzIZZ5+fiG6FMVPZsePH4/IyEhs3boVo0aNwqBBg/D0009j6tSpmDdvXpPPnT9/PoYPH273Jzg4GACQmpqKpKQkREVFQafTITQ0FED9r2OEh4dDo9EgJiYG8fHxUKvViIyMhF6vR0hIiN26ERERyMzMRGxsLGJjY5GZmWk9eVjWCQkJgV6vR2RkJNRqNeLj4xETEwONRoPw8HC7dUNDQ6HT6RAVFYWkpCQkJCQgOjoaWq0WYWFhduuGhYVBq9UiOjoaCQkJrdam4uJizJ07F7W1tVi1ahW2b9/eLG0qLi7GggULUFZWhrVr1+K7775DSkoKdu7ciRMnTuCZZ55p9XHq0KFDgzYVFxfj66+/hsFgwA8//IANGzZ45Di1xewpoU379+9vc21qqXF68MEHkZOTg3Xr1uHEiROYOXOm4tskOk6TJk3y6DYVFxfjs88+AwB8/fXXOH36dJvInpKOJ9vX3KKiomZ7zeU4tf029erVq821qS2Okye0KS4uDp5I8R8ABQCrVq3CqlWr8MQTT6BHjx7YuHEjli9fjq+++gr/+te/Gn1eYWEhioqK7JZpNBoEBwd73M3NSmP5KXFOTg4GDhyIF154AV5e7v/sxHG7oaGhWLFiRbPvR0RsbKx1Et1YnXLURZ7LWWbIOR5Lnp8XjpH8bMcgNzcXCxcu5BiQSzz9/EKew1M/AMpH7gLc9cMPP+Dll1/GiRMnMGDAAADA448/DpPJhHfeeQeTJk1Cjx49nD63V69e6NWrV2uW2254eXnhhRdeQHFxMbp169ZsL6rOttsS+3GXp9ZFpDQ8ljwfx0h+tmOwadMmjgERtRuKP9vNnz8fo0aNsk5kLR555BHo9Xqkp6fLVBl5eXmhR48ezf6i6rjdltqPq0aMGOF0udx1kedqLDPkXHs/lpSQl/Y+Rp7AMgY333yz3KWQgijh/ELUFMW/6hQUFMBoNDZYXltbCwCoq6tr7ZKonfHUewjIczEzJIJ5IRHMC4lgXkjpFH/PbFBQELZs2YLMzExcf/311uWPPfYYfv31V+Tk5KBfv34ub89Tfx+ciIiIiIhIDp46R1L8ldm33noLRqMR99xzDyIjIzF//nw89NBDWLduHV588UWhiSzR5eAXjpMoZoZEMC8kgnkhEcwLKZ3ir8wCgFqtxgcffID09HRcuHABgwcPRmhoKN5++234+Ih9xpWn/tSBiIiIiIhIDp46R1L8lVkAGDNmDH777Tfk5eWhpqYGx48fR0REhPBEluhyWL7ri8hVzAyJYF5IBPNCIpgXUro2cWW2OXnqTx3Ic+n1egQEBMhdBikIM0MimBcSwbyQCOaFXOWpc6Q2cWWWSE5z5syRuwRSGGaGRDAvJIJ5IRHMCykdJ7NEbho3bpzcJZDCMDMkgnkhEcwLiWBeSOk4mSVyk1arlbsEUhhmhkQwLySCeSERzAspHSezRG4qLi6WuwRSGGaGRDAvJIJ5IRHMCykdJ7NEbrr33nvlLoEUhpkhEcwLiWBeSATzQkrHySyRm6Kjo+UugRSGmSERzAuJYF5IBPNCSsev5nHgqR87TUREREREJAdPnSPxyiyRm4KCguQugRSGmSERzAuJYF5IBPNCSscrsw489acOREREREREcvDUORKvzBK5KTQ0VO4SSGGYGRLBvJAI5oVEMC+kdG1iMrt//36MHz8egYGB6Ny5M8aOHYuMjAy5y6J2Yt68eXKXQArDzJAI5oVEMC8kgnkhpVP8ZPbAgQO4++67cfr0abz//vv43//+h5MnT+K+++7D8ePH5S6P2oFly5bJXQIpDDNDIpgXEsG8kAjmhZTOR+4C3DVjxgz4+/tj9+7d6NGjBwBg8uTJuP766xEREYG1a9fKXCG1dWPGjJG7BFIYZoZEMC8kgnkhEcwLKZ3iJ7MpKSkYP368dSILAH379sV9992HDRs2oKKiAp06dZKxQmppkmSEwZADf/+BUKm8W337BoPBbl29PguACgEBV0GSjCgu2YtuXW+DSuVtfczffwAMhpxL/luvz4LBoAUAdOjQF15evggIuMpah21tAKDXZ0GSTFCpvO3Ws13Xz683ikv2oYNfHwQEXAWDIcfpc0ymGuiK06zrVVXlOt2Pv/8AVFXlwtf3ShQUJiAwcAQ6dbz2Yt/U95ulbyTJBADW/Vn6qGuX0aiuLkCHDv1QVZWLDh36WfsiIOAq635t+6a6ugBdu96Kqqpcp8urqwucjpulbb5XdEd1dSFUKi90734nVCrvBv1p2X9T2Wqqbx3H1bzcYJcVP79eKChMQKdON6CutsSuTZZ9N5ZDx3Gy7KdDh74oKT1gzZ7BkIMOHfo16B/b/q6qyrVrQ8eO19hlrbLyVIO+tc24l5cvAMBoNCC/YCMCA0cgwH8QdMVqSKY6qFRe8PPrhZqa8/Dz6w2Vyhsqlbe11q5dRjdot7N+toxPRcUJlJYehF+H3ujR/c/WY8w2z5YcXnFFN2hzV2NA/2fg49OpwbHa2PFjaXdVVR46dOjX5DFjqc+xTy1/Ox4/ludYxsExM5bnFhdnwWS6s8H4WI5LyzLfK7rb9a2F5Ti1rdv2/5YabMfEcmyev7ATNdUF6Bw4DLU1Ovj59YaXl6+1Psu+/Xx72j3XsZ22+7Ttc8dMO/ahY95tM+Ds/Goy1aKmpgjdut0OLy9fp+NsOVZ1xWpAMsHffwA6drzGrh5n9Ts7DzmOs2MfO7ahsfaZTDUoLtmLLoE3o6Q0HX6+PZ2e752dA7t1u93u9aWysgwVFSesmbUcx5Z9WM61tlny9x9gzVBtrc7pOci2BpOp1i63jjl3duw6OzYt55Ru3W4HAOiK0xptu+3YOPu3YxsNhhxUVxegS5dRKClNtx4fjsexs+PEkiPbc52zsbfNYZfAm1FadrDJ13vbDDW2D9vzVd8+j+GCLgW9ez0ILy/fBseLpb22518Ly2uDn29PAEBVVR4ANMh7ZWUZ9Posu9dcyznZWZuMxiqUlx9BYJeb0anjtZAkIy7odkMFNHgdtX3tauo1xvH1zfZ1zVKrbe78/HoDgLX/DIacBudoV84zfn69G22ns9cGx5zY5lmSjA1eix2fY3t8ODsmnNVne1w6ntcct6/XZ6GqKq/R87Tt64bteNuey5z1neW9Q0nJfngixU9mq6ur4e/v32B5QEAAampqcPjwYdxxxx1On1tYWIiioiK7ZRqNpkXqpJYhSUbsP/A0SksPoEuX0bhl9A/NOqF1ZfunTp2yrrtv/1MoK0sHAHTuNBJ6w0kYjZXw8gpAx47Xo7w8AwDg5RUAk0nf5L9VKn9IkgGOugSOxi23/AAA1toCA0cBElBWnt5gPctJ07IuoAIgNdif7XMkyYik5Fusj3l7d4TRWOl0P5bHbHXufDO8VN4oLTP32+hR32P/gWesfWNdz6aPzHc9mKzbs60tsPMoAPX7te+b+vbYLzdvz3HcTKYau7ZZeHkFoFOnG1BWlt6gnbZ96ciVvrX9d5fA0dBo7kaPK5c26I969dvpEjgao0d/jwPpzzbIoWNb7MfT3H7bdjnrH0t/149j/b4DA0fh1ltWAwD27gux5tfy3M6dR0KvP2l9/r337IMkGZGYNMK6DdeYt+fYbts+t+3nwMBRMBlNqKg8WL8FL3907HiDTY3m3KhUKpSWHbAuO3XqU9x7zwFkHHzJ2v+O+bLt9337J9lts7FjBqg/Hh37tKnjx64XbLZt+9zff89F125zGoyPszFrtIcd6nb8v6POnUaivOIYgCqnjze1b2f96bhP27GxZBpo2Ie2ebfNgG32HM+vlvruuTsNB9KfsxtnxzxY29t5JLxUXigtc34+ddYux/F17FPHNjTWvlEjv0NK6u0NzqOAfb5sX19sj2XH9ids1sOvQ0B93YGjMHrUSpt9NDzeGo5jw2PRsQbHdjobM6Dha6OlLyVJQnlFhrU9KpXqksdWYOAoqKCyjpPl35fqR0eN5b/hcnNfOWbC0lbbHNpuo7HXe+fHRv0+LO2xOHXqUwDA0aNvIzDwZpSVZVj7V5KMSE651e78a5nQNvY6Z2Gb981bquDXoYPT14/G2mTRqdNNqKw8aZdFy+uN5bXf8trV2GvMLaNj7V7fRo38DskpY6y1dO48EiqoGj1vOhI5z1yqna6cywDz+bJSf6KR12Iz2+PD2XsiZ3l3PC6dndcsnL1ndNbnzs5Xjb3vsvSdZdtZWTWNdbusFH/P7A033IA9e/bAaDRal9XU1CAtLQ0AoNVqG33u/PnzMXz4cLs/wcHBAIDU1FQkJSUhKioKOp3O+mlvlu/jCg8Ph0ajQUxMDOLj46FWqxEZGQm9Xo+QkBC7dSMiIpCZmYnY2FjExsYiMzMTERERduuEhIRAr9cjMjISarUa8fHxiImJgUajQXh4uN26oaGh0Ol0iIqKQlJSEhISEhAdHQ2tVouwsDC7dcPCwqDVahEdHY2EhIQ216ZfflmF5OSdWL26BDk5ezF5ckiztuntt6ehtPQA3puej9LSA3jyyUcatKmqqgoajQZTp76MsrJ0vDc9HwDw3ntbUFxchtWrS5CefgHbt+/CL+tKcb6oDnPnZJvXmZ4Pk0mPL+YV4XxRHeJ/zoNarcfBgwb88EMeysqM+HR2oXVdAPhk9hYcPpyChQvnYOPGFBw7VoX50b+jsGg/Zs4ssK5bWnYAb789DZmZmfj222/w88/JOH26BsuWXrDb98yZBaiqMmHVymKkqXdh9eql+Cb6feTklGL+/PMAgHf/a56wT4/YjHPafVi9ugQHDxqgVuvx89pcnC+qwxfziqzbLS8/iA8/3IzzRXX4bsUO/LT2a6Sk7MLq1SV2bfr3vxNgNFZi/vzz0GqrsWlTGZKSCnHsWBW+W6FFVZUJM2cWoKw8HdOmbQIALFuqw6lTpdi+vQLbt1fg9OlqLFuqu1jfGQC42KY6c5vSzG2yZO+frz0Hk0lv7c9PZxeirMyIuLhcpKTsglqtx8rvEnH69F5rm6ZO/Q0GQ47T42nWrPeQk7P3Ypsk63a/+eYstNpabNpUhuTkIhw7VoVVK4tRULgP69evscvKsqU6nD5d47RNU6f+huKSvXjjjU2oqjIh+pvtSElZj/j4+AbjFPHuaZs21Vqzt23bTvyyrhRFheU245QLAJjzeRbOF9Xh57W5F7Ont47T9IjNMBhyMGHCWJSXZ1wcp1ps2lSC1NRK7N27Byu+PYeqKhPef/80ikv2Yvz4ewBITtpUY22Tpd312buAY8eqkJpagU2byqDV1uKT2VtgMORYj8/Jk0OQk7MXq1eXICVlF37fsdt6PH0xrwgmkwH/npYAANbjaeXKRGzdloqDBw122cvKXohpU815mj//PI4eU2P1miSkplbajdPjj49HeXmG3ThpNCV2bZo7d5u1j0pLD2DmzAJUVpZj1cpiHDlyAampldiwIQ9abS1mz96KsvL0BtmzHE979py3tmnO51nWY+/Pf+5oHadf1pVYzxGxsdqLbSqw69f6cSqztsn2eLLNSmPjVF6RgfemZzmMU/HFcapv0/z5RXb7/nR2Ic5p92HJ0h3Wc4Sz815ZebrdOeKXX1Zhy5YfsXjx7ygrM2LWx+Zjeeq/zMdeeHg4Dh9OwQ8/JDbI3gcfnGkwTidPFmPhwgjEx6dY21RWno6pU39z2qZNm3bih9WJTY7TkqU7kJK6y9qmgvxSfDGvCEZjZYNz+S/rSrF7dxEOHjRg8eLfodVmYvLkEOvrieW898cfafjyyzet571VK4vtxsly7nn77WnIyEizjtOpU6XW4yni3dMoL8+wtik/z2Adp02bynD0qBphr4ZY6wRMF9tUZ3Mur7Q7nmzPZR9+uBmnTu3FF198jG3bdjY4nizbtW3TwoVzrK+577//FgoL7V+fysrT8cUXv1uzt21bETSaErtzRGmZ+TX3woUTiP5mO44dq8Jvv6XajVNpWf3r89OTHrK+5jpmz/b1CQDmzsm2jpPleFq9ugQlJeUOr7km8zniqP05wpK9t97abNOv9eeIdetSrcfTksXn7Nr95lsJDsdTuXWcPpm9pcHxZD5HFCMlZTfUaj2+W7EDp07txYsvhdj1/YsvhVhfn35a+zXS0y80eM21bvfTbfjjaBo2bSqDj3eNk3OEqck2Wcbp9X9vgSQZrNn7boUWavVupKZW4ocfErH/QDw++WSL9VxmblOB9byXkrILP639Gt+t2IHzRXX48IPNKCjcZD0/fTGvCGdO78PKlYl24+SsTZbz3saN+dZxmj//dxQU7sPMmQUoLT2ACRPGwmDIwdw52y5mr8yuTSaT3vo6MnNmAQqL9mP+/N/tjietthbffHPWbt/vvbcFJSXlTs/lluxZ2v/hB5vxxx+/YeV39m3KOWd+D2sw5GDqv3672KYiu3P5kSMX8N93X2xwPAHA0iXaBufyxYtyLq6TZ22T5fXpjz901jadPVuC+fPP2703mj59M3LOmV9zMzJ0UKv1+H17OTyR4r9nduHChXj11VcRGhqKt99+GyaTCR999BF+/vln1NbWYuXKlZg8ebLT5zZ2ZTY4ONjjvkOJnPOEK7NhYWFYuHAhr8za4JXZpq/MLlnSFX//RzGvzNb3PlrryiwAxV2ZnfN5Ft5482pemeWVWZeuzH7xRTFef71bfd28MtuAUq7M1lO12JXZL78owb9f78ors07aySuzDa/M/v2lcx43R1L8ZBYApk+fjqioKNTW1gIAbr31VowbNw4ff/wx4uPjrVdbXeGpXwhMjZP7nlnHdXnPLO+ZvdQ9s7b9wXtmec/spe6ZbWx8eM8s75l1ds+s7b1zvGeW98xe6p5ZZ6+5vGfW/pzBe2bN7x0OHtyDu+8O9bg5UpuYzAJAcXExjhw5gi5dumDEiBGIiIjAJ598giNHjmDo0KEub4eTWRIVFBSE9evXy10GKQgzQyKYFxLBvJAI5oVc5alzpDYzmXU0ZswY5OXlITs7G15ert8a7KkDRUREREREJAdPnSMp/gOgnFm9ejX27t2L119/XWgiS3Q5LB9QReQqZoZEMC8kgnkhEcwLKZ3ir8wmJydj5syZGDt2LHr06IE9e/Zg+fLl+L//+z+sX78ePj5i3z7kqT91IM+l1WrRv39/ucsgBWFmSATzQiKYFxLBvJCrPHWOpPjLlv3794e3tzeioqLw2muvITU1FR999BF++eUX4Yks0eVYt26d3CWQwjAzJIJ5IRHMC4lgXkjpFD/bGzJkCDZv3ix3GdSODRkyRO4SSGGYGRLBvJAI5oVEMC+kdIq/MkskN39/f7lLIIVhZkgE80IimBcSwbyQ0nEyS+QmtVotdwmkMMwMiWBeSATzQiKYF1I6TmaJ3PTSSy/JXQIpDDNDIpgXEsG8kAjmhZSOk1kiN4WHh8tdAikMM0MimBcSwbyQCOaFlE7xX83T3Dz1Y6eJiIiIiIjk4KlzJF6ZJXJTUFCQ3CWQwjAzJIJ5IRHMC4lgXkjpeGXWgaf+1IGIiIiIiEgOnjpH4pVZIjfxfhMSxcyQCOaFRDAvJIJ5IaXjZJbITa+99prcJZDCMDMkgnkhEcwLiWBeSOk4mSVyU3JystwlkMIwMySCeSERzAuJYF5I6TiZJXJTt27d5C6BFIaZIRHMC4lgXkgE80JKx8kskZv69+8vdwmkMMwMiWBeSATzQiKYF1I6j57MVlRU4P3338f48ePRvXt3qFQqfPvtt07XPXr0KMaPH49OnTqhe/fueO6551BUVNS6BVO7tHnzZrlLIIVhZkgE80IimBcSwbyQ0nn0V/NkZWVh8ODBGDRoEK655hokJiZi+fLlmDJlit16586dw6hRo9ClSxdMmzYNFRUV+PzzzzFo0CCo1Wr4+vq6vE9P/dhp8lx6vR4BAQFyl0EKwsyQCOaFRDAvJIJ5IVd56hzJo6/M9u3bF3l5ecjOzkZUVFSj682aNQuVlZX4/fffMW3aNERERGDNmjU4ePBgo1dyiZqL4w9XiC6FmSERzAuJYF5IBPNCSufRk1k/Pz/06dPnkuutXbsWDz/8MAYNGmRd9re//Q3XX3891qxZ05IlkgOjJOGMvhpGz73g3+yYsbarpfLc2pnxxOOyqZo8sV5Hl6rRnfbVmExI1pWjxmQCwHOMLVezoYQMtZTmykt77sO2znZseX4hpfPoyawrtFotCgsLceuttzZ4bMyYMUhPT2/0uYWFhThy5IjdH41G05LltmlGSULwgZO4M+0ogg+cbDcvgEFBQXKXQC2gJfPcmpnxxOOyqZo8sV5Hl6rRnfbVmEwYmnoYIQdPYWjqYdSYTDzHXORqNpSQoZbUHHlp733YljmO7cM8v5DCKX4ym5eXB8D8K8mO+vbtC51Oh+rqaqfPnT9/PoYPH273Jzg4GACQmpqKpKQkREVFQafTITQ0FED9i0R4eDg0Gg1iYmIQHx8PtVqNyMhI6PV6hISE2K0bERGBzMxMxMbGIjY2FpmZmYiIiLBbJyQkBHq9HpGRkVCr1YiPj0dMTAw0Gg3Cw8Pt1g0NDYVOp0NUVBSSkpKQkJCA6OhoaLVahIWF2a0bFhYGrVaL6OhoJCQktGibpr79DvaW6VEc8W/sLdPjkScnKr5NrozTY4891uba1BbHSbRN6lNnsP1D83a3/OsfOGuoabY2+fv7t1qbftyyDanbtkK/bjX2nMrCc/94WfZxGjvhYewt06Pkw7ehLryAt97/wNqmzxcuxu6jx1Ae/Tn2lukxdsLDHpe9r7/9Dsnxa1F7+iR+n/spzhpq7Mbp+IUS7Ij+ArVHDyNl4wZ8vnCxdZzOGmqw5V//AABsi3gDh7T5dm165/N5KM3PR9m8j1BhNOH+hyZg/fr1ij+emmOckg8fRfLqWFSl/I5daWq89f4HTts09e13sCvjIAzbNyE5fi227D3gsW1qiXEaM2aM222yzen2DyOgPnWmXWevLbXprKEGv38yE3Xas0heHYuHn31O8W1qi+PkiW2Ki4uDJ/LoD4CytW/fPtx2220NPgAqJSUF9957L1avXm0dWIv//e9/iIyMRHFxMbp27dpgm4WFhQ0+8Vij0SA4ONjjbm5WAstP+/aW6XFbYADWjb4O3iqV3GW1uIiICMyaNUvuMqiZtWSeWzMznnhcNlWTJ9br6FI1utM+y5XZCqMJnby98Mfdw/HBe+/xHAPXs6GEDLWk5ji/tPc+bMscx3bYT8sx+5NP5C6LFMBTPwDKR+4C3GW5wuHs6mtVVZXdOo569eqFXr16tVxx7Yy3SoV1o6/DWUMNBvn7tpsXvkmTJsldArWAlsxza2bGE4/LpmryxHodXapGd9rn62WewO4pqcQdXTvC18uL55iLXM2GEjLUkpojL+29D9syx7H9w/cZuUsicovif83Y8uvFll83tpWXl4fu3bvDz8+vtctqt7xVKgwO8GtXL3yZmZlyl0AtpKXy3NqZ8cTjsqmaPLFeR5eq0Z32+Xp54d7uneHrZX6J5jmmnqvZUEKGWkpz5aU992FbZzu2PL+Q0il+Mtu/f3/07NkT+/bta/CYWq3GyJEjW78oIiIiIiIialGKn8wCwBNPPIENGzYgJyfHumz79u04ceIEJk6cKGNl1B6MGDFC7hJIYZgZEsG8kAjmhUQwL6R0Hn/P7DfffIOSkhLk5uYCANavX49z584BAKZOnYouXbogIiICP/74I/7yl7/g3//+NyoqKhAVFYURI0bghRdekLN8agfi4uL4YkBCmBkSwbyQCOaFRDAvpHQe/2nGV199NbKzs50+dubMGVx99dUAzJ+w9Z///Aepqanw9fXFhAkTMGfOHPTu3Vtof576SV1ERERERERy8NQ5ksf/mnFWVhYkSXL6xzKRBYBhw4Zh8+bNqKysRHFxMVatWiU8kSW6HM3xBfXUvjAzJIJ5IRHMC4lgXkjpPP7KbGvz1J86EBERERERycFT50gef2WWyNOFhITIXQIpDDNDIpgXEsG8kAjmhZSOV2YdeOpPHchz6fV6BAQEyF0GKQgzQyKYFxLBvJAI5oVc5alzJF6ZJXLTnDlz5C6BFIaZIRHMC4lgXkgE80JKx8kskZvGjRsndwmkMMwMiWBeSATzQiKYF1I6TmaJ3KTVauUugRSGmSERzAuJYF5IBPNCSsfJLJGbiouL5S6BFIaZIRHMC4lgXkgE80JKx8kskZvuvfdeuUsghWFmSATzQiKYFxLBvJDScTJL5IaCigI8+eaTKKgokLsUj1NQUYCpv01l3zhgZkhUdHS03CWQUhQUIPrJJ4ECnl/sFBQAU6eyXxwxL9QGcDJL5IYZO2bg4KiD+N+O/8ldiseZsWMGvtn7DfvGATNDoubNmyd3CaQUM2Zg3sGDwP94frEzYwbwzTfsF0fMC7UBnMwSXaaskiwsz1gOxAIxGTHILsmWuySPYe0bsG9sMTN0OYKCguQugZQgKwtYvhxBABATA2Tz/ALA2i8A2C+2mBdqIziZJbpMs1Jmoc5UBzwD1JnqMCtlltwleQxr34B9Y4uZocuxfv16uUsgJZg1C6irw3oAqKsz/5+s/QKA/WKLeaE2gpNZostge+UR8ea/eKXNzK5vLmLfMDN0+UJDQ+UugTydzdVHa1p4tc3+qqwF+4V5oTaFk1miy2B75REXv2+cV9rM7PrmIvYNM0OXj/fM0iXZXH20poVX2+yvylqwX5gXalM4mSUS1ODKY3r9P9v7lTZnV2Ut2nPfMDPkjmXLlsldAnkyh6uPdmlpz1fbnF2VtWC/WP/LvJDScTJLJKjBlcf+9f9s71fanF2VtWjPfcPMkDvGjBkjdwnkyRyuPtqlpT1fbXN2VdaC/WL9L/NCSqeSJEmSuwhPcuDAAdxyyy1Yt24drr32WrnLIQ+jLdPiodiHYDQZ6xdmA7iq/r/eXt7Y9Mwm9Avs1+r1yclp3zhoj33DzJC7UlNTcffdd8tdBnkirRZ46CHAWH9+SQVglxZvb2DTJqBfOzq/OOmXBtgvAJgXcp1Go0FwcDD279+P0aNHy12OFSezDlasWIEpU6bIXQYREREREZFH+fbbbz3qgwl95C7A01x//fUAgDVr1mDo0KEyV0OezvJTKl7JJ1cxMySCeSERzAuJYF5IxB9//IGQkBDrXMlTcDLrIDAwEAAwdOhQDBs2TOZqSCmuvfZa5oWEMDMkgnkhEcwLiWBeSIRlruQp+AFQREREREREpDiczBIREREREZHicDJLREREREREisPJrIOePXvi/fffR8+ePeUuhRSAeSFRzAyJYF5IBPNCIpgXEuGpeeFX8xAREREREZHi8MosERERERERKQ4ns0RERERERKQ4nMwSERERERGR4nAyS0RERERERIrDySwREREREREpDiezF1VXV+Odd95Bv3794O/vj9tvvx1bt26VuyxqIXv37sW//vUvDBs2DB07dsSgQYMQEhKCEydONFj36NGjGD9+PDp16oTu3bvjueeeQ1FRUYP1TCYTPvvsMwwePBgdOnTATTfdhLi4OKf7d3Wb5Jk+/vhjqFQqDB8+vMFju3btwt13342AgAD06dMH06ZNQ0VFRYP1RM45rm6TPMuBAwfwyCOPoHv37ggICMDw4cPx1Vdf2a3DvBAAnDx5Ek8//TQGDBiAgIAA3HjjjZg5cyb0er3desxL+1JRUYH3338f48ePR/fu3aFSqfDtt986XVfO9yoi26SW40peTCYTvv32WzzyyCMYOHAgOnbsiOHDh+Ojjz5CVVWV0+0uW7YMf/rTn9ChQwdcd911+Prrr52up9VqERISgq5duyIwMBCPPvooTp8+7dY2XSKRJEmS9PTTT0s+Pj7Sm2++KS1atEi68847JR8fHyklJUXu0qgFPPHEE1KfPn2kqVOnSkuWLJEiIyOl3r17Sx07dpQyMzOt6+Xk5EhXXnmlNGTIEOnLL7+UPv74Y6lbt27SzTffLFVXV9tt87///a8EQPrHP/4hLV68WJowYYIEQIqLi7NbT2Sb5HlycnKkgIAAqWPHjtKwYcPsHktPT5c6dOggjRo1SlqwYIE0ffp0yc/PTxo/fnyD7bh6zhHZJnmOzZs3S76+vtLtt98uzZ07V1q8eLH0zjvvSG+99ZZ1HeaFJEmSzp49K3Xt2lW66qqrpE8++URatGiRNGXKFAmA9Mgjj1jXY17anzNnzkgApEGDBkn333+/BEBavnx5g/Xkfq/i6japZbmSl/LycgmAdMcdd0gfffSRtHjxYumFF16QvLy8pPvvv18ymUx26y9cuFACID3xxBPS4sWLpeeee04CIM2ePbvBdq+77jqpV69e0qeffirNnTtXGjhwoDRgwADp/Pnzl7VNV3EyK0lSWlqaBECKioqyLjMYDNKQIUOkO++8U8bKqKXs3Lmzwcn4xIkTkp+fn/Tss89al7366quSv7+/lJ2dbV22detWCYC0aNEi67Jz585JV1xxhfTaa69Zl5lMJumee+6RBgwYINXV1QlvkzzTU089Jf31r3+V7rvvvgaT2QcffFDq27evVFpaal22ZMkSCYC0efNm6zKRc46r2yTPUVpaKvXu3Vt67LHHJKPR2Oh6zAtJkiR9/PHHEgDp8OHDdsuff/55CYCk0+kkSWJe2qOqqiopLy9PkiRJ2rt3b6OTWTnfq4hsk1qWK3mprq6Wdu7c2eC5H374oQRA2rp1q3WZXq+XevToIU2YMMFu3WeffVbq2LGj9dwkSZL06aefSgAktVptXXb06FHJ29tbevfddy9rm67iZFaSpLfeekvy9va2O5lLkiTNmjVLAiCdPXtWpsqotY0ePVoaPXq09f+9evWSJk6c2GC966+/XnrggQes/4+OjpYASEeOHLFbLzY2VgJg99NwV7dJnicpKUny9vaWDh061GAyW1paKvn4+NhdeZMk8wtHp06dpJdeesm6zNVzjsg2yXMsWLBAAiD98ccfkiRJUkVFRYNJLfNCFu+8844EQCoqKmqw3MvLS6qoqGBeqMnJrJzvVUS2Sa2nqbw4c+jQIQmA9NVXX1mXbdy4UQIgbdy40W7dXbt2SQCklStXWpfddttt0m233dZgu2PHjpWGDBlyWdt0Fe+ZBZCeno7rr78egYGBdsvHjBkDAMjIyJChKmptkiShoKAAV155JQDz7/4XFhbi1ltvbbDumDFjkJ6ebv1/eno6OnbsiD/96U8N1rM8LrpN8ixGoxFTp07F3//+d4wYMaLB45mZmairq2swtr6+vhg5cmSDvLhyzhHZJnmObdu2ITAwEFqtFjfccAM6deqEwMBAvPrqq9Z7kpgXsrj//vsBAC+99BIyMjKQk5OD1atXY8GCBZg2bRo6duzIvFCj5H6v4uo2ybPl5+cDgPU9MFA/do45uOWWW+Dl5WV93GQy4dChQ43m5dSpUygvLxfapghOZgHk5eWhb9++DZZbluXm5rZ2SSSD77//HlqtFk899RQAcy4ANJoNnU6H6upq67q9e/eGSqVqsB5QnyGRbZJnWbhwIbKzsxEZGen08UuNre15xNVzjsg2yXOcPHkSdXV1ePTRRzFu3DisXbsWL774IhYuXIgXXngBAPNC9caPH4/IyEhs3boVo0aNwqBBg/D0009j6tSpmDdvHgDmhRon93sVV7dJnu2zzz5DYGAgHnzwQeuyvLw8eHt7o1evXnbr+vr6okePHtaxteTB1fOOK9sU4SP8jDbIYDDAz8+vwfIOHTpYH6e27dixY3jttddw5513IjQ0FED9uF8qG35+fi5nSGSb5DkuXLiA//3vf5gxYwZ69uzpdJ1Lja3teaS58sJzk2eqqKiAXq9HWFiY9dOLH3/8cdTU1GDRokWYOXMm80J2rr76atx777144okn0KNHD2zcuBGzZs1Cnz598K9//Yt5oUbJ/V6F76GVb9asWdi2bRvmz5+Prl27WpcbDAb4+vo6fY7tOcLVvIhsUwQnswD8/f2dXg2z/DqYv79/a5dErSg/Px8TJkxAly5d8NNPP8Hb2xtA/bi7kg1XMySyTfIc7733Hrp3746pU6c2us6lxtZ2XJsrL8yKZ7KMy6RJk+yWP/PMM1i0aBF2796NgIAAAMwLAT/88ANefvllnDhxAgMGDABg/uGHyWTCO++8g0mTJvH8Qo2S+70K30Mr2+rVq/Hee+/hpZdewquvvmr3mL+/P2pqapw+z/YcIZoXV7Ypgr9mDPMlcMuvVNiyLOvXr19rl0StpLS0FA8++CBKSkqQkJBgN9aWX41oLBvdu3e3/hSqb9++yM/PhyRJDdYD6jMksk3yDCdPnsTixYsxbdo05ObmIisrC1lZWaiqqkJtbS2ysrKg0+kuObaO2XLlnCOyTfIclnHp3bu33XLLr1UVFxczL2Q1f/58jBo1yjqRtXjkkUeg1+uRnp7OvFCj5H6v4uo2yfNs3boVzz//PCZMmICFCxc2eLxv374wGo0oLCy0W15TU4MLFy5Yx9aSB1fPO65sUwQnswBGjhyJEydOoKyszG55Wlqa9XFqe6qqqhAUFIQTJ05gw4YNGDp0qN3j/fv3R8+ePbFv374Gz1Wr1Xa5GDlyJPR6PY4ePWq3nmOGRLZJnkGr1cJkMmHatGkYPHiw9U9aWhpOnDiBwYMHY+bMmRg+fDh8fHwajG1NTQ0yMjIa5MWVc47INslz3HLLLQDM2bFluReoZ8+ezAtZFRQUwGg0NlheW1sLAKirq2NeqFFyv1dxdZvkWdLS0vDYY4/h1ltvxZo1a+Dj0/CXdS1j55iDffv2wWQyWR/38vLCiBEjnOYlLS0N11xzDTp37iy0TSHCn3/cBu3Zs6fBd7JVVVVJ1157rXT77bfLWBm1lLq6OumRRx6RfHx8Gnw8uK2wsDDJ39/f7uuZtm3bJgGQFixYYF2Wk5PT6Pes9e/f3+571lzdJnmGoqIiKT4+vsGfYcOGSYMGDZLi4+OlQ4cOSZIkSePHj5f69u0rlZWVWZ+/dOlSCYC0adMm6zKRc46r2yTPceDAAQmA9Mwzz9gtnzRpkuTj4yNptVpJkpgXMnv44YclX19f6fjx43bLg4ODJS8vL+aFJElq+qtW5HyvIrJNaj1N5eWPP/6QevToIQ0bNqzJ73XV6/VS9+7dpYcffthu+eTJk6WAgADpwoUL1mWzZ8+WAEh79+61Ljt27Jjk7e0tvfPOO5e1TVdxMnvRxIkTrd+3tmjRIumuu+6SfHx8pKSkJLlLoxbw73//WwIgBQUFSStXrmzwx+Ls2bNSjx49pCFDhkhfffWVNGvWLKlbt27SiBEjpKqqKrttvvXWWxIA6eWXX5aWLFkiTZgwQQIgff/993briWyTPJfj98xKkiTt379f8vPzk0aNGiUtWLBAmj59utShQwdp7NixDZ7v6jlHZJvkOV588UUJgBQSEiJFR0dLEydOlADYfXk880KSVP/91b169ZJmzpwpRUdHSw8++KAEQPr73/9uXY95aZ++/vprKTIyUnr11VclANLjjz8uRUZGSpGRkVJJSYkkSfK/V3F1m9TyLpWXsrIyaeDAgZKXl5c0e/bsBu9/d+3aZbc9y/cIP/nkk9KSJUuk559/XgIgffzxx3brlZWVSUOGDJF69eolffbZZ9K8efOkgQMHSv369ZMKCwsva5uu4mT2IoPBIL355ptSnz59JD8/P+m2226TEhIS5C6LWsh9990nAWj0j63Dhw9LY8eOlQICAqSuXbtKzz77rJSfn99gm0ajUZo1a5Z01VVXSb6+vtKwYcOkVatWOd2/q9skz+VsMitJkpSSkiLdddddUocOHaSePXtKr732mt1VDwuRc46r2yTPUVNTI33wwQfSVVddJV1xxRXStddeK82bN6/BeswLSZIkpaWlSQ8++KDUp08f6YorrpCuv/566eOPP5Zqa2vt1mNe2p+rrrqq0fcqZ86csa4n53sVkW1Sy7pUXs6cOdPk+9/Q0NAG21y8eLF0ww03SL6+vtKQIUOkefPmSSaTqcF6OTk50pNPPikFBgZKnTp1kh5++GHp5MmTTut0dZuuUEmSwx3bRERERERERB6OHwBFREREREREisPJLBERERERESkOJ7NERERERESkOJzMEhERERERkeJwMktERERERESKw8ksERERERERKQ4ns0RERERERKQ4nMwSERERERGR4nAyS0RERERERIrDySwREREREREpDiezRERETZgyZQquvvpqucuw+uCDD6BSqaBSqdCpU6dW3//IkSOt+3/44Ydbff9EREQWPnIXQERE1NpUKpVL6+3YsaOFK7l8K1euxBVXXNHq+501axZ0Oh3Cw8Nbfd9ERES2OJklIqJ2Z+XKlXb//+6777B169YGy//0pz9hyZIlMJlMrVmeSyZPnizLfh966CEAwHvvvSfL/omIiCw4mSUionbHcSK4Z88ebN26VbYJIhEREYnjPbNERERNcLxnNisrCyqVCp9//jmio6NxzTXXICAgAGPHjkVOTg4kSUJkZCQGDBgAf39/PProo9DpdA22u2nTJtxzzz3o2LEjOnfujAkTJuDIkSNu1Xr11Vfj4YcfRmJiIm699Vb4+/tjxIgRSExMBAD8/PPPGDFiBDp06IBbbrkF6enpds/Pz8/HCy+8gAEDBsDPzw99+/bFo48+iqysLLfqIiIiagm8MktERHQZvv/+e9TU1GDq1KnQ6XT47LPPEBISgr/+9a9ITEzEO++8A41Gg6+//hpvvvkmYmJirM9duXIlQkNDMW7cOHz66afQ6/VYsGAB7r77bqSnp7v1gVMajQbPPPMMXnnlFUyePBmff/45goKCsHDhQkREROCf//wnAOCTTz5BSEgIjh8/Di8v88+2n3jiCRw5cgRTp07F1VdfjcLCQmzduhVnz571qA/BIiIiAjiZJSIiuixarRYnT55Ely5dAABGoxGffPIJDAYD9u3bBx8f80tsUVERvv/+eyxYsAB+fn6oqKjAtGnT8Pe//x2LFy+2bi80NBQ33HADZs2aZbdc1PHjx7Fr1y7ceeedAIChQ4di3Lhx+Mc//oFjx45h0KBBAIBu3brhlVdeQXJyMu6//36UlJRg165diIqKwptvvmnd3rvvvnvZtRAREbUk/poxERHRZZg4caJ1IgsAt99+OwDz/biWiaxleU1NDbRaLQBg69atKCkpwaRJk3D+/HnrH29vb9x+++1uf4Ly0KFDrRNZ27r++te/WieytstPnz4NAPD394evry8SExNRXFzsVg1EREStgVdmiYiILoPtxBCAdWI7cOBAp8stE8STJ08CME8unQkMDJSlLj8/P3z66ad444030Lt3b9xxxx14+OGH8fzzz6NPnz5u1URERNQSOJklIiK6DN7e3kLLJUkCAOvX/KxcudLpJNH2qm5r1gUAr7/+OoKCgrBu3Tps3rwZM2bMwCeffILff/8do0aNcqsuIiKi5sbJLBERUSsaMmQIAKBXr17429/+JnM1DQ0ZMgRvvPEG3njjDZw8eRIjR47EnDlzsGrVKrlLIyIissN7ZomIiFrRuHHjEBgYiFmzZqG2trbB40VFRTJUBej1elRVVdktGzJkCDp37ozq6mpZaiIiImoKr8wSERG1osDAQCxYsADPPfccRo8ejaeffho9e/bE2bNnsXHjRvz5z3/GN9980+p1nThxAg888ABCQkIwdOhQ+Pj4ID4+HgUFBXj66adbvR4iIqJL4WSWiIiolT3zzDPo168fZs+ejaioKFRXV6N///6455578MILL8hS08CBAzFp0iRs374dK1euhI+PD2688UasWbMGTzzxhCw1ERERNUUl2X7yAxEREXm0Dz74AB9++CGKioqgUqnQo0ePVt1/SUkJ6urqMHr0aNx0003YsGFDq+6fiIjIgvfMEhERKVDPnj1x1VVXtfp+77//fvTs2RM5OTmtvm8iIiJbvDJLRESkIKdPn8bp06cBmL/G5/7772/V/aelpaG8vByAeUJ98803t+r+iYiILDiZJSIiIiIiIsXhrxkTERERERGR4nAyS0RERERERIrDySwREREREREpDiezREREREREpDiczBIREREREZHicDJLREREREREisPJLBERERERESkOJ7NERERERESkOJzMEhERERERkeJwMktERERERESKw8ksERERERERKc7/A0H7krGmIRuTAAAAAElFTkSuQmCC", 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\n", + "image/png": 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\n", 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", 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\n", 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", 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cZREhdvbZZ4e8nrc/+ywpmzeTsGAhvVvQh3O0aY66Fi2D1HX0kLqOHlLX0aMF17Vfww8lAZQQotmUl5eH/Bj2ggIAbLt3h/xYom7NUdeiZZC6jh5S19FD6jp6RHpdSzArhGg2mzZtCvkxHCWlANjy8tB2e8iPJ3xrjroWLYPUdfSQuo4eUtfRI9LrWoJZIUSzMcdAhJSj1Ahmsdux5+eH/HjCN/e6dpSVsf2qq9g29kocZWXhK5QIiea4rkXLIHUdPaSuo0ek17UEs0KIZjNlypSQH8NRUuL6v23fvpAfT/jmXtdFX3xB6Q8/UvbTTxR//XUYSyVCoTmua9EySF1HD6nr6BHpda201uEug4hiSqlBwNq1a9e21MHnIoJoh4O/Bw0G83Ot+ysvkzJsWJhLJbZfcy2ly5cDkH7O2XR57LEwl0gIIURzcDgc7N27l8rKShwOR7iLI8JEKUVsbCxpaWmkpqailKpz3XXr1jF48GCAwVrrdQ3tW1pmhRDNZuTIkSHdv6Os3BXIgrTMNhd7UVGt8cnOurYXFFD600+u5aU//IjcRG1dQn1di5ZD6jp6BKOuHQ4H27dvp6CggKqqKvnsb6GKi4tDun+tNTabjeLiYrKysti+fTs2my1o+5epeYQQzWbevHmN2q70hx/Ie+NN2t0wjsRDDqlzPdd4WVNjg9nSn36mOmsn6eedh7LIPb/6lK3+lW1jxpB44IH0fOdt191WZ10Xf/MNuP3Rsu3bR9XGjcT37x+W8orga+x1LSKP1HX0CEZd7927l/Lyctq0aUOHDh3qbY0TrZ/NZiM7O5vCwkLy8/Np3759UPYb8d/SlFJaKTXJ7fex5rJejdjXCHPbEW7LFiul1vqxbS9z27FuyyYppbTXeluVUrMCLZsQrcG4ceMatd32q66mZMkStl50cb3rOUpLPH63ZQcezNqLi9lx/fXsvv8BSpYuDXj7aFOyeDFUV1O+erVrWiSoqeuihQsBUAkJrudKf/ihOYsoQqyx17WIPFLX0SMYdV1ZWYnVapVAtoXbtm1bsxwnJiaGzp07Y7VaKSkpaXgDP7XIYNYtIK3rcVS4yxgsSqkDzKC3V7jLIkSoPfjgg03eR33dlBxeH462nJyA92/buxddWQlA1ZatAW8fbard5vN1v3nw4IMP4igro/RHo4tx+jnnENOpEwAlEsy2KsG4rkVkkLqOHsGoa4fDgdVqlUC2hevcuXOzHUsphdVqDWqX8xYZzLp5CLjcx2NjPdu8BSQCjbnNsNTctjHNMdvMbd9qYL0BwLVuvx8ATAR6NeKYQkSUuXPnNnkftuzsOp+rFcw2opuxvahm7Ii9sCDg7UPFlp/fIscA29yD2Zya8s2dO5eq7duhuhqA5COPIPmYYwAo+3kFRV98IeOnWolgXNciMkhdR49g1bUEsi1fgVuvquYQ7PdESx8z+6XWemUgG2it7YC9wRV9b+sAKhq5rfZnW611ZWP2L0Rr0Ldv3ybvo/Lvv4nt2NHnc/YgjJl1FBfV7K+wMODtQ8FeUMCmk/+Frqqi78IFxHbpEu4iuXi0zLq93n379qV6507X77HdupF2+mkUfvIJuqKCrDvuJHPlKjo9JC09dXGUlVG2ahVJRxyBJT4+3MWpUzCuaxEZoqGutcMBSkV9EBYNdS0M8S3474s/WnrLbMB8jZlVSlnMrry7lFJlSqnvzO69HuNXfY2ZdXtuqFLqB6VUuVJqi1JqnNfztcbM1lE+1zHNdT80n/rOrRv1CKXUG0qpHKVUrI99fKWUWu/nS+K97eFKqeeVUuuUUqVKqe1KqQ+UUvv5sW193b87NaY8IrokJiYGvI02W/acKtb/U+e6jpLawWygrX/24prWXXsz362sS8X6f3CUlqKrqyn79ddwF8dF2+1U793r+t09mE1MTKQ6K8v1e2y3bqQcfzydp07F2qYNAPnvvos9xFkUI42jtBRdVQXArgn3sOPa69jTwucAbMx1LSKTr7re9/wMtl54EVU7doShRMFVvTebjSecyLaLLsZhXofRSq7r6GGJ8ESXLb306Uqpdl6Pto3Yz6MYXXlXAncDG4CFQLKf22cCXwCrgP8AO4EXlVJXNaIs7pYCz5r/n0pNN+q/MLortwVOdd/ADBpPBN5u5DEnAOcD3wC3Aa8Aw4DVSqnBfu7DV/fvgkaWR0SRFStWBLyN3avrcOXff9e5rnc3Y11ZiSPAYMm9ZdbRQlpm3cvUkroa23Jya2UqdlqxYgVVO41gViUlYc3MBCBj1Hl0+d+jxkpaU756da39Vu/NpsqtVTccKv75h9zXZlL0xRcerc+hoquryX7qadYfcSRbRl9I2epfKf76awAKP/o45MdvisZc1yIyede1vbiYnBkzKP/9d/LeeDNMpQqe4oULse3dS/nvv1P2yy/hLk5YyXUdPUq9erVFmpbezXiRj2WVQIKP5T4ppToCdwBztdbnuS2fCEzyczddgDu11k+a274M/Aw8qpR6S2tdXe/WddBab1ZKLQNuBb7WWi92K98+jKD5MuBzt80uxrgJ0dhg9kngEq2165ajUup9YA1wj3m8hgTc/VsIgKuvvjrgbbyn26lYX3enBO9sxmAEWNa0NL+P5z5m1tZCWmY9ytSIDM2hYtu9y+N3u1vCrauvvprS+x8AIK5rV48ue4mHHgoWCzgclK1cRcrw4a7nqrOy2DzqfHRZGb0+eJ+E/fcP8VnUprVmx/XjXOOBVVwcXZ95mtQTTgjN8aqr2Tb2SspXrQKMGzbbr7nG9bxqRBewgo8/oeyXX+hw913EtG3MPWD/FH/7HRe3b492OII+jZWurkbF1uqcVEve7NkUL1hIp8mTiO/du951q/fsoejzz6natg0Vn0CH8bdjSfb3vnbdylatIv+d2WRedhlJhw5p8v7CSVdVUb5uHUopEg46CG2zUfzV18R171brM7zy779dc3uX/fxzOIobVBV//eX6f9mKX0g59tgwlia8GvP3WkSmdu3ahbsITdLSW2ZvAv7l9Tg9wH2chBG0v+C1/LkA9mEDXnb+YgaCLwMdgKEBlscv5vjdd4CzlVKpbk9dCvygtd7SyP3+4B7Imss2AOsAv781KqVSlVLWxpRBRK/x48cHvI13y2rVli04KnwPT/dumYXAWzIdJTXHcxS0wJbZehJgNTfvFkv3QHv8+PGuMbOx3bp5rGdNSSF+4AAAylZ63hfb9+xzOAoL0dXVFISpRbJ6+3aPxFa6qopd99xL9a5ddW6jHQ52PzSRLaPO9+heXbUzi+3XXkfem3W3WhUvXuwKZDGDN11W5no+0GA0//0P2H3//RTOnUvBhx8FtG0gqrZvZ+ctt1D8v8fqPb9Aaa3Zfu11/HPkURT6Mdfl3oenULZiBdvHjG1w3Z0330L29Cco+PAj8t9+m7w338SWn8/WSy5l52231xrW4FS9N5u9jz7K7ocm4igv93iuZMkStl95FUVffMHOm25qUb0nApXz4ousP/wItl18CVsvupitF17ElvNGseuuu9h6yaU8et11OCorKVmyBHtxMRV/1fSUqdywAVteXhhLX5ujrKxWfTlpu52iBQvZetHFbDjxRCr++ccrmDVaJqt27nR1/Y8mjfl7LSLTjiYOEaiuruaAAw5AKcX06dODVCr/tfRgdoXWepHX47sA99HT/OmRAVlrnQfk+7mPXVpr7zZ458C9XgGWJxBvYmRIPg9AKTUAI3huKGNyQJTRZNIR8Hcek++AIqBMKfWZUqq/n8fpoJQa5P4AJMNAFHnjjTcC3qZWgOpwULlxk891vRNAAdj2BTY9j2c245YRzHq0zLagL8rVu/d4/O5etlmzZlFlBnXewSxA0mGHAVC+dq3r5kTF+n8o/Owz1zpFXy1E2xuVzy9g2m6n9KefsRcVUbFunWt5mzFXAEaX86w776qzPHmvv07BBx9Q8eef5L1Z8xFd8P57lC5bxt7/PYYtv+ZPji0/n7KVK9EOB5Vu48B7f/RhrZZC794J9Sn+7jv2PPyw6/fqrNB11y794UcwX4+c52c0aiosX8pW/ELpsmU4ysrY9Z8J5Lz0EkVffknV1q211nVU1uRUtGVn1xt02HJyqFjrOW18ydJlFHz4EeWrV1O8cCHFixYZ74UffjDG3Nts5Lzyf2w67TTy3niTgg8+IG/WLAC0zUbeG2+w4+ZbXMe15+ez+6GJEZmpu3rvXvY9P8M1NRlAxZo1VG0yP2/tdm60Wtl+xRh2XD+OXffcS8V6z2EfZd7dkEtKyXvzTXZPnMSu++5v1jH/1Xuz2XjKqWw69bRan5va4WDnrbeRdfvtlP/2G7Zdu8l/6y0qN9Z8VSxfs4bsJ55k08n/YncUTknUmL/XIjL1bqBHS0Oee+45tm/fHqTSBK6lB7NRTWv9J8Y4XWfX38uAKuCDIB/qUqAr8H4D65UBszBazM8DHsdo+f5BKdXdj+PcCKz1enwKsHz5cpYsWcK0adPIy8tjzJgxAIwcORIw7hBu3LiRmTNnMmfOHFasWMGUKVMoKytj9OjRHuved999rFmzhtmzZzN79mzWrFnDfffd57HO6NGjKSsrY8qUKaxYsYI5c+Ywc+ZMNm7c6Lob6Vx3zJgx5OXlMW3aNJYsWcKCBQuYMWMGWVlZrknFneuOGzeOrKwsZsyYwYIFC+ScvM5p5MiRgZ9Tbm6tN9KOpUt9nlNFrtEq4EhKcq2bu3FjQOf0gzlOEYwg4s7bbgt7Pa1YXHMPb9/69S3mvffJK64OKwCUZmW5zun4gw92tS7Gdu1S65y+NsfTUl3Nuw8/TFZWFt9cdZWryyKAfV8O27/6qt5zmnH0MWy//nruuemmxp/TH3+w4NRT2T52LPNGnEC5M5i1Wnm1ooKqE43uxeW//sqGjz6qVU8Tzj+f7KeedpV7j9v1tPLjT8w3k4PSH35g3LhxbPvqK/484QS2XXY5K/73GGs+N0aSFMTHkzBgAG+mpqASakbTVJeUNHxO997L2ocfZseNN7kCTDBalUP1GbHA7Q68o6SEZVdfw4IvvuD7119n4dlns/urrzzee7qqyq96+uymm2reVFqz7+lnyBp/BxvPOZcp4+/wKOc1F13k8R786umn6zynx8deWfOa9ugBQOlvv5E75xPX8iX33c/uBx9i+1VXs+HEk1h13PHse/JJtFvr3oaXXqZ6zx6+PXQoex/9nzH9VEwMxV2MuRpLvvuON6++mrKyMi76979xVFY26TPi81df5fVXXvE4pytOO43Sn35izBVXBO2zvOCjj1zvneUH7I/lwtE4YmJwxMRgG2DkiKz4/Q/Kf/8dgMJvvqF85SqP1/+3t9/2OKdXTz6ZvVMfpeD99yn85BO2XHoZq598sln+Pr1y2WXYc3KwZWdT+Pl8j8+9xffcQ8k333iUvfDTzzxyAGCzkft//wdAwefzmXj33fXWU0v8m+u+bqDvveOOO67J57R8+XIAtm3bRlVVFdnZ2RQWFlJcXMyePXuw2Wxs2WJ0NNywYQNgtBJWVFSQk5NDfn4+paWl7Nq1C7vdzibzxopz3Z07d1JWVkZubi65ubmUlZWx0+wR5Fxn06ZN2O12du3aRWlpKfn5+eTk5FBRUeFqkXSuu2XLFmw2G3v27KG4uJjCwkKys7Opqqpi27ZtHuu2tHNybteYc/rtt98afU5//fUXkydPdr0/HA5Hg+dks9lYs2ZNne8953P+Ui3x7qGZ5fd14PCGxmYqpTQwWWs9yWvb3lrrrUqpSzC6656itf7abbu2GC2Rb2itx5rLRmC0Op7gHL+qlFoMHAtkuLfOmtmMXwSO1lr/ZGZP3gJcqbWeZa4zCZiotVZu220FFrsd83zgI/djep3frRjjXLsDy4Hftdaj6ntNAqGUGogx/ncdcLw5tVEg2x+HkcjqFa31uAbW7QC091rcF/h07dq1DBo0KJBDiyhROG8eu+7+j8eyjH//m85THq617o4bbqTku++IHziQqs2b0VVVtLnySjpO+E+tdeuy/drrKF22zPV7/+XLiAnzeJJd99xLoTnnnyUlhQErW0Zikh0330zJIs8vhANWr8KSlET5H3+wdfSFAHR7/jlSTz7ZYz1bbi4bjj0OgHa33kLbq69m/SFDQGtSTjyRkiVLwG4n89JL6fTgAz6PX713LxuHjwCg8yNTyLjggkadR97s2ex9uCZjcHz//lRu2ED8gAH0+XQu9uJi/jn6GLDZyLzkEtd0QhX//EP2/x6j9McfPYJwgH7fLCK2a1c2nvwvV3fr9HPOIfX008i67XZX61fKiSdStWULVVu2kHLCCXR/0RgRo7Um96WX2PeMkSNw4B+/o+Li6jyH7CefIveVVwBjjK1r/277DCatNRuGDcPu1fMhrmdPY35hrYnp1Il+332LUgp7SSlbL7qQqo2biOnYkZQTRtDpwQdRVs/RKracHDaccCJUV5M4dChVW7Zgd+u62mnSRDLdAtjKjRvZfNZI1+8ZF19E54kTfZZ5z8NTyJ892xgD/dST7LzpZr/PN65vX5IOPZSCD40JCGK7d6fa/NIY27MHnR+eQsKA/dh01kjsOTkkHXYY3WY8z5bzRuEoL6fPZ58S0977z1/Dcl5+hX1PPUXy8GH0eNm4eeSorGTjiSdhz82l69NPk3baqQ3spWHabmfjyf/Ctns38QfsT++PPzbqrbgYHA5UTAybzhrp0f3el7g+fej7xXzX75vPPofKf/5BJSSgbTZXsBisctdn68WXUG62BCcOGUKvd2cDULllC1vOG4WuqCC2SxfSzh5J7ksv17erZitza7N582YA+vTpE+aSBN+kSZOYPHkyGzZs4JFHHmHu3LlorRk1ahQzZswgye2mOsDbb7/NU089xZ9//kliYiKnnHIK06ZNo3v3mragXr16MWLECGaZvT+cRowYAcDixYtdP0844QTeffdd1q5dy+uvv87u3bvJy8sjIyODDz/8kP/973/8+eefJCcnc9ppp/HYY4/RtWtX1z7Hjh3LRx99xPr167nppptYtGgRiYmJjBkzhsceewyr1b+RhFdddRXr1q3jvffeo0+fPkybNo277rqr3m0ael+sW7eOwYMHAwzWWq/zuZKbaGiZ/QZjzOsNXsv9/ytmjLm93vmLUirO/H0fRstpUzgD5Iw6nn8X0MAzQB8an/ipFjMz8nygELgg0EAWQGu9HCMYPtmPdbO11uvcH4Dv/qKiVWrUmFm3bsbxZjKg4sXfGXMB1rGuNSWFmM7GbFGV6+vOfuzzeEVFHr+3hOl53KevcZSUBNTtNJRsXt2Moaar8atTp7qW+epmHNO2LXFm16byVauNgMUMCFOGDyf5yCMAKP7qqzq7jtr21By/sfVUvmYt2Y/+z2NZpXk3OcG8wWZNTSXpcKNbdMnixa4upNnTp1P6ww+ucqefc45rHyXLluMoK/MYP1uybBm777nXoxtn2apVVJl3x+P3q5khTSmFxe3LUF3j/gCqtm4l9/XXASPI6vX+eyQdfjgA9uKiOrcLRMEnc/hr8IHkvPSS65jOQPaPXj2J6dDBWL5tm+v1sO3Z4wrkc557jipzeIBt714K3nufkqVLASOQKvhkDjvG3WC0LJvjVjvceQf9vvuW3p/OdQWCxd95jjTyHgpQ8s23Pj8bAFd22sSDDiL52GPrvTmgkpJIGT4cS3IybcaOpffHH9Hhrjtd2zgD2bQzzqDPZ5+RfOQRWDMySD/zDONYq1eTPf0Jqnftwp6fT5Fbjw9/Vaxfz77njPQepUuWurKDV27ciN3sseLeLb8xtNaUr1lL3qxZrkA1c/SFroRt1tRUrOnpWJKT6fzIFKpiYkj91788eg6AcRMDoGrzZvY9+yxlK1diLyl1XUttrriCHjNfw5JqpADJf/fdJpW7IbZ9+yg3W5vA6FVRvXcvZb/+yvYrxqDNoQ2dH32UtDPO8NhWJSYSP3BgrX2WLFkS0jK3NDJm1j+jR4+muLiYRx99lNGjRzNr1iwmT57ssc5///tfrrjiCvr378+TTz7J7bffzjfffMOwYcMoaMJ3jClTpjB//nzuuusupk6dSlxcHLNmzWL06NFYrVYeffRRrr32Wj755BOOO+64Wsey2+2ceuqpJCQkMH36dIYPH84TTzzBK+aN0YasWLGCN954g6effjqs8zK39GzGp5sth95+0Fpv9mcHWuu9SqlngDuVUp8BC4CDMRJJ5WAEig3ZBUwwW1//AS4EDgGua2wmYze/AXZz/+kY2Zq/1Vpnm+Xfp5RaAPwbY/qb+XXsJyDmsb7ECKKP11rXndmkYTuAAcEol2jdbnLvPugn96l50s85m+y//sK+L4eKNWtIPPhgj3WdQZ4lOZmU/Y4lf9t2Slf8gr2gAGtGhn/H80o41RLGzXoH2LZ9+4gLQgbWpnImgIrp3Nn1RdiWk0Ncz56ccsghOH4zuiP6CmYB4gcMoGrLFqqzsjwSx1jbZJJ66mmU/vAjtn372HHLLXR7+mksXvMeuo+D857Cya/yZ2Wx48YbjKQ/ViuW+HgcbomXEgYd4Pp/6ogRlP34E9W7dlG1caPRemuOdU046CA6PfQQCQfsT8ny5dhzcylZtoyEwYM9u027nWPSkUdS9vPPHtM/xff3TD+g3IPZ0lKs6emAEfxhsbi+POydNt0IAJWi61NPkTBwIBYzg7ejyPP93Bhaa/Y9/xyY40fbjB1L2Yqa3gGH3nknfY4+mrw33iB/9rvEdOhApZlIp2zlKhzFxeS9ZYwjjh8wgMpNm8Bmo+ynn0kYOJAd111H5QaPtBbE9+9H4pAhRkbdAQNIGTGCgg8/pOzHn3CUlbkCfXuh17WRnU3FmjXEdOrEjuuuJ2HQILpM/S+2/HxXYJV0xOFYEhJIOuww42YEYG3blvg+fVwBb/tbbqHtlWPRWtd8SUtIIPWUUygyu4XHdOxIp0kTsbhlm0458SRjihqHw9WKC+AoDuz9qW02dt//gEe315JvFtFmzBiPMdalP/yAo7y81rXhr33PPOPRKmlJSiLtrLN8rpty7LEkzfmEbv37s2PcDZSYrUQAmVdczt4pjwCQ88KL5Lzyf3R64AHX+z/xkINJPuII0s87l/w336Lsl1+w5efjKDWut7huXWsdrymKv/uuVm+J3fc/QOnPP7tulrS9/nqSjzwCrTUxHTtiM+fMTthvPxKHDnVNAxffvx+VGzZSsmxZSLJ2t1SN+Xvtrz1Tp1L5V2A3mkMpfv+BdDK7XAdqyJAhvPbaa67fc3Nzee2113jssccAo+vuxIkTeeSRR1zdugFGjRrFkCFDeOGFFzyWB6KiooKVK1e65gSurq5mwoQJDB48mKVLl5Jg3nQ67rjjOOuss3jqqac8Au2KigouvPBC7r77bhISEhg3bhyHHnoor732Gjfc4N0G6ElrzS233MKFF17I0UcfzVYfOQ2aS0u/Ih/GSHbk/RgW4H4mAFOAw4HpQD/gFEABvtOiesoHzgAOA6ZhdPm9WWv9fwGWoxat9R5gHEZm5NcwWmIP8FrNmSbyA611JU2klEoA5gH7AWeZY3Obog9GK7UQ9VpqtsQEwvUl0Gol7fSaO+jFXt1bAezm1DyWlBRSTznFWGizUfzd4gCO1/KCWe8AuyUkgXJUVLiCs8SDDnItd5Zt16+/AWBNT8eakuJzH84svbbcXOx5NcmRYtq0If2cs0k42Nhv6ZKl7PrPhFrbu78OjpLAWqvtxcXsGDfO1brY8Z57at4zpkS3oQ8pZjcvMLIP20tKXV9+U08YQeLgQSiLhZTjjK7TZT/+SOXff+FLwsEH0eE/d9daHr+fZzBrdbth4QyybTk5bD7jTDaecCLV2dmUrljhGvuXfs45JA6uaU0GsJcEHswWfPwJeW+9jcNsEa/4/Xdsu4ybFbqsjJKlS12Jfqzp6Szbvh1rSgrtb7qJ/b5fTu8PP3AF4mWrVrJnyiPgcEBMDF2nTyPxwAMBKP35Z7KfeNIVyFrbtiW2a1es7dvR4a67PO70p5jTIumqKlcACr6vz/K1ayle+BWV69dT+MknVO/e7ZE129lqnew27UrKCSNod8vNqNhYko85mjaXG6kqvFsbMi+u6eLc+eHJtab9Sjp0CBbzpoM7297avRjqU/TlglrJqoq/NmYrrHSbnkxXVHi8HoEoW7mS3Jc9W2Ayr7gca0rdN8qWmUMwUoa7fQ2LjSXj3/8m/Zxzam4a2mzse/ZZ1yrOG4+u4QYOB/uefZbNZ53F5pEjqdzSqAka6lRsXhPWdu2IMccyly5fbgSysbF0mvgQ7W+/DTDqOPn441zbJgw6gLbXXkPamWfS6eHJZF5qvBfsOTlUrGvq16XI0Zi/1/6q/Otvyn75pcU8mhJYO8cHOx1//PHk5uZSZN6E/uSTT3A4HIwePZqcnBzXo1OnTvTv35/vvHqbBGLMmDGuQBZg5cqVZGdnc+ONN7oCWYAzzzyTgQMHMn9+7fawcePGUeJ2M/j44493dQOuz6xZs1izZo0raA+nFtkya445neXnusrr91rbmt1nHzIfACilMoC2GHO5OtdbjBHgum87wu3XY+opx1Yf207Cay5brXUvH9u+Crxa174xkj5BELoYm9PpvA8cDZyjtf6xjvU6A+nAJmfrs1KqvdZ6n9d6Z2BkWH629l6E8JSZmRnwNu5dh2M7diDh4IOo+P0Pir/9lg533uG1rtkym5JC0mGHYc3IwF5QQPHXX5Nx3rl+Ha9Wy2x+QcBlDjbvltnqFjA9j3sX38SDDqR44UJjuTk9T4oz+VMdrbIAMe2MYNZRXIwte69ruTWzDZaEBHrOnMmO68dRtnIlxV9/XasFyjOY9b/lS1dXk3Xbba4gKvOKy2lz+WUUffWVa2wyVqtHV8O4nj2J692bqi1bKFm8hOSjjq55rnfNuJ/k44+n8NNPcZSVkf/e+659xXbrSvU2I9tjx7vvJmHAAFRSUs0UPDExxPfq5VFOj5ZZc719zzzj6pZc8OGHrqlEVEIC7cff7lrfkmYEs4G2zJZ8/z27778fgPz336PL1KkUfbnAY53CTz9zJQFKPPwwMtu08Sx3TAxJhxxM6Q8/UvzFl66ytxlzBfH9+5N01JGU//orlX//7cpQnDzseLo9+ywWr+6rTslHH+UaC5z/4Ydom43ko47CUVQ7mLUXFBjjM03Ve/a4WlyJjSXxkEMAI0DOfuopsNlIO/10ko84ggGrVxmt3nWMF0saOpQer88Ei9XVFd7j3GNjSRk2jCKvKYWqd9U/1tRb2WpjBJNKTCT9nLMpeO99ylavxpabS8U/nnNtF3/zLaknnRTQ/u0lJeyacA9ojYqPp9vzzxHXuzdx9VyvUPMZnnx8TTAb368flrg4ujxmdNffPGoUlX/+5brZFdu9u+vGVdLQoVjbtMGel0fBu++59lH48cdkXnIJ2dOfIOWkE0k/88yAzsfj3IqKKPvB+GqTeuKJWJKSXBmoY9q3p+szz9SaCzjluOMpNKcCi99/f2IyM+n6hJHgzH1KrpKlS0g8cHCjyxZJGvP32l/x+/vqdBk+TSlPDzOZnJPzdcvPzyctLY0NGzagtaa/V88bp1g/5tKui3cWYmdCpwEDaneWHDhwoCshl1NCQgLt27cn3y3TfmZmpsfvvhQVFXHvvfdy9913e4z5DZcWGcwGm1IqUWvtPeDodvPn4uYtTaNcC2zGSADVVE8AZ2O0zLZRSl3m/qTW2hkwPwqMAXoDW81lPyilfgVWYoyzPRS4CqOb8VSEaIB78gF/OdxaWwFSTzyJit//oGrTJiq3bCHe7cPcGdBYUpJRMTGknHQihR9/Quny5dhLSuttcQBwVFW5xlI5Scusb+5zzCbsvz9YrWC3u8qWZAbgsfXUubVNzfyp7tMtxbQxvgxYkpNJO3ukq1XNXlBQdzBb2nAwW/TVVxQvWkT1rl2uLKwpJ51ExwlGq2/KsceiYmPR1dXE9+1bK7BKGTGCvC1bKP/1V4/xeHF9at6DKccf59qHs2UtrkcP2lxxOXsmP0z6+aNc0xIlHnQQZT/9BEB87961xnBavILZij//9Jh7t+DDj1zT4aSddSaxHTu6nrOmmMFsSQnabq8zOPOW9/os1/+rNm5i26WXoby6sLpngU0ZNszndZ04dCilP/xY0207Npa2Y8cCkHzkUeS+aIy9dV5vmRddXGcgC2BJTCT5mGMo+e47SpcspXTJUpKPP97Vygu4bg7YCwrRtpoRQLY9e6j402hRS9h/f9d7KL5Pb3q88jL20lJSzFZa5ccXy+Sjj673+dSTTqwdzDaQOMmbs6UoYcAA0s86i4L33geHg+Jvv6Xyb89gtmTx4oDqGKDw009d47k73HUXKccf79d2zrqO69aVhEGDqFi3jqRDD/VYJ/2MM8j+s6ZXgvtwEGW1knrSibXmPy78bB7l69ZR9uNPFH/9NcnHHENMI4OpwjlzXPMFp556CnE9e1GydClx3bvT+ZEpPhNxpQwfRsIBB2AvKKh1YyC2SxdXV+PS73+gfQi737Ykjfl77a/GdultiepKlOTMreBwOFBK8eWXX/pcN8Wt51Jd407tdrvPbRMbObzAybnPuHryB/gyffp0qqqquPDCC13di50Zl/Pz89m6dStdunQJeL+N1dK7GQfLhUqpxUqp/yilblRKzQYmAl9prb8Pd+HqopS6SCk1FTgTeEYHJ/X0IebPkfjuwl2f94H+wH3Ac8BpwP9hZJ3eW9+GwVS9Zw/VewLrsiVahoVm610g7MVewezJNV80ij6v6TKjq6tdiXWc83Sm/utfxnNVVZQsWdzgsby7GEP4E0Bph6NWq6Oz9TOcqvfUXPKxXbrUdBnOycFeUoIyW4/jvFob3TlbZqEm6RJWq2u8J+Ax1tm7Ltxfh4bGzNr27SPrjjsp+myeK5BNGDyYrtMedwUBluRk0s44HYAUczoed8nHmJ1zHA4KPjGnc7FYXMlvwOh2m/ovz3x48f36knHRRez38090fuQR13L31iHv8bLO8jg5SkvZ+7/HPMYB2vbscY2pzBjlmeTe2TIL/rdaV/zzj9EVE4g/YH+IiUFXV7t6Brh3ywUjQ2zGqFE+r+ukoUM9fk8/43RXEJE45BCPwN2ank7KcZ779iXjgvM9fi//4w/XzSZLWhoxZguxPT/f471SvWcv1VlG61pcr54e+0g+5hjSzM+JYEk+7ria97D55TSQv1nabqfiH2NcbPz+A0kcMgSreW7578zGbraaxPfvBxhjsd1vrvjDOZ+qJSWFzEsv8Xs797ru+szTdJo0kfa33eqxTuppp3v87p3bwCOzeYzRpmLLzqbsR+PGjq6upqiRia20w0HebCNrcVyvXiQffTRx3brS94v5dH/5pTozSlsSE+n18Uf0XfS1633kLumIIwFj3l1HhT+j0yJfY/5ei9r69u2L1prevXtz8skn13ocddRRrnUzMzN9JoRytrg2pKf5t2j9+vW1nlu/fr3reW+FAd603759O/n5+QwaNIjevXvTu3dvjjdviE2dOpXevXvz55/N1yU/WoLZPzAyGv8HeBo4HiM78Pn1bNMSvAvcgjGWNihzK2itR2itVV0Pt/XGmsu2ui17QGs9RGudobWO01r31Frf2KyB7N69bDrlVDadcWbQx9iI0LvzzjsD3sbV2ppqBLPxffsaiXUwulk6uxO6Z/h1jtFMPuYY15dK75YAn8fyFcyGuWXWUVJSK5FJS2iZdR8DGNOxo+tLom3fPspXrUKZZU46bKjP7QHXF3So+XJtzcz0SLBiTc9w/b9WMBvAmNnC+fNdgV9M584kHXkk3V98waP1E6DzlCn0/uxT2t96a619JA45BMyyORMcxXbr5pEACCB9lOeflri+fVFKYU1P97jznjjELZh1y2Ts5F626t17XONU08443WgJd+6/Vy+PfQFYU2tuCNj9TD6U96aZnkEpuj39NN1fmIFynpvFQucpD7vKZElJocu0x1ExMT6v68SDDnIFKgCZl9V0ArLEx5Po1pqXevpp9WYWdq130kn0mf85GRcaUz45CguxmTdNrGlprhsf9oICj+EB1Tt2uMY319dTIFisKSn0fPMNuj71JO1vv91VVruf47qrtm93dT9PGLg/ymol7XQjQHQmJQJoe911rmC5+JtvAypj9XZzWqEe3QNKaORe13HdupF50UW1xg3Hdevq6soNePwfIOnoo4nfbz9UUhLdnn7KZ93nf/Ahjbl/X/r9967u/JmXXBLQuSml6lzfOc5aV1dT/scfAZcrEjXm77WobdSoUVitViZPnlzrPa21JtfMTA5G4PvTTz9R5ZbB//PPP3fNHduQww47jA4dOvDSSy9R6ZY1/8svv+Svv/7izDq673d069Xjj1tvvZU5c+Z4PF42pw4bO3Ysc+bMqdUFOpSiIpjVWq/WWp+stW5nBmHdtda3a60DT3/ZjMxgMlVrfY3W2tbwFq1f2S8r0VVV6LIydt93f7iLIwI01uxmGAjXmNnkmq44mRcZX2Zt2dmuqTrcvyhazHUtcXFknHceAGU//eQKmOri3Z0Xwh/M2n2MebS1gDGz1WZwYElLw5KY6BHMlppBF1arR9DizdmaCzVjcL27Fnq0zHrVRSBjZgs/NVp64nr2pN+339DzjVk+W2lUXBwJ++3n80utNSWFBK8pO+J9/MFOPvooYjp3rlmnbz+fZUo69FCs7dqBVwIaJ0tSTcus+xQ/KcOHe3QLTR81qlb3NI+WWT+m56ncvIUi8zVKPfkk4nr0IGXYMHrMfI3EIUPocMd4Yrt0of2ddxDXpw9dpk9zja/0dV1bkpJIMoOYxCFDPLoDAyQfdWRN+UeOxF/xfft6jFms3GR0T7emp3sGs243Psp//91IQAXENUMwC5AwcCBpp59ObJcurmW2Pf51NXYPWBPMsXy+Wk+TjznGFSiWfPNNQMFflfnlOK57jwbW9OTvZ7izFd3avh0JAzxv1Fji4uj98Uf0X7KY1JNPdiX3AlzJmqo2bXLNEetUuWUL5evqn3Iy/+13AKPLebqfeRL84X5TzjX+upVrzN9rUVvfvn155JFHmD17NscddxzTpk3jpZdeYsKECQwYMIDXzWnVAK655hr27t3LaaedxksvvcTdd9/NtddeS9++ff06VmxsLI899hh//PEHw4cP55lnnuG+++7jggsuoFevXnVOtxRoJuJDDz2Uc8891+NxiplAcdCgQZx77rmk+0iEFypREcyK1sP9y2v5r7+2iEQ4wn8ffPBBwNvYvcbMgjG3o3O+wgIzyY77mEn3dd2zj+bPrn9uQ7t7oiUzmAl3N2OPQMQcz9cSglnbXqMMsR2N+UVjexhJICo3bKB44VeAMU9rXZmMwTOYdbJ6dfGrq5uxttuxud3Rri+YrVi/3tWSmn7uOU2aDy/Rq6U5zsek78pqJf3cmjln4/v5/iJiSU6mz7zP6Pv1Vx6Zk2ued2+ZrQmELOnpZF5ysWsf7vPbOnm0zDaQBErb7ey+/35jnKFStL32WtdzSUOH0uvd2bS95hoA2lx6KX2/mE+qW3bnuq7rzo9Mod2NN9D16adrPZd50UUkHX0UmZdeWu8ND1+cc9oCrmRY1vQ0rOaNEO9g1pkkC5qnZdZdbJeamxoVf/7J7gcfpGjBglrrabudrDvvYsuFF9ZMeWOxuLqfx/fp49HN29quHTFt25J60omA8TpU+ZGBFIxpf5xJjeJ6BJa8xd/P8PTzz6fbCzPo9fbbPlteVWysK+N2mysuB6uVmM6d6fHqa67PuXy3BFHVe7PZcv4FbD3/Aircgn1dXU3Z6l9xVFRQvXu3a+7i9LNHuvYfDDHt2rmudffM2K1ZY/5eC9/uuecePv74YywWC5MnT+auu+7is88+45RTTuHss892rXfqqafyxBNP8M8//3D77bfz448/8vnnn9OtgcRs7saOHcv7779PVVUVEyZM4OWXX+a8885j+fLlZNQxRaG/wXJLJcGsiCjVuz2nw81/q8kJnkUzGhlAC4yTc2oeZzdjMFp9nF/gS7//nspNmzy6GbuPNYzr1Ytkc7qUwrlz6x1b6T4XZGynTkDLapl1ZrttGd2MjZbZmI7G6+QKqBwOqs1EEEmHH1bvPlRSEsor6Y+1jXfLbM3dXfcAxZ6X52ptA7CX1t2F09kqC5A28uw61/NH0lDPc4rr3cvnem0uv5zEoUNJO/NMj6zI3mIyM+vMIOue7Mo9o2pMRgYpw4bR85236fX+e64bCh7bul0vDbXM5r31lqsVrM0Vl3tMteSPuq7ruF69aH/rrT7LZ83IoOfrr9PpwQcCvrng0aJutwNGgF9Xy6z7+6TZg1m3Fvq9j/6Pgg8/Yte997kSFDmVrVxF0fz5VPz+R00vgt69Pd4DmZfXdNVOMLulp5xYk0PA367G1bt3u7rcxwaYidTfz3ClFKknnugxnrwuSUOH0u/rr+gz5xPi+/R25UUomj/f1fJe8u03rq7X7i22ua/PYtsll7D9yquMcexm63Tm6NEBnZc/nInbyn/9De3WDbS1aszf62gyadIktNa0a9fOY/nYscb81L288kWMGjWKZcuWUVJSQklJCX/99RfPP/88+3kNMbnjjjvYuXMnFRUVLF++nKFDh7J48WIWu83rPGLECLTWXHDBBT7LNnr0aFavXk1FRQW5ubm8/fbbtRJ6zZo1yzUlzwZnzgq38wpUr1690Fpz1113BbxtU0kw2wIopUYrpfKUUnU3Yfje7iel1OOhKldL5P6FDiD/3Xexmen/Rcs3zyvDpz/cp+Zxl3nJxa7xYtlPPOnRMuedtdjZRc9RVkau2+Tm3uxuX/qdX/LshQUBlzmY3AOROPPuqaOkpCZLbJhUZzuDWSNQSRw0qNbYuOQjak9d4k4pVat1NibTs2XWEh/vyqZrL6i5seAd0OuyMrQZ2Hgs15oic269pMMPJ65b04IZ7zHA8T5aZsGYK7fXO2/T9YnpjW4JVlar69zdP/uc85gmDR1KfD/fXZjdxzHWN2ZWOxzkvmSMdYrt0cM1xjMQjbmum8K9ZdbJmpbuuvHhKCmplZUcAKVcN6maS0yHDjW9PMzETbq8nKqdOz3WK1mypNa23l3aU4YNc90YSTa7mcf36U2c2dXdPcs0GNdI4bzPayUsqtq+3fX/uB6BdTMOVV3HduniuhnR/sYbjc92h4N9Zqt+sdsX+aodNa9dnvl5Xv7rr673cfz++5NwwAFBL6Pz5pyuqGiwu3Nr0NzXtQifuqYNihQRHcwqpY5RSk0y54yNSOa8r5OB5xoxhvcx4CalVPP+dQ4jm9dcfY6SErIfnxam0ohA3RdgOn5HVZXrDrjFK5iN79OHdHM8bMm331L8bU2rhPe6KcOHu5JG5b36mqtrYq3jubWCxnY3WsvcA6hwcG+ZTRhYM3dcoY/Jz5uLrq7GnmN08XWfDibz0ktd/3dgTM/SEKtXMOvdzRjwaHFz8tU67fDROluxdp2rFTn19NMaLE9DYtq2dQUP4LubcTA5Ey7ZzSl4wLPrdV3cu1jW1zJb8ddfrte17TVXe7QE+ivQ67qprJmZHsmlwHPMbF1iOnb0K9FUMKmYGJ/Bd5WZwFCbrcY+g1mvuS+VxUKP12fS/bVXaePWSuvsalz+xx/YzIC5Yv16No8axa677ybrjjs9Wlqq3ZLJxAXYMtscdR3fv7+rp0fx14so/eknyn762fV8tfuNALcbRc7WbmeehGBztswCru7MrVlzX9cifHZ63VyLNBEdzALHYEyxkxHmcjTFSGAA8Eojtv0UKAJuDGqJWjBn60TGv/9Nijlmq3DuXEp/XhHGUgl/XXzxxQGt797aakmpPf6p/W23uVqunGNnjXU9g1llsdDpwQcA4wvPnqlTfXajsZeYgaPF4uoeqMvKcISxS5l7IJI+ciQxZvCY/fg0qveGZ+ysLSfH1Z0vpkNNMJt66imu4FT17VvveFkn72kwrJkZtdbxO5j10YW8+Nua1qrUE09ssDz+SDrSaHG2tm/nGqcZKu5d5p38GQvofg3UN2bWPUhwTT0UoECv66ZSFkutFn1relqD85I2dxdj13Hduho7VW3ZQs6LL7L+sMPJnj6dKrdEVk7xA/evtV1MZqYxH7JbMJ/oDLK0pmrzZir++ottl1+BfZ9xA6Tk2289prqpMjMZExtLTIAt1c1V1+1vudk15+/OW251TbsGULXTKL+joqJWTgMVG0vayLNCUqbYzp2NKauA/Dff8hiz3xo193UtwqeNj5vIkSTSg1m/KaUsSqm6Z2QPnyuB77XWWQ2u6UVr7QA+Aq5QTcloEiEcZWWuP1yxXbsYY63MQGb3Aw+47kiLlmvNmjUBre8ZzNb+Uh/bsQNtr7qq1nJfAUDiwQeTfr4xF2fpkqXkvzO79vHML/2W1FSPICWcSaDcA5GYTp3oNHEiYEwjtPeRKWEpk/ucmTFu4yEtcXF0eXQqSYcdxkavOUnrYm3n1c3YV8us+QW/oWDWOR7alpPDnqlTKVm2jJJvjWzXCYMGBa2LabsbbiDjwgvpMvXRJiWT8of31EGW1FSPQKYuKibGtW19LbOlPxtze8Z27Vrn2N2GBHpdB4N3a6c/LbOxXbvU+3yo+ApmKzdtJu+NN9FlZeS+WjP0oetTT5J0xBGkjBhB8pH1d9N3iutRMy61att2cl540TU3sPOzcM9/p7qu2+odRjfjuK5dXXMs+6u56jq2a1dXIjLvKdOqdxpfl6p9TFeSduaZDd7UaIoO4+8wylRayr7nnw/ZcVqCcFzXIjzKy8vDXYQmidhgVik1CXD2L92ilNLmo5f5vFZKPa+UulQptQ6oBE4zn7tLKfWDUipXKVWulFqllPI5ilopdZlSaoVSqkwpla+UWqqUOsVrndOVUsuUUqVKqWKl1HylVO3UlLX3nWCWaVFjjw18DfQEDmnoeJHOPZtnbJcuxHbt6poLsnrHDrJuuz0qkjJEE89xsL5b+dpee02tBDveAYBThzvvdLVs7v3f/2pNseAcM2tNSfFoIXGEMQmUs0yWlBSU1UrqiSeQZs4VV/z1orB0d7O5tQjHes1PlzJsGD3ffouSXg0nfgGIaePVwpZZTzfjwrrHzELNXLN5b7xJ/ptvsePa66g0J49POSk4rbJgnHPnyZNI8TGdTrB5v5f96WLs2tYcN1vXmFldXU3ZylUAJLlNlRMJvKdVsrjNM1uXsLXMdqkdzJYuW1brJllMhw4kHX00Pd98g+4vvehqmWxw/926usblVu3YTsU/5nv+xBPp8vhjADiKithxw43YS0pcLbOxAWYybm7tbryh1jh8MM7FXljoMfa3+6uv0vXpp+g08aGQlinl+ONcCQULPvgwauacbYrGJBMSrVuw3xMRG8wCnwDOeTbGA5ebD/dvOCcCTwHvA7cBW83ltwG/Ag8B9wE24EOllMdswkqpicBbQLW57kRgh7lf5zqXA/OBEmACMAU4AFjuDKzrMRSIA1Z7P+HPsU2rzJ/+NYNEsGq38bLOO91txlzhGgdXtmIFu+5/AG2TKXlbqgO95ppsiPuXcO+uw67lCQl0e/opj2V1tTbEtGlDt2efMb4k2mzsuPkWYw5KkytzcloasW4tP+Ecn+pqLXabN7TjPRNcr8fe/05t9m7QNjP5E+C6OeDN37qOaec9ZrZ2q4ozsU/DY2aN+qvwkZwlWF2Mm5t3LwNrAHP3Obsj19UyW75mrStDbPJRRzWyhIFf18EQ08EzmLWmZzQYzDbXHLPe3OcctrY3Mp/6ev+mDB/WqJZ+S1yc629i5YYNVJsJkuL79yf1pJPIMOflrvzrL3bedDOV//wDBD7HLDRvXauYGLpMn+6ahi1l+HDXc1U7d1K1rSaYTRh0AGmnndaoMd+B6nD33cbNA7udHddeR4X5erY2wahri8WC3W6XgLaFS2yG68ZJa43dbg9qr6aIDWa11n9QEwTO1Vq/bT7cM4AMAEZorR/WWr+gtf7NXL6f1vomrfUMrfVTwHHAWuAO54ZKqX4YQeQc4Hit9XSt9bNa60uBe811UoBngVe11qdrrZ/XWj8OHAUojEC5Ps7mpC3uC/05ttvrkAVUYQTQrZp7Nk/nRPTKYqHL1Kmu5D5F8+aRdedd0kLbQr37bv3zvHrznDu27nGCcb160e2lF4np1Im2119f7z4TDz6YTpMmGfsvLGTblVe5WjddLbOpqSQOGeIaH5X7f696zFXZnOxmFzv3eUNj2ren3c03Acb8krmv/F+zlqnaTKhEbGydY0b9rWtrG3+6GWcARsusM2GOLdsIBqxu0yI4W/K9W7xiu3QhfsAAIlGtltkAgllXy2wdY2bLzC7GAElHNL5lNtDrOhi8W2bd55n1WM8tkAxXy2zy0ceg4uKI7dKFzNEXejynEhNpf/vtJB11FG2vH9foYzhbWct+/Mk1FVF8XyM5WacHHiDFvJlT9vPPrvHucT0DD2abu67junWl95w5dP+/V2h3yy2u5dU7s1yJ/CypqQH1WGiqhAH7uXIw2AsL2X7lVa0yb0cw6jo+Ph673U52drYEtC1YXjPNCmKz2di9ezd2u50UP3Jq+KvhgTeRbYnW+k/vhVprV+dwpVQmYAWWAe6j3c/FCPYfNsemum/vvCL/hZF86l2llPtEU3bgZ+CEBsrn/BbnPdjTn2O7ywfa+Vjuk1IqHngYoyU7E/gDeEBr/bUf23bFaO0+xSzjd8B4rbV/s7U3gWuOWYvFY7yUJTGR7q+8zParr6Hyr78oXriQLVu30nnKwwHPlyhCa+rUqQGtX990O95SR4wg5bvhft3tyzh/FNpuY8/ESeiyMnZcdz2Zl1/uCpCc4xK7/Pe/bPn3aLDZyLr7brq/8ELAU1k0lXPsm3fSnzaXXkrBRx9RtXETOc8/jyUpibZXXdksZXJ2M47t0AFl8X1P1N+6rtUy6+NLqWuZw4GjpARrWpqrZSu+Vy/KzEy/zjGzziEJ1owMYnv0oO2114R8bGuoNCWYdb5n7HW0zDq72cf16eNzLlh/BXpdB4OvMbOWxERUfLwrWZAlOZm4bt2wme+HcAWz8X1603/pElRiIqXf/+DxXOLgwbQbdz3txtV/E64hcT16UvbjTx4ZveP6GFN5qZgYuj75BDtvvJHSH350PR/oHLMQnrqO69aVuG5dPYYZVO/cQdV2I5iN69mz2a/vzIsvxlFWTva0adhzc9l+5ZW0ve5a2l13XZ3DXCJNMOq6Y8eOVFZWkpeXR2FhIVarNWI/i1u7zZtD9zVea43D4cBm9pxMSkoiM4hj2yO2ZdZPW3wtVEqdZc7RWgHkYXRNvgFw/5bQF2N2iVrBsBvnxEzfmvtwf5wC+PvtwPvK9ufY3tsHcstrFkYr9DsYXa7twBdKqXoHgJkt0d8Bw4GpGF2fhwBLlFJt69s2GJwtszEdO9YaSxTTpg0935jlGl9TuX49Wy+8iJ233W50pZM7gi1CoJOw290Sf9TVzdhdIH8kM0ePputTT6HMLx75b71FtTkGyxkEJOy/P22vuRqAqo2b2HLueeS9/U6ztvw7XwOL27yhYGTt7Pr44645R7Mff5wdN99M2epfQ/5+d051U1cXY/C/rt2n4rGmp/tMbuQe4NoLCnBUVFCdbQTUzrl3wRgz6ygvd83n2WbsGHp/8D5p//qXX2VpiWp1M84IoGXW1c3Y95jZir+NsZVNvekX6HUdDLVaZs3rw/29Ys3IqMnWG4Y5Zt1ZMzKwxMcT17uXx/LEQw4Oyv593WSL71MzhZQlIYHuL79M5mXGlD4qNpaEQQ2m9qglHHXtZE1Pd72nq3bupNrsZtzcNxid2l59FZ0fmYKKjwdzvuZNp51O3jvvYC+pPU1YpAlGXVssFnr06EFGRgZxcXESyLZQy5cvD+n+lVLExMSQmppK165d6dGjBzF+JDL0V2tvma2VnkspdTzwGbAUY0qb3RjjUq8ELglw/86bAZcDe3w839DgTWde90ygKZM8ZQA5Da0EoJQ6ArgIuFtrPd1c9iZGN+vHMaY7qsuNGAH8EVrrX8xtvzS3vZOGu1U3iXOOWV+ZIcH4MtPjzTfIfeX/yH35ZXR1NcULF1K8cCFx/fqSdsopJB11FIkHHtgs42pEbYFOwu5w+0Jg8WM6kkClnXYqCfsPZNd/JniMnXU/Vvubb8ZRWkb+W2/hKCtj7yOPkPfGG6Sfcw7JxxxNwsCBIb0TX1fLLEDCAQfQ88032H7V1dhzcylZ9A0li74hrlcvUk87leSjjibx4IOC/n6vdgWzdd+v87eu3adY8TXHLHgGcPaCAmw5ueC8w3vE4RS8b0zL5CgpoXp3zUdxXZ8VkaQpCaBcY2aLarfM2nJysJtdy+L326/xBSTw6zoY3Me0Exvruillzchw3WyxZmSQNHQoRfPmkThkSLPPMetLXLduEBsL5pyovhIcNYZ3MqfYLl1qvXdUbCydHriftDPOwJKU6Pka+ikcde0utns3Kv/8i6pNm109MOL8TDYXChkXXEDCgQeya8I9VP79N7bsbPZOeYR9TzxJygknkDJiOIkHHkhsjx519mJpqYJV1xaLhc6t4LO4NesT4vnSQy3Sg9nGND+cD1QAp2qtXROXKaW8++dtwghWDwB+q2Nfm8yf2VprnxmJG/C3+bM34J4D3Z9jA65uv3GAvwP6LsBoiXXNa6u1rlBKvQZMVUp111rXzndfs+0vzkDW3PZvpdQ3wGhCHMw6W2ad42V9scTF0f7mm0g78wxyX3qZws8/B7vd6Iq58UV44UXjDn3XrsT360dc3z7EduyItW1bYtoac0ZakpOwJCYaXdYSE+VOYhCNHj2aDz74wO/1Xd2MY2ND9kU0rmdPes5+h6IvF5AzYwbVO3eSMqIm0YiKiaHT/feRMmwYeyZPpnrnTqp37CDn+efJef554/3UvTvx+/UnvncfYtq3J6ZDe2Lat8eSmoolKRlLUiKWpCRUfHzA76e6WmadEgYMoPcH77PvhRco/GweVFdTtXUruS+9TO5LLxvl69aN+D59iOvbl9hOnYhp1xZrm7ZY22TWlC8hAZWQ0OAXLq21K1iI7VB3y6y/dW3NyDCSqTgcdQez5phZMILZSrfuUEmHHIIlKQlHWZkZzNaMrY9pBV+gmjZm1tnNuBittcd7r3LDBtf/4/v3r7VtIAK9roPBvWXWmpbmOjf3cbPWzEwyRv+bhP0HerTgh5OKjSWue3eqzPdwsIJZ9+l5gHrPN+nQIY0+Tjjq2l1cVyOYLVtRM0Y1Nkwts04JAwbQ++OPKPz0M+NvSFYWjrIyiubPp8hMHmhJTiZ+4EDi+/YlplNHYjt2JKZDR6wZ6ViSkrAkJxuPpKSAp0sKlXDXtWg+kV7XkR7MOpttMgLYxo4RBLs+Lcysw+d6rTcXeAx4SCl1gfvYVaWUMseuLgSKgPuUUt9pravdd6CUaq+1rp2ysMYqjORNh2G0FgdybKeh5k/PgTh1GwL8o7X2vlXv/MtwCEbWZA9KKQtwEDDTxz5XAKcopVK11r4zjRj76AC091rcF2DnnXeS1MCXNOccef60tsT37k2Xx/5H+9tvo/Dzzyn64ksqnQl8tDYCkp07YfHiBvelEhNRsbHGl/yYGPOnFWWxGn90rOZP9yDAO2Bx/93jv6qOdfz5f4NFb3EedWi2XHhhwyuaqrOMwMSanBzSmwrKaiX9rDNJO/MMdFUVlvj4WuukHH8cfb+YT/5HH1Hw7ns1wYDWVG/fTvX27ZTwTf0HsliwJCS4vY98vJ+cy5QCpVxzLPpqmXWK7dqVLv/9L+1vu42ieZ9T9MUXNRl9taZ6xw5jTsYlSxp+LZzvd+d72618WC0oi9U1JrG+bsazZs1q8FhgvPbWzEzsubnE+MhkDF7djAsLqTCnw7C2b0dMly5YUlKMeahLS1zjI6H+G1+RwrubsSWgMbPmDRCHg+xp04nt1JE2V1wB4MpoC01vmfW3roPJ2qYNWK1gt3sE+N7djJXFQuLBwenKGyzx/ftTtXkzsT17ePRMaIq47p5zBMeHqKUlHHXtLtbHXMjegXw4KKuVjFHnkX7O2ZQsW0bh3E8pXbbMNYbZUVpK+apVlK9a1cCeMG56Ov8WWK3G56/V+/8WXF8CfH1H8P6J2+p+bveow8GW0RdG5HcNEZhHHZqS5d+TclxkTowS6cGs81Phv0qp9zC6C8/zymjsbT7GeNEFSqnZGONabwI2YgRrAGitNyql/gs8CCxTSn2CMVft4cAu4F6tdZFS6gaMKXRWm2XYB/QAzgS+B26uqyBmi+hXwMkY2Yv9Prbbbv4FbMeYasgfnTG6VntzLqvr218bIN6PbdfXc+wbMcbZ1lK5/h8qfAQQvqzNyyNlxQoWLlzInXfeydixY/nggw8YOXIk8+bN47777uPiiy92Tfh94FFH8e6WLTz86v/x0PkXMH7UKJa88zaHtGlL5datWBoYX6jLy9ERPqF0pMvTmhUrVpCVlUV+fj7Dhg1jxowZPPXUU656HzNmDE899RSvvfYaRxxxBOXl5WzatIlzzz2XKVOm8NJLL7nWHTduHA8++CBz586lb9++JCYmsmLFCq6++mrGjx/PG2+84Vp3/Pjx3HTTTSxdupTMzEy69uvHwiMO57bnn+PJa6/jprPOZPEbbzKkbVsqd+yo//3kcOAwp0IJ1ObCQlYtWNDwOVWU0/faa0iy2dj2xZcM79mDVXM/5aC2bSjfuImG7vkH8n5//K23eOyqKxk9ejSzZs3iiSee4NRTTyUrK4s333yTadOm+VVP8e3a0ik3l8+2bOVGqHVO8z/5mOPNY3718cccZI6VSzzoYM4++2yeTkmB7GyK9uxh7Rdf0B3QSvH4q69yx3/+0/BnxIEH8u677zJ16lTXOr7OKRzvvRv288zC/NGXC7jklFP8OqdfFi3iaHO7vJnGfUi1//48v2ABZ+/cSRxgS0hga1EhL/zv0Uaf0/Dhw5k7d27jrqeuXf3/LHerp7PPPZcn27bFlp2NSklhypQpnHrqqdjy83DeEvlhzR/82+391GyfEQ2d0yn/onjnDnKHDKF8zZqgvfdOz0jHWmAkSSpr24Zx48YF/ZyqqqpYv3592K6nT5cvq5VZMzc+jtdnzGi2955f56TgyR9/4KYzz+S/V1/Nly+8wOFt21G2eTNxlZXUR1dWNqrboRBNYS8oCO3nXgDXU/8AewupSE+Mo5R6ABiHEaRZgN5a661KKQ3M0FrXCiaVUlcB92AEnVswWkF7ARO11spr3SuBWzC6/JZhZP59xL1bsVJqhLm/ozACviyM7MjPa63rvQ2nlDoP+Bjo6d29t6Fjm62lO4HXtNYP1ncct31uAtZrrc/wWt4Ho3vzeK310z62644RNE8wpx9yf+4q4DVgiNv0R76OXVfL7Kdfjzqf/fzIbBbXozsd7r47aGMAtcOBvbAQ27592HNzsRcW4igrx1Fehi4vN/9fbsxda7ej7XZw2NE2O9puA7vDWGa31STd8b6k3K8xP/6vqWudOvYZQQoLC0kPoGUJQMXF0eaKy5s0D2Zz0Q6HMaZz3z5s2ftwlJYY76GyMhzlZTjKytDlFWiHHWx+vJ8cGrQmtmtX2t9+e4MZnRssn91ulC8313i/5+fjKK/AUe75ntc2W025HHazXO7lsxPXpw/tb72lzi5xK1as4IgjjvC7XNW7dxvjCet4/u9BxvRbGRddSMF7xhjZ9uPH0+7669gy+kIq/viD5OOOI6Z9ewrnzCGmQwf6L224JbqlK1qwgKzbx7t+7zl7tt/dRL23BWOOzLZXX8WWCy+k4vc/SDxsKL3efrtJZQykroNp22WXU7ZyJamnn0a3p4y5prOfftroXg+0u/lm2ptTWEWDrZddRvlK4ytHz3feJmno0Aa2CFy46tqpctMmNo882zX9UNKRR9Jj1usRNRzIUVmJLTsbW3Y29qIi4+9DaSmOUuOnrig3/yaYfwucfx/MZc7/G9y+O3h/B/H1HcP7J27fOby2LywsID0tsL/XIjIVFhbS5667SD4yfNe2u3Xr1jHYmHJzsNa69sTxXiK9ZRat9SPAIz6W1/nJprWeie/uspN8rPs68HoDZVgMLK6/pHX6DNgAXIfREhvIsc/G6GL9QgDHK8cIuL0luD1f13Y0clsAtNbZQLb7MucfoM4PT6ZHIzIrNpWyWIjJzCQmiCnCRd3mzJnDeeedF+5ihIyyWIhp08aYK7UFzmuqrFZi2rYNWtfG+mRlZfm9rrJa6wxknc9b0tJwFBW55gQGSDzY6EzjDPIdJSVUm4mhYjqHL3NtMDUlAZSvpGllq1fT5sqxVG7YCEBCE7sYQ2B1HUwd7rmHgo8/os3ll7uWxXiMmc0IQ6nCJ65HT1cwGxeibsbhqmun+L596fvVV1TvyiKmTRvi+vSJqEAWMLJad+9OXCOmRmpOrf3vtagxZ84cDmwhgWxjRHwwG+m01nal1EPAi0qpx7TWvudQ8G0CRuuvr66/ddkN+JpszzkQdZeP58CYwqjSbb1AthUCgPx87ymVRWsV7Lq2ZmTgKCpyZTVHKRIGHwiAJdmYtslRWoIj38jQG9s58sfLQtOm5vE1zrp89Wqqs7LQZnf3piZ/gvBd14mDB5E42PMmqPeY2WiSfPTRFH7yCQkHHBCyG7Qt4TPcOe+sCK2WUNeieUR6XUsw2wJord8H3m/Edkc3vFYtvwEnKKXSvJJAHen2vK9jOZRSazCSVXk7EthcX/InIQCGDRsW7iKIZhLsurZmZLjmAQaI79fP1SLrnIPYXlTsmmO2NUzLAz5aZuvIau2Le8ZfFReHrqrCnp9P8Vdfu5Y3NfkTtKzr2iObcZQFs2lnnUn8fv2J7Vp3L4emakl1LUJL6jp6RHpdR9akVyIYPsLI5Hydc4FSKh5jnt2fneN2lVI9lFIDfWx7uFLqMLdtBwAnAh+GuuAi8s2YMSPcRRDNJNh17R3UpZ15Zs1zZjBr27sXXVUFtM5g1pKSggpgovnYzp3pcPddtBlzBT3ffsu1PP+Dmnun8f36NbmMLem6Tjx0KLE9ehDXsydJQxo/BU0kUkqRMGBAk8fW16cl1bUILanr6BHpdR3xCaBE4JRSHwDnAU9hZHEeAxwBnKS1XmqusxgY7j72WCmVipE1ORWYjpE9+g6M4PiQBqYhqqssg4C1a9euZVAYxsyK5uU912W0iMbzDvY5737wIQo+NO6ZtbvxBtrdfLNrTtzsZ54h98WXPNbv9vxzpJ58ctCOHy62nBw2HGfkco7t2pV+3zRmSnMjidY/Rx5VM3czxjQn/RZ9Xc9WkUmbyYEamjNZNILWtaeeiwbReN7ReM6iRQg0AZR80kenK4CngcuBZ4FY4CxnIFsXsxvxCGAp8AAwBfgdI+gNOJAV0WXR5kXE7B/Dos2N+zIeqRZtXkTifxOj6rxDUddtr7ma9PNH0e3552h/660egYrVbJl1F9MKW2ab0m1WWa0kHnKIx7IOd93Z6P25GzlyZFD2EyzKYpFANhQWLWJkTAwsip7PMsA438TE6DrvaK3rKNXSPsMDJZ/2UUhrXaG1vltr3VlrnaC1PkJrvdBrnRG+MkJrrXdqrf+ttU7XWqdqrUdqrTc2X+lFJNJac8+ie3Bc7ODeRfcSLT1CnOddaa+MmvMOVV3H9exJl//+12drqzMBlIvV2uIzhfpLJSa6WkesAU5r5S3p8MNd/+8wYQJpp53WpP05zZs3Lyj7ES2Y1nDPPcxzOODeeyN2eriAmedNZWX0nHe01nUUi/TPcAlmhRAhN3/DfFbtXgVzYOXulXyx4YtwF6lZuM6b6DnvcNS1xatlts1llwaUKKklU0q5WmcDyWTsS+all5Lx73/TadIk2l45NgilM4wZMyZo+xIt1Pz5sGoVYwBWroQvWv9nGeA6byB6zjta6zqKRfpnuASzQoiQ0lozafEkFApOBYVi0uJJrb6V0uO8iY7zDlddW5I9k0O1v/32kB6vucWac/DG9uzZpP1YU5LpPOVhMi+6MBjFcnnqqaeCuj/RwmgNkyaBUjwFRk+BSZNaf4ud23kD0XHe0VrXUS7SP8MlmBVChJSzpU6j4VfQ6KhopfQ4b6LjvMNV1wkHDELFxaHi4ug5ezaWxMSQHq+5dXn8cTrcfTdtx44Nd1F8eu2118JdBBFKztZJrXkNjMAmGlrs3M4biI7zjta6jnKR/hkuwawQImS8Wycx57lv7a2Utc7b1JrPO5x1HduxA32++II+X8wn6dDWNx1LwoD9aHv1VU0eMxsqRxxxRLiLIELFq3XSVdOtvcXOu1XWqTWfd7TWtYj4z3D/J6wTIjTiADZulBxSrdHirYtZ9fuqmgX7gCSzxS57JS9+8SLDew0PW/lCpdZ5m1rzebeYui4sDP0xhIe///6bdu3ahbsYIhQWL64ZMwr8DbSDmha7F1+E4a3rswyodd4urfm8o7WuRYv7DHeLCeL8WV/mmRVhpZS6HHgz3OUQQgghhBBCtBjnaK0/a2glaZkV4faP+fMCjBuBovXqC3wKnANsCnNZRGhJXUcPqevoIXUdPaSuo0dLrOs4oDuwxJ+VJZgV4VZi/vxba70urCURIaVqxh5tkrpu3aSuo4fUdfSQuo4eUtfRowXX9a/+rigJoIQQQgghhBBCRBwJZoUQQgghhBBCRBwJZoUQQgghhBBCRBwJZkW47QMmmz9F6yZ1HT2krqOH1HX0kLqOHlLX0SPi61qm5hFCCCGEEEIIEXGkZVYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSRYFYIIYQQQgghRMSJCXcBRHRTSqUDw4EdQFWYiyOEEEIIIYQInzigO7BEa13Y0MoSzIpwGw58Gu5CCCGEEEIIIVqMc4DPGlpJglkRbjsA5s6dS79+/cJdFhFiv/zyC4cffni4iyGagb91bS8tpWLNGir+Xk/1rl3YcnNwlJahS0uxl5ejq6vB4QCtm6HUQoi6JB50IFnnnMPhRx4Z7qKIZiB/r6NHS6vrjRs3cu6554IZIzREglkRblUA/fr1Y9CgQeEuiwixHTt2SD1HiYbquuLvv8l95RWKFn5FrN1Oal0rxsifKSFahPX/EJeXJ5/hUUL+XkePFlzXfg0/lG8JQohms2nTpnAXQTST+uo6/9132TP5Yc+FViux3boS26UL1rR0LKkpWJNTUAkJYFEoi9X4abUCCpQK7QkIv/30048cddTR4S6GCBWtyXnlFXRZGXy3GO66K9wlEs1A/l5Hj0ivawlmhRDNxuw2IqJAXXVdsnQpe6Y8YvxitZJ2xhmkn302SUMPxZKU1HwFFEEz5Kwzade1a7iLIUKoautWCufOpcP27dgLCrBmZIS7SCLE5O919Ij0upapeYQQzWbKlCnhLoJoJr7qumr7drLG3wEOByohgV7vzqbrtMdJOf44CWQjmFzXrV/6uecY/6mupvCLL8JbGNEs5LqOHpFe10pLUg0RRkqpQcDatWvXttT++kKIINkz5RHy33kHgK7PPkPaKaeEuURCCH9oh4ONJ5+MbdduEg46iN4fvB/uIgkhWql169YxePBggMFa63UNrS/djIUQzWbkyJHMmzcv3MUQzcC7rh0VFRSavycfe6wEsq2IXNetn7JYSDv9dPJem0nFmjU4KiqwJCSEu1gihIJ1XTscDvbu3UtlZSUOhyMIJRPBtnz5co477riQHkMpRWxsLGlpaaSmpqKCmPdCuhkLIZqNfOGNHt51XbxwIY6iIgAy/v3vcBRJhIhc19EhYeBA4z9aU7V1a1jLIkIvWIHs9u3bKSgooKqqCukN2jKFOpDVWmOz2SguLiYrK4vt27djs9mCtn9pmRVCNJtx48bx0ksvhbsYohl413X+hx8CYG3ThtQTTwhXsUQIyHUdHeL69HH9v2rz5prgVrRKwbiu9+7dS3l5OW3atKFDhw5BbY0TwbNt2zZ69uwZ8uPYbDays7MpLCwkPz+f9u3bB2W/0jIbIkqpWUqprU3YtiTIRRIi7B588MFwF0E0E/e6rtq2jfKVqwBIP+9cVFxcuIolQkCu6+gQ37u36/+VmzaHsSSiOQTjuq6srMRqtUog28J17ty5WY4TExND586dsVqtlJQEL8yJqmBWKTVaKaWVUuf5eO5387laTQZKqe1KqR+ap5T+U0olKaUmKaVGhLssQvhj7ty54S6CaCbudV3608+u/6effXYYSiNCSa7r6GBJSqIiNRWAqi0SzLZ2wbiuHQ4HVqtVAtkWrqCgoNmOpZTCarUGtct5VAWzwHLzp0fncKVUGjAYsAHHej3XHejutq2/rgUGNK6YfksCJgIjQnwcIYKib9++4S6CaCbudV2+ejUAlrQ04vv3D1eRRIjIdR09tDmfsLTMtn7Buq4lkG354uPjm/V4wX5PRFUwq7XeBWzBK5gFjgYU8KGP55y/BxTMaq2rtdaVjSmnEK1VYmJiuIsgmol7XZf99qux7JCDUZao+rMTFeS6jh66SxcAqrZuRdvtYS6NCCW5rqOHJcL/Lkd26RtnOTBEKeV+lR4LrAO+BI5SSlm8ntPA984FSqnLlFKrlFLlSqk8pdR7ZgsubuvUGjOrlGqrlHpLKVWklCpQSr2hlDrY7N481rugSqmuSqm5SqkSpdQ+pdR0pZTVfK4XsM9cdaK5D62UmtS4l0WI0FuxYkW4iyCaibOubTk5VG/bDkDSoYeGs0giROS6jh4bKysA0JWVVO/aFebSiFCS6zp6lJaWhrsITRKtwWwscKTbsmOBH8xHOkaXY/fn/tZa5wIope4H3gQ2AHcATwMnAUuVUhl1HdQMkOcBFwNvAPcDnc3/+2IFFgK5wF3AEuBO4Drz+X3ADeb/5wCXm49P6j51IcLr6quvDncRRDNx1nXZr7+6liUeMiRcxREhJNd19Bh+ySWu/1dtlq7GrZlc19GjXbt24S5Ck0RrMAtm92GlVAxGYPu91noTsNftuVTgQOc2SqmewGTgAa31RVrrF7XWDwMnAN2AG+s57rkY3Znv1FrforWeAZyGEaz6kgC8r7W+Wmv9ktb6AuBX4GoArXUp8JG57h9a67fNxx+BvRwGpdThSqnnlVLrlFKlZtKrD5RS+3mtN8utFdj98Xdjjiuiy/jx48NdBNFMnHVd/utvxgKrlcSDDgxfgUTIyHUdPSa/9prr/5Wbt4SxJCLU5LqOHjt27Ah3EZokGoPZvzACSOdY2IOBZIxWWcyfziRQR2O0kDoD4FEYr9kHSql2zgewB6Oltr7JE08DqoH/cy7QWjuAGfVs4z3B1zKgj68Vg2ACcD7wDXAb8AowDFitlBrstW4lNS3BzsfdISqXaEXeeKOujgiitXHWtTP5U8L++2NJSgpnkUSIyHUdPV545x0s6ekAVG3eFObSiFCS6zp69HabdqsxqqurOeCAA1BKMX369CCVyn9RF8xqIxf0D9SMjT0WyNZabzRXcQ9mnT+dwWx/jERRGzC6+bo/9gc61HPonsBurXWZ1/KNvlYGKrTW+7yW5QOZ9RyjKZ4Eemqtb9Vav6q1fgQ4HogB7vFa1+bWEux8zAtRuUQrMnLkyHAXQTSTkSNH4qiqomLdOgASh0gX49ZKruvocfbZZxPfx7inXvnPhjCXRoSSXNfRY8OGpl3Lzz33HNu3bw9SaQIXdcGsaTnG2NgDqRkv6/QD0FMp1RWj9XaX1to5MMSCkQzqNOBfPh7XB7GMzZomUGv9g9a6ymvZBozEWPt7r6+UsppTGgnht3nz5J5HtJg3bx7VO7PQ1dUAJBxwQJhLJEJFruvoMW/ePBIONDprla9di724OMwlEqEi13VkqaiowOFwNGrb/k2YMi87O5uHH36YCRMmNHofTRXNwSwYweqxuGUqBlZhdKMdgTmW1u25TRgts1u01ot8PH6q55jbgM5KKe9+dv2acB7Bm3HYB2VMBNURyPF6KgkoAgrNbM4zlFIpfuyvg1JqkPsDkAkKo4iMwYke48ePx7Znt+v32M6dw1gaEUpyXUeP8ePHk3L8MOMXu53SH34Mb4FEyMh1Xb9JkyahlGLjxo2MHTuWjIwM0tPTufLKKykr8+6ECW+//TZDhw4lMTGRNm3acNFFF9Uaq9qrVy/Gjh1ba9sRI0YwYsQI1++LFy9GKcV7773HAw88QNeuXUlKSqKoqAiADz/80HWsdu3acdlll5GVleWxz7Fjx5KSkkJWVhannnoqKSkptG/fnrvuugt7ANNu3XPPPQwYMIDLLrvM722CLVqD2ZVABXAp0BW3lllzbtjVwE0YY2nd55f9BKPFdKLymvFXGdrWc8yFGFmUr3XbxmIep7GcV0tGE/ZRH+fr877bst3A48CVGJmZP8NIfLXATKZVnxuBtV6PTwGWL1/OkiVLmDZtGnl5eYwZMwao6eYyfvx4Nm7cyMyZM5kzZw4rVqxgypQplJWVMXr0aI9177vvPtasWcPs2bOZPXs2a9as4b777vNYZ/To0ZSVlTFlyhRWrFjBnDlzmDlzJhs3bnR9gDvXHTNmDHl5eUybNo0lS5awYMECZsyYQVZWFuPGjfNYd9y4cWRlZTFjxgwWLFgg5+R1TjfddFOrO6fWWE/BOKcOHTqQ9XtNPrqbJj4U8efUGuspGOe0Z8+eVndOrbGegnFOV111Fdc98zQqIQGAkqVLIv6cWmM9BeOcjjvuuCaf0/Llxlfobdu2UVVVRXZ2NoWFhRQXF7Nnzx5sNhtbthiJxJxdXXfs2EFFRQU5OTnk5+dTWlrKrl27sNvtbNq0yWPdnTt3UlZWRm5uLrm5uZSVlbFz506PdTZt2oTdbmfXrl2UlpaSn59PTk4OFRUVrmDSue6WLVuw2Wzs2bOH4uJiCgsLyc7Opqqqim3btnmsW1BQAMCoUaPIy8tj4sSJnHXWWcyaNcv1WjnX/c9//sMVV1xBjx49eOSRR7jxxhv5+uuvGTZsGL+aGf+d65aWltY6p8rKSo91nIHpxIkTmTdvHjfeeCP3338/DoeDJ598ktGjR1NdXc2jjz7Kv//9bz755BOOPvpoduzY4Tonh8OBzWbj1FNPJTU1lenTp3P44YfzxBNP8MQTT/hVT8uWLeONN97g4Ycfpry8HACHw9FgPdlsNtasWVPne8/5nL+UMYQ0+iillmKMCa0E0s0g1vncdIxpcACGaq1Xuz13D/AoRgA8FygGegPnAa9oraeb680CRmite5m/W81thgIvAn8DZ2OMsz0EGKu1fsNt2wu01h6tneYcshO11spt2TqgDTAFyAPWaq3XNuGlce53IPAzRjfj47XWdd6mUUrdB/wXuFhr/V4963UA2nst7gt8unbtWgYNGtTUYosWbubMmVx11VXhLoZoBjNnzmRkeTk5zz0PwIDff8MSHx/mUolQkOs6ejjrevv111O6ZCkxHTrQb4nRSiRal2Bc15vN6Zv69PHMXbpn6lQq/2o5k2DE7z+QTmZg769JkyYxefJkrrrqKl5zy/I9atQoli5dSk6O0alx27Zt9O3bl4cffth18wBg7dq1DBkyhMmTJ7uW9+rVixEjRjBr1iyPYzlbZRcvXuz6ecIJJ9CnTx/Wrl1LYmIiYCRi6tatGx06dOCXX34hwbzpNH/+fM466yweeughJk+eDBgts85A9IYbbnBNz3PooYdisVhYuXJlveevteaoo46ib9++zJ49m61bt9K7d2+mTZvGXXfdVe+2db0vnNatW8fgwYMBBmut19W7M4zkPtFqOUYwu8o9kDV9jxHMFgO/uz+htf6fUuofYDww0Vy8A/gKo5XSJ621XSl1JvAMMAZwYMwPO9k8XkUjz+Ma4DngKSDO3F+TglmlVCdgPlCIEVQ31N/gKYxg+mSgzmBWa50NZHsdqylFFREmMzNU+ctES5OZmYnNvJNrzcyUQLYVk+s6ejjrOuX4YZQuWYotO5vK9etJGDgwzCUTwRbK67ryr78p++WXkO2/OTlboZ2OP/545syZQ1FREWlpaXzyySc4HA5Gjx7tCnABOnXqRP/+/fnuu+88gtxAjBkzxhXIAqxcuZLs7GwmTZrkCmQBzjzzTAYOHMj8+fNdwax7+a1Wq0f533rrrQaPPWvWLNasWcNHH33U4LqhFrXBrNb6PsDnu0drPQdjbGxd236C0eW4vv2P9bEsB6PrrotS6lzzvzu9tvW1/SRgkteyH4HD6itLIJRS6cCXGF2Xj9da72poG611uVIqF6OFWIg6de3aNdxFEM2ka9euVM//AoCYzp3CXBoRSnJdRw9nXacMO5695rKSJUslmG2FQnldx+/fst4vTSlPjx49PH533gTIz88nLS2NDRs2oLWuM8lSbGxso4/tPaWOsyv0gAEDaq07cOBAV7dvp4SEBNq3b09paalH+fPz8+s9blFREffeey9333033bt3b2zxgyZqg9lwUEolaq3L3X63ArdgJFNaXeeGzUQplQDMA/YDTtZa/+nndqlAO4wpioSo08KFCzniiCPCXQzRDBYuXMile/cAENtJkj+1ZnJdRw9nXcf16EFcnz5Ubd5M/rvv0mbsGOl90cqE8roOtEtvS+bequnOOYzT4XCglOLLL7/0uW5KSs2Iwrp6K9rtdp/burfKNoZzn4WFhSQnJ/u93fTp06mqquLCCy9k69atAK6xyvn5+WzdupUuXboQFxfXpPL5S4LZ5vWcUioR+BGIB0YBxwD3uQe54WAG1u8DRwPnmC2+3uskALFaa+9c/A9itGQvCHlBRUS78847G15JtAp33nknO4YNByC2k7TMtmZyXUcP97pue9WV7H7gQWx79pA/+13aXjk2fAUTQSfXdXD07dsXrTW9e/dmv/32q3fdzMxMV2Ipd9u2batzfKm7nj17ArB+/XpOPPFEj+fWr1/vet5bx44dG9y3u+3bt5Ofn+8z183UqVOZOnUqv/76K4ccckhA+22saM1mHC7fAgMxkiVNxejKe4vW+tFwFsr0BEZCqi+BNkqpy9wf5jqdgO1KqReUUreaj/nA3RiB7KfhKbqIFL5SzovW6frLL8dRUgJIN+PWTq7r6OFe1+nnnkuc2c0x9+WXsZvXu2gd5LoOjlGjRmG1Wpk8ebKrtdZJa01ubq7r9759+/LTTz9RVVXlWvb555/XmsKnLocddhgdOnTgpZdecmVABvjyyy/566+/OPPMM31u52xd9dett97KnDlzPB4vv/wyYLxv5syZU6sLdChJy2wz0lrPBmaHuxx1OMT8OdJ8eHsbKAA+B/6FkcTKCmzEGHs8XWvduNmaRdT44IMPwl0E0Uxe/d//2DzybEC6Gbd2cl1HD/e6VjExtL/tNrJuvx17QQF7HppIl+nTUBZpJ2kN5LoOjr59+/LII49w7733snXrVs4991xSU1PZsmULc+bM4brrrnNl/73mmmv46KOPOO200xg9ejSbNm3i7bffpm/fvn4dKzY2lscee4wrr7yS4cOHc/HFF7N3716eeeYZevXqVefcwf7u3+nQQw/l0EMP9VjmDIgHDRrEueeeG9D+mko+cQQAWusRWmtV18Ncp0BrfbnWur/WOllrnaC1Hqy1flRrXR3ucxAtn3M+MdH63Xf99a7/x0rLbKsm13X08K7r1FNPIenwwwEo+uILsqc/Uav1SUQmua6D55577uHjjz/GYrEwefJk7rrrLj777DNOOeUUzj77bNd6p556Kk888QT//PMPt99+Oz/++COff/453bp18/tYY8eO5f3336eqqooJEybw8ssvc95557F8+XIyMjJ8buOcDzZSRe08sy2NUmo08BLQQ2vd6L46SqnTgI+A3lrrFp+QSSk1CFgr88wK0brkf/ABex4yZi/ru2gRcd0k460QrZEtP59tF19Cldkyk3jwwbS9YRzJRx6JpYkJakRka2g+URGdZJ5ZL0qpY4BTgKe11gVhLk6jmMmXJgPPNSWQBdBaL1BKbQTuBe4IRvmECJb77ruPqVOnhrsYohl8NXs2BwEoRWzHDuEujgghua6jh6+6jsnMpPur/8e2Sy/Dtncv5b//zs5xN6BiY4nr1ZOY9h2I6dCBmPbtsCQnoxISsCQkouLiQCmURYEyHzj/b2Z29V4eBiouluSjjoq6wFyu6+ixc+fOgFp/W5qID2YxsgFPBGZhjOmMRCOBAcArQdrfy8B0pdREH5mHhQibiy++ONxFEM1kcKfO8Pd6Ytq1QzVhHj3R8sl1HT3qquu4bt3oM+8zcl99jbw330RXVKCrq6ncsJHKDRubuZTBl3LySXR//vlwF6NZyXUdPdq0aRPuIjRJVI2ZVUpZzOllWporge+11llB2t/HGFP//DtI+xMiKNasWRPuIohmUmpO3h7TWZI/tXZyXUeP+urampZGhzvG03/pEro9/xxtxlxBysknkXDQQcR06gQxkdt+UvbziqgbCyzXdfQoLw/r7KBNFrmfLIBSahJGqyzAFrfJhntrrbcqpTQwA2Ne1/uA/TACvLlKqbsw5nkdACQBfwKPaq0/8nGcy4BbgcFAJbAGeERr/ZXbOqebxzgUcABLgf801NfbDK5Pw5iqx335J0AvrfWhbsvmAWdhzAP7mbnsSOAn4Ayt9ZcAWutspdQfwDnAzPqOL4QQoRBbVGj8DHD+OiFEZLOmpZF68smknnxyred0dTWO8nIc5RXo6irQGhwO0NoIFjWANpabj5rlza/o83nk/t+rOIqLsefnExPhLVhCtEYRHcwCn2AEqBcD44Ecc7l74qMTgdHA8+bzW83ltwGfAe8AccBFwIdKqbO01vOdGyulJgKTgB+Ah4Aq4Ehzv1+Z61wOvAEsBCZgBMc3AMuVUkO01s5j+jLUPP5qr+XLgHOUUmla6yJlROrHYgTKx5tlx/y/A/jea/tVwLn1HFeIZnfggQeGuwiiGWiHg/giY4RDbBdpmW3t5LqOHk2taxUbizU2FmtaWpBKFFrVWTXTj1Rt3RZVwWywrutoa9GORInNPB5ca40K4hj4iA5mtdZ/KKVWYwSzc+sIGgcAB2qt//Ravp/W2tWurpR6HiOgvAOYby7rhxHAzgEucJ9H1QwuUUqlAM8Cr2qtr3N7/g1gPUZrrWu5DwPNn1u8li/D6AZ+LPAlRqtwJvAhRgDrdDzwu9a6yGv7zUA7pVQHrXV2PccXotm8++678sU3Ctj27EFVG7N1xfXqFd7CiJCT6zp6RFtdx/Xs4fp/1fZtJB06JIylaV7BqGuLxUJVVVXQgxcRXHl5eSQlJTXLsbTW2O12YoOYSyMaxswu8RHI4hXIZgLpGAGk+yzA52K8Rg+7B7Lm9s5bTf8CMoB3lVLtnA/ADvwMnNBA+dqaP/O9lv8KlADDzN+PB3YCbwKHKqWSzID6OLPc3pz7a9fA8YVoNpIZMTo4p+gACWajgVzX0SPa6jq2e3ewGF+Vq8w8ANEiGHUdHx+P3W4nOztbWmhbsObKZGyz2di9ezd2u52UlJSg7TeiW2b95N3iCYBS6izgAeAQjGRJTu5XW1+MLry1gmE3/c2f39bxvHeLaV08bllpre1KqR+paYU9HiNoXQ5YgaOAvUAbfAezzv3Jp4doMUaOHMm8efPCXQwRYpUSzEYVua6jR7TVtSUujtjOnanOyqJ62/ZwF6dZBaOuO3bsSGVlJXl5eRQWFmK1WqWFtgUqLi4mNTU1ZPvXWuNwOLDZbAAkJSWRmZkZtP1HQzBbK0WXUso55nQpcCOwG6jGyCp8SYD7d7ZuXw7s8fG8rYHtc82fmRgtr+6WA/ebSaKOB/6rtS5QSq01f99rrucrmHW+S3J8PCdEWETTl6Bo5myZVfHxxEgCqFZPruvoEY11HdezB9VZWVHXMhuMurZYLPTo0YO9e/dSWVmJw+FoeCPR7EIZyIIxZ3RMTAyJiYmkpaWRmpoqY2a9NKbl8XygAjhVa13pXKiUutJrvU0YweoBwG917GuT+TNba72oEWX52/zZGyNLsrtlGMmhLga6UhO0LqUmmP1Ha72X2noDOVrrfT6eEyIsRo8ezQcffBDuYogQcwazcT17oizRMJolusl1HT2isa5je/aEH36katu2qBr7Gay6tlgsdJYp2lq0SL+uW8O3jFLzZ0YA29gxgmCrc4FSqhe1s//Oxehm/JBSyuO1UjWfZgsxuhLfp5SqNZpZKdW+gbKswsiQfJiP537GaDGeAOQBzml+lmF0Mx6O71ZZMLIk/9jAsYVoVrNmzQp3EUQzqNpqtGBIF+PoINd19IjGuo7r0RMAR0kJ9nzv9CatVzTWdbSK9LpuDcHsKvPnf5VSlyulLlJKJTewzXyM6XMWKKXGKaUewggcN7qvpLXeCPwXOA9YppS6Uyl1s5mpeKq5ThHGNDzHA6uVUvcrpa5TSj2ilPqVmnlwfdJaV2BM8VNrQjatdZl5fgOA792STi0FkvFsrXVRSnUADgI+beB1EKJZPfHEE+EugggxXVVF9U5jxIQEs9FBruvoEY11Hdezp+v/zht10SAa6zpaRXpdR3wwq7X+BXgQOBiYBbwL1NsaqrX+Frga6AQ8jdGNdwLGFDze6z4EXAUkYgS2DwM9gW/c1pkNnARkAXcDz2DMW/sb8LofpzETOEop1d3Hc85gdbnb8fZQE3j7apkdBVQCkdtnQLRKp556ariLIEKsaudOMMdFSTAbHeS6jh7RWNdxvdyC2SgaNxuNdR2tIr2uW8OYWbTWjwCP+Fhe58AGrfVMjCDS2yQf675OA0Gp1noxsLj+ktbpM2ADxny0D3rt9z/Af3wcr7/3MjfXA69orYsbWR4hQiIrKyvcRRAhJtPyRB+5rqNHNNZ1bLduxvQ8DgdV26MnmI3Guo5WkV7XEd8y2xpore3AQ8BNSqkmTbyklDoNY7qgR4NRNiGCKT+KxhtFq6otW13/j+vdK2zlEM1HruvoEY117ZyeB6Byw4Ywl6b5RGNdR6tIr+tW0TLbGmit3wfeD8J+FgDBm4lYiCAaNmxYk/ehHQ50RQWOSjMRuXMoudYe/3cNMdeuf8LD4cBeXIyjqAh7URGO0jKjPA6HUUaN2S3XKL92ODyL6zHRvK5jOZ4T0nv8v459+bHfWpPc+7Gv4m/MERgpKVgzMhCtXzCuaxEZorWuEw85hOqsLEqXf4+9pBRrSkOpWSJftNZ1NIr0upZgVrQIe/73GOlt24a7GCLE/v7tNxIOOSSwjew2qnfvoXrvHhylZeiyspCUTQRXttXK/lEyhUW0mzFjBk899VS4iyGaQbTWddrIsyiaPx9dUUHJN4tIP+eccBcp5KK1rqNRpNe1qnXnXYhmpJQaBKz9tFdv+sfHh7s4QoggULGxdJo0kYzzzw93UYQQosl0dTUbhg3Hnp9P8rHH0uO1V8NdJCFarXXr1jF48GCAwVrrdQ2tLy2zokWI7d6duNTUcBdDhNiOHdvp3r1HYBspiGnfntguXbCmpmFJSsKSlIiKiweljIe5HkrVTGivlLnQ/H+4GgmVwpKcjDU9HWtaGpbkZJTFUlN2iwVQRnHdl7sX2P2/3q2dSgX2/1rFC3D7WvtStZ+KjeWc889nngSzUWHkyJHMmzcv3MUQzSBa61rFxJB2+unkz55N6Y8/Ytu3j5j29U6cEfGita6jUaTXtQSzokXo8eIL9B00KNzFECG0aPMizpp9Fp9f8iQn96k1rXKrVXPen3Nyn2PDXZxmsWjzIr4+8msWbV4UVXUdrSL5S5AIwKJFzPv6a1i0CE6Oout60SI46yzSnn2OfACHg33PPkenyZOMG5OtUbTWdZSK9M/wVnoVilBSSsUrpR5TSu1SSpUrpX5WSv0r3OUSLZfWmnsW3UPlR5Xcu+je2omFWinXeduj57yjta6j2ZgxY8JdBBFqWsM99zCmshLuvbdWArpWyzxvKitJfOVl4gcOAKDgww/Z/eCD2CI8C6xP0VrXUSzSP8NlzKwImFLqXeAC4GmM+XHHAocDJ2itlwe4r0HA2rVr1zJIWmZbrc//+ZyR746EMiAJPr/4c87c78xwFyvkXOft/D0Kzjta6zqa5eXl0aZNm3AXQ4TS55/DyJHkAW2cv58ZBde1ed5O1W+9zfa33qJqmznfbEwMSYceSlzfPsS0aWsMgUlMxJKQCBZj3IXn0BdqD4HB/dcWkDRv9Wp4/HFKMKfG+M8EOHRImAslQqmkpIT2xx5LbNeu4S4KEPiYWQlmRUCUUkcAPwN3a62nm8sSgLVAttb6mAD3J8FsK6e15vD/O5zVu1ejv9eoYxVDOw9lxbUrWsYf7hDxOG80itZ/3tFa19Fu2rRp3H333eEuhggVreHww2H1aqZpzd1KwdChsGJFvePxI57beaO1ca5Dh2KbP58dN9xIxboGv2MLETG6TJ9O+lkt4wZVoMGsdDMWgboAsAOvOBdorSuA14CjlVLdw1Uw0TLN3zCfVbtXodHQFTSalbtX8sWGL8JdtJDyOG+i47yjta6j3RFHHBHuIohQmj8fVq0CrTkCjMBu5Ur4opVf127nDbjOO+aXX+j14Qf0fPstMi68kIQDD8QiCSyFCBtJACUCNQT4R2td5LV8hfnzEGCHrw2VUh0A7/R/AwE2btwYxCKKlkJrzYSPJsA+c8E+IMn474TZE+h5Qc9W2WJX67zdtNbzjta6FvD333/Trl27cBdDhILWMGGC69e/AVdNT5gAPXu2ztZZr/P24DzvxEQY/e+aTRwOdEUFjspKdGWl51hTt4DY1SPS9bT2XCec7rgDNm0CrVkFDAWjfvv2gyefCHPhRKisWv0rR3Roj7WF9DZwiwni/FlfuhmLgCil1gJ7tdYneS0/AFgHjNNav1zHtpOAiSEvpBBCCCGEECKSnaO1/qyhlaRlVgQqEaj0sbzC7fm6vAB86LXsQMCZUOrvJpdOtGR9gU+Bc4BNYS6LCC2p6+ghdR09pK6jh9R19GiJdR0HdAeW+LOyBLMiUOVAvI/lCW7P+6S1zgay3Ze5dTv8259B3iJyudX1Jqnr1k3qOnpIXUcPqevoIXUdPVpwXf/q74qSAEoEajfQ2cdy57JdzVgWIYQQQgghRJSSYFYE6jdgP6VUmtfyI92eF0IIIYQQQoiQkmBWBOojwApc51yglIoHrgR+1lr7zGQshBBCCCGEEMEkY2ZFQLTWPyulPgQeNafa2QiMAXoBVzdil/uAyficxES0MlLX0UPqOnpIXUcPqevoIXUdPSK+rmVqHhEwpVQCMAW4DMgE/gAe1FovDGvBhBBCCCGEEFFDglkhhBBCCCGEEBFHxswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4EswKIYQQQgghhIg4MeEugIhuSql0YDiwA6gKc3GEEEIIIYQQ4RMHdAeWaK0LG1pZglkRbsOBT8NdCCGEEEIIIUSLcQ7wWUMrSTArwm0HwNy5c+nXr1+4yyJC7K0XX+Sy665DWa3hLooIsZkzZ3LVVVeFuxiiGUhdRw+p6+ghdR09Wlpdb9y4kXPPPRfMGKEhEsyKcKsC6NevH4MGDQp3WUQIFX39NVd88y0plVX0+L9Xwl0cEWJnn322XNNRQuo6ekhdRw+p6+jRguvar+GHkgBKCNEsSn/4AaU1pcuW4SgtDXdxRIiVl5eHuwiimUhdRw+p6+ghdR09Ir2uJZgVQjQLe0GB6/+VW7eGrRyieWzatCncRRDNROo6ekhdRw+p6+gR6XUtwawQolk4CmsS0lVt3hLGkojmYI53EVFA6jp6SF1HD6nr6BHpdS3BrBCiWdgLaoLZys2RfRdQNOz5e+4h/733cJSVhbsoIsSmTJkS7iKIZiJ1HT2krqNHpNe1BLNCiGZhl5bZqHJNbh57Jk0m9/XXw10UEWIvvfRSuIsgmonUdfSQuo4ekV7Xks1YCNEs3MfMVknLbKumbTYqNm/GApT9sjLcxREhNnLkSObNmxfuYohmIHUdPYJV1w6Hg71791JZWYnD4QhCyUSwLV++nOOOOy6kx1BKERsbS1paGqmpqSilgrZvaZmNQkqpeKXUY0qpXUqpcqXUz0qpf/mx3QCl1FNKqR+UUhVKKa2U6tUMRRYRTldXe2Qwrtq6DW2zhbFEIpTsBQWuPy4Vf/2F1jqs5RGhJcFN9JC6jh7BCmS3b99OQUEBVVVV8reghQp1IKu1xmazUVxcTFZWFtu3b8cWxO+A0jIbnWYBFwBPAxuAscAXSqkTtNbL69nuaOBW4E/gL+CQUBZStB72oiKP33V1NdU7dxLXq1d4CtTMqnfvpmTxYtJOPx1rRka4ixNyttxc1/8dhYXYdu0itmvXMJZIhNK4ceMivpua8I/UdfQIRl3v3buX8vJy2rRpQ4cOHYLaGieCZ9u2bfTs2TPkx7HZbGRnZ1NYWEh+fj7t27cPyn6lZdYPSqlJSqlWcTtJKXUEcBFwr9b6bq31K8CJwDbg8QY2/wzI0FofCLwT2pKK1sS9i7FTZRSNm919/wPsmfwwe6dNC3dRmoXdLZgFKP/zzzCVRDSHBx98MNxFEM1E6jp6BKOuKysrsVqtEsi2cJ07d26W48TExNC5c2esVislJSVB22+jglml1Fizi6nzUWF2WV2olLpVKZUatBKKYLsAsAOvOBdorSuA14CjlVLd69pQa52ntS4OfRFFa+Oe/MkpmsbNVvzzDwCly5ZHRTcrW26ex++Vf/0VppKI5jB37txwF0E0E6nr6BGMunY4HFitVglkW7gCHw0OoaKUwmq1BvW7UFNbZh8CLgduAJ4zlz0NrFFKHdTEfbckjwCJ4S5EkAwB/tFaF3ktX2H+PCRUB1ZKdVBKDXJ/AH1DdTzRcrhPy+MULS2zuqoKe04OALbsbKqzssJcotCz5eZ4/F7xpwSzrVnfvvIxHi2krqNHsOpaAtmWLz4+vlmPF+z3RFOD2S+11m9rrV/XWj+qtT4VOBnoAHymlGoVAaDW2ma2XrYGnYHdPpY7l3UJ4bFvBNZ6PT4FI5PakiVLmDZtGnl5eYwZMwYwsukBjB8/no0bNzJz5kzmzJnDihUrmDJlCmVlZYwePdpj3fvuu481a9Ywe/ZsZs+ezZo1a7jvvvs81hk9ejRlZWVMmTKFFStWMGfOHGbOnMnGjRsZP368x7pjxowhLy+PadOmsWTJEhYsWMCMGTPIyspi3LhxHuuOGzeOrKwsZsyYwYIFC+SczHMq35ftehMUWq0AbP7224g+J3/raep//uNxETx+5ZURf04N1dNfP/7kcc4Vf/0V8efUGuspWOf0wgsvtLpzao31FIxzUkq1unNqjfUUjHPaunVrk89p+XIjDcu2bduoqqpyjZcsLi5mz5492Gw2tmwxbmxv2LABgB07dlBRUUFOTg75+fmUlpaya9cu7HY7mzZt8lh3586dlJWVkZubS25uLmVlZezcudNjnU2bNmG329m1axelpaXk5+eTk5NDRUUFO3bs8Fh3y5Yt2Gw29uzZQ3FxMYWFhWRnZ1NVVcW2bds81m1N57Rr165mPSebzcaaNWvqfO85n/Ob1jrgB0bCIA0cVsfz95rPX+u1/ERgGVAKFGAEMvt7rdMTeAFYD5QDucCHQK86yjAMeNlcrwh4E8j0Wncr8DkwAlhp7ncNMMJ8fpT5ewWwChjitf0k46XyWKaB54FzMYKySmAdcJqP16MrMBPY67beVY157Zv6ADYBX/hY3sc8p9v93M9d5vq9Ajh2B2CQ1+NsQK9du1aL1itn5uv6zwED9Z8DBupdDz5k/H/g/ro6NzfcRQu50lWrXOf+54CBetcDD4a7SCGXdd99Huf854CBujonJ9zFEiHy+OOPh7sIoplIXUePYNT1pk2b9KZNm4JQGhFKu3fvbtbjNfS+WLt2rTZjjEHaj/giVAmg3jJ/nuJcoJQ6GVhoBjSTgCeBY4DvvaZ3+f/2zjw+yupq/N8zkxVCIOz7prhhW0CrP1u34r5VbTVqq4KtVXArVhRFqiiKr1VfrYLrC0VrURGlVlFsUZGiVlwroCKgrLInEEJISCbn98d9JkwmEzJJZjLMzPl+PvfzzHOfe+9zbk6e5Tz33nN+7OU/j/Oc+zhwAjBPRFpFONck4GCvzWeAXwN/l7pj2PsD04FXccZ2AfCqiPwaeBB4FrgdN+11hohE87c5Gmd4Pw/cBOQAL4lIh5B+dwH+gxuxngT8HlgOTBGRUVGcI9bsAiLNJ8gJOR4XVHWTqi4JTTjj2khxAtu3uR8+H/mnn+5+q7LzvfcSJlNLUbVxY639sk8/TZAkLUdgy9Y6eTbVOHX57W9/m2gRjBbCdJ0+mK7Th44dOyZahGYRF2NWVdcC26m9HvI+oAg4SlXvU9U7cUZqW+COkHKzVXWQqt6uqk+p6q3A6bgR219GON1u4ARVfURVrwFuxo3WnhVW7kDgl6p6h6o+BPwGyAOeAo5R1XtV9V6cUbq/10ZDHOzVvUtV/wycC7QCLgopczfgx432TlDVx1X1bJwBPD4BU7HX46YahxPM+74FZTHShKADqDKfj1aHDcHXujUApfP/nUixWoTKDbWN2d0rVlBVXJwgaVqGqiLnACpn4MCavHT4cJGuBKcfGqmP6Tp9MF2nD8GpyU2lsrKSQw45BBHh/vvvj5FU0RPP0DylQBsAEemGcyw0TVVr3Fyq6hfAv3DGajCvZmRQRDK9Uc7luGnJQyKc50lVrQzZfwyoCm3T40tV/SBk/0Nv+7aqro6Q37+B/gHMVdWakUWvPyXBut7o8C9xo8EiIh2DCTdK3baePsWTz4EDRCQ/LP/IkOOGEVOqPWO2XY8eSGYmrX9yFAA7FyxAq6sTKVrcCR+ZBdiV4qOzwdA82fvvR6vDDweg5PXX0UAgkWIZceLpp59OtAhGC2G6Th9M1+lDv379mlX/kUceYfXq1Q0XjBPxNGbzgGAYl2Ak3qURyn0FdBSR1gAikisid4rIGtz60i3AZqAdzvgLZ1nojqqW4kYf+4aVWx1WLuheNfxzRDC/IMK5womkueKQup1wcl+B60No+otXpnMU54klM3EjxVcEM0QkG7gM+FBV13h5vUXkoBaWzUhRgnFml23cAEDrY45x+cXFlC9enCixWoRKr88ZnTtDRgYAO956O5EixRVVpcozZv3tO5B/5pmA8+Rc9tHHiRTNiBNBBx5G6mO6Th9M18lFeXk51U0cHAg6amoKmzZt4s4772TMmDFNbqO5xMWYFZGeOMNzeROqPwLcCswACnHrbk/COXhqjrz1DQnUlx+N3+iG6gblfRbXh0ipRefeqeqHOIda94jIn0TkCuBtnPEf6nb1GdyHhhpEpK2IjBORcbgp4gDXeHnXxF96I1kJhuY55Eg3ASDv2D2z+EvnzUuESC1GlTfNOKtPH9r87HgASl57rWYqbqpRvbMMragAIKNDe9qccnKNEV8y+7VEimbEiVdffTXRIhgthOk6fTBd753x48cjIixfvpzhw4fTrl072rZty2VexIJwnn32WQ477DByc3Np3749F154YZ3pvX379mX48OF16h5//PEcf/zxNfvz5s1DRHj++ecZN24cPXr0oFWrVpSUuKibL774Ys25OnbsyMUXX8y6sLCAw4cPJy8vj3Xr1nHjjTeSl5dHp06dGD16NIFGzKK6+eabOfDAA7n44oujrhNr4jUye4m3fdPbrvK2B0YoexCwRVV3evvnAU+r6g2qOlNV/wUswI1wRmJA6I6I5OHWf65smugxZTNudNqvqnPrSZsaaiQOXIqLB3wJ8DCQCZypqvMbqFcATPDSqV7eDd7+6LhIaqQEwTWzny9z37cyu3Yl+5CDASh+7nkCpTvrrZvsBKcZZ3TtSsEl7taou3ez7YUXEilW3AgU7XH+5O/QkYyCAvKOPhqAkjf/SfXu3YkSzYgTtrYufTBdpw+m6+goLCxkx44d3HPPPRQWFjJt2jTuuOOOWmXuvvtuLr30UgYMGMD//u//MmrUKN566y2OPfZYtnkz15rChAkTmD17NqNHj2bixIlkZWUxbdo0CgsL8fv93HPPPfzud7/j5Zdf5uijj65zrkAgwCmnnEJOTg73338/xx13HA888ABPPvlkVOdfuHAhTz/9NA899FBC4wnH3JgVkaHAH4HvgL8BqOp63FrMYSLSLqTsobiR19dDmghQd1T0WtzU2EhcISKZIfsjgQzgjSZ3IkaoagB4Cfil19daiEinlpcKVLVcVW9U1W6qmqOqR6jqm2FljldVCctbqapST+rbop0wkoqgMXvgYYfV5HW8ws10DxQXU/RMaq7N0epqKje571WZXTrT6sc/Jvtgz4if/hyagoZdVYgn44wO7QHIP8tNNa4uKaH4r88mRC4jflx99dWJFsFoIUzX6YPpOjoGDx7MSy+9xMiRI3nqqac499xzmTJlSs3xVatWcfvtt3PXXXfx/PPPM3LkSG677Tbeeecd1q5dy6OPPtrkc5eXl/P+++9z/fXXc/PNN5OZmcmYMWM49NBDmT9/PqNGjeKee+7hxRdfZOXKlTz44IN16l9wwQVMmzaNESNGMHPmTAYPHlxL/vpQVa699louuOACjjrqqCb3IRZkNLP+ad66ygygCy6O7Em4kdifq2p5SNkbcQbmByIyBcjFGanbcWF1grwGXCIi24EvgaNwYW3qxnpwZAFvicgM3MjvVbiR3H80s2+x4mbgZ8CHIvIUrk/tcY6fTvR+G0bKopWVVJeWArCqqKhmekabk08m+5CDqfjyK4qm/oWCiy4ioyCaperJQ6CoCKqqAMjo0hURof0ll7B+7FiqNm9m65QpdBw5MsFSxpZaI7PtXZSyNieeSFafPuxetYrNjzxCm5NPIqtXr0SJaMSY+fPns//++ydaDKMFMF2nD/HU9YaJE6n46uu4tN0Usg8+iK5jxzap7ogRI2rtH3PMMcyaNYuSkhLy8/N5+eWXqa6uprCwkC1bttSU69q1KwMGDOCdd95hbBPPPWzYMHJz9wRF+fjjj9m0aRPjx48nJyenJv+MM87goIMOYvbs2XVGjUeMGEFpaWlN+WOOOYa//vWvNMS0adNYtGgRM2fObJLssaS5xuyd3nY3LuzOImAU8BdV3RFaUFXnisipuDA8dwKVwLvAGFX9LqTo73Gjs7/GxT59D2f01Ro5DOEar+yduOmyzwHXqao2s28xQVU3isgRwG3AL3DG9lZgCZCQ1dKew6c7cdOMC4AvgHHelO6G6vbAxeU9GTey/w5wvap+Gz+JjWQm4K3hAMhsv+fbjfh8dB41ijVXXEl1aSnrRl1Pr8cfw5fb0tGq4kdoWJ6MLs7XW/6ZZ7D1iSecYffwI+QMHFhrDXGyU7V1z1rgjI7OmPVlZ9N1wp2svnQYWl7O+lvH0eupJ/FlRwp5bSQbBSn2EcqoH9N1+hBPXVd89TVlH30Ut/Zbkt69e9faD/7diouLyc/PZ9myZagqAwYMiFSdzMzMiPnREO6FeNUqt6rzwAPrruo86KCDWLBgQa28nJwcOnXqRHFIuMCCgoJa+5EoKSnhlltu4cYbb6TXPvBhuknGrKpOA6Y1od5bwFsNlNmGiwEbTt96qpSp6pXAlXtpM2Ld8Gm0Xt5KwqY5q+p4ao8eR6xb37m8dbHXeGlfYBpubfJDOG/Qw4HXReRnqrqgvkreeuR3cM69JuI+SFwPvCsig1S1vtFzI40JTjEGaNujR61jrY85hrwTTqD0rbco+/BD1l59Nd3vu4+MDh1aWsy4ULVpjzGb2bUrAL6sLHo88jArL7gQ3bWLdX+4gW533kH+6eHRxJKTqq17vjz7Qz5etD7iCNoVFrJtxgzKFi5k9fDL6Dl5EhntbXJKstMj7Lo2UhfTdfoQT11nH7xvBctojjx+f+RVkMExterqakSEN954I2LZvLy8mt/1rTsNBAIR6+Y28+N/sM2srKxG1bv//vvZvXs3F1xwAStXrgRg7dq1gDPiV65cSffu3RvdblNp7siskWR4o8QXAjeq6v1e3jPAYuBPwE/2Uv0qnMOtI1T1I6/uG17dG4CmzZMwUppAiMOBj5d+XSuwsojQ44H7WTNyJGUf/Ied73/AilNOpf2wYbQ55WSyBwxIqFOB5lK5YUPN74wuXWp+5xxwAN0n3s266//gRqX/cAPb/v532p1/Pnk//Sm+Vq0SIW5MCHgjs7szM/GFPcg633QTFd+uYNfHn7Drs89YccqpFFx0EflnnpH0uk5n3nzzTY444ohEi2G0AKbr9CGeum7qlN5kZL/99kNV6devHwcccMBeyxYUFER0CLVq1Sr69+/f4Ln69HGRUJcuXcrQoUNrHVu6dGnN8XC2b99O69atG2w/yOrVqykuLmbgwIF1jk2cOJGJEyfy2WefMWjQoKjbbA5mzKYf5+Gmcde4KlPVcm8d80QR6RWMNVtP3Y+ChqxX92sReQsXRqnJd6cd895l+3crm1rd2Iep+HpPhKfzf1N30oUvJ4dekyezbvSNlL79NtWlpWyZPJktkyfjb9uWrAH7k9GpE/62bfG3bYe/TR74MxC/H/w+xJ9RsxW/D3yx8mvXfMOq7IMP3A+/n4yOHWsdyz/tNMjIYMMfbyOwbRs75/+bnfP/DT4fWf37kdm1Gxkd2uNv3wF/23wkMxPJyICMDO93JvjqyhjRIIwqL8p6DVD+5ZcAtOrevc4xf15rek+dyvpx4yj5x6tU79jB1iefZOuTT+Jv146s/v3J7N4df34bfHlt8OXl4cvJBvE5Hfv8YVtfk2RsPgkyuvdRY3/EwIFsf212osUw4kyrw4Zwww03NLqeqqLl5QS2byewbRvVpaVoVQANVEF1NVoV3AagOgCNWCXWpBVljawiWZm0/slP8edF/7IPzgFgYPt2AkVFbrlNVRUaTJWVaGVVWF/DBAvvW9h+nb7HcHGdr3Ur/nDttY2up6pU79hB9Y4dBEpLqdqxA39+PoEdO4IFam33kRWBTaK63LkFqtq+naqMPeZUwAvLU1VSQtW2bfz8xBO5xe/n9ltv5Zknn6z1jFZVioqL6eDNUOrfuzcLPviAsk2bakY1Z8+Zw5o1a+jXuzdVnqEb8PyQBHburMkDGLT//nTu1InHJk/m0l/8gmxvKc+cf/2Lr776inE33VRTPhhZoGrbNjrl5lK9e3edD9D1cd1113HOOefUytu0aRNXXnklw4cP5+yzz64zBTqemDGbfgwGvlHVkrD8hd52EFDHmBURH/BDYGqENhcCJ4tIm/C10mFtdAbCPTjvB7Dp/vtpa+vnUp6b77qLJ155pU6+r1Urej06mdL589n04ENUfOUM4MD27ez6+JOWFjPmZHTs6IzvMPJPOolWgwax+eGHKXn9Dap37oTqanYvX8Hu5SsSIGnsWLF5M5FWCPmysuh+773kn3oqW598il2ffw64Efxdn37Krk8/bVE5DcOIDn9BAeN7dGd6Aw5fAqU72fnee5TOf5eKr76m4rvv0F27WkjK+JA3dCi9Hp281zIVy5ZRMudNdv33v1QsXepiiTciXue+xocdOjD8vXpXngFQXVbGjrffoezD/7Drv1+we+1aNCTGasW119L6J0exe9WqvbSSnAT9gVR+/z2VIf/fAS+GfNX69VT6fPTOzOT2a67htj//mZXLl3PW0KHktW7NqrVr+cfbb/Ob885jlBdb9tLTTuOlV17h9LPO4hennMJ3a9bw3Guv0b9XL7SigkpvKm/V5s3uXFu31uQFmXDddVz5xz/ys5NPpvC009i4dSuP/u1v9OnRg6vOPrumvHrvG8F96dkzamN2yJAhDBkypFZecLrxwIED6xi68SZecWbjjqpO80LCfJxoWZKMbsD6CPnBvLrDKY72QHYT6wa5CjclOTTVtWyMlGRDTg6Pv/wyZ511FgBjx45l0aJFTJ8+nenTp7No0SImzplD/1kvc2+f3nS59VY+KSgg+0c/YkebNlS3aYPuoyNTDdHm5JNr+l1YWEhZWRkTJkxg4cKFvLpgAW/064fv6Wm8OWQwHa64gq9atSLn0EPZnpUFLbTmJNboEUewfPnymliFwf4PGzaM4uJiHv/kE1aNuJJ1t9zM0uOPI/Pkk1nXNp/Mnj3Z6fNBPeuQDMNIDIHiYh674w4KCwsB6tzLn3vmGd666mqWHnMM637/e7a/9DLlX36Z9IYswI6PPqrxOBt+L580ahSLzziTb8/6OVsmT2bnggXO2EhiQxbg8LZtmTVrFlOnTq1zL68uK+OpE07gm+N/xvejR7PtxZlUfPNNLUPW2MPoyy9n+oMP4vP5mPjYY4y9/35mz5vHCUcdxRnHH19T7qSf/pT/GT2aZStXctO99/Lhf//LS5Mm0SNkmVJDXHLOOfz1vvvYXVnJuAcfZOqLL/LzoUOZ+/TTtMvP32vdVatWEfD+b7dv386OHTvYsGEDVVVVfPed89W7bNkyANasWUN5eTlbtmyhuLiYMk/31dXVrFixolbZtWvXUlZWxtatW9m6dStVVVUsWrQIqHs9TZgwoeZYtEgyD/EbjUdEVgBLVfX0sPz+wAqcZ+KHItTrBazGeZ/+U9ix3wBTgMGq+vlezl3fyOwrn74xh0MaWEtgJDECWb178/NzzuHVV19tcjNaXY3u2uW2YVPTNBBwLw8xuqfF6t7oy8oisxmONFQVrayEysraU9SqwqeoEbnvUeRF7Gszuu9r3YpfXH5583TtTU3UigonXyCABqo9Xbst1dVNF7IZciWEffhRPXLkCB577PFEi2HEiV2ffcr6W8cBMLlnDybNnVunTOWGDawefhm7vdEZAMnNJfeHPyR7//3J6NLFWyrSFl+bPCQjE8nwg8/nlk94W/E1YalIoz9yRl+++PnnKH7GhSk58Iv/1hq5UlW2TH6ULY89Vstwzerfn5xDB5LZrfuepSL5bWqWikhmJmRkIpkZdWSvs0yksfsxWAKx6YEHKH3rLYoyMvjp4rpGReX69ay5+moqvtyzhEhyc2k1eBBZ++1fa6nIhoJ2+Nu1o2+Pnp6o4kQMlTtJP1KnEqtXraLPfvtFnEEWD7791gVAqW8d8JIlSzj00EMBDlXVJQ21Z9OMY4SIFAKPA71VtbSRdUfg1psOUNWKeMgXwi7cCGs4OSHH66tHE+sCNV6dN4XmBW/cWb16kt2/5ebXG4mhOcYNuHA+0ggnBamAiCBJOELbbF2LILm5kEKhmlKVqW/WFznPSAWqd+55pbln7K11jldt2VLLkM0esD8dr7uOvGOPTfrwWzkhH9mrNm0iq2fPmv2tTzzBlkmT3E5mJh2GXUq7888nqx4nO8lCMAZ4h4wMVLWWgb17zRpW/upXBDY7r/U5hxxChyt+R5uhQ91zKowtntHib528Tg3Tgb5JPpiU8GnGIvITERkvIu0SLUtTERE/Ln7uI401ZD2mAVnsJbxQDFmPm2ocTjDv+3rqFQEVTaxrGABNDgxuJB+m6/TBdJ3a+Nu2rfn9wpT/q3VMAwHWjLyqxpAt+NVF9Js1i/yTTkp6QxZqe6GvCvFOv2PePDb/+WEAMnv2pN+LM+g8enTSG7KwJz64lpfXmjas1dWsv2VsjSFb8Ktf0XfGC+SfempEQ9ZIHtaGrbtNNhJuzOJCwdwOtEuwHM3hLOBAQjwENwZVLQeeBv4g8Y9N8TlwgIiET5w/MuR4HVS1GlgEHB7h8JHAt3tz/mQYABdddFGiRTBaCNN1+mC6Tm387drV/P5/bupfDSWzZ1PurW9re+65dBk3zk0bThEyOu8xZis3urjhge3b+f6mMaCKtGpFz0cnk3PQvhU3tTn42++J8161dWvN7+Lnn6fsY+empt2FF9D1tj+mlK7TmfZJHu99XzBmo0ZEfCKS03DJFucy4D1VXdeMNmYAfYCfxUakepkJ+IErghkiko3rw4fBsDwi0ltEwu/OM4Efi8jhIXUPBIYCL8ZZbiMFaOyifiN5MV2nD6br1MaXl1ezjnWzN20UQCsr2fyIm2br79TRGTcxC422b5DZNWRkdqNbJbVt5ktUe55su024s9ZU5FQgo8MewyZozFZt2cLm+x8AILN7dzqPvjEhshnxYVeSO2lL6F1HRMYD93m734mIeqmvd1xFZJKI/FpEluCmuZ7qHRstIu+LyFYR2SUin4jIefWc52IRWSgiZSJSLCLzReTksDKnici/RWSniOwQkdkiUjcacN22czyZ6nhECJH/HBFZLCIVIrJERE4NL6uqn+Cm8p7d0Dmbg6p+iDM87xGRP4nIFcDbQF/gppCizwBfhVV/FOckaraI3Cgio4B/ARuBB+Ipt2EYhmEYLY/4fPg9L6j+kJfebS+9TOUaF8mv44gR+FJwfbsvPx/JcWMoVRs3olVVFP/tbwBk7bcf+aefvrfqSYm/w56Y6MEwM9tffY1qb8px1zvGNzrmrmHEk0R/QnsZeM77fT1wiZc2h5QZCjwIvAD8Hljp5f8e+Ay4Dec8qQp4UUTOCD2BiNwO/BWo9MrejoujOjSkzCXAbKAUGANMAA4BFgQN671wGG69a33BEY/GGYHP44zFHOAlEekQoeynwE8bOF8suBR4CPe3fhjIBM5U1fl7q+RNIz4emA+Mw/2d/gscp6qb91LVMAD4wQ9+kGgRjBbCdJ0+mK5Tn+C62Q5Ze9bBFk2bBriRuoLzz0+EWHFHRMjo0hlw04x3vP02ld879yDtL7m4rvfhFCDSyGzJa68BkNmnN62PPrpR7VnUlH2f3Bb+EBXr/4mETnZX1S9E5FPgIuDvqroyQrEDgR+o6pdh+Qeoas0nQhGZhDMG/4AzTBGR/XEG7CzgPG/dZ7C8eNs8nEH3f6oaOvX2aWApzlCuyY9AcCrud/UcPxg4RFVXeO2+gzMALwImhZX9FmdgxhVvje6NXqqvzPH15K8FUvOpZcSd5557zl580wTTdfpguk59/O3awapVbFi+nIHA7pUra5w+tbvowpR2AJTZpSuVq1ZTtXEjxX99FnAjtm1//vMESxYf/CHrJwNbt1Lx7XeUL3HRUdqecWajDHifz8fu3bvreEU29i2Kiopo1aplPE6rKoFAgMzMzJi1meiR2Wh4N4IhS5ghWwC0Bf4NDAkpdg6uj3eGGrJe/eBngZNwzqeeE5GOwQQEgA9peA1rcIS1uJ7jc4OGrHfeL4ASIFJwpWIgV0TMh7mRkkycODHRIhgthOk6fTBdpz6+dm5ktn9HNwW1dP6eiVx5xx2XEJlaiqBH493ffkvZRx8B0O7cc/G10Mt/S+PLzsbXpg0AVVuLakZlAfLPPLNRbWVnZxMIBNi0aZON0O7D9AwJORVPqqqqWL9+PYFAgLy8vJi1mwxuyCKOeIrImbiproOoHfs09GrZD6gG6hjDIQzwtm/Xc7wkKinrj1S9OkJeMVCwlzbiesV7YZD+BJwLtAIWAjeoan1TpUPrHgEMx3kw/iGQoar2uc2IirPOOqvZ8UeN5MB0nT6YrlOf4DTj77/5hn5A6bvOmM3o1o3sAQP2UjP5yfSmGQe2b6/Ja310S6wISxwZ7duze8cOqrZuofTfTtc5AweS3b9fo9rp0qULFRUVFBUVsX37dvx+v43Q7oPs2LGDNt4HjHigqlRXV1NVVQVAq1atKCiIZAY1jWQwZuu42BKRY4B/4NZuXoWLnVqJ88j7q0a2HxydvgTYEOF4VQP1g37LC4BIgZoC9dSLdDUXAGWho86xRkR8uGnYP8I539qC+xvOE5HDVHVZA02cDlwOfIGbFp1abvyMuGIvvOmD6Tp9MF2nPv627QDomJNDdVkZZQsXApB37LEpb5yEhucBQITcQYMSIktL4e/QAVatovy/X9SsEc4//bRGt+Pz+ejduzcbN26koqKC6urqhisZLU48DVnw1p5nZJCbm0t+fj5t2rSJ6X1jXzBmmzIK+UugHDhFVSuCmSJyWVi5FThj9RDqiZ/qlQHYpKp1PBJHwdfeth8uDmtz6EddD8Kx5jxcbN/zVXUmgIjMAL4B7qDhjwGPAfeq6i5vnbIZs0bUFBYWMmPGjESLYbQApuv0wXSd+vi9acbVpaWULliAVlYCkHfcsYkUq0XI6FrbmM0+4AD8cX75TzQZHdwKuqAhC5A7eEh9xfeKz+ejW7duMZHLiA/Jfg/fF9bM7vS27RpRJ4Azgv3BDM/r8Dlh5f6Om2Z8mzciSUj54CeBN3FTiceKSJ3VyCLSqQFZPgF2A4c3UC4ahgDvx6CdvXEeLpTOy8EMzxPxDOBsL+ZsvajqxniOHBupzTTP+6WR+piu0wfTdeoTHJkFKHltNgCSmUnrI49MkEQtR2aX2sZs7pDBCZKk5fCHeDQGQIScA23sIlVJ9nv4vmDMfuJt7xaRS0TkQhFpKIDVbNxazzkiMkJEbsM5a1oeWkhVlwN349aG/ltEbhCRazxPxRO9MiXASOAY4FMRuVVErhCRu0TkM1won3rxPAP/EzixMZ0OR0QOA9oDrzSnnSgYDHwa7hALt262FXEcaRWRziIyMDTh1jUbacIDD1g44nTBdJ0+mK5Tn+CaWYCd//kPADk/+iG+1qkfbzQjzJhtNeSwBEnScmS0rx09MqtPn7TQdbqS7PfwhBuzqvoR8EfcGs5puLizex0NVdW3gd8CXXHxUi/CxYedFaHsbcBvgFycYXsn0Ad4K6TMdOAEYB0uXM2fgQtxU5P/EkU3pgL/T0R6RVG2Ps7HOYuqzxFVrOiGW2McTjCvexzPfRWwOCy9ArBgwQLeffdd7rvvPoqKihg2bBjgHIsAXH/99SxfvpypU6cya9YsFi5cyIQJEygrK6OwsLBW2bFjx7Jo0SKmT5/O9OnTWbRoEWPHjq1VprCwkLKyMiZMmMDChQuZNWsWU6dOZfny5Vx//fW1yg4bNoyioiLuu+8+3n33XebMmcPkyZNZt24dI0aMqFV2xIgRrFu3jsmTJzNnzhzrU1ifTjnllJTrUyrqKRZ9qqioSLk+paKeYtGnzz77LOX6lIp6ak6flm/cSJDqEucX851vliV1n6LV04tz56Ih6/uumTwp6fvUkJ7++dFCQqns1Svp+5SKeopVn/75z3/uU31atKhxqzbFXGU3HxHx4zwmz1DVPzahfjawEvgfVf1zI+r5gGiDu1WoqopIAHhCVa8Ka2sozsA/V1X/HuX5JwFXR+vNWEQ6U/dDxX7AK4sXL2bgwIHRNGMkMbNmzeLcc89NtBhGC2C6Th9M16nPrkWLWHl+Ya28LmNvof2llyZIopZl2bHHUbVpExldurD/vHdS3ulVyZw3WTdqVM1+pxv+QMff/S5xAhlxZV+7hy9ZsoRDDz0U4FBVXdJQ+X3BAVTSo6oBb6rzYyJyr6qWNrKJy3DemB9vZL1jgXeiLHswzlnVLmqHMgqS423jth5WVTcBm0LzUv2BYNSmuLi+cMxGqmG6Th9M16lP6DTjIFn9+idAksSQfdCBVG3aROtjjk6L95aMsDWzOQcdnCBJjJYg2e/hZszGCFV9AXihiXUfp/GGLDjjNNyDc32sD9lGcisXzPs+wjHDiAnHHpv6ni8Nh+k6fTBdpz6RjNns/dLHmO024S52/ns+bU46KdGitAj+Dh1r7eccYsZsKpPs9/CEr5k1mo6qblDVaVGmYLTvz4Eh4d6dgSOBMlyIHsOIC5MnT060CEYLYbpOH0zXqY+vTRvw7XltkNxcMrp2TaBELUtml860O++8iEZ9KhI6MpvRuXNNqB4jNUn2e7gZs+nHTKAL8Itghoh0xDmgejUsbu9+ImLeho2Y8eCDDyZaBKOFMF2nD6br1Ed8Pvz5+TX7Wf36Ij57hUxVfPn5kOmiVWYffFCCpTHiTbLfw+1OlH7MBP4D/EVEbhORq4B5uJi94WGI3iLE6zOAiPQRkXEiMg4vtm5wX0Quibv0RlIT9FqXbqSjo7101XU6YrpOD0JHJbP7p9l37jS7h4sI3/r9AOQdd1yCpTHiTbLfw82YTTNUNQCcjlvfex1wH7AFGKqqS6Nooh8wwUvBaOnB/d/GXGAjZZj77Vz+deS/mPvt3ESL0qLM/XYuuXfnplW/01XX6cqrr76aaBGMFsAX4vgoq3+/BErSwsydC7m5bpsuzJ3LaUu/pu/oGyi48MJES2PEmWS/h5sxm4aoarGqXq6qHVW1taoer6ofRyjXV1X7huXNU1WpJx3fUn0wkgtV5ea5N1Mxs4Jb5t6SNiOVNf0OpE+/01XX6Uww/qCRwqjiX7OmZje7f5o4f1KFm2+Gigq45Zb0GKH1+nxZeTm5TzyRFt6b051kv4ebMWsYRtyZvWw2n6z/BE6Bj9d/zOvLXk+0SC1CTb9Jn36nq67TmWRfb2VEwezZ+IuKanaz1q5NoDAtyOzZ8Im7h/Pxx/B6GtzPvD4/COnT5zQn2e/hZswahhFXVJXx88YjCHwGgjB+3viUH7Gr1W/So9/pqut0Z8qUKYkWwYgnqjB+PP7qQM1+1uOPp/4opddvgiOTIm4/lfsd0ucpkB59NpL+Hm7GrGEYcSU4Uqco9ABF02LErla/SY9+p6uu050jjjgi0SIY8cQbqWtbUkKgspL2xUX4Pvkk9UfsgqOyQUNONfVHKkP6fASkR5+NpL+HZyRaACPtyQJYvnx5ouUw4oCqMmbmGNjsZWwGWrmfY6aPoc95fVJyPU6dfoeQqv1OV10b8PXXX9OxY8dEi2HEA1UYM8b9Li/nvW9XcDTOayRjxkCfPntGLlOJ0H6Hk6r9Duvz10DNVZ2qfTaAfe8eHmITZEVTXmz6l5FIvHA+zyRaDsMwDMMwDMMw9hnOVtV/NFTIRmaNRPONtz0P9yHQSF32A14BzgZWJFgWI76YrtMH03X6YLpOH0zX6cO+qOssoBfwbjSFzZg1Ek2pt/1aVZckVBIjroRMMV1huk5tTNfpg+k6fTBdpw+m6/RhH9b1Z9EWNAdQhmEYhmEYhmEYRtJhxqxhGIZhGIZhGIaRdJgxaxiGYRiGYRiGYSQdZswaiWYzcAcRg5gYKYbpOn0wXacPpuv0wXSdPpiu04ek17WF5jEMwzAMwzAMwzCSDhuZNQzDMAzDMAzDMJIOM2YNwzAMwzAMwzCMpMOMWcMwDMMwDMMwDCPpMGPWMAzDMAzDMAzDSDrMmDUMwzAMwzAMwzCSDjNmDcMwDMMwDMMwjKTDjFkjIYhItojcKyLfi8guEflQRE5KtFxGbUTkxyIySUSWiMhOEVktIjNE5IAIZQ8WkTkiUioiRSLyVxHpFKGcT0RuEpHvRKRcRL4QkYvqOX9UbRrxQURuFREVkcURjv1ERBaISJmIbBCRh0UkL0K5qK/1aNs0YoOIDBGRf3jXVpmILBaR68LKmJ6THBEZICLPi8ha72/+tYjcJiKtwsqZrpMIEckTkTu8Z2SRd68eXk/ZhD2fG9OmEZlodO39nYd79/Q14t7ZFovIOBHJqafd34rIV55elonItfWU6yHu3W+biJSIyCsi0r85bcYUVbVkqcUT8BxQCdwHXAG87+0fnWjZLNXS00xgPfAwcDkwDtgAlAKHhpTriQu4vRy4DhgLFAGfA1lhbd4DKPAk8DvgNW//wrByUbdpKS667wns9HS9OOzYIGAX8CkwArgLKAfeiNBOVNd6Y9q0FBP9ngxUAP8Brveuxf8B/mR6Tp0E9AKKgZXAzZ5u/uLdc18xXSdvAvp6elwFvOP9Hh6hXEKfz9G2aal5ugbyvPwPgFu9v/VUIODVkbDyV3rlZ3pln/H2x0Ro9xtgI3AT7nmxGlgDdGhKmzH/+yRaQZbSLwFHeP/co0Pycryb4vuJls9SLV39JMKDaYD3QvJsSN6jQBnQOyTvRE/PV4Tk9QB2A5NC8gSY790Y/Y1t01LcdP888BYwj7rG7OvA90B+SN7lnm5ODsmL+lqPtk1LMdFtPu6j1MuAby/lTM9JnnBGhgIDw/Kf9vILTNfJmYBsoKv3+3DqN2YT9nxuTJuWmqdrIAv4SYS6t3nlTwzJywW2AK+FlX0W9wG7ICTvJq/+j0PyDgKqgIlNaTPWyaYZG4ngPNyXoieDGapaDkwBjhKRXokSzKiNqr6vqrvD8pYBS4CDQ7J/ibuBrQ4pNxf3Na8wpNzZQCbuQRgsp8BjuC+9RzWhTSPGiMixuOt0VIRj+cBJuI8ZJSGHnsE9sEJ1E9W13sg2jebzK6ALcKuqVotIaxGp9T5gek4Z8r3txrD89UA1sNt0nZyoaoWqboiiaCKfz41p06iHaHStqrtV9f0Ih2Z529B3tp8BHQjRi8dkoDVwRkjeecBHqvpRyLm+xn3sDtV1Y9qMKWbMGolgMPBN2AMOYKG3HdSy4hiNQUQE9yK8xdvvAXQGPo5QfCFO30EG46aufhWhXPB4Y9s0YoiI+IFHgP9T1UURivwAyCBMN95Hj8+pq+9orvXGtGk0nxOBEqCHiCzFGRclIvJYyNoq03NqMM/bThGRQSLSS0QuAEYCD6vqTkzXKcs+8HyOqk0jrnT1tltC8oJ/93AdfoL7yBXUtQ/4YYRy4HS4n4i0aUyb8cCMWSMRdMN9FQ4nmNe9BWUxGs+vcVOHXvD2u3nb+nTaXkSyQ8pu9L7MhpeDPbpvTJtGbBkB9AH+WM/xhnTTPaxsNNd6Y9o0ms8AnKHxCvAmbpRlKk73f/HKmJ5TAFWdg7uWTwI+w611ex54RFWv94qZrlOXRD+fo23TiB834T5evhGS1w0IqOqm0ILex6at7NFLe9wU52iv+WjajDkZ8WrYMPZCLs7xSDjlIceNfRAROQg3ZeQD3Jor2KOvhnRaQfS6b0ybRowQkQ7AncAEVd1cT7GGdJMbVjYW+rZ7QmzJA1oBj6tq0HvxyyKSBVwpIrdhek4lVuLWKL6Ee6k8AxgrIhtUdRKm61Qm0c9ne99LICIyFjcT5ypV3RZyKBe3ljkSoddntLpuTJsxx4xZIxHswn3pCScn5LixjyEiXYHZwHbgPFUNeIeC+opGp9HqvjFtGrHjLpxHykf2UqYh3ewKKxsLfZuuY0vw7/lcWP50nDfKo3DOXcD0nNSIyIW49a0HqOpaL/tlb/rgvSLyHHZNpzKJfj7b+16C8JYT3AVMUdXHwg7vwjmMikTo9dlYXUfTZsyxacZGIljPnmkqoQTzvm9BWYwoEJG2uCkq7YBTVTVUR8GpJvXptEhVK0LKdvXW3YaXgz26b0ybRgwQkQG4MBsPA91FpK+I9MU9hDK9/fY0rJvw/41orvXGtGk0n+DfM9wpUHB6WAGm51ThKuCzEEM2yD9wo/ODMV2nMol+PkfbphFDvLjPz+AGIEZEKLIe8ItI57B6WTgnTkG9FOFGZaO95qNpM+aYMWskgs+BAzxvh6EcGXLc2EfwHMK8ChwAnKmqX4YeV9V1uHhzh0eofgS19fk57gXq4LBytXTfyDaN2NAD90x4GPguJB2J0/13OBf/i3Eu+WvpxntgDaKuvqO51hvTptF8PvG2PcLyg2uaNmN6ThW6AP4I+ZneNgPTdcqyDzyfo2rTiB0iciTOg/HHQKGqVkUo9rm3Ddfh4bj3gM8BVLUaWBShHDgdfquqOxrTZjwwY9ZIBDNxD9crghmes4DLgA9VdU2iBDNq43m2fQE37fB8Vf2gnqIvAWeGhlUSkRNwRtCLIeVeASpxowXBcoL7crgOCHUrH22bRmxYDJwbIS3BOY05FzddaTswF7g4xIshwCW4tZihuonqWm9km0bzmeFtfxuWfznOAJlnek4ZvgEGi8gBYfkX4TyMfmG6TnkS+XxuTJtGMxGRg3GjsStxgw/1Te19GzfqOjIsfyRuicnskLyZwI9FpMZIFZEDgaHU1nVj2owt8Qpga8nS3hLuZaoS+BPuofiet39somWzVEtPD+GCZf8DuDg8hZTrhXP7vhy4FrjFu6l9AWSHtfknr80ncC/Pr3n7vworF3WbluL6PzAPWByWNwTn0OFT3EvJXbj1MG9GqB/Vtd6YNi3FRK9TvOvuBdyL5gxvf6LpOXUScCzuA8VGnFfjq4DXPV0/ZbpO7gRcA4zDxfZUnJE5zkttvTIJfT5H26al5ukaaIP78BwAxlD3ne2osPau8tp50dPL097+2LBybTw9bwRuxMWfX437GNGpKW3G/G+TaOVYSs+EW4d3H26OfTkuXtUpiZbLUh09zfNuRBFTWNmBuDAfO4Fi4FmgS4Q2fd6DbyVuLcZi4Nf1nD+qNi3F/X9gcYT8o3Evsbtway0nAW0ilIv6Wo+2TUsx0WsmcLt3He4GlgGjTM+pl3BTP1/3dLMbWAqMBTJM18mdvOu3vmd035ByCXs+N6ZNS03XtZfqfV8DpkVo83fA155eluMMVYlQrifOQN0O7MAtPdu/HjmjajOWSbwTG4ZhGIZhGIZhGEbSYGtmDcMwDMMwDMMwjKTDjFnDMAzDMAzDMAwj6TBj1jAMwzAMwzAMw0g6zJg1DMMwDMMwDMMwkg4zZg3DMAzDMAzDMIykw4xZwzAMwzAMwzAMI+kwY9YwDMMwDMMwDMNIOsyYNQzDMAzDMAzDMJIOM2YNwzAMwzAMwzCMpMOMWcMwDMMwDMMwDCPpMGPWMAzDMAzDMAzDSDrMmDUMwzAMwzAMwzCSDjNmDcMwDMMwDMMwjKTDjFnDMAzDMAzDMAwj6fj/fXkh/Y5u3LQAAAAASUVORK5CYII=\n", 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", 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\n", 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", 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\n", + "image/png": 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lpdKvjyK//PILbt26hS1btuB///sfevfujaSkJBw7dgyZmZnYsmWLVlr7vL298euvvyos3gFp1/AnT55gx44dOHPmDPr06YNatWohISEBYWFhuH37NlauXMkNFmZkZITZs2fDz88Pbdu2xfDhwyESiXD58mU4OzvD2dlZ5Rh1/Vpt3boVjx8/xvfff49z586hbdu2iIyMxKlTpyAQCPB///d/GuvmTAgh5APtzQJECCGEZcueZ7Y0+/btY1u3bs2am5uz1atXZz08PNinT59y835ev3692DYhISHs119/zTo7O7NGRkaso6Mj26NHD3bnzp3F1o2MjGS/++47tmHDhqyJiQlraWnJNmnShB03bhx78uRJlc/1m2++4ebefPDggdrOCwrmmWVZln3z5g3r6enJ2trasqampmyHDh3Yv//+u9R5TjMyMtiVK1ey7dq1Y6tVq8aampqyrq6u7KBBg9idO3eyWVlZLMtK55719fVle/fuzTo7O7PGxsZsjRo12J49e7KHDx+Wm+u0NGXNuZqamsr+9NNPbMOGDVljY2PW2tqa/fTTT9mLFy+qvK/SFJ1ntqgLFy5wuSs6zyzLsqxEImH/+OMPtk+fPqytrS1rZGTEOjs7s127dmVXrlzJvnnzptj6q1evZuvXr88aGRmxLi4u7I8//shmZ2eXOs9s0TlhC1Pna6UohrIkJCSwM2bMYOvUqcMaGRlx79379++rtB9CCCHlw7Asy+qghiaEEEIIIYQQQsqN7pklhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3qJglhBBCCCGEEKJ3DHUdAOG3tLQ03LhxAy4uLjAxMdF1OIQQQgghhBAdycvLQ0xMDHr27AkbG5sy16dilujUjRs34OHhoeswCCGEEEIIIZXEqVOnMGzYsDLXo2KW6JSLiwsA6Ru2YcOGOo6GaNqiRYuwatUqXYdBtIByzR98znVmchIenT8N19btULdlG12Ho3F8zjXfUK75o7LlOjw8HB4eHlyNUBaGZVlWwzERUqJnz57Bzc0NISEhaNGiha7DIRqWkpICOzs7XYdBtIByzR98zvWNg3vx4MwJWFZ3wORt+3QdjsbxOdd8Q7nmj8qWa1VrAxoAihCiNXv27NF1CERLKNf8wedc52ZkfPg3XceRaAefc803lGv+0PdcUzFLCNGaTp066ToEoiWUa/7gc65F+XnSfwvyIRGLdRyN5vE513xDueYPfc81FbOEEK3Jzc3VdQhES7SZa5Zl8eDMCTw894/Wjkk+4vN1LSrI5/5fkCfUYSTawedc8w3lmj/0Pdc0ABQhRGsiIiJ0HQLREm3mOiEyAjcO7gUA1G7uBqd6DbR2bMLv61qU/7GYzRfmwsS8mg6j0Tw+55pvKNf8oe+5pmKWEKI1NA0Tf2gz19lpqdz/MxLfUzGrZXy+rgsXswXCqt8yy+dc8426ci2RSPD+/Xvk5eVBIpGoZZ9EvXr16oXXr19r9BgMw8DIyAhWVlawtLQEwzBq2zd1MyaEaI2fn5+uQyBaos1cy+5bBIDczAytHZdI8fm6lmuZ1fOuesrgc675Rh25lkgkePPmDdLS0pCfnw+aQKVy0vSXDCzLQiQSITMzE7GxsXjz5g1EIpHa9k8ts4QQrdmxY4euQyBaos1cF+QVLmYztXZcIsXn67rwFykFwqpfzPI513yjjly/f/8eubm5sLOzg6Ojo1pb44j+EYlESEhIQHp6OlJTU+Hg4KCW/ep9yyzDMPDx8eF+9vf3B8MwiIqKUnlfAQEBYBgGAQEB3LJevXrBzc2tzG2joqLAMAz8/f25ZT4+PsUuXFdXV3h7e6scG/koX5jLi+5cVdGQIUN0HQLREm3munDrGLXMah+fr2txQQH3/3wefC7xOdd8o45c5+XlQSAQUCFbyYWFhWnlOIaGhqhZsyYEAgGysrLUtt9KWczKCtKSHvfu3dN1iGrz/Plz+Pj4lKv45qPcrEzsnj4Bu76bQH+06qEzZ87oOgSiJdrMdeHWMSG1zGodn69rvrXM8jnXfKOOXEskEggEAipkK7lGjRpp7VgMw0AgEKi1y3mlLGZlli9fjgMHDhR7NGzYsMRtvv76a+Tm5qJu3boqH69Hjx7Izc1Fjx49VN62bt26yM3Nxddff13qeqGhodi9ezf38/Pnz+Hr60vFrJLeR4RBmJ0FYVYm3r16oetwiIqmTp2q6xCIlmgz1/Its+laOy6R4vN1LT+acdVvmVU21xlJiTi2fBHu/n1EwxERTVHXdU2FbOUXHR2t1eOp+z1Rqe+ZHThwIDp06KDSNgKBAAKBoFzHMzAwgKmpabm2ZRhGqW1NTEzKtX8iVXgev6yUFB1GQspjyZIlug6BaIk2cy13z2wWtcxqG5+va76NZqxsrm8c3IuYZ08R8+wp2g4YAtNqFhqOjKgbn69rvqlZs6auQ6iQSt0yWx6K7pmVSCTw8fGBs7MzzM3N0bt3bzx//rzY/auK7pmVefjwIdzd3WFmZoZ69eoVuzFe0T2zihQ+pr+/P0aPHg0A6N27N9eNOiAgAF5eXrC3t0dBoftxZPr164cmTZoo9XpUNaJCf7RmpSbrMBJSHqdOndJ1CERLtJlr+W7GdPuBtvH1umZZFqKCwsVs1e9mrGyu37/+eA9eZlKihqIhmsTX65qP0tLSdB1ChVTqYjY9PR1JSUlyj+Rk1QuYhQsXwtfXFx06dMC6devQqFEj9O/fH9nZ2Uptn5qaikGDBqF9+/ZYu3YtateujWnTpmHv3r0qx1JYjx49MGvWLADAokWLuG7UzZo1w9dff43k5GRcvHhRbpv4+Hhcu3YN48aNq9Cx9VXhFhhqmdU/DRrQ/J98oc1cy0/NQy2z2sbX61pc5Mvm/Lyq3zKrbK7Nray5/6cnvNdUOESD+Hpd85G+9xqt1MXsp59+CgcHB7lHrVq1VNrH+/fvsXHjRnh4eOD06dP47rvvsGvXLkyaNAlJSUlK7ePdu3eYP38+fv/9d8ycORNXr15FmzZtsHDhQoUtp8qqX78+unfvDgD47LPPMG7cOIwbNw5OTk7o06cPateujYMHD8ptc+TIEUgkknIXs//73/8wY8YMtGjRAtWqVUOdOnXg6emJV69elbltaQNzxcfHlyseVcl1M6aWWb1jZmam6xCIlmgz14W7egqzsyCRiLV2bMLf67rw+w7gR8ussrk2K1TMZiRSMauP+Hpd85GBQfnKQYlEgu3bt6NNmzYwMzND9erV0adPHzx58kTNEZauUt8zu3XrVjRu3Fhumar3w169ehUikQjTp0+XWz5z5ky5KX1KY2hoiClTpnA/GxsbY8qUKZg2bRoePnyITz75RKWYlGFgYICvvvoKv/32GzIzM2FpaQkAOHToENzd3VGvXr1y7XfNmjW4ffs2Ro8ejVatWiE+Ph5btmxBu3btcO/ePaWmIVq+fHmx49vY2JQrHlUVbpnNTqFiVt8EBQWhZ8+eug6DaIE2c1349wJYFsKsLLmWIaJZfL2uC/cIAPhxz6yyuTYy/tjSQy2z+omv1zUfZWdnc3WGKiZOnIhDhw5h/PjxmDFjBrKzs/H48WMkJCRoIMqSVepitlOnTioPAFWUbISuoiMg29nZwdbWVql9ODs7o1q1anLLZEV2VFSURopZABg/fjzWrFmDkydPYvz48QgNDcXDhw8rNJH1999/j8OHD8PY2JhbNmbMGLRs2RK//PJLsZZgRcozMJe6FG6ZzUylbsb65ptvvtF1CERLtJnrokVFbmYGFbNaxNfrumjLbD4PWmaVzXVBoWsyPVG7f9gS9eDrda2vhEIhjI2Ny9XKam9vr/I2x44dw/79+3HixAkMHz5c5e3VqVJ3M+a75s2bo3379lyBefDgQRgbG8PT07Pc+3R3d5crZAHp/FItWrTAixfKT3WTmZkJsVj7XfkKF7PCzAyIKtDNm2jf3LlzdR0C0RJt5rpoMUtzzWoXX6/rwoM/AfxomVU216JCn9UZCdq5DYmoF1+va2X5+PiAYRiEh4fD29sbNjY2sLa2xoQJE5CTk1Ns/YMHD6J9+/YwMzODnZ0dvvjiC8TExMitU3RgWplevXqhV69e3M+yAWuPHj2Kn3/+GbVq1YK5uTkyMqQDIP7111/csezt7TFu3DjExsbK7dPb2xsWFhaIjY3FoEGDYGFhAQcHB8ybN0+pv+83btyITp06Yfjw4ZBIJEqPQ6QJVb6Ylc03Gx4eLrc8OTkZqampSu3j3bt3xZIku8fU1dW1QvGVNdfS+PHjce3aNcTFxeHw4cMYPHiw0i3KymJZFu/fv1f6m5nevXvDysoK5ubmGDp0KMLCwsreSE0Kj2YMANl036xe2b9/v65DIFqizVwXFGkhy6URjbWKr9d18ZbZql/MKpvrAqF8yyzLspoKiWgIX69rVXl6eiIzMxOrV6+Gp6cn/P394evrK7fOypUrMX78eDRq1AgbN27EnDlzcPXqVfTo0aNCIwn7+fnh3LlzmDdvHlatWgVjY2P4+/vD09MTAoEAq1evxrfffosTJ06gW7duxY4lFovRv39/uLi4YP369ejZsyc2bNiAXbt2lXrcjIwMBAUFoWPHjli0aBGsra1hYWGB+vXr49ixY+U+n/Kq8sVs3759YWhoiO3bt8st37Jli9L7EIlE2LlzJ/dzfn4+du7cCQcHB7Rv375C8cm6L5f0Zh47diwYhsHs2bPx+vVrjYxifOjQIcTGxmLMmDGlrmdubg5vb29s3boVJ0+exE8//YSrV6/C3d292LdLiiQkJODZs2dyj6JfMpSloEgxSyMa65chQ4boOgSiJdrMddEvuXKzqJjVJr5e18XvmdWPbsYp794io5xdf5XNdeFeVPm5ORBmZ5XreER3+Hpdq6pt27b4+++/MW3aNOzevRvDhw/Hnj17uOejo6OxbNkyrFixAkePHsW0adOwdOlSXL9+HW/fvsW2bdvKfWyhUIg7d+5g7ty5WLBgAYyMjDB//ny4ubnh5s2bmDNnDlavXo2//voLUVFR2LRpU7Htx4wZgwULFmDq1Kk4fvw42rZtKxe/IhEREWBZFkePHsXevXuxdu1aHDp0CA4ODvjiiy9w4cKFcp9TeVTqYvb8+fM4ePBgscfr16+V3oeTkxNmz56NkydPYujQodi2bRumTJmCPXv2wN7evsyWUUB6z+yaNWswa9YsbNmyBX379sV///2HlStXwsjIqCKniDZt2kAgEGDNmjXYv38/jh49KnfjtIODAwYMGIC//voLNjY2GDx4cIWOV9TLly/x3XffoUuXLvDy8ip1XU9PT+zbtw/jx4+Hh4cH/Pz8cPHiRSQnJ2PlypVlHmvbtm1wc3OTe3h4eAAAAgMDcePGDaxbtw4pKSlcLLJfpnPnzkV4eDgiioy6nBz/jut2LVt30aJFCA4OxuHDh3H48GEEBwdj0aJFcut4enoiJycHfn5+CAoKwsmTJ7F3716Eh4dzXWtk63p5eSElJQXr1q3DjRs3cOHCBWzduhWxsbGYOnWq3LpTp05FbGwstm7digsXLih1Tnv37sXJkycRFBQEPz8/5OTkVNlzOnPmTJU7p6qYJ3Wc0/Dhw7V2TkVbyB7cvUt50uI51apVq8qdkzJ5WrRggdz7LjkhodKf08v/HmHf3Kn4vzmTceXCeZXz9Oeffyp1Tu/j4uRem2kTJ9D1pGfntGTJkgqfU2BgIABpQZefn4+EhASkp6fj4u4tOLD4exz1mY/9C+bgT98F8J8/G3/6LsAfC+fiyLKfcPDnH3Do53k4vPQnHFj0PY76LIB/0XUXzcWRpT/h4M/zcPDneTiy9Cf8sWiu3Dr+C+bgqM8CHFj0PQ4v/QmHfp6Hgz//gCPLfsIfC6Xrnvx1LQAgMjISIpEI8fHxyMzMRHp6OhISEpCfn8+NwSPrjShrhPL09ER6ejoyMzMRHx8Pd3d3JCcnIyMjA2FhYThx4gQkEgmGDRuG0NBQhIeHc/tq1KgR/v33X7n9ZmdnIycnB8nJyUhOTkZOTg7yPnxhK1tH1mV4xIgRkEgkSE1NRVJSEm7fvo2EhARMnz6da2SKjIxE//790bBhQ5w5c4Y7J4lEwr3fZKKjo+Hu7o6IiAi5cxKJRIiMjORiyMqSfjmVnJyM/fv344svvsCwYcNw8OBBVK9eHT///LNcvG/fvpU7J5FIhODg4BLfe7LnlMWwlbDvh7+/PyZMmFDi8/v27eP6lDMMg2XLlnEjE8u2jYyM5LoAi8Vi+Pr6Yvfu3UhPT0eXLl2wdetWdOvWDaNHj+ZabQMCAtC7d29cv36d65veq1cvJCUlYf/+/Zg5cyYeP34MJycn/Pjjj/juu++4mKKiolCvXj252Hx8fODr6yvXvcbV1RW9evWCv78/t+z//u//sHr1akRHR0MsFssdH5D2fff09MTkyZPlWogrKj4+Hl27dkVBQQHu3bsHZ2fncu2nS5cuSExMLLOVNSEhAYmJ8pOnh4eHw8PDAyEhIWjRokWZx/prxc94E/wf93Ov8d+i/eBh5YqbaN/cuXOLfTNIqiZt5nrX9AnITP74u6Xj0JHo8VXJnyFEvfh6XYc/uI9/1vlxP5tb22DarrIHUdSll3du4txm6R/unktXwaVFK5W2VzbX2yePQ056GvfzkO8XonHnriodi+iWOq5rWeNT/fr15Zb/6bsAb5+HVGjf6lS7uRvGLPtFpW1kf+PHx8fDycmJWy6rQ6KiolC3bl1Mnz69WO/Qwlq1asVNZaOoRgDA1QQBAQHcv71798Yff/yBr7/+mlvv6NGjGDt2LK5evYo+ffrI7WP48OEIDAzk/g739vbGn3/+idzcXMTExMDFxUXuvEorDx88eICOHTuiXr16xRoYJ06ciIMHDyInJweGhorHGS7pfSHz7NkzuLm5KV0bVMrRjL29vRXeAK1I0Rdb0bYCgQDLly/H8uXLuWVpaWlITk5G7dq1uWW9evUqtj/ZGwcA7ty5U2Icrq6uxbb18fEpNv1PVFRUsW0nTZqESZMmlbhv2YBN6uxinJ6ejoEDByItLQ23bt0qdyELAC4uLggNDS1zPUdHRzg6Opb7OIB81yWA5prVN4W/ACJVmzZzXaBgNGOiPXy9rvVxap783I8D0+RkpKu8vbK5Lvpa0PQ8+keT17VjXcVFjK5UJJ6SpgyV1QQSiQQMw+D8+fMK17WwsOD+X1JvUbFYrHDbis4FLNung4ODStvJaobCRbyMo6MjCgoKkJ2dDWtr7cwqUCmLWXXLzc0tlvBff/0VAORaQCur3bt3o379+ujWrZta9icUCjFkyBC8evUKV65cQfPmzSu0v9evX6t8IZSXqMgHZBbNNatXbt68WWyaLFI1aTPXxafmodGMtYmv13XR7u0FeUKwEgmYckyNoS35hUZZLdxyqixlcs1KJMW+eM5IpGJW32jyuu7tPVkj+62MGjRoAJZlUa9ePW5az5LY2toqHEMnOjq6xFbMwmSD3oaGhhZrmQ0NDeWeLyorKwumpqZl7l/G2dkZNWrUKDZCMiAdNNfU1LRc89aWV+X9jatGf/75J3r16oW1a9di27Zt+PLLL+Hr64t+/fqha9fK2+3l6NGjWLRoEc6dO4fZs2crdX9vWcRiMcaMGYO7d+/ir7/+QpcuXRSuFxcXh5cvX6Kg0NQ3RbsIA8C///6Lhw8fYsCAARWOTRlFW2Cyaa5ZvaLukbhJ5aWtXLMsW3wAKGqZ1Sq+XtdFi1mg+GdUZZOX+3GQqvK0zCqTa0WvC7XM6h++XtfqNmLECAgEAoVdd1mWRXLyx0aZBg0a4N69e8gvdA2dPXtWqUFWAaBDhw5wdHTEjh07uPtsAekYRC9evChx3J2SWpdLM2bMGMTExODy5cvcsqSkJPzzzz/o06dPuea7LS9etMy2atUKhoaGWLt2LTIyMrhBoVasWKHr0Eo1duxYWFhY4JtvvsH06dPVss8ffvgBp0+fxpAhQ5CSksLNYSsj68q8cOFC7N+/X+7eY3d3d7Rt2xYdOnSAtbU1Hj16hL1798LFxYUbREDTio1mTN2M9UqtWrV0HQLREm3lWqxgrmkhFbNaxdfrWlygoJgVCmFsWrGuf5ok1824HC2zyuS6aKssQMWsPuLrda1uDRo0wIoVK7Bw4UJERUXBw8MDlpaWiIyMxMmTJzF58mTMmzcPgPS2w+PHj2PAgAHw9PREREQEDh48iAYNGih1LCMjI6xZswYTJkxAz549MXbsWLx//x6bN2+Gq6triXMHy25nVMXChQtx7NgxjBw5Et9//z2sra2xY8cOFBQUYNWqVSrvryJ4Ucy2a9cOV65c0XUYKtPE2Fz//fcfAODMmTM4c+ZMsedLuy93zJgxOHfuHC5duoScnBzUrFkT3377LZYtW6aw37wmFL0PJyslBSzLqqXVmg9YloUoPw9GJsp3J1GnixcvolOnTjo5NtEubeVaUUsYtcxqF1+va0UtkPnCXFRD5W3Rki9mVW+ZVSbXhYtZc2sb5KSnITUuFqL8fBiW449moht8va41YcGCBWjcuDE2bdrEzUHr4uKCfv36YejQodx6/fv3x4YNG7i5aDt06ICzZ8/ihx9+UPpY3t7eMDc3xy+//IL58+ejWrVqGD58ONasWQMbGxuF26Snp3NThSrLyckJgYGBmDdvHjZt2oSCggJ06dIFBw8eROvWrVXaV0VVytGMCX+oOmLZpi+HQSIWQ2BoCLFIBAD4bu9RmFazKGNLAgAXd2zG85vX8Pmc+WjUyV3rx8/JyYG5ubnWj0u0T1u5zkxJwq5p3gAAMytr5Gakg2EMMPfwqUp972JVwtfr+vafB3DvxJ9yy75e8xscXSvX4DaFndm4Gq/u3wYA1GraHF/4rlVpe2VynfQmCvt/nAEAaNTJHWFB0sEzv1q5ETUaln7PIKk81HFdlzVqLakcShpgSlPUPZoxfdITvSEWFUAiFgMA7Ou4csuTYqJ1FJH+eXUvEBKxGM9vXtfJ8ZUdpZzoP23luvD9spbV7QEALCuBMDtLK8cn/L2uCxS1zBZq+ayM8irYMqtMrgvfDlSr6cc/RBOiXitanVRSfL2u+UjRTCv6hIrZSuDYsWOws7PjJiFW1ieffIKffvpJQ1FVPgXCQh+QTT6OwJwQGaGLcPSOWCRC/ofBPxKidPOaHTt2TCfHVYfE6EgcXvwDHl88q+tQ9IK2cl24q6e9y8eRGpNj3mjl+ES/r+uKKOme2cpMfmqeNJW3VybXhbsZO9R1hdGHe4jfR5Y+Fz2pXPh6XfORsvfkVlZ6XczeuXMHPj4+Coex1hdisRjLli3DzJkz5eaaUsb8+fOxdetWxMfHayi6yqUg/+MHpF0tF5haSIf9pmJWOXmFWqoyEhOQm6X96UuGDBmi9WOqy5MrFxAXHoo7fx4se2WitVzLtQIV/pJLR1/Y8JE+X9cVofie2cpezH4czTgvOxtiUfEB1EqjTK4LF7PGpmZwdK0HgFpm9Q1fr2s+CgsL03UIFaL3xayvr69eF7NnzpxBaGgoJk9Wfc6tYcOGwcrKCtu2bdNAZJVP4ZZZI1NTONaTfpP0nopZpRQtXnXxJYCiQcf0RU56KgBAmJ2lcLROIk9buS5cUNjWdIaZpRUA+r2gTfp8XVeE7L1nUOheswJhbkmrVwp5RbpBqzo9jzK5Ltw6bWRqCkdX6Wd1UnQUd6sQqfz4el3zUaNGjXQdQoXodTGrColEAmEl/MZ037596Nq1a7mGQDcwMMCoUaPwxx9/aGTk48qmcAFhZGICpw/FbPLbN5V+br/KQFikG7suilltTeGkCYVHyM1OTdVhJPpBW7kWFbr2DU1MuC+5qBVIe/T5uq4I2XtP9gUKoActsznZcj/nZqg28rcyuS7cW8LI5OMXz6KCfKTEKjdfJtE9vl7XfPT27Vtdh1AhelvM+vj44McffwQA1KtXDwzDgGEY7iZmhmEwY8YMHDp0CC1atICJiQkuXLgAAFi/fj3c3d1RvXp1mJmZoX379jh+/LjC4xw8eBCdOnWCubk5bG1t0aNHD1y6dElunfPnz6N79+6oVq0aLC0tMXjwYDx79qzMcxAKhbhw4QI+/fTTch/7s88+Q3R0NDflTlUmKuEDkpVIkPQmSkdR6Q9hkZZZXbRcjR07VuvHVBdh5sfXj+Y3Lpu2ci1XzBp/LGbpSy7t0efruiJkLbNmVtbcssrcMstKJHLdjAHV55pVJteFv3g2NDGRG92ZekzoD3Vd13xobNF3dnZ2Wj2eut8TelvMjhgxgrvQNm3ahAMHDuDAgQNwcHDg1rl27Rrmzp2LMWPGcBMGA8DmzZvRtm1bLF++HKtWrYKhoSFGjx6Nc+fOyR3D19cXX3/9NYyMjLB8+XL4+vrCxcUF165d49Y5cOAABg8eDAsLC6xZswZLlizB8+fP0a1btzJHB3v48CHy8/PRrl27Ys8pc2wAaN++PQDg9u3bSr92+qroB6SsZRag+2aVUbSY1UXLVXBwsNaPqS5yLbNp1DJbFm3lWq4VyPjjH86sRILkNzTSuTbo83VdEaIPA0CZVrMAw0j/nKrMtyAoajVWtZuxMrku2s24eu06EBgaAqAeE/pEHde1gYEBxGIxFbSVXG6u9r6EY1kWYrEYDMOobZ+GatuTlrVq1Qrt2rXDkSNH4OHhwRWqhYWGhiI4OBjNmzeXW/7q1SuYmZlxP8+YMQPt2rXDxo0bMXjwYABAeHg4li9fjuHDh+P48eMwKDRfoeyizMrKwqxZszBp0iTs2rWLe97LywtNmjTBqlWr5JYX9fLlSwDSluXClDm2TK1atWBsbIznz5+XeJyqQr6bsSlsnGrC2MwM+bm59G2vEop2M06Ni0V+bg6Mzfg3P6SqWJZFbuGW2ZQUHUZDCit8z6yhsbHcl1zvIyNoXkuiMbL3nqGxMYzNzJCXk438Stwyq2jaIFVbZpXBfcHEMDA0MgbDMHCoWw/xEWGICXmi9uORysvExAS5ublISEiAo6OjWgsYon9EIhESEhIgFotha2urtv3qbTGrjJ49exYrZAHIFbKpqakQi8Xo3r07jhw5wi0/deoUJBIJli5dKldMAuAuxsuXLyMtLQ1jx45FUlIS97xAIEDnzp1x/Xrpc3kmJ0u7KhZNqDLHLszW1lbu+FVV0W7GjIEBHF0b4O2LELx/TUP+l0WYXWT0YpZFQnQkajcte0JqdWnZsqXWjqVO+bm5kIhF3M/ZaVTMlkVbuS56z2w1G1vuSy4a0Vg79PW6rqjCxayRqSnycrIr9dQ8CotZFVtmlcm17ItnY1NT7m+W+u07IT4iDIlvopAUEy03jRapnNRxXTs5OSEvLw8pKSlIT0+HQCCggrYSEolESC/HvNPKYlkWEokEIpH07yjZ7ZPqorfdjJVRtMVT5uzZs/jkk09gamoKOzs7ODg4YPv27XKJjIiIgIGBgcJiWEY2lHWfPn3g4OAg97h06RISEhKUirNoa6syxy66PR9+OcgPKmECAHBqIB2BLTEqEpkpVb+grwhZN2NZdzgAiH1R9r3d6lT4CyN9UriLMQBkp1IxWxZt5Vq+ZdYEjIEBHOpKuxrT7Qfaoa/XdUXJvkgxNDbh5lKtzANA5eVUvGVWmVzLilkjE1NuWdOuPbn/v7x9U6VjEt1Qx3VtYGCAOnXqwMbGBsbGxrz4W1UfvXjxQqP7ZxgGhoaGsLS0RK1atVCnTh0YGqqvPbVKt8wWboGVuXXrFoYOHYoePXpg27ZtqFmzJoyMjLBv3z4cPnxYpf1LJBIA0vtma9SoUez5shJVvXp1ANLW4dq1a6t07MLS0tJgb29f7u31RdEREgGgaZfueHj2JFhWgmcBV/HJiDG6Cq/Sk3UztnJ0hMDQCCmxMXh55yY6D/fUWgyrVq3S2rHUSVikmM2iYrZM2sq17PcCwxhw9+XVaNAQsS+f4f3rCKQnvIe1o5NWYuErfb2uK0pUIJ2jVWBkBGNT6WdSZR4ASlHLbK6KLbPK5FrWOl24mLWt4YwaDRsjPvwVXt65ga5jxlFhU8mp67o2MDBAzZo11bIvohn169cve6VKTK9bZsvzi/Dvv/+GqakpLl68iIkTJ2LgwIEKRxNu0KABJBJJqfeiNmggvTfL0dERn376abFHr169So2ladOmAIDIyEiVjy0TGxuL/Px8NGvWrMx19Z3cPbOmH1tmHeq4AgBCAi6D/fAFAylO1jJrZmGJ5t17AwCS3kRpdUAOfZ2EvVjLLA0AVSZt5fpj69jHb/2b9+gLAGBZCR5fOK2VOPhMX6/rivrYzdgExh9aZivz74bCxWw1W+nopap2M1Ym17IvmGQ9qGSafWidTX8fj/jwVyodl2gfX69rPtL3XOt1MVutWjUA0pZJZcn664sLTdwdFRWFU6dOya3n4eEBAwMDLF++nGuBlZF1C+7fvz+srKywatUqFHz4hrawxMTEUmNp3749jI2N8eDBA5WPLfPw4UMAgLu7e6nHqgpkxSxjYAADgbQFhmEYuPXpB0D6ARnznJ+jaipDVsyaWljKdfl6ERigtRj0dRL2osUsTc1TNm3lmitmC/3h7OhaH3XcWgEAgq9dUti9kqiPvl7XFVX4i5QajZoAkHZtT3sfr8uwSpRXqJi1cZK2lOWoeJ+cMrmWfVYbmprKLW/cpTt3m8uTy+dVOi7RPr5e13yk77nW62JWNi3N4sWLceDAARw9ehTZ2dmlbjN48GDk5ORgwIAB2LFjB5YvX47OnTujYcOGcus1bNgQixcvxsmTJ9G9e3ds2LABW7ZsgZeXFzeRtJWVFbZv345bt26hXbt2WLlyJXbt2oWff/4Zbdu2ha+vb6mxmJqaol+/frhy5YrKx5a5fPky6tSpg7Zt2yr1mukzEfdtr6lcq3yz7r0hMDICADy59K9OYtMHsm7GphaWsHZ0Qq0PAz+9DAyARCIubVO18fTUXpdmdSo8kjEA5GVn0xymZdBWrgsPwlNY+8HDAUgH7wq+dlErsfCVvl7XFcGyLPfeMzI2RvNuvbjnXgSWPvijruTnfOwCbVPjQzGbkabSPpTJtayrdeFuxgBgYWuHBh06AwCe37yGlHdvVTo20S4+Xtd8pe+51utitmPHjvDz88OTJ0/g7e2NsWPHltka2qdPH+zZswfx8fGYM2cOjhw5gjVr1mD48OHF1l2+fDn27t2L3NxcLF68GEuXLkV0dDT69u3LrfPll1/i6tWrqFWrFtatW4fZs2fj6NGjaNOmDSZMmFDmOUycOBH37t1DTEyMyseWSCT4+++/MX78eF7ce8INKlHk214zC0s0/qQbAODV/dt49+ql1mPTBx9bZi0AgOtqnJWagvD/3dNKDP7+/lo5jroVbZkFgOzUytudsDLQVq65Lo3G8l0a67VpD1tn6VgE/zv9N7XOapC+XtcVIRGLgA89pQRGxrCv4wqHD3Mcv7h1vVLOq1m4m7FtDWcA0i+J0+LjlN6HMrkuKPTFc1FdPb8CGAYsK8GdY4eUPi7RPj5e13yl77nW62IWAH7++We8ffuWm5RZNt8sy7LYsmWLwm0mTpyIV69eQSgU4sWLF/D29oaPj4/CD58JEybg0aNHEAqFSElJQUBAQLF7bHv16oULFy4gLS0Nubm5CA8Px759+7iW49IMHToUjRo1UjgfbVnHPn36NNLS0jB9+vQyj1MVlPRHKwC4j/6Ka529vn8X3TtbhEQihjBH2mvB1MISANDEvTv3/1uH/SEWFe8qr24bNmzQ+DE0ITezeFc8GtG4dNrKdeERZQtjDAzQZeQXAKQjtt47cVQr8fCRvl7XFVF0fmMAXOtsatw7xEdUvntC8z58BhiZmKJB+07c8v8uK9+jSZlcfxzNuPhntX0dVzR17wEACL17i6bVq8T4eF3zlb7nWu+LWX0nEAiwfPlybN26FVkfuoEqa82aNZgxYwZvRokraVAJALBxqoEOn0tb1+PDXyEk4EqxdfgsLyeHa0UwrSYtYE3Mq3F/7KfFx2mli3b//v01fgxNEGYWn9aIRjQunbZyreieWZmmXXvCuYl0irNH/56mbo0aoq/XdUUUnRIKkL7fZL8j7p/8q9K1zspaZo3NzWFfxxUuzaXziIZcv6T0/LjK5Jobzdi0eMssALh7fgUDgQAAcH7rRrnXklQefLyu+Urfc03FbCUwZswYpKSkwOJD909l3b17F2vXrtVQVJVPSYNKyHTyGA2LDyM0XvPfiaSYaK3FVtnJuhgDH7sZA0DrfoNgW1Pa3ezu8SPISFRubuTyio2N1ej+NUXWzVh2nxkAZKdRMVsabeW6oIR7ZgHpAHF9vCcDDAOJWITzWzbQH84aoK/XdUWICt0zL3vvWdhVR+NPugIAIh7cw3+XzukktpLk5UrvZTU2MwcAtB0gHcE0Lztb6YEAlcl1ad2MAWkX587DpdPoJb99g8Cj+5U6NtEuPl7XfKXvuaZilugNruuSgm7GAGBsaob+0+YADANRXh5Ob1xN98l9IF/MWnL/Fxgaoce4b6TrZGfh1Do/pb+hL49UPb3PVFbM2jrX4loUqJtx6bSVa1EpPTYAwKl+Q7Tt/zkAID4iDFf37qh0LWb6Tl+v64oQ5X+8LcPwwy0uANB30nRYVncAANz44/8q1RgOspZZEzPpNEINOnTmYr1/6hhy0tPK3EdZuWZZtlA3Y8XFLAB8MmIMajaUjgD98Nw/eHGrcg6axWd8vK75St9zTcUs0RvcH60ltMwCgGvrdnAf9SUAIPXdWxxf+TNyszJLXJ8vhIW6sBcuZgGgYYfOaDdwKAAgMToSZzev0dhIvT169NDIfjVN9h4yt7KBuY0tAOpmXBZt5ZobzdioeMusTM+vJ8K5sXQu7pDrl3Dn2EEqaNVIX6/ripBvmf34RYqZhSUGz/oRjIEBxCIRTvyyTKtzeZcm/8OXu7KWWQOBAB2HjgAAZCQm4NRavzJ/95eVa1FBPndLS0lfMMmOPXDG91ws57dtQviD+8qdCNEKPl7XfKXvuaZilofy8vIwf/58ODs7w8zMDJ07d8bly5eV2jY2Nhaenp6wsbGBlZUVhg0bhtevtfNBrcy3vYD0G9+GHbsAkN4/e8xnAVLe6XcXiooqqZuxTM+vv0HdVtLpnV4/+h/+8luMnAzV5h9UxtatW9W+T01jWRa5GdKWWTNLS64re2WdS7Ky0FauuWK2lD+cBYZGGPL9Qi539078icu7fodIwfzgRHX6eF1XlKIBoGRqNW2OTyd9B0Dahff4ip8rxRzo3D2zHwpIAGjT/3NuZPu48FCcWLUM2Wklt9KUlevCPXtK++IZAGxr1oLHT0tgaGQMViLBmY2r8Oj8afqiqZLg43XNV/qeaypmecjb2xsbN27EV199hc2bN0MgEGDQoEEIDAwsdbusrCz07t0bN27cwKJFi+Dr64vHjx+jZ8+eSE5O1njcsvtwio5aWhRjYIDP58xHkw8jJibFROPAgln47+I5SMTamU+1silczJoVaZkFpN+Sfz5nPmo3dwMAxL16Cf8fpuPF7Rtq/cNi48aNatuXtuTn5kqn4QBgZmmFGg0aAQDehT5HXHioUvvg4x9n2sp1QQmjGRdlYWsHz2WrYe3oBAAIvnYJhxfNrTStZvps06ZNug5B60orZgGgVd/+6O31LQDpbQp/LV+MO38d1un81HmybsbmH4tZhmHQb+os1HFrBQB4+yIEBxfOQeR/DxXuY1MZ17WsBxVQ9hfPAODSvCU+n7sAAkNDSMRiXPffhdMbViI94X2Z22oVD3+Hl5VrUnXo++9wKmZ5JigoCEePHsXq1auxbt06TJ48GdeuXUPdunXx008/lbrttm3bEBYWhrNnz+Knn37C3LlzcenSJcTFxWllWO+P3YxL/6MVAASGhhg08wd0GDKC2/bq3u3w/2Eagq9dQr4wt4w9VC2FuxmbVFM80JhpNQuMXOTHfUufm5GOf39bh0OLvser+7chFokqFMOV11dg2MwQV17r10jTwqyPc8yaWVqh45CRMBAYAgBu/3mwzO2vvL4Cs5VmenfeFaHNXMu6e5bWpVHGtmYtjPVbD6f60i8kEt9E4cCC2Tj76xrEhYfy8ksHdRgyZIiuQ9A6UUGhYraELu7tBg1Dv6mzpC2PrAR3jx/G3tmT8ej8aW6aHG1S1DILSHsueMxf9nHu8ZRknFi9DCfX+CLmefDH6+LKFQwxNASulHxdy3pQAcpdkwDQoH0njPFdw92/G/6/e9j3/VRc27ezcvSqunIFMDMr9byrHCVyTaoOff8dTsUszxw/fhwCgQCTJ0/mlpmamuKbb77B3bt3ERMTU+q2HTt2RMeOHbllTZs2Rd++fXHs2DGNxg2UPQBUUQYGAvQcNxGjfl4BS3vph2Rq3Dtc2vkbdkwZj7O/rsGzG1eR/DYGEknVbrEVZkuLWSNTMwgMDUtcz9DICAO++x6DZv0IMytrAMD712E4s3E1dkz5Ghd3/IaXd24iMzlJpT/8WZbFgisLIBkrwcIrC/WqaJB1MQYAU0srWDk4otWnAwAA0U8f49H5MyW2tsjOO0+cp3fnXV7azDXLstyXXIpaxxSpZmOLsX7r8MnIsWAMDACWRejdWzi8+Af4fz8NNw/7I+rpY27QL1K2M2fO6DoErSurZVamZe9+GLtiParXrgNAWihe99+FHVPH4/TGVQi+fglJMdEa7zXEsizyc6Rf4hZumZUxMjbBgO++x6eTvuOK3deP/odjvguxd85kBPzxf3i9fCmOGBsBCxeW2FKpSjfjwmo2bIJxv/yKZh/m6hUXFODxhTPYN3cKDi2ai/snj+FNyFPtfwnAssCCBUBeXqnnXaV8OOczEgl/zpnn9P13eMl/1ZIq6fHjx2jcuDGsrKzklnfqJJ1A/b///oOLi0ux7SQSCZ4+fYqJEycWe65Tp064dOkSMjMzYWlZvAurOohFBdyHvTJdlwqr27INJm7aiadXLyDon+PITk1BgTAXoXdvIfTuLQDSb9bt69RF9dp1YGFXHdVs7WBhYwdTCwsYm5nDyNQURqamMDY1g5GJKRgDAzAMo/bz1BRZN2NF98sWxTAMmnXtCdfW7fD4/Gk8Pn8GwuwsCLMyEXL9EkKuXwIg/Xa/em0XVK9dB5bV7WFubYtq1jYws7KC0YfXyfjD63Yp+ioexj0ETgIPhj/Av2H/YnDjwRo9Z3UpXNSYWUqvm09GjEHI9csQ5efhuv9O3Drij+q16qB6rdqwq+UCKwdHmFpY4kHKf4iOegFrA1O8iHmKMyGnMLjZ5zAQGOrV+0cV58LOaS3X4kL3vJbVzbgwgaEhunp+habuPXD/1DG8DLwBlpUg5d1bpPxzHP/75zgAoJqtHexd6sLOuTaq2dhyD5Nq1WBkYvrhfW4CY1MzGJqYVNmclsXLywv79/NrepWSBoBSxNG1Psav+x3Pb17HvRNHkf4+HqK8PITdv4Ow+3cAAAIjI9i7fPgMsrVDNdvqsLCzg2k1S+nvUTMzGJuZlfszSJSXB5aVACjeMivDMAxafzYQDTt+gsCjB/Di1jWIRSKkxcfh4blTeFjTDhj6KcxzhXD8fjqsW7jBwra69DPTxhbG5tWQWmguZ1U/q82trDFo5jy07jcYd48fRvTTxwCko5DHR4Rx69k610b1Wi6wtLeHpZ09LOyqw9TCEsamZjA2N+f+NTI2gYGhAAxTgc/rc+eAhx+6XD94APz7LzBYPz67yu3DOXsB2M+Xc+Y5ff8dzrB8aCogHDc3Nzg5OeHq1atyy58/f44WLVpgx44dmDJlSrHtkpKS4ODggOXLl2PJkiVyz23btg3fffcdXr58iSZNmpR47ISEBCQmJsotCw8Ph4eHB1aMH4Na9nYlbstKpH9oAkCv8ZPQfrBHWaeqkFgkQtSTh3hxKwBRTx8hL7v83/IaCAQwMBCAMTCAgUAARiCAwYf/S6dv+fjhyX2OFvpAZWTPF/qMlf/AZRRso2A/SnxIZyYnIj83Fw6u9TF+zW9ln1wh+cJcRPzvHl7euYk3IU/l/ohThQSs9MGwYAwYWJhagjH4+JpJ/zgzgPxLoOD1kv5QaBUFr1mxbUvYpxKvXV5ONrJSpPeET9i0A3bOtQEAYffv4Ore7aUOllIagZERDI2MwQgEYCC91xsf/mU+xMkwBgAD7nX5+DMDMAaoFKVTkdcwMjUSQlEuwAJgAFNDM9SzraeRQ7Msy/3x3NvrW7QbNKxc+8lMScLLwBsIvRuI95Hh5W6JYBgDGAgMPvwukL63mQ+/DxgDA+nvC3W9v4ttX8JyLRTYYrEYgg9TVvGFMDuLm55ryvb9sLCrrtR2rESC6OD/8PzmNUQ+eQRhBXoAcJ9BgkLvtSKfQQwD6fuBZbn7UD+d9B1afzawzP3nZKTj+c1rCA+6i3cvn4FV8b305YoNqNmo5L8JypIcG4MXt67j1f07ckVyeRgIDD+8LgYf///hNft4jUj//XiaDBD7FsjLA/Ph9xlMTAAXl2LbyDZSdB3q15dcLPD6NZArhBiAAJB2sa5fD8V+/5AqQywWo/f4SajfrmPZK2vBs2fP4ObmhpCQELRo0aLM9alllmdyc3NhouA+FtMP3YFycxXfSypbXp5tZbZt2wZfX1+Fz6W9j4OpMEvhc0U9DwuHOCgIFy9exA8//ABvb28cO3YMQ4YMwZkzZ7Bo0SKMHTsWwcHS0SNbtmyJI0eOYNWqVfAYPhxnzpzBwjUbsHfPHmxevQItG9TH+8gI5CS9h0BUAGFmhlK/siVisd4NKPUiXDrYjZeXFzZt2oQ9e/agU6dOyM3NRUREBDw8PODn54cdO3Zwr+esOXOxZMkSvHv6HI2+mAhJRipePHyAZq4ueBh4Cw4W5kp1yTQAAwMw0iJHjAp9kaATjAGuB96Gi2s97r13PVUIvx8WYsea1fikTStEv3wOA7Fy9xaLCwrkWharCmsYwhqFemjkAyk5Jd++oC7HT5+BVeMWuHnzJmxtbVGrVi2VfkecvPcQq1ZvwvAhn2OD7zJs/mUV+nbpjND/HsFIIoZYiS9xWFYCsUgCVPD+cqI/BEZGWOq7HNNnzlTqvbf4558xduxYpFV3hk3vGnB1dMCVf06iR4d2uHb2NGo72iMzKanod0QKcZ9BKv4auXH3HuLEDMzMzBAUFIRvvvkGc+fOxf79+7k4586di++++w5PE1JhKzbCJ6cu4bqtNQQ2Vki3tUZTa0vEWVrASKD4bjWWYWDtVIPbn6enJ/z9/bFhwwb0798fsbGxSE1NRY8ePbB161Zs2rSJW1f2+bT38FF06tQJzv0dkfP8GTq5NcepQ3+gQ7MmCHn4ADbmZihQcvwLiVjEDeSnEiND6aOw+DjV96NPjI2kj8Leav53ONGtvNwcTJ06FUuWLMGpU6fQoEEDpX5HlPczV/Z3uaLfEY0aNVIpdmqZ5ZnK2jK75cfZqFPDqcz4bWrURJdRXyp9f1x5SCRi5KSnIzs1BXk52cgXClEgzEWBUIj83BwU5OVBIpGAlYi5PyYkEjEkYtkyifyH5odLTO5Cky0r4fLjlhd6nv34ZLH9KMPIzAwdh4zg7t1SJ7FIhJyMNOSkpSE3MwMFeUIU5OWhQJiLtTd+QWJaPAxYBgZpDAysGQhYAziZO8Gz+SiwYgn3erISycdTK3yAwq9DWa9Z0fVL2I9KrW8Mg0aduqBp155lriprsfnq8Bi8SXgNM7ERjFgDGLIGMJIIUMfCBd+2+QYSkQiignxIxJIPsbBgJSzYD/+i8L+s9AH24/8rxa9uuRhYXHl9BanCNAAskA2gGgAwsDW1xaf1+0JT3+zb1KiJLiPHavT3QoFQiOz0NGSnpUp/DwhzUZCXh/wPvxsK8vLASiSQfHgfy343yJZJxGKwhb78qtD7u+g2JSzX1r1uiUmJcPgwLgGvMAwadXZHU3f1ztEokYiRm5GBrNQU5OdkI1+Yy30O5efmoiBP+OE9Jv/eknCfSR8+g1hW+t4o9PvCzrk2Og/3/NByqwSWBTp2BB49AlgWNwD0/HDuaN8eBbduIistFTnp6cjPzZF+ZubmoEaDxnB0ra/W16V4aCzyc3OQlZIsPW5ODvKFucjLzUF+Ti5E+XmFPp+LPkTcZ7ZsX9z5yn4+fx5I+TifOHc1VbcD+vUv9pms8DqsDL+nVXH1KpAq7W2UCIC7qm1tgb59dRUV0bDEpET0G/8NajctuxVUG6hllpSqZs2aiI0tPjpgXJz0m0ZnZ2eF29nZ2cHExIRbT5VtZRwdHeHo6Ci3LO/D4C21u/ZG/YYNyz4BAKFhYWWvpC6MIWBmAZhZQADA7MNDX8WnZyI+/ZlmD2JoIn1UAwKjAnA49dbH59IB2EBa0wifo02NUejp2luz8aiJGNJfsMoIiArAxeh7ip/MeI3OFp7o6Vp2YaxPAqIC8Fv4NUBWT8YBsP3wfwnQpPEIjZ6zVn8vGJlKH5bS09VcCa0f3gUGon63broOQydU+b1QPgLA1AIwVd9n0IuXL5VfOSDg4z2jAF4CsAekRdqDB8DefUDPD9e1kSlgbQqBdXUkZuciUaOviwIfrksDS1uodreuAgEBwPlrJT8/eOTH864qAgKAfz82dLwDIPd1xOARVe+cCQDp7/B0MZCu7Wu2BOHh4QA+1ghlYgmvzJs3jxUIBGx6errc8pUrV7IA2Ddv3pS4bYcOHdiOHTsWW/7ZZ5+x9evXL1c8/v7+0qYnetCDHvSgBz3oQQ960IMe9ADYU6dOKVVLUMssz4waNQrr16/Hrl27MG/ePADSbz727duHzp07cyMZv3nzBjk5OWjatKnctgsWLMCDBw/QoUMHAEBoaCiuXbvG7UtVjRs3BgAcO3YMzZs3r8ipkUpO1qX81KlTaKhkKzzRT5Rr/qBc8wflmj8o1/xRGXOdl5eHmJgY9FSyJwAVszzTuXNnjB49GgsXLkRCQgIaNmyI/fv3IyoqCnv27OHWGz9+PG7cuCF3n9b06dOxe/duDB48GPPmzYORkRE2btwIJycn/PDDD+WKRzZFUPPmzZXqF0/0X8OGDSnXPEG55g/KNX9QrvmDcs0flS3X7dq1U3pdKmZ56I8//sCSJUtw4MABpKamolWrVjh79ix69Ch9EAtLS0sEBARg7ty5WLFiBSQSCXr16oVNmzbBwYGHg38QQgghhBBCdIaKWR4yNTXFunXrsG7duhLXCQgIULi8du3a+OuvvzQUGSGEEEIIIYQoR/EEYYQQQgghhBBCSCVGxSzRKQcHByxbtoy6KfMA5Zo/KNf8QbnmD8o1f1Cu+aMq5JphWX2b0ZkQQgghhBBCCN9RyywhhBBCCCGEEL1DxSwhhBBCCCGEEL1DxSwhhBBCCCGEEL1DxSwhhBBCCCGEEL1DxSwhhBBCCCGEEL1DxSwhhBBCCCGEEL1DxSwhhBBCCCGEEL1DxSwhhBBCCCGEEL1DxSwhhBBCCCGEEL1DxSwhhBBCCCGEEL1DxSwhhBBCCCGEEL1DxSwhhBBCCCGEEL1DxSwhhBBCCCGEEL1DxSwhhBBCCCGEEL1DxSwhhBBCCCGEEL1DxSwhhBBCCCGEEL1jqOsACL+lpaXhxo0bcHFxgYmJia7DIYQQQgghhOhIXl4eYmJi0LNnT9jY2JS5PhWzRKdu3LgBDw8PXYdBCCGEEEIIqSROnTqFYcOGlbkeFbNEp1xcXABI37ANGzbUcTSE6A7LspCIRWDZDz9D9h+20EpF/lPoucKrKXlEFWJTdd+qYVWIRdVgWE0GX6li0ewGKuVIxd2r/rpUplhUo9ruNZ0j1da3sK0OgSH92UgI0azw8HB4eHhwNUJZ6LcS0SlZ1+KGDRuiRYsWOo6GaJqXlxf279+v6zB0hpVIEBceiogH9/E+MgIZiQkQZmVClJ8PUX4+WFai6xAJIUQhW+fauJmcA/8//tB1KEQL+P55zSeVNdfK3n5IxSwhRGs2bdqk6xB0Jj0hHmd/XYP4iDBdh0IIISpLffcWs76doeswiJbw+fOab/Q911TMEkK0Zs+ePfjxxx91HYbWRQf/hzObViMvO1u6gGHgUMcVNk41YW5tDUNjkw8PYzAGHweZZxim2L64ZR/+ZeSfVCkuRfsvZW2V9n3t+jX07dNHlWA0Fotqu1Zx3yrGosr+VQwFqr8uKqxfyqoXL15C//79KkUsilfXZI5UTpJKVHtdVH3vKocFcHXPduTn5uDaX0fQ7tMBKh2H6Ce+fl7zkb7nmopZQojWdOrUSdchaJ0wOwvnNq/lCtl2A4eik8doVLOx1XFkmpVlYYN2PXvqOgyiBamGZmhFua7S3oQ8wbOAKzDISIMwKwumFha6DoloGB8/r/lK33NN88wSQrQmNzdX1yFo3d2/DiM3MwMA8NnkGejtPbnKF7IAP3PNV5Trqq9Zt14AAFYixqv7t3UbDNEKuq75Q99zTS2zhBCtiYiI4P6fl5ODpDdRyM3KhPDDQ5SXB5ZluQfAAoV+1vRIo+omEYvx+OJZAEDt5m5o2ae/jiPSnsK5JlUb5brqc2nREtVs7ZCdmoKXgQFo1Zc/v8v4iq5r/tD3XFMxSwjRmmHDhuHV/dv43+m/8T4inDej9zKMAfp4T9H4/XWVCc0fzR+U66rPwECAxp90xePzZ/D25TOICgpgaGSk67CIBqnrupZIJHj//j3y8vIgkfDjM1/f9OrVC69fv9boMRiGgZGREaysrGBpaanWv4eomOWZgIAA9O7dW+Fzd+/exSeffFLitj4+PvD19S223MTEBEKhsEJx5efmIi8np0L7IJWXRCJG3KuXOLBxDSwKVHuvMIwBwEj/ZRiUZ1QcnTIQGKKzx2g41K2n61C0ys/PDzt27NB1GEQLKNf8UKNBYwDSKcZS42LhUMdVtwERjVLHdS2RSPDmzRvk5uZCIBBAIBDw6ktdfaHpLxlYloVYLIZQKERmZibMzc1Rq1YtGKpp3moqZnlq1qxZ6Nixo9yyhg0bKrXt9u3bYVFo8AeBQFDheA7//ANqWFtWeD+kcpO9a0wtreDW61PUatIcFnbVYWphCVMLCxiZmIIxYD4UrvSBp8+ouOEPyjU/VK9dh/t/Ukw0FbNVnDqu6/fv3yM3Nxd2dnZwdHSkz3WeE4lESEhIQHp6OlJTU+Hg4KCW/VIxW0He3t4ICAhAVFRUubY9fvw4srKy1B9YGbp3745Ro0aVa9tRo0bB3t5ezRERPpCwQMtefdFj3ESYW1nrOhyiQUOGDMGZM2d0HQbRAso1P9jVqg2WlXaOSY55o+twiIap47rOy8uDQCCgQraSCwsLQ6NGjTR+HENDQ9SsWRNZWVnIysqiYrY0x44dw5gxY3DixAkMHz5c7rnWrVvj6dOnuHbtWrHutnXq1EHt2rVx584dbYZbppycHKxduxa9evVCr1691LbfzMxMmJmZqdzMz7IsMjIy1NrnvcOQEWhQt07ZKxK9ZeNUE3XcWsHYzFzXoRAtoOKGPyjX/GBkbAI7Z2ekxr1DUky0rsMhGqaO61oikVDXYj2gjUJWhmEYCAQCtQ7oWSWL2W7dugEAAgMD5YrZjIwMhISEwNDQELdv35YrZmNiYhATE4MvvvhCpWPt3r1b433Nc3JyuHtV1VXMTpgwAVlZWRAIBOjevTvWrVuHDh06KLVt/fr1kZWVhWrVqsHDwwMbNmyAk5NTheJx6/UpWrRoUaF9kMpv6tSp1CWRJyjX/EG55o+YpBRYAEh+S8VsVaeu65oK2covOjoadevW1drx1P2eqJLFrLOzM+rVq4fAwEC55Xfv3gXLshg9enSx52Q/ywphZRnp2Wh+xsbGGDlyJAYNGgR7e3s8f/4c69evR/fu3XHnzh20bdu2xG1tbW0xY8YMdOnSBSYmJrh16xa2bt2KoKAgPHjwAFZWVqUeOyEhAYmJiXLLwsPD1XJeRD8sWbJE1yEQLaFc8wflmj869eqD55f/Rdr7eBTkCWFkYqrrkIiG0HXNHzVr1tR1CBVioOsANKVbt254/Pix3ETAt2/fRosWLTBw4EDcu3dPrkX19u3bYBgGXbt25ZYdPHgQ7du3h5mZGezs7PDFF18gJiZG7jje3t5wdXWVW5acnIyvv/4aVlZWsLGxgZeXF548eQKGYeDv718s1tjYWHh4eMDCwgIODg6YN28exGIxACAqKorrU+7r6wuGYcAwDHx8fMr1uri7u+P48eOYOHEihg4digULFuDevXtgGAYLFy4sddvZs2fj999/x5dffomRI0fi119/xf79+xEWFoZt27aVeext27bBzc1N7iEb+j0wMBA3btzAunXrkJKSAi8vLwDSezYAYO7cuQgPD8fevXtx8uRJBAUFwc/PDzk5OfD09JRbd9GiRQgODsbhw4dx+PBhBAcHY9GiRXLreHp6IicnB35+fggKCsLJkyexd+9ehIeHY+7cuXLrenl5ISUlBevWrcONGzdw4cIFbN26FbGxsZg6darculOnTkVsbCy2bt2KCxcu0DkVOadTp05VuXOqinlSxznNnz+/yp1TVcyTOs5pzJgxVe6cqmKe1HFOLyI/tMiyLMaPHlUlzqkq5kkd5/Trr79W+JxkDUXR0dHIz8/nBv/JzMxEfHw8RCIRIiMjAUjv2wSkPSWFQiGSkpKQmpqK7OxsvHv3DmKxmJsPVbbu27dvkZOTg+TkZCQnJyMnJwdv376VWyciIgJisRjv3r1DdnY2UlNTkZSUBKFQyP1NL1s3MjISIpEI8fHxyMzMRHp6OhISEpCfn4/o6Gi5demcyn9OIpEIwcHBJb73ZM8pja2idu7cyQJgr1+/zi3r06cPO3nyZDY8PJwFwD558oR7rk2bNmyzZs24n1esWMEyDMOOGTOG3bZtG+vr68va29uzrq6ubGpqKreel5cXW7duXe5nsVjMdunShRUIBOyMGTPYLVu2sJ999hnbunVrFgC7b98+uW1NTU3ZFi1asBMnTmS3b9/Ojhw5kgXAbtu2jWVZls3KymK3b9/OAmCHDx/OHjhwgD1w4IBc7OrwxRdfsMbGxqxIJFJ52xo1arB9+/Ytc73379+zISEhco9Tp06xANiQkJDyhE30zPnz53UdAtESyjV/UK754+Thg+x6z8Hses/B7LMbV3UdDtEgdVzXERERbEREhBqiIZqUlpZWru3EYjG7bds2tnXr1qypqSlrZ2fH9u7dm/3vv/9K3a6s90VISIhKtUGV7GYMyN8326tXL4hEIty/fx9eXl5o0KABnJycEBgYiFatWiEzMxPBwcGYOHEiAOk3E8uWLcOKFSu4b60AYMSIEWjbti22bdsmt7ywU6dO4e7du/j1118xe/ZsAMC0adPw2WefKVxfKBRizJgxXHeOqVOnol27dtizZw+mTZuGatWqYdSoUZg2bRpatWqFcePGqe01KszFxQX5+fnIzs4us7uwom1TUlLKXM/R0RGOjo7lDZFUAWZmZroOgWgJ5Zo/KNf8Ye1UEwYCASRiMQ0CVcXRdc0fBgbl66g7ceJEHDp0COPHj8eMGTOQnZ2Nx48fIyEhQc0Rlq7KdjNu1qwZqlevznVxePLkCbKzs+Hu7g5A2t329u3bAKT30orFYq4APnHiBCQSCTw9PZGUlMQ9atSogUaNGuH69eslHvfChQswMjLCt99+yy0zMDDAd999V+I2su4YMt27d8fr16/Ld+Ll9Pr1a5iamsrNH6sMlmXlukITUpqgoCBdh0C0hHLNH5Rr/njw8CFsajgDAJLeROk2GKJRdF3rF6FQWO4BabOzs1Xe5tixY9i/fz+OHTuGPXv2YNKkSZg9ezb8/f1LbMDTlCpbzDIMA3d3d+7e2Nu3b8PR0RENGzYEIF/Myv6VFbNhYWFgWRaNGjWCg4OD3OPFixelfuMQHR2NmjVrwtxcfvoR2XGLMjU1LVYI2traIjU1tXwnXoaiAzAB0kL/9OnT6NevH/ftzJs3b/Dy5csyt92+fTsSExMxYMAAjcRLqpZvvvlG1yEQLaFc8wflmj+++eYbONWX/j3z5tlT5GSk6zgioil0XZfOx8cHDMMgPDwc3t7esLGxgbW1NSZMmICcnJxi6yszDo+rqyu8vb2LbVt0as6AgAAwDIOjR4/i559/Rq1atWBubo6MjAwAwF9//cUdy97eHuPGjUNsbKzcPr29vWFhYYHY2FhMmTJF4bg9pdm4cSM6deqE4cOHQyKRlKsgVpcqW8wC0uI0PT0dwcHBuH37NtcqC0iL2ejoaMTGxiIwMBDOzs6oX78+AOm8WAzD4MKFC7h8+XKxx86dO9UWo0AgUNu+lDFmzBgMHjwYK1euxO7duzF37ly4u7vD3Nwcv/zyC7fe+PHj0axZM7lt69atiwkTJmDjxo3Ytm0bvvzyS8yYMQNt2rTBlClTtHoeRD/JBpAgVR/lmj8o1/wxd+5ctOwtbXURFxQg+NolHUdENIWua+V4enoiMzMTq1evhqenJ/z9/bnpNGVWrlyJ8ePHo1GjRti4cSPmzJmDq1evokePHkhLSyv3sf38/HDu3DnMmzcPq1atgrGxMfz9/eHp6QmBQIDVq1fj22+/xYkTJ9CtW7dixxKLxejfvz9MTEywfv169OzZExs2bMCuXbtKPW5GRgaCgoLQsWNHLFq0CNbW1rCwsED9+vVx7Nixcp9PeVXZe2YB+ftmb9++jTlz5nDPtW/fHiYmJggICMD9+/cxaNAg7rkGDRqAZVnUq1cPjRs3VumYdevWxfXr15GTkyPXOluRKWjUOR+Th4cHDh06hI0bNyIjIwMODg4YMWIEli1bVmLrscxXX32FO3fu4O+//4ZQKETdunXx008/YfHixcVaoglRZP/+/boOgWgJ5Zo/KNf8sX//frAsC3uXukiKicaTy/+i45ARMNDyF/NE8+i6Vk7btm2xZ88e7ufk5GTs2bMHa9asAVCxcXjKIhQK8eDBA+7+5oKCAsyfPx9ubm64efMmTE2lU2d169YNn3/+OTZt2iRXaJc1bk9JIiIiwLIsjh49CkNDQ6xduxbW1tbYvHkzvvjiC1hZWWm1x2aVbpnt0KEDTE1NcejQIcTGxsq1zJqYmKBdu3bYunUrsrOz5eaXHTFiBAQCAXx9fcGyrNw+WZZFcnJyicfs378/CgoKsHv3bm6ZRCLB1q1by30eskKxIt/eyMyaNQv3799HcnIyCgoK8O7dOxw4cKBYIRsQEFDs3Hfv3o1nz54hIyMD+fn5CAsLwy+//AJLS8sKx0X4QTYEO6n6KNf8QbnmjyFDhoBhGLTp/zkAIDMpEeH/u6vjqIgm0HWtHEXj3iQnJ3NdfisyDk9ZvLy85AbqevDgARISEjB9+nSukAWAwYMHo2nTpjh37pzC+GVT6MjiL2vcnqysLADSwv2ff/7BtGnT8OWXX+Lq1auoXr06VqxYUe5zKo8q3TJrbGyMjh074tatWzAxMUH79u3lnnd3d8eGDRsAQK6YbdCgAVasWIGFCxciKioKHh4esLS0RGRkJE6ePInJkydj3rx5Co/p4eGBTp064YcffkB4eDiaNm2K06dPc6P9lqeV1czMDM2bN8eff/6Jxo0bw87OjpunlRB9cubMGV2HQLSEcs0flGv+kOW6WfdeuHXYH3k52bi44zdUs7FDrabNdRwdUSdNXtfX/XchIVq7A52WxrFuffT2nlyubevUqSP3s62tLQAgNTUVVlZWcuPwKGJkZFSu4wJAvXr15H6WzRvbpEmTYus2bdqUGxRXRjZuT+Gxe5QZt0dWQNerVw+dO3fmlltYWGDIkCE4ePAgRCIRDA21U2ZW6WIWkBapt27d4roVF9a1a1ds2LABlpaWaN26tdxzCxYsQOPGjeWa5F1cXNCvXz8MHTq0xOMJBAKcO3cOs2fPxv79+2FgYIDhw4dj2bJl6Nq1q9w3Jar4v//7P8ycORNz585Ffn4+li1bRsUs0Ttz587Fpk2bdB0G0QLKNX9QrvlDlmtjUzP0HP8NLu34Dfm5OTi+agla9R2AJl26w75OXRib0rQu+k6T13VC9Gu8fR6ikX1rW0lj38h6N8rG4Tl//rzCdQvPIlJSg5dYLFa4bUWnT5LtMyYmBi4uLkpv5+wsHdHcycmp2HOOjo4oKChAdnY2rK2tKxSfsqp8Mbtq1SqsWrVK4XPDhw8v1pW2sBEjRmDEiBGl7t/f37/YMnt7exw6dEhu2alTpwAAtWvXlttW0fY+Pj7w8fGRW9alSxc8ePCg1FgIqexKm6KKVC2Ua/6gXPNH4Vy37N0PDBhc2vk7RHl5ePTvP3j07z8AgLqt2mLEAh+6l1aPafK6dqxbX2P7Lg9NxqPKODy2trYKbymMjo7mBqktTd26dQEAoaGh6NOnj9xzoaGh3PNFqTq9prOzM2rUqFFshGQAePfuHUxNTbV6C2KVL2Z1ITc3V+7bErFYjN9//x1WVlZo166dDiMjRLdu3rxZ5kBjpGqgXPMH5Zo/iubarfdnsLCrjqB/jiPm2VNuefTTx4iPCINz46a6CJOogSav6/J26dVHI0aMwMKFC+Hr64uDBw/Ktb6yLIuUlBRUr14dgLTwvXXrFvLz82FsbAwAOHv2LGJiYpQqZjt06ABHR0fs2LEDEydO5Hqknj9/Hi9evMDSpUsVbpeVlaVyz9ExY8Zg8+bNuHz5MjevbFJSEv755x/06dOHm+pTG6iY1YCZM2ciNzcXXbp0QV5eHk6cOIE7d+5g1apVFe4SQIg+k91LQqo+yjV/UK75Q1GuXVu3g2vrdshITED4g/u47i+dvjA9IZ6KWT1G17V6qDIOz6RJk3D8+HEMGDAAnp6eiIiIwMGDB9GgQQOljmVkZIQ1a9ZgwoQJ6NmzJ8aOHYv3799j8+bNcHV1LXG6pfJME7pw4UIcO3YMI0eOxPfffw9ra2vs2LEDBQUFJfaI1ZQqPZqxrvTp0wcvX77E4sWLsWjRIqSlpeH333/HwoULdR0aITpVq1YtXYdAtIRyzR+Ua/4oLddWDo5w69WX+zkjMUEbIRENoetafRYsWIC///4bBgYG8PX1xbx583D69Oli4/D0798fGzZswKtXrzBnzhzcvXsXZ8+elbtFsSze3t74888/kZ+fj/nz52Pnzp0YPnw4AgMDYWNjo3AbWSuwKpycnBAYGIhPP/0UmzZtwuLFi1G7dm3cuHGj2DhEmsawpd00SqqcgIAA9O7dW+Fzd+/exSeffFLq9rGxsZg7dy4uXboEiUSC3r17Y9OmTUp1f1Dk2bNncHNzQ0hICFq0aFGufRD94efnx81nRqo2yjV/UK75Q5lcb530JYSZGWjZpx/6TZmlpciIuqnjupZN8VLevxGJdrx7944b1EkbynpfqFobUDdjnpo1axY6duwot6yseyOysrLQu3dvpKenY9GiRTAyMsKmTZvQs2dP/Pfff1yff0JK8sMPP+g6BKIllGv+oFzzhzK5tnZwgjAzA+kJ77UQEdEUuq75Q9GoxPqEuhnrwLFjx2BnZ8dNOlxeFy5cgIWFBRITE1Xetnv37hg3bpzcw97evtRttm3bhrCwMJw9exY//fQT10IbFxfHzddLSGm8vb11HQLREso1f1Cu+UOZXFs7Sv8wTk+kYlaf0XXNH1FRUboOoUL0qpi9c+cOfHx8FA5brS/EYjGWLVuGmTNnys0tVR4DBgxAw4YNsXr16nJtn5mZCZFIpPT6x48fR8eOHeVadJs2bYq+ffvi2LFj5YqB8Au9T/iDcs0flGv+UCbXsmI2MykREolY0yERDaHrmj+UHWCqstK7YtbX11evi9kzZ84gNDQUkyerZ1jyKVOmYOfOncjMzFRpuwkTJsDKygqmpqbo3bt3mXPYSiQSPH36FB06dCj2XKdOnRAREaFyDIR/hgwZousQiJZQrvmDcs0fyuRaVsxKxGJkpSRrOiSiIXRd80dYWJiuQ6gQvSpmVSGRSCAUCnUdRjH79u1D165d1TZK3MiRI5GXl4e//vpLqfWNjY0xcuRIbN68Gf/88w9WrFiB4OBgdO/eHY8fPy5xu5SUFOTl5aFmzZrFnpMte/fuXanHTkhIwLNnz+Qe4eHhSsVNqoYzZ87oOgSiJZRr/qBc84cyubZy+Hj/Hd03q7/ouuaPRo0a6TqECtGbYtbHxwc//vgjAKBevXpgGAYMw3D9vBmGwYwZM3Do0CG0aNECJiYmuHDhAgBg/fr1cHd3R/Xq1WFmZob27dvj+PHjCo9z8OBBdOrUCebm5rC1tUWPHj1w6dIluXXOnz+P7t27o1q1arC0tMTgwYPx7NmzMs9BKBTiwoUL+PTTT+WWjxgxAu3atZNbNmTIEDAMg9OnT3PL7t+/D4ZhcP78eW6Zo6MjWrVqhX/++afM4wOAu7s7jh8/jokTJ2Lo0KFYsGAB7t27B4ZhSp06KDc3FwC4CZgLk020LFunJNu2bYObm5vcw8PDAwAQGBiIGzduYN26dUhJSYGXlxf3OgDA3LlzER4ejr179+LkyZMICgqCn58fcnJy4OnpKbfuokWLEBwcjMOHD+Pw4cMIDg7GokWL5Nbx9PRETk4O/Pz8EBQUhJMnT2Lv3r0IDw/n5uGSrevl5YWUlBSsW7cON27cwIULF7B161bExsZi6tSpcutOnToVsbGx2Lp1Ky5cuEDnVOScFi1aVOXOqSrmSR3nNHjw4Cp3TlUxT+o4p3bt2lW5c6qKeVLHOf34449lntP7tHTI+C5aWOnPqSrmSR3n5O3tXeFzCgwMBABER0cjPz8fCQkJSE9PR2ZmJuLj4yESiRAZGQngY+tgTEwMhEIhkpKSkJqaiuzsbLx79w5isRgRERFy6759+xY5OTlITk5GcnIycnJy8PbtW7l1IiIiIBaL8e7dO2RnZyM1NRVJSUkQCoWIiYmRWzcyMhIikQjx8fHIzMxEeno6EhISkJ+fj+joaLl1q9I5BQcHa/WcRCIRd0xF7z3Zc0pj9cSTJ0/YsWPHsgDYTZs2sQcOHGAPHDjAZmVlsSzLsgDYZs2asQ4ODqyvry+7detW9vHjxyzLsmzt2rXZ6dOns1u2bGE3btzIdurUiQXAnj17Vu4YPj4+LADW3d2dXbduHbt582b2yy+/ZOfPn8+t88cff7AMw7ADBgxgf//9d3bNmjWsq6sra2Njw0ZGRpZ6DoGBgSwA9vTp03LLN27cyBoYGLDp6eksy7KsRCJhbW1tWQMDA3bevHnceuvWrZNbT2bSpEmsvb29Sq9nUV988QVrbGzMikQihc8nJiayANjly5cXe27r1q0sAPbly5elHuP9+/dsSEiI3OPUqVMsADYkJKRC8RP98PTpU12HQLSEcs0flGv+UCbXBXl57HrPwex6z8Hs7WMHtRAV0QR1XNcRERFseHi4GqIhmpSdna3V44WHh7MRERElPh8SEqJSbaA3U/O0atUK7dq1w5EjR+Dh4QFXV9di64SGhiI4OBjNmzeXW/7q1SuYmZlxP8+YMQPt2rXDxo0bMXjwYABAeHg4li9fjuHDh+P48eMwMPjYaM1+mIo3KysLs2bNwqRJk7Br1y7ueS8vLzRp0gSrVq2SW17Uy5cvAUhblgvr3r07JBIJbt++jYEDByIkJASpqakYPXo0bt26xa1369YttG7dGlZWVnLb169fH0lJSUhISICjo2OJxy+Ni4sL8vPzkZ2dXWz/AGBnZwcTExPExcUVe062rKw5qhwdHcsdH6kagoOD0bJlS12HQbSAcs0flGv+UCbXhsbGsLC1Q1ZqCnUz1mPquK4NDAyQn58PlmXBMIyaIiPqlpubC3Nzc60ci2VZiMViGBkZqW2fetPNWBk9e/YsVsgCkCtkU1NTkZ6eju7du+PRo0fc8lOnTkEikWDp0qVyhSwA7gK8fPky0tLSMHbsWCQlJXEPgUCAzp074/r166XGl5wsHQjB1tZWbnnbtm1hYWGBmzdvApAWrbVr18b48ePx6NEj5OTkgGVZBAYGonv37sX2K9tfUlJSqccvzevXr2FqalriCMsGBgZo2bKlwoGi7t+/j/r168PS0rLcxyeEEEJI1SC7b5aKWX4zMTGBWCxGQkIC1zBE+EskEiEuLg5isbjCM7oUpjcts8oo2uIpc/bsWaxYsQL//fcf8vLyuOWFvyWKiIiAgYGBwmJYRtb3u0+fPgqfV9SiqUjRC1ogEKBLly5cK+ytW7fQvXt3dOvWDWKxGPfu3YOTkxNSUlIUFrOy/SnzrVdiYiIcHBzklj158gSnT5/GwIEDuUL+zZs3yMnJQdOmTbn1Ro0ahQULFuDBgwfcqMahoaG4du0a5s2bp9S5E36j1hv+oFzzB+WaP5TNtbWjE969eoGMxAQNR0Q0RR3XtZOTE/Ly8pCSkoL09HQIBAJqoa2ERCIR0tPTy16xnFiWhUQi4aYDlY1LpC5Vqpgt3AIrc+vWLQwdOhQ9evTAtm3bULNmTRgZGWHfvn04fPiwSvuXSCQAgAMHDqBGjRrFnjc0LP3lrF69OgBp63Dt2rXlnuvWrRtWrlwJoVCIW7duYfHixbCxsYGbmxtu3boFJyfpt5yKitnU1FQAgL29fZnnMGbMGJiZmcHd3R2Ojo54/vw5du3aBXNzc/zyyy/ceuPHj8eNGzfkCu/p06dj9+7dGDx4MObNmwcjIyNs3LgRTk5O+OGHH8o8NiFHjhyhP3x5gnLNH5Rr/lA219xcsylJEOXnw9DYWNOhETVTx3VtYGCAOnXq4P3798jLy+P+jiaVy4sXLzT6O5xhGBgaGsLMzAxWVlawtLRU65caelXMlufE//77b5iamuLixYtyI/Hu27dPbr0GDRpAIpHg+fPnaNOmjcJ9ySYVdnR0LDYisTJkrZyRkZHF3jTdu3dHfn4+jhw5gtjYWK5o7dGjB1fMNm7cmCtqC4uMjIS9vX2xFldFPDw8cOjQIWzcuBEZGRlwcHDAiBEjsGzZMjRs2LDUbS0tLREQEIC5c+dixYoVkEgk6NWrFzZt2qTUsQlZtWqVrkMgWkK55g/KNX8om2u7Wi7S/7AskmNj4FSvgQajIpqgruvawMBA4bSOpPKoX7++rkOoEL26Z7ZatWoAgLS0NKW3kXVpEIvF3LKoqCicOnVKbj0PDw8YGBhg+fLlxb45krVO9u/fH1ZWVli1ahUKCgqKHSsxMbHUWNq3bw9jY2OF95127twZRkZGWLNmDezs7NCiRQsA0iL33r17uHHjhsJWWQB4+PAhunTpUuqxZWbNmoX79+8jOTkZBQUFePfuHQ4cOFCskA0ICFB4f0Pt2rXx119/cUN2nzlzpswimBAZmoSdPyjX/EG55g9lc+1Qx5X7f9KbKM0EQzSKrmv+0Pdc61Ux2759ewDA4sWLceDAARw9ehTZ2dmlbjN48GDk5ORgwIAB2LFjB5YvX47OnTsXK8AaNmyIxYsX4+TJk+jevTs2bNiALVu2wMvLi5uHy8rKCtu3b8etW7fQrl07rFy5Ert27cLPP/+Mtm3bwtfXt9RYTE1N0a9fP1y5cqXYc+bm5mjfvj1CQ0PRtWtXrhW6R48eyM7OlmutLSwhIQFPnz7FsGHDSj02IZUBTcLOH5Rr/qBc84eyubZ1rg3Bh1uvEqNfazIkoiF0XfOHvudar4rZjh07ws/PD0+ePIG3tzfGjh1bZmtonz59sGfPHsTHx2POnDk4cuQI1qxZg+HDhxdbd/ny5di7dy9yc3OxePFiLF26FNHR0ejbty+3zpdffomrV6+iVq1aWLduHWbPno2jR4+iTZs2mDBhQpnnMHHiRNy7d4+b1LgwWbHarVs3blmNGjW4wltRMXvixAmYmJhwk2MTUpnR+5Q/KNf8QbnmD2VzLTA0hF3tOgCAxOgoDUZENIWua/7Q91wzLI2VrVVisRjNmzeHp6cn/Pz8Kry/tm3bcvet6qNnz57Bzc0NISEhXNdqUnXl5ORobS4zoluUa/6gXPOHKrk+v3Ujnt+8BjNLK0zbfYhGsdUzdF3zR2XLtaq1gV61zFYFAoEAy5cvx9atW5GVlVWhfV24cAFhYWFYuHChmqIjRLM2bNig6xCIllCu+YNyzR+q5NqhrnS6xNzMDOSkp2koIqIpdF3zh77nmopZHRgzZgxSUlIqPGHwgAEDkJWVBUdHRzVFRohm9e/fX9chEC2hXPMH5Zo/VMm1Q5163P8To+i+WX1D1zV/6HuuqZglWLlyJRiGgZubW5nr+vj4gGGYYg9TU1MtREr0XWxsrK5DIFpCueYPyjV/qJJrh7qu3P8TaURjvUPXNX/oe671ap5Zon5v377FqlWruGmPlLV9+3a5lmWBQKDu0EgVlJqaqusQiJZQrvmDcs0fquTa3NoG1WxskZ2WSsWsHqLrmj/0PddUzPLcvHnz8Mknn0AsFiMpKUnp7UaNGgV7e3sNRkaqoh49eug6BKIllGv+oFzzh6q5tq/jiuy0VMSFvQQrkYAxoA6B+oKua/7Q91zTbxUeu3nzJo4fP45ff/1V5W1ZlkVGRgZoMGyiiq1bt+o6BKIllGv+oFzzh6q5rtuyDQAgLT4OYUF3NBAR0RS6rvlD33NNxSxPicVizJw5E5MmTULLli1V3r5+/fqwtraGpaUlxo0bh/fv32sgSlLVbNy4Udch6AQfv/Tha675SF+nhiOq26Tidd36s4EwtbQCANz56zAkErEmwtI8Hv4OVzXXRH/p++9wKmZ5aseOHYiOjlZ5rltbW1vMmDEDO3fuxPHjxzFp0iT8+eef6N69OzIyMkrdNiEhAc+ePZN7hIeHV+Q0iB658voKDJsZ4srrK7oORauuvL4Cs5VmvDpvvuaar4YMGaLrEIg2XLmCIYaGwBXlr2tjM3N0HDICAJD89g2eBVzVVHSac+UKYGam0nnrvXLkmugvvf8dzhLeSUpKYu3s7Nj169dzy3r27Mm2aNGiXPs7dOgQC4BdvXp1qestW7aMBaDwsWPHDjYgIIBdu3Ytm5yczI4fP55lWZb9/PPPWZZl2Tlz5rBhYWHsnj172BMnTrD3799nly9fzmZnZ7OjR4+WW3fhwoXs06dP2UOHDrGHDh1inz59yi5cuFBundGjR7PZ2dns8uXL2fv377MnTpxg9+zZw4aFhbFz5syRW3f8+PFscnIyu3btWjYgIIA9f/48u2XLFvbt27fslClT5NadMmUK+/btW3bLli3s+fPn6Zw+nFNWVhZr296WhQ9Y65bWrEQi0ftzUiZPT548YWsMqCF33vp+TmXl6d69e2z9qfVZDAXr5ufGzp49W+/PqSrmic6Jzkmlc7p3j13u7MxmA+xoW1uWlUiUPqf83Fx29ejB7HrPwew6z8Hsnxt/YY//eVT356RMng4eZA/Vq8c+BdiFNWrInXelzJM63ntZWexyZ2f2PsCeaNCA3fN//6f/51QV81SFz+nIkSMsADYkJIRVBsOyPOw7wXPTpk3DlStX8OzZMxgbGwMAevXqhaSkJISEhJRrnzVr1kSLFi1wpZRv8RISEpCYmCi3LDw8HB4eHggJCUGLFi3KdWxS+Z19dRZDjgwBTgIYDpwdexaDGw/WdVgax5237GcenDdfc81nXl5e2L9/v67DIJp09iwwZAi8AOyX/TxY+es64mEQzm5eA1FeHgDAQGCImo0aw8apJsysrGFobAxDI2MYGpvIDRLFMPL/YcCg6JPcOoWeYxgG+DB1IJgP2xWaThDMhz0xRZaDke6PYaTbPHwIZuVKACwYFmCWLQPTuTMYAwMYGBhItzMwAMMYgDEoFJs+u30b+PFH+AFYAgDr1wPu7joOimiSn58fNmzdDnMra12HAgB49uwZ3NzclK4NqJjlmbCwMDRt2hS//vqrXLeCL774Aqmpqbh48SKsrKxgZ2en0n47deoEkUiER48eqbSdqm9Yon9YlkXH3R3xKO4R2BwWjDmD9jXbI+jboA9/PFRNcucNFgyq/nnzNdd8l5KSovJnBtEjLAt07Ag8eoQUloUdwwDt2wNBQYUryTIlv32DM5t+QfLbNxoMlhBSHoNm/YhmXXvqOgwAqtcGdM8sz8TGxkIikWDWrFmoV68e97h//z5evXqFevXqYfny5Srtk2VZREVFwcHBQUNRE312LuwcHsY9BAsWeAywYPEg7gH+DftX16FplNx5gx/nzddc892ePXt0HQLRpHPngIcPAZbFHkBa3D54APyr2nVdvXYdfL1mM0Ys8EHrfoNRs3FTWNjawdDIWCNhE0L4geaZ5Rk3NzecPHmy2PKff/4ZmZmZ2Lx5Mxo0aAAAePPmDXJyctC0aVNuvcTExGJF6/bt25GYmIgBAwZoNniid1iWhU+ADxgw0gKnlnQ5AwY+AT4Y1GhQlWyxK3beH1Tl8+Zrrom0Zw6polgW8PGRtsCyLLhMM4x0+aBBKrXOCgyNUK9tB9Rr26HIYViICvIhzi8Ay0q4ZcViKbR+0e0Lr8eCBSv5MCwHK3ueBctCun+W/bA7Vvpc4eUAIJGA/fJL4MUL6c8MwIIBa8CAbdoMkt27ABaQSCRgWQlYiaRqjHg8cyYQHg6wLJ4CaAVI89uoEfDbbzoOjmjK0+BguDRXfWaTyoKKWZ6xt7eHh4dHseWyuWYLPzd+/HjcuHFD7kOibt26GDNmDFq2bAlTU1MEBgbi6NGjaNOmDaZMmaJyPHkf7p+hUY2rpoCoADx88vDjgkQA5h9a7BIeYPu/29HTtXJ0a1GnYuf9QVU+b77mmgAvX76Evb29rsMgmhAQIG2V/eAlAHvgY+vs9u1Azyp4XQcEAHfvK37u9l3g+k3peTMC6aMq9HMMCAAC73I/xgFoIPshPhG4c79q5pogLicP0e/igHdxug4FwMeaQFYjlIXumSUAFA8A1atXr2LF7Lfffos7d+4gJiYGQqEQdevWxciRI7F48WJYWlqqfNz9+/fD29tbHadACCGEEEIIqQJOnTqFYcOGlbkeFbNEp+7evQt3d3ccO3YMzZs313U4RINkI1efOnUKDRs21HU4RIMo1/xBueYPyjV/UK75ozLmOi8vDzExMejZsydsbGzKXJ+6GROdsrKyAgA0b96cRjPmiYYNG1KueYJyzR+Ua/6gXPMH5Zo/Kluu27Vrp/S6VaGXPyGEEEIIIYQQnqFilhBCCCGEEEKI3qFilhBCCCGEEEKI3qFiluiUg4MDli1bVmzuWlL1UK75g3LNH5Rr/qBc8wflmj+qQq5pNGNCCCGEEEIIIXqHWmYJIYQQQgghhOgdKmYJIYQQQgghhOgdKmYJIYQQQgghhOgdKmYJIYQQQgghhOgdKmYJIYQQQgghhOgdKmYJIYQQQgghhOgdKmYJIYQQQgghhOgdKmYJIYQQQgghhOgdKmYJIYQQQgghhOgdKmYJIYQQQgghhOgdKmYJIYQQQgghhOgdKmYJIYQQQgghhOgdKmYJIYQQQgghhOgdKmYJIYQQQgghhOgdKmYJIYQQQgghhOgdKmYJIYQQQgghhOgdQ10HQPgtLS0NN27cgIuLC0xMTHQdDiGEEEIIIURH8vLyEBMTg549e8LGxqbM9amYJTp148YNeHh46DoMQgghhBBCSCVx6tQpDBs2rMz1qJglOuXi4gJA+oZt2LChjqMhmlSQJ8TGJYswafZcVK/loutwiIYtWrQIq1at0nUYRAso1/xBueYPyjV/VLZch4eHw8PDg6sRysKwLMtqOCZCSvTs2TO4ubkhJCQELVq00HU4RIOC/jmOW4f9YeXgiEm/7wHDMLoOiWhQSkoK7OzsdB0G0QLKNX9QrvmDcs0flS3XqtYGNAAUIUQrUuPeAQAyEhOQm5mh42iIpu3Zs0fXIRAtoVzzB+WaPyjX/KHvuaZilhCiFXnZWdz/ZYUtqbo6deqk6xCIllCu+YNyzR+Ua/7Q91xTMUsI0QphVib3/9S4WB1GQrQhNzdX1yEQLaFc8wflmj8o1/yh77mmYpYQohVCuZZZKmarurBH/8Otw/7UpZwHIiIidB0C0RLKNX9QrvlD33NNoxkTQrRCmPWxmE2jbsZVnuGbcAQ9uQ+WZdHjqwm6DodoEE2vxh+Ua/5QV65FIhFSU1ORlZUFGnO2curVqxdev36t0WMwDAMTExNYWVmhWrVqah0ElFpmeSgvLw/z58+Hs7MzzMzM0LlzZ1y+fLnM7UJDQzF37ly4u7vD1NQUDMMgKipK8wGTKoFaZvlDLBIhJzUZABAXHqrjaIim+fn56ToEoiWUa/5QR65ZlsXbt2+RlJSEgoICNURFNEEikWj8GGKxGOnp6YiJiUFCQoJav9igllke8vb2xvHjxzFnzhw0atQI/v7+GDRoEK5fv45u3bqVuN3du3fx22+/oXnz5mjWrBn+++8/7QVN9JpYJEKB8OM9GanxcWAlEjAG9H1aVVT4/ujE6EiwLEtTMVVhO3bs0HUIREso1/yhjlxnZmYiNzcX1tbWqFmzJn0O8Fx+fj7i4uKQkpKCatWqwcLCQi37pb8kleDj41NlLsCgoCAcPXoUq1evxrp16zB58mRcu3YNdevWxU8//VTqtkOHDkVaWhqCg4Px1VdfaSliUhUUHskYAET5echMSdZRNNqXFh+HB2dOICc9TdehaEVORjr3/7zsbGQmJeowGqJpQ4YM0XUIREso1/yhjlxnZEjHTHB0dKwyf0dXRWFhYVo5jrGxMWrWrAng43tDHcpVzPr7+4NhGO5hamoKZ2dn9O/fH7/99hsyMzPL3gnRiePHj0MgEGDy5MncMlNTU3zzzTe4e/cuYmJiStzWzs4OlpaW2giTVDG5WcV/J/Cpq/Hl3b/jxsG9uHFwr65D0YqiRXtCdKRuAiFacebMGV2HQLSEcs0f6sh1QUEBDA0NYWhIHUErs0aNGmntWMbGxjAyMkJeXp7a9lmhltnly5fjwIED2L59O2bOnAkAmDNnDlq2bImnT5+qJcDK4Oeff9b7YatlHj9+jMaNG8PKykpuuWyOKeo6TDShaMsswK+5ZpNi3gAA3gT/x4sBMHILtcwCQGK0ZgeWILo1depUXYdAtIRyzR/qyDXLsjCg24kqvejoaK0ej2GYynPP7MCBA9GhQwfu54ULF+LatWv4/PPPMXToULx48QJmZmYVDlLXqtK3SnFxcVwTf2GyZe/eaa7ASEhIQGKifHfD8PBwjR2PVB5CBcVsWjw/WmbFIhHX7TYrNQWZyYmwsnfUcVSalVOk+1AitcxWaUuWLNF1CERLKNf8oa5cU/fiyk9RXaBJ6n5PqP3rkj59+mDJkiWIjo7GwYMH5Z67du0aunfvjmrVqsHGxgbDhg3Dixcv5NaJjo7G9OnT0aRJE5iZmaF69eoYPXp0sVFzZV2db968iSlTpqB69eqwsrLC+PHjkZqaKreuq6srPv/8cwQEBKBDhw4wMzNDy5YtERAQAAA4ceIEWrZsCVNTU7Rv3x6PHz+W217RPbMMw2DGjBk4deoU3NzcYGJighYtWuDChQvFXpPY2FhMnDgRTk5O3Hp79+qmu2Fubi5MTEyKLTc1NeWe15Rt27bBzc1N7iEb+j0wMBA3btzAunXrkJKSAi8vLwAf79mYO3cuwsPDsXfvXpw8eRJBQUHw8/NDTk4OPD095dZdtGgRgoODcfjwYRw+fBjBwcFYtGiR3Dqenp7IycmBn58fgoKCcPLkSezduxfh4eGYO3eu3LpeXl5ISUnBunXrcOPGDVy4cAFbt25FbGws982lbN2pU6ciNjYWW7duxYULF+icPpxTRvLH+2PFH76Mu3v9ml6fk7J5WrZoAVDoG8ifpk/V+3MqK0+Pg+6jsMToSL0/p6qYJ3Wd05gxY6rcOVXFPKnjnI4dO1blzqkq5kkd5/Trr79W+JwCAwMBSP+2z8/PR0JCAtLT05GZmYn4+HiIRCJERkq/7JTdtxkTEwOhUIikpCSkpqYiOzsb7969g1gs5uZDla379u1b5OTkIDk5GcnJycjJycHbt2/l1omIiIBYLMa7d++QnZ2N1NRUJCUlQSgUcrfWydaNjIyESCRCfHw8MjMzkZ6ejoSEBOTn53Otl7J16ZzKf04ikQjBwcElvvdkzymLYcvRzuvv748JEybgf//7n1zLrMzbt2/h4uKCUaNG4a+//gIAXLlyBQMHDkT9+vUxadIk5Obm4vfff4dYLMajR4/g6uoKQHpP54oVKzBs2DDUrl0bUVFR2L59O6ysrPD8+XOYm5vLxdCyZUvY2Nhg9OjRCA0Nxfbt29GtWzcEBARwBairqytMTU2RkZGBKVOmwNraGuvXr0d6ejp27NiBRYsWYfr06QCA1atXw8HBAaGhoVzXCB8fH/j6+so1iTMMg9atWyMhIQHTp0+HpaUlfvvtN8THx+PNmzeoXr06AOD9+/fo0KEDGIbBt99+CwcHB5w/fx6nT5/Gpk2bMGfOHFVf/gpxc3ODk5MTrl69Krf8+fPnaNGiBXbs2IEpU6aUuZ/169fjxx9/RGRkJJe7spTUMuvh4YGQkBC0aNFC6fMg+uXR+TO47r8TAFDHrRXehDyFmaUVpu06WOVHNI4LC8Xhn3/gfm47cAj6eJd9jemzy7u34OkV+S/2Zvofg7GZuY4iIpp04cIFDBgwQNdhEC2gXPOHOnItm7u0fv366giJaEh6ejqsra21dryy3hfPnj2Dm5ub0rWBRvrO1q5dG9bW1lxlDgA//vgj7OzscPfuXdjZ2QGQTsjctm1bLFu2DPv37wcADB48GKNGjZLb35AhQ9ClSxf8/fff+Prrr+WeMzY2xtWrV2FkZAQA3Ki8Z86cwdChQ7n1QkNDcefOHXTp0gUA0Lx5c/Tv3x/ffvstXr58iTp16gAAbG1tMWXKFNy8eRO9evUq9TxfvHiB58+fo0GDBgCA3r17o3Xr1jhy5AhmzJgBAFi8eDHEYjGCg4O5Anfq1KkYO3YsfHx8MGXKFK12xa5ZsyZiY4t374yLiwMAODs7a+zYjo6OcHSs2t0riWKFp2pp1Lkb3oQ8RW5mBt5HRqBGA+0NPKALWanyoza/C32po0i0J1fBKIWJb6JRq0kzHURDNK0q3E5ElEO55g/KNX+U975miUSCnTt3YufOnQgNDYW5uTlat26NTZs2oXXr1mqOsmQaaxKxsLDgRjWOi4vDf//9B29vb66QBYBWrVrhs88+w7///sstK3zxFBQUIDk5GQ0bNoSNjQ0ePXpU7DiTJ0/mClkAmDZtGgwNDeX2CUiLV1khCwCdO3cGIO0WLStkCy+XfWtQmk8//ZQrZGXnY2VlxW3Lsiz+/vtvDBkyBCzLIikpiXv0798f6enpCs9Jk9q0aYNXr14VGxL7/v373POEqJtsACjWQID67T725oj676GuQtKarNQUuZ8To1+jIE+oo2i0IycjDQBgae/ALYt79aKEtYm+CwoK0nUIREso1/xBueaP7Ozscm03ceJEzJo1C+3bt8fvv/+OpUuXok6dOkhISFBzhKXTWDGblZXFTeMi65PdpEmTYus1a9YMSUlJ3AuZm5uLpUuXwsXFBSYmJrC3t4eDgwPS0tKQnp5ebPuiw0lbWFigZs2axe6xLVywAuCa011cXBQuL3rfrSJF9wlIW3Zl2yYmJiItLQ27du2Cg4OD3GPChAkAoPWEjxo1CmKxGLt27eKW5eXlYd++fejcuTP3erx58wYvX1b9FiSiHbKWWUsbW1jZO8KulvR9FvVUu1/m6EJ2kWJWIhbjfUTVHvhMNgBUzQaNYeMkHVji1f3bugyJaNA333yj6xCIllCu+YNyrV+EQiEkEkm5trW3t1d5m2PHjmH//v04duwY9uzZg0mTJmH27Nnw9/fHZ599Vq44yksjxezbt2+Rnp6Ohg0bqrztzJkzsXLlSnh6euLYsWO4dOkSLl++jOrVq5c7SQAgEAhUWq7MrcRlbSuLd9y4cbh8+bLCR9euXZUJX206d+6M0aNHY+HChfjpp5+wa9cu9OnTB1FRUVi7di233vjx49GsmXyXwPT0dKxYsQIrVqzg7rndsmULVqxYgS1btmj1PIh+kY1mnPjhix7X1u0AAO9evUReTvm+EdQXWSnSYtbIxJRbFvNctcEN9I1sah4zK2s07tINgPTe4YxE7X55R7RDNjAMqfoo1/xBuS6dbHDY8PBweHt7w8bGBtbW1pgwYQJycnKKrX/w4EG0b98eZmZmsLOzwxdffMEN1iTj6uoKb2/vYtv26tVL7tZH2bhAR48exc8//4xatWrB3Nyc63X5119/cceyt7fHuHHjit1i6O3tDQsLC8TGxmLQoEGwsLCAg4MD5s2bB7FYXOb5b9y4EZ06dcLw4cMhkUjK3bqrDhq5Z/bAgQMAgP79+wOQ3scKSO9bLerly5ewt7dHtWrVAEgHgPLy8sKGDRu4dYRCIdLS0hQeKywsDL179+Z+zsrKQlxcHAYNGqSWc6kIBwcHWFpaQiwW49NPP9V1OJw//vgDS5YswYEDB5CamopWrVrh7Nmz6NGjR6nbpaamFhuqXZanunXrcvcJE1KUMEtazDb5cCO/a+t2ePTvP2AlErwJeYJGndx1GZ5Gye6ZrV7bBeKCAiS+iUJIwBV0HuEJAwPFX4jpM7FIxLXEm1tbo2HHLgg6JR0I8NW9QHQYMkKX4RENkI15Qao+yjV/UK6V4+npiXr16mH16tV49OgR/u///g+Ojo5Ys2YNt87KlSuxZMkSeHp6YtKkSUhMTMTvv/+OHj164PHjx7CxsSnXsf38/GBsbIx58+YhLy8PxsbG3AC5HTt2xOrVq/H+/Xts3rwZt2/fLnYssViM/v37o3Pnzli/fj2uXLmCDRs2oEGDBpg2bVqJx83IyEBQUBCmT5+ORYsW4ffff0dWVhbq1auHX375hRtJW1vU3jJ77do1+Pn5oV69evjqq68ASAcdatOmDfbv3y9XlIaEhODSpUtyhadAICjWKiob9ViRXbt2oaCggPt5+/btEIlEGDhwoBrPqnwEAgFGjhyJv//+GyEhIcWeLzqyr7aYmppi3bp1iIuLg1AoRFBQEPfFg0xAQECxPLi6uoJlWYWPot26CSlM1jL78L+nAIDazVpA8OFe97D7d3QWlzZkpUiL2Wq21dHqU+nvpYzE94j6r2p2sS482JeZlTUc6taDbU3pwHKh9wJ1FRbRINnUCqTqo1zzB+VaOW3btsXff/+NadOmYffu3Rg+fDj27NnDPR8dHY1ly5ZhxYoVOHr0KKZNm4alS5fi+vXrePv2LbZt21buYwuFQty5cwdz587FggULYGRkhPnz58PNzQ03b97EnDlzsHr1avz111+IiorCpk2bim0/ZswYLFiwAFOnTsXx48fRtm1bufgViYiIAMuyOHr0KPbu3Yu1a9fi0KFDcHBwwBdffKFwmlJNqlDL7Pnz5/Hy5UuIRCK8f/8e165dw+XLl1G3bl2cPn2am7sUANatW4eBAweiS5cu+Oabb7ipeaytreHj48Ot9/nnn+PAgQOwtrZG8+bNcffuXVy5coUbCbio/Px89O3bF56enggNDcW2bdvQrVs3uZGMdemXX37B9evX0blzZ3z77bdo3rw5UlJS8OjRI1y5cgUpKSll74QQPScbAKpPv34ApF1uG7TvjFf3AvHy9k10GTUWtjVr6TJEjZHdM2tha4dm3Xvj5qF9KMgT4snlf1G/XUcdR6d+ORkfxzYwt7IGwzBo/El33D/5J+LDXyHl3VvYOdfWYYRE3c6cOaPrEIiWUK75Q5O5vu6/CwnRZQ+0qi2Odeujt/fkcm0rm1NXpnv37jh58iQyMjJgZWWFEydOQCKRwNPTE0lJSdx6NWrUQKNGjXD9+nVuvl9VeXl5yQ2c++DBAyQkJMDHx0euBhs8eDCaNm2Kc+fOwdfXt1j8Dg4fB2vs3r0718O2JFkfetslJyfj3r173OC5Q4cORb169bBixQqtTuFVoWJ26dKlAKTT49jZ2aFly5b49ddfMWHCBG7wJ5lPP/0UFy5cwLJly7B06VIYGRmhZ8+eWLNmDerVq8ett3nzZggEAhw6dAhCoRBdu3bFlStXirUcymzZsgWHDh3C0qVLUVBQgLFjx+K3337j5pjVNScnJwQFBWH58uU4ceIEtm3bhurVq6NFixZyXRAIqapYluVa6+78f3t3HhdV9f8P/DULMMwgssjmAhqKC7ihYpa75RJprqiVuZUfzSX9fTIyNRGUUj7Jx0pEKrUPpmYU9k1zI9NcwQUTcwFUEBVFZBOGdeb8/hjnMsOAzMgMw8y8n48HD+Hccw/n8nbuzLlnSzqH4U+3WH1xwhSknj0JxuQ4E7cLry380Ii1NIzKinKuV9rO0Qk2YjE6DxiMywkHcSv5PAoeZMPB3cPItdQvaWEB973YXrGgXqeXByIx/kcAwJ/ff4PxH4c0mXs0abglS5ZoPPEn5olibTkMGeuczFu4e1VzxKIpqrkYrKOjIwDF1Dx7e3ukpaWBMaaxYK2S6o4sulJtPwHPXnC3U6dOOHlSfXSUSCSCi4sLsrKyuAVgVReyrYuyAd2uXTuuIQsoFuEdPXo0duzYgaqqKgiFBpnNquG5fsuMGTNqnaBcn2HDhmHYsGHPzOPg4ICtW7dqpNc1jFUsFnN7HNWlrnNrW+RJOZRWVUhIiFrvcV3n1vW7XF1d8fXXXzeZRZLKy8vx6aefqs2ZXbNmjVarj927dw9LlizB4cOHIZfLMWTIEERGRtKG2KROVRXlkFVVAQACXqpe8MzFsy18+g1A6pkTuHbqOPqMmQAXr3Z1FWOSSlTeECRPtyXr/upruJxwEGAMBzZtQNCqzyBopBt+YyhV6Zm1fdqYbdHGC35DhuPKn4eRcekC0hJPwefF/saqItGz+fPnG7sKpJFQrC2HIWPt6tW0PjM2pD7aLAbL4/Fw4MCBWvPa2dlx39f1kFcmk9V6bkP3AlaWqdozq42WLRVTh9zc3DSOubq6orKyEiUlJdwOMYZmPp+giNZmzJiBuLg4LF68GB06dMD27dvx2muv4c8//0T//nV/wCwuLsaQIUNQWFiITz75BFZWVoiMjMSgQYNw6dKlOoeCE8umXPwJADLvqq+m99LEN5F69iTAGPZGhGHK6vVo5qz7EvFNlXLxJwCwc1S8PlzbvoBur4zE5YSDuJ96DSd2fY/B08xnCwSpyh7W4uYO3PcD35qB9PNnUfakCEe3bYFzay84t25TSwnE1Pz111/PtXsBMT0Ua8thyFg/75BeU+Tt7Q3GGNq1awcfH59n5nV0dKx1wdvMzEytOo1UF9wdOnSo2rEbN25wx2sqLi5WG5Zcn5YtW8Ld3V1jhWQAuH//PkQikcYIXUMy2D6zpGlKSkrC7t278dlnnyEiIgJz5szB0aNH4eXlhY8++uiZ50ZFRSEtLQ379u3DRx99xPXQZmdnq60+TYgq5TBbALBzcFQ75ty6DfpNmAoAKHqUg5/WrMDDW+azB6vqHrN2jk7c90Omz4FLW8Ub04V98TgUvRGVZWWNXj9DKH1S3TMrUnnibNvMHoPengUAKCnIx+5VHyEz5VJjV48YgHJYHTF/FGvLQbHWj/Hjx0MgEGD16tUaozoZY3j8uPqht7e3N86ePYuKigoubd++fRpb+NSld+/ecHV1RXR0NMrLy7n0AwcO4Nq1awgMDKz1vLp6l59l8uTJyMrKwpEjR7i03Nxc/Prrrxg6dCj4/MZrYlJj1sLExcVBIBBgzpzqp2IikQizZ8/GmTNnnvmCiYuLQ58+fdCnT/WiNZ06dcKwYcOwZ88eg9abmC7V1W1dnw5NUdVv4lT0HKlYNTH//l3s+GQJ9m1cj7RzZ9QawqZIuZIxANg5VY9cEFpbY/SSj7lhuFf+PIKti+fg1I+xeHgrnRuWbYqUc2aFtmKNrYd8Bw3Dy0FvA1D8v4hbswI/hS3HtRN/oqTg2XN0SNPVqpV5Lt5GNFGsLQfFWj+8vb2xZs0a7Ny5E/3790dERASio6MRHByMjh07Ytu2bVzed999Fw8fPsTIkSMRHR2NpUuX4r333oO3t7dWv8vKygrr1q3D5cuXMWjQIGzcuBGffPIJJk6ciLZt29a5d7C1tbXO17Vs2TJ4eHhgwoQJCAkJQWRkJF5++WVUVlYiPDxc5/IawmSHGT/vvF1Ll5ycDB8fH9jb26ulBwQEAAAuXbrETQJXJZfLcfnyZcyaNUvjWEBAAA4fPownT54897CClKOHUZJ+7bnOJU1b3r3qByTnki9hxKQpasd5PB6GTH8P1ra2OPd/P0Muk+HG6b9w4/RfABSNQDtHJ4jsmkFk1ww2EjvwBXzw+QLw+HzwBQLw+Xzw+Mp/DfyMToeFizL/Vmy/IxAKIbJTf204urfEtHUb8ftX/8Hdq1dQnJ+Hs7/8iLO//AiBlRXsHJ0gdnCEpLkDRHb2EAiFEAiF4Cv/FQjB46vXhYcadVOpa70LLumS9xmyU68DACrkmusK8Hg8vDhhCuycnJHwXRRklZW4c+Vv3LnyNwBF721zVzdFnMUS2EgkEFrbKOL8NLbKf3l8Png8ftNcSEpPdWqS11aLP/74A8i+Y+xqEAPz6toDhw4d4j4vaKu0+AmkhQUoKy5GWXERKqRSyOVyyGUysKf/yuXV39e1JomxCIRW8On3Mpo5aT8FhsnlKH1ShJLCApQU5KO8pATyqkrIqqogl8kgk1VBXlWlfq01e+3UftDs0TMka5EtDp1O1DnW5VIpivNyUVZSgnJpMYoqZBA7OFavcs+Y4rq4+jetWOuioqwUAFBSmA9bYfXnjnKp4iG8tKgAJQWK0VkL586BZysPfB0Vza0m3KpVSwwZNBCvDB7I5evftw8+WxOGr6KisHjxYvj36IGfdv2AZSs+hayqistXWqyYzlNWUsylKU0aOwZ89h02/HcjgoODIRGLMTrwNYSFrIIV5Fz+qgpFz21JQR6Kip7AxkoIobWN1tfv5uaGkydP4sMPP0RkZCQqKyvRr18/7NixA927d9ftj9lAPNbU7hrEoPz8/ODm5qb48KHi6tWr8PX1RXR0NP71r39pnJebmwsXFxeEhoZi5cqVaseioqIwf/58XL9+vdYV1JRycnI09tZNT0/H2LFj8eGIgXBv3njj64lxvBXxNdw929Z5PO/+XZza8wNuXUjibrTmwN7FDe99Xfu+bXK5DFePH8XfCQfwID21kWtmOC07dsHU0PV1Hi/Oe4xzv/2CK38eRkVpaSPWjBDyPKxEtnhnQzQc6lkf40leLtISz+DWxSQ8yryttsK5qfL064ZJK+vubWKMITvtBq6fOo77qdfwKDMDcpnpjrABgI79B+P1enYZKH1ShOunjiMz5W9kp13XiHWXMZPg1bUHnCRiA9aU6ENzN3fY2jXO5/BbtxTbMtU1D/iff/6Bn58frly5Al9f33rLo2HGFqa0tBQ2NppPXpQTv0vr+FCpTH+ec5WioqLg5+en9jV27Fhdqk9MWD7jY9GHS7mN2D/55BOkpKRg586d2LlzJ1JSUvCfr6MwenEwjhaUY1zwKmQxK/j0GwCZXXPYubWEUNIMPCtrCEUiyHk8CK2sUUsHYJPCAHR7ZSR33UFBQZBKpQgLC0NSUhJ+/fX/kHQ7C31nvo9sVy+Mmv//kFUJdHp5EIr5Qjh4tAKzsoZQZAu+lTXQGL3PDcQTCPDLiTNIT0/nhjUpr3/69OnIy8vD5u+2gt/WB+2DZsC6e190DxyHQmsxvLr1RJEMcPRohSoeH0IbEcAXgCdQ9MQ38XATYrYqy0ox/713ERQUBAAa9/Id33+P6OVL8c382fhz+xZkXk42i4YsAGTfTOP2Aq15L1+7LBhbFr6HXSs/RPLB3/DwVrrJN2QBIPHYUcTHx2Pr1q0a9/JyqRQfvzkRMfNn4ui2Lbh5/qzZxNqSZWZmoqKiAjk5OSgsLMSTJ0/w4MEDVFVV4fbt2wCAtLQ0AEBWVhbKysqQm5uL/Px8lJSU4P79+5DJZLh586Za3rt370IqleLx48d4/PgxqqqqkJKSAkDz9RQWFsYd0xb1zOrJnj17MHfuXNy5c0dtmW1tREdHIzw8HGlpabU2FvWpqfbMJidfhG+XLg24MtLUWekwfOV5MLkccrkcugxbeq67n44n8fg8CITPv49cndWQy8FUr7VGtdRv7TWHqNUsjKnkbPhbAp8vMOh2Q4wxxfUzuZ7K00sxei1MH3EgRB/upFzC3vVhAIApq9ejVSfN9+rCnIfYE/oJih495NKaObugjW9XtGjjBTsn56dTRexgI5ZAIBQ+nTYgAF9QPWVEMX1AT8Pr9VBO0t44nP15FwDgg9hfIFSZW8gYw7n/+xmnfoyFXCYDAPAFAnh06Ah37w6wd3GDxMERkuaOENnZQWBlBb5ACL5QAIHQSnG9PPUHkxpVVp3+oTGNpO68DXE4+ktcP3UczVq4YM6mbRrHnzzORfznIXh0J4NLkzg4oo1vN7Ro4wV7VzfYSuxgLZagsKIK1iIR2rb14irMxZdX20UQY+HxeI02tUXfPbNGnzN7+vRpHD58GIsXL4aDg4Oxq/NcZDIZVq1ahYULF+rckAUU839DQkKwZcsWLFq0yAA1rObh4VHrUtrZ2dkAqveOqsnJyQk2NjZcPl3OVXJ1dYWrq2utx6ysrA3e2CHGN3r0aPz2228GKZvH50PQxHss9YnH5zfpjwEGjTWPB55AAED3FRiJ/hky1sT4JM2rV7Vd/vFH2L53n9rx4vw8xK1ZwTVkPTp0xKC3Z6Nlx84mM++7LvYq+28W5+fBwc2d+/nS4f04sXM7AIAvECJg7ER0f/U1tZXrTZHk6a4DBTU6HwCgKDcHu1Yu5RY3bOnTGf0mToVXt561xrrsaaPFEA90if6kpaWhQ4cOxq7GczP6J7/Tp09j9erVte6rZCp+++033LhxQ22FYF2IRCJMnz4dGzZsMPik/h49eiA1NRVFKntBAkBiYiJ3vDZ8Ph9du3bF+fPnNY4lJibihRdeaNQ9pYhpog+8loNibTko1uZNdfG6pTVWQ5XLZYhftxoFDxUPtXsFjsXU0Ai06tTF5BuyQPX+4ID6vuEP0lNx7Ptvn+Zxwptr/oOXg942+YYsUL0/uIAHjS3j/tgazTVkuw8PxOSQz9G2u79ZxNqSmXJDFmgCjVldyOVylDXBvRi3bduGl19+uUHLmAcFBSEzMxN//vmnHmumaeLEiZDJZIiJieHSysvLsW3bNvTt25dbyfjOnTu4fv26xrnnzp1Ta9DeuHEDR48exaRJkwxab2IelHOOiPmjWFsOirV5s1EZcfbzj7vVjt049Rdybivmx3UdOhyDps1u8nP6daG6pZqyEVdVUYF9G9dBLqsCXyDA60uWwe2F9saqot7Zqux2IS0q4L5PP5+IWxeSAABdBgzBsFlzwX+O/UlJ03P37l1jV6FBjHrHCQkJwdKlSwEA7dq148ZrZ2RkAFAMJVuwYAF++OEH+Pr6wsbGBgcPHgQA/Oc//8FLL70EZ2dn2NraolevXoiLi6v19+zYsQMBAQEQi8VwdHTEwIEDcfjwYbU8Bw4cwIABAyCRSNCsWTMEBgbin3/+qfcaysrKcPDgQbzyyisax5T137t3L/z8/GBjYwNfX1/uGlT16tULTk5O+PXXX+v9nQ3Rt29fTJo0CcuWLcNHH32EmJgYDB06FBkZGVi/vnrl0XfeeQedO3dWO/f999+Ht7c3AgMDERERgf/+97949dVX4ebmhn//+98GrTcxD1OnTjV2FUgjoVhbDoq1ebMRi7n5mF1VPhfIZTKc+VnRuBU3d8CQGXPMrodOtae1JF+xpcmNMydQmKMYUt1/6nS06ti51nNNlfjp/ucAuC11KivK8ef2LQAAG4lE8dBCy1jT0jxNn5NT444o0Pf/CaM2ZsePH8+9CUZGRiI2NhaxsbFwUZmjcPToUSxZsgSTJ0/Gxo0b0bZtWwDAxo0b0bNnT4SGhiI8PBxCoRCTJk3C/v371X7H6tWrMW3aNFhZWSE0NBSrV69GmzZtcPToUS5PbGwsAgMDYWdnh3Xr1mHlypW4evUq+vfvzzWs63LhwgVUVFTA39+/1uMnT57E+++/jylTpmD9+vUoKyvDhAkT8PjxY428/v7+OHXqlDZ/ugb53//+h8WLFyM2NhaLFi1CZWUl9u3bh4EDBz7zvGbNmuHYsWMYOHAg1qxZg5UrV6J79+44fvy4WswIqYuuK9QR00WxthwUa/PG5wsUDVoAD1T2Db928hjysxVrcAS8MQlWNiKj1M+QRHbNILBSzPcsftqYvXRY8TlT3NwB/qNGG61uhiK2d+C+L306Je3mubMoepQDAOg/ZTo3FLk+PB7v6cKMpCmrbzcSfWOM6fXBl1EXgOrWrRv8/f2xa9cujB07lmuoqrpx4wZSUlLQpcZKt6mpqbC1teV+XrBgAfz9/bFhwwYEBgYCUKyUGxoainHjxiEuLg58laEvyqcCxcXFWLRoEd599121obfTp09Hx44dER4erpZek3Iobrt27Wo9fu3aNVy9ehXe3t4AgCFDhqB79+7YtWsXFixYoJb3hRdeQGxsbJ2/S19EIhEiIiIQERFRZ55jx47Vmt66dWv89NNPBqoZIYQQQpoakV0zlJeUQF5ZwaVd2BcPAJA4OqHbqyONVTWD4vF4sHN0QmHOQxTnPcaDm2ncfuDdXhlplgsb2ar2zD7dbufGmZMAABuxBF2Hvqp1WVZWVigrK0NVVRWEBlzhnpiOiooKVFZWQizW397DTX5iw6BBgzQasgDUGrL5+fkoLCzEgAEDcPHiRS597969kMvl+PTTT9UaskD10uBHjhxBQUEBpk6ditzcXO5LIBCgb9++9c5hVfawOjo61nr8lVde4RqygKIBb29vzy1LrcrR0RGlpaWQSqXP/J2EmKquXbsauwqkkVCsLQfF2vyJJIpFoCRPtw988jiX25ql27CRZr0bgeTpIlDF+Y9x6ZCiV5bH56PbMPNswIvV5swWoqJUituXFGultO/TT6cGvP3TsnJycmi4cROm2qYypIqKCm4HFHuV/2cN1eQfk9TV47lv3z6sWbMGly5dQnl5OZeu2m198+ZN8Pn8WhvDSsoNfYcOHVrrcW3/2HW9SD09PTXSHB0dkZ+fX2cZ5jbnhBClXbt20QdfC0GxthwUa/MneroI1IO7imHGGX9Xdxy069nLKHVqLMpFoIoe5eDBTcVnxva9X0Qz5xbGrJbBWIlsIbSyRlVlBUqfFOHmhSTIKisBAB379deprGbNmkEsFqOwsBDFxcUQCAT0GbcJkkqleu0prYkxBsYYKp/+P3JycoJEItFb+U2+MVvb04ITJ05gzJgxGDhwIKKiouDh4QErKyts27YNO3fu1Kl85Vj+2NhYuLu7axyvb1iEs7PiJpefn4/WrVtrHBfUsdJbbY3f/Px8iMVigz8hKSgowEcffYT4+HhIpVIEBATgiy++qHPer6qkpCRs374diYmJuHz5MqqqquhpG9FaeHi4satAGgnF2nJQrM2fSKJozLo6KUahKRuzIrtmZrWSb22Ui0Ap54wCQIeAfsaqjsHxeDzY2jfHk8ePIC0s4IYYiyR28OzaXeeyWrVqhfz8fBQXF9PnxSbKkA1ZQPH/gM/nQywWw97eHhKJxHzmzALP1wv5888/QyQS4dChQ7CxqR7asm3bNrV83t7ekMvluHr1ap37pyqHALu6uta6InF9OnXqBAC4fft2g59M3759W2MFYX2Ty+UIDAzE33//jaVLl6JFixaIiorC4MGDceHChXr3mvr999/x7bffolu3bnjhhReQmppq0PoS8zJ69Gjak9JCUKwtB8Xa/Cl7ZnPu34dcLsOdlEsAAK+uPcDnm/f2LKrb8yi1NLMVjGuytbfHk8ePUJSbg+y0GwAA7z4vPtccYaFQCBcXF1ootAkz9Xu40efMKruZCwoKtD5HOUxBJpNxaRkZGdi7d69avrFjx4LP5yM0NFRjNTXl06ERI0bA3t4e4eHhXPe3qkePHj2zLr169YK1tbXa3qvP6+LFi3jppZcaXM6zxMXF4fTp09i+fTtWrVqF+fPn49ixYxAIBFi1alW958+bNw+FhYU4f/48Xn1V+0UACAFg0jdLohuKteWgWJs/kZ1izqw1n48H6akoKykGALTtXv+ILlOnuj0PoFjwyt7FzUi1aRzK1YqzU69zQ4zb9ehtxBoRQzL1e7jRG7O9einmWixfvhyxsbHYvXs3SkpKnnlOYGAgpFIpRo4ciejoaISGhqJv375o3159qEv79u2xfPlyxMfHY8CAAfjiiy/w9ddfY/r06dwm7/b29ti8eTNOnDgBf39/rF27FjExMVixYgV69uyJ1atXP7MuIpEIw4cPR0JCQgP+CootfvLy8vDGG280qJz6xMXFwc3NDePHj+fSXFxcEBQUhF9//VVt/nFt3NzcGm2iODE/QUFBxq4CaSQUa8tBsTZ/ymHGjMmRevYkl+7VvaexqtRoavbMtvTpZPbzPsXNFOvFyKqquDTXtrWvYUNMn6nfw43emO3Tpw/CwsLw999/Y8aMGZg6dWq9vaFDhw7Fd999hwcPHmDx4sXYtWsX1q1bh3HjxmnkDQ0NxdatW1FaWorly5fj008/RWZmJoYNG8blefPNN/HHH3+gVatWiIiIwAcffIDdu3ejR48emDlzZr3XMGvWLJw9exZZWVn15q3LTz/9BE9PzzoXotKX5ORk+Pv7a6zuHBAQAKlUSsOGiUFt377d2FUgjYRibTko1ubP5ukwYwC4dfEcAMC5tSeaOZnnIkiqavbMtupY96Ki5kJ1ex4AsLIRwcHNw0i1IYZm6vdwo8+ZBYAVK1ZgxYoVGunPmig+a9YszJo1SyM9JCREI23mzJn1NkoHDx6MwYMH11vX2owZMwYdOnRATEwMwsLCuPS66p+RkaH2c3l5Ob7//nt8/PHHBn/al52djYEDB2qke3goblL379832KqUOTk5Gg8q0tPTDfK7SNP0xRdfYOXKlcauBmkEFGvLQbE2f8phxgCQn30fANDCs62RatO47Bxr9Mya+XxZoHqYsVILTy/w+Ebv/yIGYur3cPqfqQcCgQChoaHYtGkTiouLdT5/27ZtsLKywty5c3U6Ty6Xo6ysTKsvZcO6tLRUbdEsJZFIxB03lKioKPj5+al9jR07FgBw8uRJHD9+HBEREcjLy8P06dMBKCalA8CSJUuQnp6OrVu3Ij4+HklJSQgLC4NUKuWGRyjzfvLJJ0hJScHOnTuxc+dOpKSkcMPKlXmCgoIglUoRFhaGpKQkxMfHY+vWrUhPT8eSJUvU8k6fPh15eXmIiIjA8ePHcfDgQWzatAn37t3jYqbMO3fuXNy7dw+bNm3CwYMH6ZpqXNOIESPM7prMMU76uKby8nKzuyZzjJM+rik5Odnsrskc49SQa7p9R3Pk2aHjf5n0NWkbp59++QVCG8VnJKGVNf615N8mf031xSnh+HG1WNs4OJv8NZljnPR1TYcPH25S15SSkgJd8Bitk22yjh07hiFDhmiV99q1a+jUqRPs7OwwefJkfPfdd2rHf//9dwQGBuLgwYMYMWKEVmUuWLAAmzZt0nqp9bp6ZseOHYsrV67A19dXq3KI6YqPj691OgAxPxRry0GxNn+P7mTgf0sXqKW9tmgpOr88yEg1alzffzgfuVmZaN3ZD5NDPjd2dQzu5oVE7F1fPdJw2Oz30WP4a0asETGkpnYP/+eff+Dn56d126BJDDMmz6dTp04a2xHVRTmM2MPDA9nZ2RrHlWktW7bUXwVrcHV1haurq8HKJ01ffn6+satAGgnF2nJQrM2fSGXOrJKTRysj1MQ4+o4Lwvl98XhxwhRjV6VR2DZTnzPr4kWLP5kzU7+HU2PWhLm7u2PGjBk6ndOjRw+cOHECcrlcbRGoxMREiMVi+Pj46LmWhFSrbb42MU8Ua8tBsTZ/ytWMVTl6GO7hd1PT6eVB6GQhvdCA5pxZF08v41SENApTv4fTnFkLM3HiRDx8+BC//PILl5abm4uffvoJo0ePVptPe/PmTdy8edMY1SRmatOmTcauAmkkFGvLQbE2f0JrGwisrLifJY5OsLYVG7FGxJDE9vbc983d3CnWZs7U7+HUM2thJk6ciBdffBEzZ87E1atX0aJFC0RFRUEmk2nsqavcvkh19eXMzEzExsYCAM6fPw8AWLNmDQDAy8sL06ZNa4SrIKYqMjLS2FUgjYRibTko1uaPx+NBJLFDSYFiOKIlDTG2RFYiWwisrCCrrISLJw0xNnemfg+nnlkLIxAI8Pvvv2Py5Mn48ssvsXTpUrRo0QJHjx5Fx44d6z3/9u3bWLlyJVauXInExEQA4H6uuagUITUpV62zNJa4zp6lxtoSUawtg+r2PI6W1pi1sHs4j8fDg9JKAIBPv/5Grg0xNFO/h1Nj1gI5Ojri22+/RW5uLkpKSnDs2DH07t1bI19GRobGnriDBw8GY6zWr2PHjjXOBRCTlHArAUf6HkHCrQRjV6VRJdxKgO1aW4u6bkuNtaX67bffjF0F0ghElVXc944tLagxm5AA2Noq/rUUCQn4bH8C/vXWexazYrUlM/V7ODVmCSEGxxjDxwkfozyuHMsSlllMTyV33TLLuW5LjbUlU+4/SMwYY7C5dYv70WKGGTMGfPwxUF4OLFtmGT20T695Rnk57MLWWMY1WzhTv4dTY5YQYnD70/bjQvYFYARwPvs8fk/73dhVahTcdcNyrttSY23JTH2+FdHC/v2wzaneJ94xNc2IlWlE+/cDFxT3cJw/D/xuAfezp9ccCVjONVs4U7+HU2OWEGJQjDGEHAsBDzwgGeCBh5BjIWbfY6d23bCM67bUWFs6Wi/BzDEGhITAtkIxh1Igk6H5hv+af4/d0+sGT3EPB4+n+Nmcr1vlmr8DLOOaicnfw6kxSwgxKGVPHQMDWgEMzCJ67NSuG5Zx3ZYaa0sXEBBg7CoQQ3raU+d3KwuS3Hz0T7kBviX02Cl7ZZUNOcbMv6dS5ZoDAMu4ZmLy93DamocYVXl5OQAgPT3dyDUhhsAYQ3BcMKAcnfYIwNPt6oJ3BsNrohd4yqfeZkTjulWY63VbaqwJcP36dbRo0cLY1SCGwBgQHKz4/kkxeEdPwxbAP4Ai3curuufSnKhed03met01rvk6AO5Vba7XTAA0vXu4sk2gbCPUh8do/Bcxou+//x4zZswwdjUIIYQQQgghTcTevXvxxhtv1JuPemaJUfn4+AAA9uzZgy5duhi5NsSQ0tPTMXbsWOzduxft27c3dnWIAVGsLQfF2nJQrC0HxdpyNMVYl5eXIysrC4MGabctFDVmiVHZ29sDALp06QJfX18j14Y0hvbt21OsLQTF2nJQrC0HxdpyUKwtR1OLtb+/v9Z5aQEoQgghhBBCCCEmhxqzhBBCCCGEEEJMDjVmCSGEEEIIIYSYHGrMEqNycXHBqlWr4OLiYuyqEAOjWFsOirXloFhbDoq15aBYWw5ziDVtzUMIIYQQQgghxORQzywhhBBCCCGEEJNDjVlCCCGEEEIIISaHGrOEEEIIIYQQQkwONWYJIYQQQgghhJgcaswSQgghhBBCCDE51JglRlFeXo7g4GC0bNkStra26Nu3L44cOWLsapEazp07hwULFsDX1xcSiQSenp4ICgpCamqqRt5r165h5MiRsLOzg5OTE6ZNm4ZHjx5p5JPL5Vi/fj3atWsHkUiEbt26YdeuXbX+fm3LJIaxdu1a8Hg8+Pn5aRw7ffo0+vfvD7FYDHd3dyxatAjFxcUa+XR5rWtbJtGPixcvYsyYMXBycoJYLIafnx++/PJLtTwUZ9OXlpaGKVOmoHXr1hCLxejUqRNCQ0MhlUrV8lGsTUtxcTFWrVqFkSNHwsnJCTweD9u3b681rzHfn3Upk9ROm1jL5XJs374dY8aMQZs2bSCRSODn54c1a9agrKys1nK/++47dO7cGSKRCB06dMBXX31Va7579+4hKCgIDg4OsLe3xxtvvIFbt241qEy9YoQYwZQpU5hQKGQffvgh27JlC+vXrx8TCoXsxIkTxq4aUTFhwgTm7u7OFi5cyL755hsWFhbG3NzcmEQiYSkpKVy+rKws1qJFC+bt7c02btzI1q5dyxwdHVn37t1ZeXm5Wpkff/wxA8Dee+89FhMTwwIDAxkAtmvXLrV8upRJ9C8rK4uJxWImkUiYr6+v2rHk5GQmEolYz5492ebNm9ny5cuZjY0NGzlypEY52r7WdSmTNNyhQ4eYtbU169u3L9uwYQOLiYlhwcHBbOnSpVweirPpu3PnDnNwcGBeXl7ss88+Y1u2bGEzZsxgANiYMWO4fBRr03P79m0GgHl6erLBgwczAGzbtm0a+Yz9/qxtmaRu2sT6yZMnDAB78cUX2Zo1a1hMTAybOXMm4/P5bPDgwUwul6vlj46OZgDYhAkTWExMDJs2bRoDwD7//HONcjt06MBcXV3ZunXr2IYNG1ibNm1Y69atWW5u7nOVqW/UmCWNLjExkQFgERERXFppaSnz9vZm/fr1M2LNSE2nTp3SeGNKTU1lNjY27K233uLS5s2bx2xtbVlmZiaXduTIEQaAbdmyhUu7e/cus7KyYvPnz+fS5HI5GzBgAGvdujWrqqrSuUxiGJMnT2ZDhw5lgwYN0mjMjho1inl4eLDCwkIu7ZtvvmEA2KFDh7g0XV7r2pZJGq6wsJC5ubmxcePGMZlMVmc+irPpW7t2LQPArly5opb+zjvvMAAsLy+PMUaxNkVlZWUsOzubMcbYuXPn6mzMGvP9WZcySd20iXV5eTk7deqUxrmrV69mANiRI0e4NKlUypydnVlgYKBa3rfeeotJJBLuvsAYY+vWrWMAWFJSEpd27do1JhAI2LJly56rTH2jxixpdEuXLmUCgUDtDY4xxsLDwxkAdufOHSPVjGjL39+f+fv7cz+7urqySZMmaeTz8fFhw4YN437etGkTA8D++ecftXw7d+5kANSe7GtbJtG/48ePM4FAwC5fvqzRmC0sLGRCoVCtB48xxRupnZ0dmz17Npem7WtdlzJJw23evJkBYFevXmWMMVZcXKzRqKU4m4fg4GAGgD169Egjnc/ns+LiYoq1GXhWY9aY78+6lEm086xY1+by5csMAPvyyy+5tP379zMAbP/+/Wp5T58+zQCw2NhYLq1Pnz6sT58+GuUOHz6ceXt7P1eZ+kZzZkmjS05Oho+PD+zt7dXSAwICAACXLl0yQq2IthhjePjwIVq0aAFAMZciJycHvXv31sgbEBCA5ORk7ufk5GRIJBJ07txZI5/yuK5lEv2SyWRYuHAh3n33XXTt2lXjeEpKCqqqqjRiY21tjR49emjEW5vXui5lkoZLSEiAvb097t27h44dO8LOzg729vaYN28eN7eK4mweBg8eDACYPXs2Ll26hKysLPz444/YvHkzFi1aBIlEQrE2Y8Z+f9a2TGI4Dx48AADuMxtQ/XevGcNevXqBz+dzx+VyOS5fvlxnrG/evIknT57oVKYhUGOWNLrs7Gx4eHhopCvT7t+/39hVIjr44YcfcO/ePUyePBmAIp4A6oxpXl4eysvLubxubm7g8Xga+YDq2OtSJtGv6OhoZGZmIiwsrNbj9cVG9fWr7WtdlzJJw6WlpaGqqgpvvPEGRowYgZ9//hmzZs1CdHQ0Zs6cCYDibC5GjhyJsLAwHDlyBD179oSnpyemTJmChQsXIjIyEgDF2pwZ+/1Z2zKJ4axfvx729vYYNWoUl5adnQ2BQABXV1e1vNbW1nB2dubiooyltq95bco0BKHBSiakDqWlpbCxsdFIF4lE3HHSNF2/fh3z589Hv379MH36dADV8aovpjY2NlrHXpcyif48fvwYn376KVauXAkXF5da89QXG9XXr77iTfcE/SouLoZUKsXcuXO51YvHjx+PiooKbNmyBaGhoRRnM9K2bVsMHDgQEyZMgLOzM/bv34/w8HC4u7tjwYIFFGszZuz3Z/q8Z1zh4eFISEhAVFQUHBwcuPTS0lJYW1vXeo7q61PbWOtSpiFQY5Y0Oltb21p71ZTD22xtbRu7SkQLDx48QGBgIJo3b464uDgIBAIA1fHSJqbaxl6XMon+rFixAk5OTli4cGGdeeqLjWpc9BVvirV+Kf+eU6dOVUt/8803sWXLFpw5cwZisRgAxdnU7d69G3PmzEFqaipat24NQPHgQi6XIzg4GFOnTqXXtBkz9vszfd4znh9//BErVqzA7NmzMW/ePLVjtra2qKioqPU81denrrHWpkxDoGHGpNF5eHhww1RUKdNatmzZ2FUi9SgsLMSoUaNQUFCAgwcPqsVIOdSkrpg6OTlxT/U8PDzw4MEDMMY08gHVsdelTKIfaWlpiImJwaJFi3D//n1kZGQgIyMDZWVlqKysREZGBvLy8uqNTc3/G9q81nUpkzSc8u/p5uamlq4cHpafn09xNhNRUVHo2bMn15BVGjNmDKRSKZKTkynWZszY78/alkn068iRI3jnnXcQGBiI6OhojeMeHh6QyWTIyclRS6+oqMDjx4+5uChjqe1rXpsyDYEas6TR9ejRA6mpqSgqKlJLT0xM5I6TpqOsrAyjR49Gamoq9u3bhy5duqgdb9WqFVxcXHD+/HmNc5OSktTi2aNHD0ilUly7dk0tX83Y61Im0Y979+5BLpdj0aJFaNeuHfeVmJiI1NRUtGvXDqGhofDz84NQKNSITUVFBS5duqQRb21e67qUSRquV69eABQxV6Wc0+Ti4kJxNhMPHz6ETCbTSK+srAQAVFVVUazNmLHfn7Utk+hPYmIixo0bh969e2PPnj0QCjUH4Sr/7jVjeP78ecjlcu44n89H165da411YmIiXnjhBTRr1kynMg3CYOskE1KHs2fPauxTV1ZWxtq3b8/69u1rxJqRmqqqqtiYMWOYUCjUWG5d1dy5c5mtra3atkoJCQkMANu8eTOXlpWVVeeec61atVLbc07bMol+PHr0iMXHx2t8+fr6Mk9PTxYfH88uX77MGGNs5MiRzMPDgxUVFXHnf/vttwwAO3DgAJemy2td2zJJw128eJEBYG+++aZa+tSpU5lQKGT37t1jjFGczcHrr7/OrK2t2Y0bN9TSx44dy/h8PsXaTDxruxZjvj/rUibRzrNiffXqVebs7Mx8fX2fua+rVCplTk5O7PXXX1dLf/vtt5lYLGaPHz/m0j7//HMGgJ07d45Lu379OhMIBCw4OPi5ytQ3aswSo5g0aRK3B92WLVvYSy+9xIRCITt+/Lixq0ZUfPDBBwwAGz16NIuNjdX4Urpz5w5zdnZm3t7e7Msvv2Th4eHM0dGRde3alZWVlamVuXTpUgaAzZkzh33zzTcsMDCQAWA//PCDWj5dyiSGU3OfWcYYu3DhArOxsWE9e/ZkmzdvZsuXL2cikYgNHz5c43xtX+u6lEkabtasWQwACwoKYps2bWKTJk1iANiyZcu4PBRn06fcM9rV1ZWFhoayTZs2sVGjRjEA7N133+XyUaxN01dffcXCwsLYvHnzGAA2fvx4FhYWxsLCwlhBQQFjzPjvz9qWSZ6tvlgXFRWxNm3aMD6fzz7//HONz2unT59WK0+5B/DEiRPZN998w9555x0GgK1du1YtX1FREfP29maurq5s/fr1LDIykrVp04a1bNmS5eTkPFeZ+kaNWWIUpaWl7MMPP2Tu7u7MxsaG9enThx08eNDY1SI1DBo0iAGo80vVlStX2PDhw5lYLGYODg7srbfeYg8ePNAoUyaTsfDwcObl5cWsra2Zr68v27FjR62/X9syieHU1phljLETJ06wl156iYlEIubi4sLmz5+v1gOjpMtrXdsyScNVVFSwkJAQ5uXlxaysrFj79u1ZZGSkRj6Ks+lLTExko0aNYu7u7szKyor5+PiwtWvXssrKSrV8FGvT4+XlVef78+3bt7l8xnx/1qVMUrf6Yn379u1nfl6bPn26RpkxMTGsY8eOzNramnl7e7PIyEgml8s18mVlZbGJEycye3t7Zmdnx15//XWWlpZWaz21LVOfeIzVmJVNCCGEEEIIIYQ0cbQAFCGEEEIIIYQQk0ONWUIIIYQQQgghJocas4QQQgghhBBCTA41ZgkhhBBCCCGEmBxqzBJCCCGEEEIIMTnUmCWEEEIIIYQQYnKoMUsIIYQQQgghxORQY5YQQgghhBBCiMmhxiwhhBBCCCGEEJNDjVlCCCGEEEIIISaHGrOEEEIIIYQQQkwONWYJIYQQQgghhJgcaswSQgghhBBCCDE51JglhBBCCCGEEGJyqDFLCCGEEEIIIcTk/H9UUvBIdJLsOQAAAABJRU5ErkJggg==", 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\n", 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", 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\n", 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", 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\n", + "image/png": 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Px+XLl3HlyhWcOnUK/v7+yMjI4DMx9+nTB6GhoSgtLcWvv/6K7OxszJ49G+7u7g1+f6xZsWIFjh07hnXr1uHff//FqFGjkJ+fj127dqGsrAzr1q1rla6rU6dOxSeffGI1eAe4ruGXLl3Chg0bsG/fPowePRohISHIzc1FYmIiTpw4gffff59PFiYWizFnzhwsXboU/fr1w/jx46HT6fDnn38iODgYwcHBjS6jvd+re+65B3K5HFFRUXB3d8e1a9ewf/9+yOVy7Nu3r0nHRAghpJHsPDUQIYQ4nfrmma3Lpk2b2Ntuu411cXFhfXx82HHjxrGXL1/m5/08dOiQxWuuXLnCPv3002xwcDArFotZf39/dvjw4eyXX35psW5ycjL78ssvsxEREaxUKmXd3d3Zbt26sU899RS7Z8+eRh/r9OnT+Tk3z507Z7PjgpV5ZlmWZVNTU9mYmBjWy8uLlclk7IABA9gff/yxznlOS0tL2ffff5+Njo5mXV1dWZlMxoaFhbEPPvgg++WXX7Ll5eUsy3Jzzy5evJgdNWoUGxwczEokEjYwMJAdMWIEu2PHDrO5TutS35yrRUVF7JtvvslGRESwEomE9fDwYO+++272999/b/S26lJzntmaDh48yNddzXlmWZZlDQYD++2337KjR49mvby8WLFYzAYHB7NDhw5l33//fTY1NdVi/Q8++IDt3LkzKxaL2dDQUPaNN95gKyoq6pxntuacsKZs+V5ZK0NdPvzwQzY6Opr18PBgJRIJGx4ezr700ktm8zcTQghpWQzLsqwdYmhCCCGEEEIIIaTJaMwsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsIYQQQgghhBCHQ8EsaZTDhw+DYRir/06fPm3v4hFCCCGEEEKchMjeBSCOafbs2bj99tvNlkVERNipNIQQQgghhBBnQ8EsaZJhw4bh0UcftXcxCCGEEEIIIU6KuhmTJisrK4NOp7N3MQghhBBCCCFOiIJZ0iTPPvssFAoFZDIZRo0ahXPnztm7SIQQQgghhBAnQt2MSaNIJBJMnDgRDz74IHx9fREXF4ePPvoIw4YNw8mTJ9GvX79aX5ubm4u8vDyzZaWlpUhISEDv3r0hlUpbuviEEEIIIYSQNkqtViMtLQ0jRoyAp6dnveszLMuyLV8s0p4lJSWhT58+GD58OA4ePFjreosWLcLixYtbsWSEEEIIIYQQR7N371488sgj9a5HwSyxicmTJ+Onn36CUqmEUCi0uo61ltm4uDjExMRg7969lA25HcjM/AH5+X+jc5f/wc010uL5kpISeHh42KFkpLVRXTsPqmvnQXXtPKiunUdbq+ukpCSMGzcO58+fR3R0dL3rUzdjYhOhoaHQaDSoqKiAQqGwuo6/vz/8/f2tPhcREYFevXq1ZBFJK8gveAr+AaVwdz+Fnj3GWTy/atUqvPHGG61fMNLqqK6dB9W186C6dh5U186jrdZ1Q4cfUgIoYhM3b96ETCaDm5ubvYtC7MRg0EGnKwUAVJQnWF1n4MCBrVkkYkdU1+0Ly7KoqLgJg0Fr8RzVtfOgunYeVNfOw9HrmoJZ0ig1uwkDwKVLl/DLL7/g3nvvhUBAHylnpdeX8Y/LKxLBsgaLdSorK1uzSMSOqK7bD52uApcuP4/TZ+7BtevzLZ6nunYeVNfOg+raeTh6XVM3Y9IokyZNglwux5AhQ+Dv74+4uDh89dVXcHFxwYoVK+xdPGJHWm0J/9hgqIRKlQ65vKPZOjdu3GjtYhE7obq2HZY1QKsthETi2+r71mpLceHiMygriwUAZGf/jC5dXodMGsivQ3XtPKiunQfVtfNw9LqmZjTSKOPGjUN+fj7WrFmDl156Cd9//z0mTJiAc+fOoUePHvYuHrEjYxdjo/KKRIt1xo0b10qlIfZGdW07V67OwbHjg5CV9WOr7zs9fQsfyHIMyM76yWwdqmvnQXXtPKiunYej1zW1zJJGmT17NmbPnm3vYpA2SFsjmK0oT4Cf711my5YuXYoNGzYAAJTKFBQUHEFg4HiIxdaThhHHZVrXzVVengCZLAgikTtYloVKlQaZLBQMw9hk+20Zy7LIzz8EAMjI2ImgoImtuv+ysqsAAJmsA0RCV5RXxCMz8wd06jQDDMPdD7dlXZO2jeraediqrg0GA3JycqBWq2EwWA4/IvZ3/vx59O/fv0X3wTAMxGIxFAoF3N3dbfr7TS2zhBCbsGyZtUwCZfrDeDXudSQkLsH1+LdbvGztiaPMpmarC97cvN9x5uwD+PfcBLCsAfEJi3Dy1CjcTP7YJttv63S6MhgM3HimktKL0GgKoNWWQqstreeVtlGhTAYAuLl1Q3DwJABApSoVRUWn+HUouLEdg0GHa9fmIyFhaZs816munYetAtnU1FQUFxdDo9G0yc80QYsHsizLQqfToaysDBkZGUhNTYVOp7PZ9p2+ZZZhGCxcuBCLFi0CAGzevBnPPvsskpOTERYW1qhtHT58GKNGjcKhQ4cwcuRIAMDIkSORn5+PK1eu1PnalJQUhIeHY9OmTZg6dSoAYNGiRVi8eLHZyR8WFoaRI0di8+bNjSobIdbodGVgWQPE4ubPL6YzGTMLABVWgtmxY8di3759AIDS0gsAgNzc32AwrIFAIObXKyuLw/X4d+Dh0R+REQucogWuIVSqTJw/PwkisSciI96Ct/dQ/jmW1YNhrM/xbA+mdd0cGRk7AQBK5U1UVt5Cbu6BquXfoXP4nDZ1zC1Brc42+YtFesZ2ZGRsh8GgxsDb90EuD22xfRsMOlRW3gIAuLiEIzBwHJJurIDBoEFa+rf8589WdU2AwsJjyMzaBQAIDHwECkUfO5fIHNW187BFXefk5KCyshLe3t7w9/en3/I2KjExEZGRkS2+H51Oh9zcXJSUlKCoqAh+fn422W67bJndvHkzGIap9d/p06ftXUSbiYuLw6JFi5CSkmLvohAHo9WW4MTJEThx8k6o1bnN317NbsYVN2EwmN95M/4w6nRlZsuLi88iK2sPkpPXoaj4X1y8NA2lpZeQlvYN8vJ+59fT69Uor5r2h2X1SE3diLS0Lc0uu6PIzNwFlToT5eVxuHDxGcRdewsGgw7X4xfi8JHeyM7+2d5F5NniglerLTFrAczL+wNabUHVcwUoLj7X7H20dWqN+bmZnLwWGk0+dLoyZGbthlqdg9grs5GZucvm+1ap0sGy3FQ8Li6dIRZ7IDBgHAAgP/8vvgvyDz98iZOnRuP4iaFIurEKKlWWzcviLIw3DwBAafK4raBA1nnYoq7VajWEQiEFsm1cawSyACASiRAUFAShUIjy8nLbbddmW2qDlixZgvDwcIvlERERtb7m6aefxuOPP97giXpNDR8+HJWVlZBIJI1+badOnVBZWQmxWFznevHx8WbT38TFxWHx4sUYOXJko1uSiXMrLb0MnY5rTS0uOYcA/webtb2a3YxZVoPKyltwde3CL5sxYwY2bNhgETwnJC5FhTFhVDIsnvP2HgadrgTn/3sCKlUaOoQ8DaHIFbducd2g3Nx6wMvLsedJa4j8gkNmf2dl/YDS0ov8e5eWthmBgY/Yo2gWjHXdHPn5f4Nlq2+IZGR+b/Z8bt5BeHkNgsGgw83kT8CyOnQOnwOhUG62HpcNuBgSiXezymMP5i2z5nJz90OpvInc3N+Qm7sfUmkAfHxG2GzfSmX1yegi535Lw8JmIiv7R7CsHsnJn6FPnw3Yum0SOnfOBADcurUB2Vl7MGTIEbPeFqRhVKpM/rHa5HFbYYvzmjgGW9S1wWCAUCikQLaNu3XrFjp16tQq+2IYBkKh0KZdztt1MPvAAw9gwIABjXqNUCiEUNi0bmsCgQAymaxJr2UYpkGvbUqQTYg1Gk31nMFqdU6zt1ezmzEAlFfEmwWz7777btX+zC/QK6xkPlYo+qG09ALU6mxcuvw81OocqFRpAID0jK1m6xYUHm33waxanYOyMm64QnBQDEpKL6KiIsHsvSstuwKdrgwikbu9iskz1nVz5OYdNPu7skZLVV7eH+ga+S7S0jfh1q0vAABFRadxW5+vIJX6A+Ba8C/HzkR+/t/oGvkeQkOnNLtcrUlTR68JpTLZLOC8GvcGBg36DVKJL/R6FbTaIkilgU2+kDQLZl07AwDk8o4IDJyArKwfkJf/J7KyfkLnztz3h1DoAr1eCbUmB8Ul5+DtdUeT9uvMKlXp/OO22ML97rvvoqjoNG7c+AihHadZvQmqVudBIBBBLPayQwlbV37+P2AYEXx8hjfqdVptERKTVsDbaygCAx+uc92KCu6GlbsiCr4+I5tR2saxxXc4AApk2ziNphABAa17o9fWn4l22c24OYxdlE277RoMBixatAjBwcFwcXHBqFGjEBcXh7CwMH58K8CNmWUYBocPH7bY7vnz5zFkyBDI5XKEh4db3O1KSUkBwzD1joU13efmzZvx2GOPAQBGjRrFd6M+fPgwpkyZAl9fX2i1Wott3HvvvejWrVuD3g/SfpkHs7W3/jSUsZsxd/HMtcgUF501W2fv3r1V+7MePIeHz0GHDlPQpfMbGND/e3go+nHbKT6DysoUANwFc01FhSeaXf62Lr/gMP84ODgG/fpugVzGzePLMMb7kgYUF//b+oWzwljXRrm5vyOnarxrQ+h0ZSgsPFbnOmp1NrKz9+LmzbX8srKyWJw+cy8SEpehvDwBN5PXIj//bwBA0o2VqKxMBcDNn/rfhadxOfYlVFamW91+W6CqOlcEAhmEQlcAQFDQo1bX1WoLkJCwGCxrwIULT+HEyTtx9t+HEBf3Bk6fuR+XY2dCr1c3eN9K5U0AgEjkDonYh18eHvYS/5mLu/YGAD0AoHfvL2C8rCjIN+9FQBpGpcqofqyuv2U2M2s30tK3tlpinb17f0TctTdRUnoBcXFvoLIyw+z50tLLOHlqJE6euhsVFUmtUiYjltW36v5KS2Nx6fLzuHhpGpTK+ruEFxQcRV7Vd9HNm2uRlbUbV+P+x7+WZVlcj1+IEydHIi1tM0pLL+PChSk4feYe3Ez+GLGxL1kM0WlJNb/DSftjMOigUmVCo0nhf2scUbsOZktKSpCfn2/2r6CgoNHbmT9/PhYvXowBAwZg1apViIyMxH333YeKiooGvb6oqAgPPvgg+vfvjw8//BAdOnTAzJkz8c033zS6LKaGDx/OT5OzYMECbN26FVu3bkWPHj3w9NNPo6CgAL///rvZa7Kzs/HPP//gqaeeata+iePTaKrPBZu0zPLBbAA8PbkeEfkFh8wusrp06VLr/ry97kR42Cx06/oewsJmgGGE6N37i6qpe7i7hiEhT2HQwP2QyztBKHSDhwe3n9KyWGittAy3NJY14HLsTBw9djuSkz/jAwWWZVFaehlabZHN9mUMDsRibygUfSCV+qN//12IiJiP2wfs4RMhFZqMMbUnY10DQEHhccReeQlXrrzS4HGuhUUnYTBoAAC+vnebPeftNRQAd2c37tobfLZfYxdbna4MaWmbcObsA0hJWc+/zmBQIz5hEViWRWbW9ygqOom8vN9x5uyDyM7+xaIMLGtAXNybOHfuUWg0+Q0/eBvSVJ0rcnko+vXdjB7dV6JH9w+gqLrRA3DH7e/3AAAgN/cAMjJ2oKQqwVp5+XVkZf+EiopE5OX9gZwcy+OsTUVVMOvi0tnsTrpc3hHdui0xS77l6zMaPt53wsMjGgCQX/BPE4/YuZl2MzYNbK0pKv4X167NQ0LCIpSUnLdpOfLy/0Zs7Cs4cXI4jhzthxMnRyA+fhEiI7P5chkMKiQmLuVfw7Is4hOWwGBQQacrRuyVV6DXK21artrcTP4U/xzqivT0bQAAna4cZeXXUVmZYZG7wVaKik5WPWJRURFf63p6fSXirs3DxUvP4vLlF5BfcBg5ub9VPWvArdQvAQA5OfuQkbENKlUaEhKX4t9z41FYdJzfjsGg5septwbT7/D2imVZ6PXqVrsZZDBooddXWimHvsXLwA23KTE7H7hrFG6/oqqbpY6oXXczvvvuuy2WSaVSqFSqBm8jJycHa9aswbhx47Bnzx5++eLFi/kMyPXJzMzE6tWr8dprrwEAXnzxRQwaNAjz58/H008/Xe842dp07twZw4YNw6effop77rmHz6AMAH5+fujQoQO2bduGhx56iF++c+dOGAwGCmYJ1LbuZlwVzIpECvh4D0NR0SmoVOlQKm/A1ZUbpy6Xy6v2nVO1rjsiI95GUfEZRHSZZ9H1RCr1Q6+eH1V9CRdCIvEFANwx+E/o9UruzvXFZwCwKCo6DX//+5pUdoNBg9LSy3B37w2hsOFd+QsLjyEv7w8AwM3kT5CV9RPCwl5GXt7vyC/4B3J5GAYPOgCBwHwc/c3kz5Cf9yfUmjy4uXVDn96fW21xNtLr1Sgs4lqffXxG8EGEVOqHTh2fAwAo3PugpPQCiopOQ6XKhE5XBjc38x4YrZnx2FjXAJB662v+cU7ub/zNjrpUX7Qx6Bj6LPLz/+Kf8/EdBXdFb37MNAAEBjyCnj1XI7/gH6SlbTa50ASEQld4et6OgoLDKCg4gvz8v/isyACg11cg7tqb8PS8HTm5vyIlZQO6dV0IgUCKrOwfAQBZWT+hU6cXGv0+NJfx3JRKAuDhEc0HiwEBY/iM4J06vgiR2AO5eQcAsEhIXAIAEAjkkEr9q25cGaDXK5GWvgVBQY82qJuXsZuxcbysqZDgSZDLQnHl6hxoteXo3Jn7ffPzHY2SknN8F2gXF8vX1n28uSgtvQiZLASurhEQCOw3tIZlDaisTINc3rFVukrq9UpotYX836p6xsxmZf3IPy4vv96g86ohVKosxMa+ZDZeXacrRXrGVghrXDXm5f+J/PxD8PUdhZycffxnEuCGj5w//zg8PKIREjLZ4vvIVvR6FVJT/w8AcOPmR/D1HY1z52OgVnPdtGXSYNx++x7+98NWSkov849ra9ViWRaXLj2HouLqxKPXry3gE9kB3HdLaIcpSEhcZvF6hhEjMHAcsrJ+AMC1fHt5DbbVIdTJ9Du8PdLrK1GpSodBr4JY7GmzzPAGgwY6XTkMBjVEIgVEIteq/amhVN4Ay+ohl4dCLPaEwaCHWpMNraYQIpE7XFzCbFKGmlhWD6UyBXq9EkKhC1xcuGEj1d83Yr7njyNq1y2z69evx59//mn278CBhndzA4C///4bOp0OL730ktnyWbNmNXgbIpEIL774Iv+3RCLBiy++iNzcXJw/b9u7qUYCgQBPPvkkfvnlF5SVVXdL2b59O4YMGWI1MRZxLjbvZlzVMioSKeBjMq7HtHvs2bNnq/bH/fBLJAEIDn4MvXp+BKm09hTtDCMwuxBhGCFEInd4ePTnA0VjsGeNwaDBxUvP4d9zE6Gu0cLGsnpcuDgV5/+bhDNnH2hUy2Za+rdmf1eqUnHt+jy+VaqyMsUiw3Bp6WUkJ3+CsvKr0GhyUVh4DOkZO6BSZeJ6/EKkpn5j1moOcN2sjS0cvr6jrZbFeIFTXh6HU6fvwpmzY1Bo0v06L+9PHD7SG4mJyxt8fE2Rl/cXzv83GXHXuJt/ZeXXzVoX8vP/atAd6PKyawC4KWEUin4mXakBhXtvRHR5AwNv/xXBwY8jMGAcunZ9DwzDwM/3LkT324o7Bv+DLp3fgJ/vPejTewN69lgFkYibgioxaTlKSy8BALw8ufeNZbVISFyKGzc+gk5XjITEpcjI3Mnvs2ZW4dZi3K9xDLBRh5AnERo6DV0j34Wn50C4u3XneyoYu1sGBU3EkDv+wcgRl9CpIxeIl5dfQ3FJ3a3j5eXxKC4+B03VvmsLSL29h2DokKO4dPFJuLv3AAD4mHw+09K3IC/vzwa1zun1atxM/gwnT43G5diZOPvvwzh2fAh/U6Os7BqUypR6t1MXltXjxs2Pcer0vbh0+UUkJ3+G0rIr0GqLUVT8r3nyJXUezv83CadOj8bNm2tq3Z4tVdZoidXpSmvtVqrXV5rdkDF2n28olmVRXh5vdb7irOyf+EDW1/dudAh5Gu7uvczWCev0EoRCNwBcAKnXK5F040MAgFjsA09PLodBWflVpGdsxdW4/zWqfI1RWHgUej3XU06nK8P5/ybzgSzAdddOTd0IgHufana1Ly+PR07ub2BZA9TqXPx7biJiY18Byxrq3K/xOwSo/YZwRUUiH8ga3y/jzVzjJTjLanHm7EN8gNu92/sID5uF4ODHMXjQAfTssQJSSQC3z7LYet+PxuC6mFrvdWL8va71tepsZGf/jJvJn1mcmwUFx5Cd/UubnVdWpytHRUUSDHqucUurLYZWW1p1Q6m40eXm5lFVQqm8hfLyeKhUGdBo8lFZeQssq4fBoOcfA9xNO71ejYqKBGg1hVVlKrNpLwKWNUClykRlZRqUylv897Ber4ReXwGdvpzv/aTRSJt0w27dunXo0aMHpFIpQkJC8NprrzW416otteuW2YEDBzY6AVRNt25xYxlqZkD29vaGl1fDkhsEBwfD1dX8jkfXrl0BcGNlBw9umbtszzzzDFauXIk9e/bgmWeeQXx8PM6fP0+ZCAkAmP2AqdU5YFm2Wa0PxpZZsUgBF5fOkMlCoVKloaDgMN96OH36dH5/ACCTBjR5fwAgFMrg4TEARUUnzQK3mgoKjqKgKhNwcvJadO9W3TUuLf1bFBefAcAlGLpw4Snc1udri6CxouIGEhOXQaHoi06dXoBanY2CqkA9OPhxuLl1Q3LyOv6ChGHEYFktbqV+CYWiD4qL/0Vg4CPIyd3Pb1Mi8YdGk4vU1P9DdvbPKC+PAwAk3fgQ3bstRXAwNybeGBwzjAg+3sOsHqOX1x1IqUqCZPyBunHjI3h5DQHDMLgcOwMAkJq2EZGRC+p7a5tEqUzGlatzYDCo0KuXH/R6FdJSzYdTqFQZKC+/Bnf3nnVuq6zqvXBz6wGhUApX165V748Abm5c4OTu3gM9ur9v9fUuLp0QFjbDbFlo6LNITv7E7MI/MnIBEhLfR3HxGbNpoLTaQrMxuwZDw8ea2grL6vmbTtIa54pAIEHXyLfNloV2eBolJoFqh5An+cfBIZORnPI5WFaD9PRv4eV5u8X+yssTkHRjJf+5NjImf7JGKJRj6tTqm72uLhH8uZ+evhXp6VsRHBSDHj0+qHUbBoMGly4/Z9aaDgA6XTE3zpoR4uy/YyEQyDDw9p/Nkso1lE5XhitXX+WPTam8gfz8v3Az+RN+HZHIHQNv3w+9QYmLF5/lA6Jbqf+HkJAnIJMF8esWFBzFlatzIBK5IyT4cYSEPNns+bpVVsZuq1RZcHOzTOjG3SSontqiMcGsXl+J6/HvIjt7D8RiHwzo/wNcXLhMpizLIitrNwDu3OvTewMYhoFeX4nY2JdQUHgUUmkQwsJehkAow82ba1Befh0XLk7h368unV+Dv/99uHHzYxTkH6qaTiweBoO6RVrac3PNE8WpqpJoeSj6wcDqUFYWi/SM7dAbVEhP/xYeHv3RP/o7MIwABQXHcDn2BRgMGkR0eRMqVRZKSy+iFBdRWnoZHh59re5Trc41C5hruyFsmsOgV8/VVd/DXKDk4zMMrEFXdSOWC5y9ve5EcPAki99id0VvqPNzUFpqu2BWqUzG6TMPQCCQYuiQYxCLFWbPG3+vTbEsi7z8P5Ce9q1Za3NB/j+4/XbuBmZ5eTwuXpoGwIDAgG9qbfHkgiolxGKvFu0xxAWJ2qr9cO9r9fUPAzAMwBqgUqXxNzBkMhYSSe3X+AaDDmp1JnS6CggEkqqA1fI3gvsOz4derzR73mCobqU1364KgBR6fQVEIgUYpultjhpNvsWNcSPTm7MMI4CHR3Cjtz9v3jx8+OGHePTRRzFnzhzExcXhs88+w9WrVy2GOLa0dt0y6+x69uyJ/v37Y9s2bgzJtm3bIJFIEBMTY+eSkbbANJg1GNT8ND1Nwd2VrOpmLPYAwzB81sXi4n/51oW5c+cCMOk62cxgFjCOn+RaQfNrSTpjOn4vM3MXf+GnVN7CjRsfAQAkEj8IBFxG8fSMbRbbSE75DAWFR5Gc8ilOnb4Hl2Nn8s91DH0WoR2ewdAhh9Gt21L06f0lIrq8WbWPZJw5+yDiExbicuxM5OZwY6U8PAbw62g0eXwgC3B36lPTNlY9ZpGffxgA4Ol5e62ZirlWamO3MO6rvbTsMgoKDkGjKTRbt74Wh8bQaAqRmbUb2dk/42rc61U/xoBWm4dr1+YhO4drmTYd45ln0mW4tm0aLw7d3big15gZ10NxG99tq7FCOzxt1pVKLu8IN7eeDeo+rFHn1btOY8QnLMGJkyNRXl77WDuNpoC/2JE04Fzx87sXEgnXguvpOQhubl3556QSXwQEcJlnc3MPorw8Hvn5h/Dff0+isPAENJpCnP/vcYtAFgDfJa02xvMa4LJU1szOmp2zjx8nplSm4MbNj5Ga+g1YlgXLGnDt2lt8IGsMoIzHoVJlVN1UYGEwVOLatXn1vg/WJCQs4Y9NJusAubyjxTo6XRmSbqzAlSuzzAIVltXwN4oALmP25dgZ0OlKoVJl4MbN1Th3fmKzx+1b61Zcc9yswaBDaellpKWbz6/d0GBWpyvHufMxyM7mAg+ttgCXLr/At9AWF//LbysoaCJ/8S8UytGnz1c49E8P9I/+HkKhDKEdnoFIxAVAJSX/AQAUitsQHPwYxGIvdO+2hO9+DhjqTJKk1uRbHUtYH4NBzSdVMv9uZNCt2xJ06cx9NvX6CqRX9aQpKTmP7OyfUVh4EpdjX+Rv/iWnfI7MrOr5msvLr9W6X9NWWaD2ltniYq51Uyz2hq/vXfD1vYt/LsB/DHr0/BCdOr6Ajh2fR0TEfERFrbV6U1nh3hsAoFKl2SwXQ37BYbCsFnp9OcqtjPk1Pa+NUtP+D7GxL5kFsgD3W2P83GRkfgdjcF5ekWjRysmyLDSafFRU3IBKlVVrwFUXvb6yQT0+tNoSKJUpfEupcf/Glnyx2IO/qW76u1jXtvX6SiiVSdBqS8CyuhqBKgOx2Auurl0gEHLXE2p1LnQ67saTSOTOB+7G73bTm2Bc1+c0VFZy/xpDpVLBYDDwx6jRmv/uC4UufIZxva4Cel1FVZk8kZ7euGnAsrKysGbNGjz99NP44YcfMGPGDHz66af4+OOP8ccff7T6fNQUzNbDOO9SUpJ5Vr6CggIUFTXsCyUzM9Oi2T0hIQEAmj03bH0tac888wz++ecfZGVlYceOHRgzZkyDW5RJ+2UwaC1+EJszblavV/Ld0sRVFzc+viMBACyrQ2raJgDAli1b6mxtaoqgoAl8963r8e/yPxo6XTmKi8+BZQ0oqAoGjeW5mfwpACDpxgo++Irq9Qk/R2tR0SmzHzODQYeCgiP832p1Fj8ljpfXEH5MsFDogg4hT8DP724EB0+CSORpVtaiolN8htKAgDEICBgLmaz6rrVCcRs6dHgGAFBRkQSdrgwVyiR+SiJfn1G1vg9CoQy9oz5Dx9DpGDTwV/7C7ubNT/hWaSPjD3lzGAxqXI17HcdPDMG1a/NwNe41lJZeBAD+xzon91ewrA4MI0a3bov4FtX8vLqDWdOLSGP31fDw2ejZ40NERX3a5DKLxZ5mrZX+/g+CYRj4eI+Amys3nk8gkKBz+KsWr63ZPb05SsuuID19C996WRvT1p6G9GIQCCTo0/tzBAc/jp49PrR4nutqLABgQNy1NxF75WUUFZ/G1bj/4Vbql/wNreCgGIR2mAqBQAZ39yi4utQ+NzvAndemwsNeQZ8+X/GBjMFQifz8f3Dt+gKcOn03UlLWITHpfWTn/Iy0tE1mNzwG9P8Bfn738GPHVKp0sxsJJaUXUNzIZEd6vZLPpO3pcTsGDdyPIXccwpA7jqJb18Xo0vkNeHvdCQDIzf2NP7c7dZrBJxXjboJlQKlMwaXLz8NgUINhhHB1jQRQ1SvhyuxmdRNUqay0zKqzUF4ej9TUjbh06XkcPdYf/54bz59rxsu4SlVag7pGZmb9wN84k0oDq8qehKtxr1UlRuOCOYYRIzDAfM5qgUCMZct+hVweAoC7MA/tUD3VFcMI0b3bMrNWNtNWdGN27JpKSi7i+PE7cObsgzAYLGdgsIZlWRQWnsSNG6v5FurIyHcgrsq6HRw8Ce7uPeHtPdyiizTADTW4dHl6VRDCXUfp9eVmrWdl5ddr3X9DglmWZfmWWU/P28EwDMLDXoZAIIVMFgI/v3shkwYiImIeIiPeQqeOz0Es9rS6P4Wij8m+bdM6a5zqDYDZWG2jmud1YeEJJCVx3ysikQIdQ6ejV8/qLvi5uQeh16uQnb2XX2bQq2AwVKKyMpUPWtWaHLNpp4y/wQ2h16ugVKagoiIJFRU3LG6AsKyBPw90ugpUqqoDQo0ml0/AZAxchUI3iMU+FjkrauuJw7IsKivTYDBo8cEHn8PDow9SUnLw0ksL0bHjnQgNHYqXXnoXajUglZgPDdn1w+8YNmwi/P37o1OnO/Hss28iK6sIMlkHfhhN16798MLzc6vKXz3MYOTIkWZ5cYyzp3z33Xd45513EBISAhcXF5SWcjelvvvuWwy7cwICAm5H584jMXPmBygqkpoNV5k58x0EBw9Gfr4Wc+fOhZubG/z8/PD6669Dr697CMWpU6eg0+nw+OOPmy03/v3dd9/V+Xpbo2C2HnfddRdEIhG++OILs+Xr1q1r8DZ0Oh2+/PJL/m+NRoMvv/wSfn5+6N+/f7PKZ+y+XFxcbPX5yZMng2EYzJkzBzdv3qTETwQAoNFa3gltzrhZY6ssAP5OvbfXnXzwkpLyBZTKZIwdO7bRrU31kUr9ERnxFgAuyEy68SEMBh0uXHga5/+bxHV/0xjnweSC3uzsn5GesYNP3hQUOAFeXoPh68N1LTYYNCgsrO7yWFLyH3+M/v4PwsOjPxTufeDtPQxdI63PxScSuSIycj4YRgRPz0E15lwUwN/vAQgEInQOn121vjt69fwYPt7G+Qq5jMgF+dWtyrWNl61+fhQiIxfAza0bQkOnAeDGrCUmrTBbT6strnM7DZGT8xuys/eAZc0vPl1du6JHjUCqZ4+VULhHwc/3Hr5M2TmWd265ljo9ykyCWbeqllmRyA1BQRMhkzW+O5Sp0I7TIZUGQih0Q3DVFDcMw6BHjxXw9ByIHt1XoFOnGXyQYmQ6xrw+OTm/IiNjZ60t4Glpm/nHZXW0/qhN5pht6Lni4dEPPbq/D7m8g8Vzbm7dEBIymdtv2RX+gk2jyeMT6Li790b37svRteu7GDH8Em4f8BMEgrpHJI0dO9bsb4FAAj/fu9Ax9Dn+nEtIXIrMzO9h7GIJAMk31/I3luSyjritz1cQCrneBcZ6VqkyLcaSGi+o62N8/wsKjvIZrzt2nA6RiCuTXB6CDh2eQljYDHTrtshsXLa7exQ6h8/lb2xwY6oXIzHpA/5GV88eH2HQwN/g53c/AKCw6LhZC25DcS1FKv44ZbIQPiC8ceNDnDn7IBKTliO/4B+zrsUuLhEIrbr5pdcrax37qFbnoKjotFkXYrm8I4bccYg/JwsKDiE+YSE/xt/X9y5IJJZzT9as69DQqfxY9NDQaRbDB0zHW1cob8Bg0FoEflwAbUBlZSqUVVOw1Scp6QNcuPg034NFIJDC3+8BREdvR/du76Nb14UAuHObu6nCQCz2RseqIS9abSEMBg0YRoSoXmv5Mb6mysuvoaTkAs6dfwyZmbvNniupJZgtK7uKy7EzcfhIH8QnLOJ/ezyruvUrFH0w5I4jGDRwf6PmA3d3j+Ifp6VtQlLSh2bzQDeFaWZkrcayccZY1yxrQGbWbsReeQWAAQKBFNH9tiEycgECAh6GXB4GAMjN+x15eb/zv5XGnk7czfMSqFSZUKtzLXq5NPQGkMGghVJ502wcuTGYZVm2ai72qygvv46KiiTu5onJDR5uTHSO2TkkErmCYRi4uITD1TWCv5lQWzDLdVnmnjMGwFOnvonKSgYffLACMTEx2Lx5MxYvXgyRSMG3zn700f/hheffRGRkJD76aBVefnkKjhw5g/vvfwYlJaUQVq1n+v0IcMMM6upJtXTpUuzfvx+vv/46li9fDolEgs2bN+OJJ6ZCKBRi4cJX8dxzz2HPnr0YNmwYSkuVkEj9wDACCAQy6PUGPPDAQxCLxfjoo48wYsQIrF69Gl999VWddaFWc+9BzSRhLi7ce9JS+YBq067HzB44cADXr1veWRsyZAg6d66725RRQEAA5syZg9WrV+Phhx/G/fffj0uXLuHAgQPw9fVt0BjD4OBgrFy5EikpKejatSu+//57XLx4EV999VWTMxkb9e3bF0KhECtXrkRJSQmkUilGjx4Nf3/u7oufnx/uv/9+/PDDD/D09MSYMWOatT/SPljrMtmcllmzYLaqy4xAIEL3bktx7vxjYFkNrse/h19++dnsbnBzx8waBQdPQnbOPhQXn0FGxnao1TkoLeMyTZqOw+sd9SkuXZ4BltUgPp4LQhlGiLCwVwBwCW0EAgkMBg1ycvahqOgUGEYIA5/Vk0G3rosgkfigIYKDHkVQ4HgwjBDp6dsRn/AeAMDLaxCf8CooaAJk8lDIpMGQy0PMLnBKSi7wia3k8rBGZYbtGPosMjN3Qa3OsrjrrtUWNztzY75J174+vTdAJPaEWpUFD49+EIk8kJW1G0VFp9Cl8xt8i3dwcAzS0rdApyvBtWtvIT//H5SVxaJj6HQEBU3AxUvTUVp6CQzDJfWSSHzrTAzWFFKJLwYPOsiX3Uih6IP+0dUJn/pHf4/KylTk5OxDatpGaDR5DRpXXlJyAVeuzgHAteZ2DjdPFqjW5CMnp3rcdHn59VqzTJuek7boxQAAncNfRU7OPv6cFQpdzHohdOr0In+M9QWxRrV1KRMKpfD1HY2cnF+qe2NIAhAQOBapqf+HSlV119iu3RaaBU8yGdf6p1bnoLLGRXtJyTmUlV+Hu1t3i30aDGpcuToXxcX/QqstgodHNH+BKhS6wruWMecuLuEICZ6M9IytYBgJevb4EAKBCApFHwQEjEVOzj7+Mw9wN8CM3al79VyFs/8mQKm8iby8Pyzq3GBQ4+bNtZBI/RDaYarZZ4hlDbh4aRqKi8/w3V2NXaBVqgyzC3epNBBeXoPh5XkHvLwGQy7vgPz8f5CWvhkAN+a/5vmi05Xh33MToFZnw9f3bpRXtTYGBT0KgUCCHj1WouTMJWg0ucjI2A6ACwyNN9lqqlnXYrEn+kd/h/Ly6wgIsLy+EIncIZUEQK3JgbLiJi5ffgEFhccQETEPnTo+D5Y1IN/khp1KlQG3GjeSasrI+I4PYgHuO7xTpxkQiVzhJoq0eL2vz0jcMfhPiMVeEArdUFBwBBUViRAIZOgdtQ6+vqMgkwXj3PkYAAa4uIRDqUxGefl1JN34ECUl/6Gk5AIkEm/4+o6GXl+JUj6TMQOAhV5fjoyM73A9/m2TclYPV/EyCZab8p0mkXhX56EoPIqCwqMoK49Dv76bG70tgLv5UVFxg//bWtflffv2gWVZXLn6KnJNcj10776cb+1mGAb+/vfj1q0NKC29iOQULlAUi73RrdsS3Lxxw2yb1d9pTNVvrdosa3ZNBoMGWm0RhEI3aDT5FmNMWVZbFchWd1fmuv5Wb1MmC4ZOVw6drhRabREYAXfdLRBI+ASSDCOAUCjnx3SzrA4Gg87iO7A6J4aAH7LSr18/bNxY/XksKCjAxo0bsXLlSshlHZGUdBnLl6/HsmXLsGDBgqrts5g06XlER0fj888/x2uvTQNQjpoMBnWd12YqlQrnzp2DTCYDy+qg0+kxb94b6NkzAgcObIJCEQKZLAjDhg3HQw89hI8//hiLFy+GVBIAoVAOlUqFSZMm4d13ueuhGTNmIDo6Ghs3bsTMmTNr3W+3blxPphMnTmDUqOoeY8eOcXkmMjLqnlbM1tp1MPvee+9ZXb5p06YGB7MAsHLlSri4uODrr7/GX3/9hTvuuAN//PEH7rzzTshksnpf7+XlhS1btmDWrFn4+uuvERAQgHXr1uH5559vcBlqExgYiA0bNuCDDz7A9OnTodfrcejQIT6YBbiuxr/++itiYmIgldpvmgPSdli7g9+cCbNNx4oZW2YBrpUoJGQyMjJ2oKjoJDZsGINHH63Oamns5tZcDCNAzx4rcebsQ9Dry82mcTFydY2Ej88IdOnyGpJMWioDAx7hk58IhS7w8roDBQVHkJP7q8U2FIq+DQ5kq8vGBSnBwZOQk7sfxcVn0THUPLGGaTIeicQbcnknVFbeQl7eHyiv4C4+62uVrUkkckfPHiurpi4yp23G+GiAu8AoqEqO5OMzks+kbBpcbNvqgw8+OGXWrUkmC0JUr7W4eGkaDAYVP+fp9fh3+ZsRHC64Mrbs21pDWkTEYg+Ixb35sWEGgxp6fXm9r83MrB5zl5y8Fp4e0fD2Hsov41psNfzfBgPXbc5aUqPq3hICSMS2mVZEIvFG18j3EHftDfj7P4CgoIm4dIn7PMrlYfD3u7fR25w7dy4+/vhjq88F+D9gNrdtZOTb8PW9C9nZv/DZkn28h/Nj7I2MwSzAorwigV+voPAoACA76ye4W0lklpt70CyRl+n8q74+o0xaQCxFRMyHVBYED0Vfs2lkunVdiKKiM3x5BQI5unR5nX+e+94YDKXyptW5YVNTN/JziRr0lRCLvZCesQNBQRMgErqZJRozHjtr0Jltq3u3ZQgOftziZorp2N/KylSL6XmSU9bzn6Pq70UGQYHjAXCf8+7dlvAJ4gCga9eFtU6jY62u3dy6mo3PrsnFtTPUmhwUFZ3iWyqTklbCzbUrxGIvs14Pqsq6L4LLyq8jPmFhVdm9Ed1vO1xcwiEQ1N0wYHojsHfU50jP2IagwPFQKLixqB4e/RDdbzv0BiVUlRmIT3gPen0FP+YVYHHl6lyEdZqB7Jxf+NY9L89B/HdEahrXu4FhRGAYAX9zQiRyh5uVGy+NpVD05oecAEBx8TmrAVdtTG/GcT1Cqlv8rAWzc+fOxbJls/hAVioJQGTXdxHg/4DZev5+9/HTpCmV3JC8oKAJCPB/AEWFZyEUukAm8zUbE56esQ0VFYlgDVqAYWqdFsagV1kEu4xAxAW1LAtGIOZuOFdlJQYjAAMBWBjAMEIwjBgMIwDLGrjeGSYttYxAzAev7m490LXru2YJyriEZdXvrV6v4ocxccmkuM6tM2aYJxocNmwY9uzZg9LSUigUCvz223EYDAbExMQgP7/62isoKAiRkZE4dOgQ3njDfMYUodCFTyrFBfFaMIzlZ3zKlCmQy+VQKm9BpyvF2bOXkJubj3nzXoRcLuevV8aMGYPu3btj//79WLx4sdn3yIwZM5CWlobQ0FC+/Fu31j78BQCio6MxaNAgrFy5EiEhIRg1ahSuXbuGmTNnQiwWo7Ky8ePfm6NdBrNTp07F1KlTG7RuzTEm1l4rFAqxZMkSLFmyhF9WXFyMgoICdOhQ3ZVr5MiRFts7fPgw//jkSfNMjabCwsIsXrto0SKLuWxTUlIsXvvcc8/hueeeq3XbEgl354m6GBMja8GsrboZi02CWQCI6PImCgtPorIyBV27JfBJOADbtTYBgFweih49PsCVK9WtIh06PM2PSTROF9QxdDoK8g9XXYAIEBZm/iPi6zPabHys2XO+tY9ZrY9AIEK/vltgMKjqDYg8FH1RWXkLZeXV3cACA8bW8QrrvL2Hmr0HRrpmdjMuLv6Xv5gzds2u6aWXZllMJwNwGTwjI95CYtLyqm5oLAwGtUkgW829hYLZxpBIqltR1Oq8OuuOG5v5m8kSrlUjut82uLl1g16v5D//YrEXfwFZVh5nPZitCp4kEt8GX7A2RFDQePj7P8i3SgQGjkdOzj5ERi5oUlbRl19+udbnvL1HQCRyh05XBm+vofw45bCwl5CQwHXtjbASlFYHs4Cx652n12Doqz4r2Tk/o0uXNy3el9yqQFYodIOra6TZvKf+NS7CaxIKpQjr9KLFcrHYCz16fMAH/WGdZlh8d8mkXHl1uhLodOV8V2adrgy3qrpwA8CNm6v5x4mJcSZJ20y3Fcx1Zay65ySVBpolYzJbVxYKY+tgzSRQSmWyWZd2I2+voWbd9f387kFQ0GPIyvoBwUExCA6qPUlkXXVdGxeXLmaBLIc7N2q2lJsG8EplCgoLjyMg4CG+dT09bUtVcCNAnz4b6gyia+Pq2hndulo2dnh5ca2ntY3J1uvLcePmR9Xrew5Gp04v8sGssduvn9998PEejmvXuWRlHh4DbJKtt2Pos1BW3IBAKENp6SUYDJWoqIi3Oia4ppRbXyI19f8QFvYSOoY+i7LSK2bP10wWBHB1bdqTqk+fDWZjd43c3XtDLuvI97Tw87sf4WFcy75xSj2x2Bs6XRl0ujIIBGJUVt4yGffddhi7RgPGrsbVQbZpBmDTm9odO5onkzPmpSkqKoJCoUBiIpcEKzLSeo8DsVhs8T0gErlBJPLkMx4bDBoIBJafofDwcOh0Ffw1WGoqd8OgW7dIuLh0MZvjvnv37jh+/LjZ62UyGfz8/KBSVY9b9vLyalBOoB9//BGTJk3CtGnckCahUIjXXnsNR44cQXx87YkNW0K7DGZtrbKy0qJf+CeffAIAZgOy26qvv/4anTt3xp133mnvopA2wvROuLEVsHndjK23zHJ/u+O2Pl/i33MTodeXm8wHK+CTddhKgP+DKA29iNS0jQgJeQrdui6CTNYBpSUX+Xk2GUaAXlFrcfPmGnh63G7RddfXdzQSEpeCZXXw8R6OCuUN/gKrtsCtoQQCcb0tCACg8OjLJ8UBuMy01i4iGiIy4m24uXaDWOyF2CvchWhzs64as4cyjJBPkFPT0aNHLaY0M+rYcTr8/R+AWOyJwsLjfGZosdgLvr53IyvrBwCAexOP2ZakJsGsRpMHV9fOYFkDikvOV72v1Z/33Nzf+SA/wP8h5OT+Cq22EP9deBJ9+25GUeFJvst3ZMQCXLv+FlhWz82pa3KzgmVZZGX/iLy8P7ky2PCmj5FQWN0C0bPHKvTssarJU3PVVddCoRS9o9ajoOAIOnV6gd9Hh5CnIBZ5QCYPsdqtVG4WzFYvCwqcgOLiM9Bo8lFYeMzsBpNeX8nfiPLzuwddI9/Fv+fGobIyFQKBHD4+wy222VC+PiPRO2o9VKpMPkmbKdPgUKXK4Fs209K28N+PDCOyaGUyjuX18hrCD4lwdY2AsrK6a3WHDs+YXZSaEgqlkEoDoFZnWwSzSTdW8WPaO4e/yk9DZBw3bapH9+UID3sJMllonZ+Duuq6Nq41smELBNKqDPqlZt1XgepglmUNuHT5eSiVN5Ga9g363vYNxGJvZFe18vv53gVPj+blHKmNMRmckVjsjfCwV3Az+VPodMVgGBE6dnwOncPnmrWUGikUvREUNBEVFQnIzvkFHavyFzSXh0c0Bg36DUplMk6dvhsAN6yhvmCWZfW4dWsDdLpSJCYug05bapFszFrL7NGjR3HnMC5RE8OIa22tZxgGUVFrkZPzKwICHrL6W8UwDOTyUGi1JRCJ3ODu1hOsQcePPxUIXSymoWFZPQzGBE+MEAALgUBa1RJbybXOMkIwYLjzihFYJHKqyWBQV7cGC1y4aXlQfeOU+33mbg6ZjpvVakugq/rdFIs9zFpwhULrNyqMDVQGgwEMw+DAgQNW13Vzc4NAIDE7fqHQDUKhFHJ5RyiVydDr9RAILJMyyeVyvscIGIbPjCyTBdfZC6Vm2cvLyxvU09RUSEgIjh8/jsTERGRnZyMyMhKBgYEIDg7mpx9tLRTMNsD333+PzZs348EHH4SbmxuOHz+OnTt34t5778XQoUPr34CdfPfdd7h8+TL279+PtWutp3tvCrVajffeew9bt25FUVER+vTpg2XLluGee+6xyfZJy1NXBbNCoRtcXMJQWXkLGpNkM42lNW2ZtTLXoqtrBKJ6fYKLl14Ew3BfyAzD2LS1ySgycgE6dXoRYjE3/s44x60pqcQXPbovt/p6mSwYfXp/AWXlLXQIeQJKZQrirr0Jd/deNukq1hAeir5mfzdk6pjaCARihIRMhl5v8sOsK27y9ripgrgxbh4eA2qdW7O+rOnGi38/v3vRvdv7yMr+CRFd3oSHRzRc5GHQ6Uqa1OXV1owtCwAXzBoMGly5Ogd5eX/Aw2MABvT/nn/emFxHLPZGz56r4K7ojaSkD6DVFuH8+Un8jQxX10gEBo7DrdSvUVGRwM+pa3Qz+WOkpKzn/67ZBdfWmvvbUF9de3sPNetqbdxnzSl8TEmllom+ZPJQuLp0QXzCQhgMKmRl/2QWzBYUHuUzo/r73Qex2AN9b9uE5OTP4Od3T70XuvXx97+/1udk8urg2xjM6nQVSE3j5ll2c+uBiC7zcP36Ari790JIyJOIvfIK9PpyeCj6oV/fLcjI2AGVOgt+fvdBIJQhJ2cfJBJfdAh5os5yyeWdoFZnQ2kSzFZWpvIJ7gIDxyE8fBY8PAdAqymEn999FttgGIHV6YpqaspsCC41eh34+z8IN9euSLqx0mJdYxKswqKTfPbjyspbOHf+Mfh4D+frN8QkK7mtiURu/E1egLvBGRo6BaGhU6rGMAv46cGs3WhSuPcGwzCIjFzQInN6y+VhfM+OkpIL6NCh7l535eXxZr2nklMsM8JbC2a9vLxQVsp9htzcutU5R7BC0afeG64MI+THxXft+i50ujIolSkAuOm/ak65plJl8zfe3dx6mF0vVFamQastNutmLBK581nQa8OyLLTaYggEEqtTvHGJkbixvMZg1mDQ8l2kGUYIqTTI4nV16dKlC1iWRXh4eJ1BnkAgg6enAiUl5XwiPON3VlpaFsLDLXNm6PVqvuuzROyNiAiuDhISknDXXebX5PHx8fwMLTXVFpA3RGRkJN/qHBcXh6ysrAb3jrUVCmYboE+fPhCJRPjwww9RWlrKJ4VatmyZvYtWp8mTJ8PNzQ3Tp0/HSy+9VP8LGmjq1KnYvXs3Xn31VURGRvKB/qFDh6j110EYuxlLJL6QSrgfY1Vzuhlrq38ohULr3TB9fUfBRf4WKlXvA+CmyGgpjR3XWpPp+FQ3t24YePvPdaxte25u3fnWC1fXrvDxtt762RhCoRQCgRwGQyV/h7kpyivi+dYIP5M5E2sKCbFsWat93ccRElKd4j8sbEYda7cu02BWpc7mA1mAS0TEsgYwjADp6dv57oaBgY9AIJCgU8fnIBBIkJCwBAaDir8QDw+bBYYRwN2tJyoqEsymIiouPoeUlC+q9u2PrpHvwN//wdY63CZpTF03lFAohUTiazYkQi4LgUjkBl/f0cjN/Q0lxebdQfNyuXoRCOR891UXlzD06rUaLc20W7QxICsuPsu3yoaFvQQfn2EYOrR6fOyA/ruQk7sfHUKeAsMIzIISX5/RGNB/N6TSwHqHJcjlHVFcfIYPvgAgPWM7jN2zjb1SjHM1N0dT6rpmy6yPzwgEBoyFUOSG+Pj3wDBiKNx7oaT0At8ym5GxAwAXPLCsHlptIbJz9gLgjrfmzRFbc3Prwb+fxozPgOV4e6HQBSKRwiRYZBrU7bc5GIaBQtEXBQWH+Pl961JkMoRDLPa2Og2PtWzGwcFB/I024zy3tmSaPbxmVnwA0Ou55GdcYibzcMU4fpRrZa26Qd6AXk8Mw0AiqfuGjPG3l+s9UIbKynS+R4VUGtSg3lWmJkyYgPnz52Px4sXYtm1bjQRwLAoLC+Hj4wOx2BPh4aE4ffoitFodJBKutfbgwWNIT8+2Gszq+BvTDCQSXwwY4Ad/f39s2LAB06ZN4/PkHDhwANeuXas1l5BxOGJzGAwGvPnmm3BxcbEYR9zSKJhtgOjoaPz1V93zIrZFDZlzrrHOnj2L7777DqtWrcLrr3MJMJ555hlERUXhzTffrHNcMGk7jBeIUokfn4RJqy1ASeklKNz7NLqlpjozqludra1//52Bua8dRFbWj3wCEmJJIJAgPHwOMjN3oVu3JTbrVSEWe0CtrmzW1Dw5OdWJsfzqaDn9/fffMXCg5XQXjoZL9MFdUKelbYZanWX2vEZTgLLyq4hPWFS1vo9Zgq/QDs/A1aULrsa9Do0mF26u3fixm27uPYCcvdBo8qFW5/Fz93LTX0jQr++WJo0JbG0tVdcyWQj/XSUQyPlhCS5VU4GoNXl8Ahy9Xon8Aq7HgK/PyAZ1sbMlqcQfDCMGy2r5gKw64y03TrUmN7dudXbd9PDo16B9u1S1qGq1hUhMXA7/gDHIzOS66nt6Dqp1H03RlLrmpsIyZs0WwKfqRkOHkCf4LL85OftRUnoBGk0uKivT+WRVgYHj4eU5GAmJi/nMziEhT1h0SbU1T49o5OUdhEjkXm/gLJUG8L+BXAtjw6fcaSoPj34oKDiESlUqNJp8s5tuNRmTWEkk/hg0cB+uXZvPnytyeUduDlgrAe6xYz+gXzQ3J7m7oiWC2eqg0GDS/V5f1YVYX5XUyTi9lynT6wzj1DUCKwmSmsLYAm0waPiWY4DL3F3bPMB16dKlC5YtW4b58+cjJSUF48aNg7u7O5KTk7Fnzx688MILeP311yGR+ODFF1/Fzz+Pwf3334+YmBjcuHEDW7duQXh4KGpO2wOAf4/EEq+q7Mxc0tpnn30WI0aMwOTJk5GTk4O1a9ciLCwMc+fOtVrGkpISfqrPhpozZw5UKhX69u0LrVaLHTt24OzZs9iyZYvFOOKWRsEsaZTdu3dDKBTihRequz3KZDJMnz4dCxYsMMuIRtouY9cdicTXrEXh3LkJEIt94OU5EJ6eA+Dh0R8uLmH1/jgbs+PWTP5U0//+9z+4uLjw88KS2oV1etFqMprmEIs9oVZnNzmbMcuyfDCrUPSrc3qf//3vf7U+50gYhsskrNbkWASyAJc4LTHxA3ABqAx9b/s/yGTm3dC8vYdi8KDfkJf3J7y9h/EX4qYJrs6dnwi1OodvAejS5U2HCGSBlqtrmSwEpVXzecrlHfibOlL+/TVAo8mDTBaE5JT11XNBB7R+SzbDCCCTBqFSlVodzJZxZXdxCa+1O74tmI4tT03baDZtTaiV8b3N0ZS6ZhhBVTKuS/BQ3GYWELi6cuNvTX+HkpPX8lOwhIQ8AQ/FbfDyvgM3b6yGTq9ESHDd3a5tISTkCYARwENxG9/lszZSaSAqKhIBtEwLpjUeiuobHSUlF+Dnx7UeGww63Lr1BXS6Mri7R8HHZySKi/8FwM11K5H4ok+fr5CX9we02iKoNXlITv4Een15VZKh6ha6xx4biKQbe6uOq3qeW1vhkmJx41PZqrlmdbpyi/lzjcnUzF9rGbjWNq68sWp2p2YYAaTSoKobm027sfzWW2+ha9eu/NQ4ABAaGop7770XDz9cPdzigQcexOrVq7FmzRq8+uqrGDBgAHbv/hrz5y/jG6i4hFDVLdkMI4BUUp1scerUqXBxccGKFSswb948uLq6Yvz48Vi5ciU8PT2tli8goPF5Gfr164dPPvkE27dvh0AgwMCBA/H333+bTdXTWiiYJY1y4cIFdO3aFQqFedBivFN78eLFJgWzJSWxKCqqsEkZSf3UVfPMSqS+8PO7B7m5+6umWmGh1RYgN+8AcvMO8OsLhW6QyYIgkfhCJHKHSOgGocit6rErysu4rkgicd3B7NSpU7Fr16461yEtRyTiLqib2jJbWnqR72IcGPBQneu2p7qWSH3NMrFKpYF89m+VKoMf2xfa4Zlax42JxV4IDjbPEqtQ9OEz/ZpmcQ0KegyhHabY+jBaTEvVtWmAY/rYdJyiWp0Dnb4cqVUZgxWK2+DvV/vY1pYkkwVXBbOZYFmWb5lVuN/Wovv18b4TvaM+R1r6FrOs4FJpIHx977bpvppa1xFd3kRa2mZ06mS9+6FpAi1j8js3tx5QuHPnk0waiJ49VzWhxE0jFMrRMfTZBq1r+nl0V9g+6LNGobgNgACAASWlF/lgNiv7Rz7RFwCIRJ58V1Qvz0EAjHPDcuOm09O38+tqtcVmGej37PkEvftwQaJrPXP/NgXDMNw0OwYt38245m8TU0tSJ9MuytXLbNMya9qrg2FEcHHpbJYwz8jajCNA7TOqTJgwARMmTKh3/6+99hpee+01/m+l8hb27/8GAoEUen0lKpQ3MWBAIEpKuO8XicTfoutzTEwMYmJqz0oOAJs3b8bmzZsBcDOldOnSpc7jqqkxM8e0NApm24Fdu3ZhxowZSE1NhZub5R2s2gwePBjDhw/Hhx9+2ODXZGVlISjIcvC7cVlmZqbFc0a5ubnIy8szW5aUxM1Jdu36G6hU2eauGmk4icSPS5LSdxNU6mzk5f2J4uKzKC7+1yzjsV5fjoqKRP7uc22MwVJt2ktw46iMLSK6JrTMsqweWdk/Vf0lqHccZ3uqa9PpeQBubmLjvKElpRdhnK9RXk/ykZpEIncMvP1X5ObuR1HxGYhFnggNfZaf+9JRtFRdmwawcln1TVKZyfzUanU2MpK/46dr4brlt2wX1NoYy6tSZUClSuOT6jQ1E3lj+PvfB3//+1BZmYb8/H9QXn4dwcGTbJ5kr6l17eU1mJ+P2hrTuja2ygb4j7HZEIuWZDpfemu1zIpErpDLOpj1BABgNscyYDqmEvD0suweLjYZP6rVFpkFs3cOC0VJSW5V8qWWuT4TMCLooQXL6sCyLJ8NXiCQcuORxR5Wz2dr41YbO5a1NkKhHFJpIFhWB6nU3ybTKjUHU3UOs6yO633CVs8PLBBImp0jBAAfyDoq+3zjtxEnT57EokWLUFxcbO+iNJler8fChQsxa9asRgWyADBv3jysX78e2dkNT/xTWVnJDyg3ZUzpXddEyZ9//jmioqLM/o0bN65RZSa2deC3Gzhy5AgOHjyIjf/3IwTMaKxfp8WdQ09h0zcRiOq1FpcuRcLLcyLKyrrAYOgMIARqtRuEQncYDKZbE+DYUSWSkpLwzTffYM+ePTh79iyWLl0KpVKJmJgYjB07FmPHclOQLFiwALGxsdixYwd27NiB2NhYLFjAZX40rhMTEwOlUomlS5fi7Nmz2LNnD7755hskJSXxYz+M606ZMgWFhYVYtWoVf0zr169HRkYGn4zAuO6MGTOQkZGB9evX4+DBgzhy5AhWrVqFwsJCTJkyxWzduXPn1nlMpuu29WP65x+u1aagILUBx/QQysri8PXXD+PosUfw9z+9+KQshYW+kEr96zym2267rd3UU2mN2H/r1usw/nyWmMxJue+Xk40+prNnb2DXrlJ0DP0IH35YAIWit8N99jp16tQi9bRr19/8e3vtWi5/TKYtYV9/vRyFhdx0X2LRCPz9V6LdviOuXecywms0edjy7Tt8GRWK21qtno4cuYpffimHQvEK5s3b0OxjqllPDz74YIt89mSyINRM8/HLL2kO8R1x4ADXM8lgcMWePedb7bNnDGJKitOqjmknCgq4c8HPbxzOn6tueBCLvbH8/W8sjunbLT/y62i0hfwxffLJKygq4r7b0tPFTT4m47ymt27dgkajQW5uLkpKSlBWVlZ17Smqeu+0SE5O5LvPMow7KipkKC/ToaKiApmZmdDr9bhx4wYA4ObN6mRnRkVFZVAqlUhP56YdSkzkbr7fuHEDer0emZmZqKioQFFREfLz86FSqZCWlma2bnJyMnQ6HYqK9NBq3VBaWo7c3FxoNBrcunXLbN3ajkmn0yE5Odls3bS0NKhUKuTn56OoqMjqMRnXTU9Ph1KpREFBAQoKCqDXVXcvLikp4N4vlsv4XlbmCqWyskHHlJ2djbKyMpSUlFgc08WLF1v1mHQ6HWJjY80+T6bfEcbnGophWyJLkIP46KOP8MYbbyA5ORlhYWH2Lk6T7N27FxMmTEBaWlqjswwaDAaEhITg+eefx5IlSxr0mqioKAQEBODvv/82Wx4XF4devXphw4YNePFF6+P8amuZHTduHE6c2Iru3TtbfR1pGXJ5hwZNxVAX7k6qEgaDGgwjMptzk7Q9SUkrcSv1KwgEEowcEWe11UOnq0BW1m6kZ2zju8/WFBW1DgFVSYycwY0bHyHlFpdhWCz2xrA7z+L4iSHQaHLBMBKwrAYAcMfgv+udGoI0nFKZglOnuYzZt/X5P34aHpY14NDhXmBZDXx9RvPJbHr2WIWgoPq78bWUzKzduHZtHgDw5WIYMUYMv2S1myIxd/zEUL77votLF9wx+A87l6hhWNaAwsJjkMs7Wsxb3pIuX56BvPw/4eoaicGDDiIn9wCuXHkFQPX5civ1/3Dr1gZ06jTD6jR15eXxOHOW62UTFfUZAvwfhF6vxtl/H4JSeRMCgRSDBu5v8nHdvMn9hnTubP36rlKVAa2msGrKmwB+ChxX18h6k7iVlcXxrfgCgcSmic7aEo2mgH9fjJmWhUIXuLo6bmtqfZ+Lq1evIioqCleuXEGvXvVnB6duxg1kMBig0WgaPalwS9u0aROGDh3apHT5AoEAjz76KL799lssXry4Qd15goKCkJGRYbE8K4tLjBIcbDk3oJG/vz/8/f2tPufh0Q/e3i2bzp7YHsMwVXO1NSwL3oIFC7B8ufX5XUnLE1V1MzYYNDAYVBaJTZTKFJw7HwOttsBsuatrJDw9b4fCvTcUHv3g1oDxU+2prk0zhXp5DgLDMJBKA6DR5PKBLMBYJH5yFi1V1y4uYejWbSk06jz4+FRPT8UlZPGHSpWOoqpMrdz69r0hatpV1hhgu7l1b1eBbEue1zJZMB/M1pUpva1hGIHZ57O1GL+XjBm/jRmghUIXeHkNAcDNs94xdHqt13disUk3Y00RNJoCXI9/j7+R2Tl8TosG6ALG2IVWzydwYxhRnXPaGnHZw/X84/bKdHywce7bhkxD1Bjp6eno0KGDTbfZmpy2m/GiRYvwxhtvAADCw8O5gegMg5SUFADcRforr7yC7du3o1evXpBKpTh48CAArkV3yJAh8PHxgVwuR//+/bF7926r+9m2bRsGDhwIFxcXeHl5Yfjw4fjjD/O7jQcOHMCwYcPg6uoKd3d3jBkzBlevXq33GFQqFQ4ePIi777ae4KEh+77nnntw69YtvotBffr27YuEhASUlpaaLT9z5gz/PCG1mTx5sr2L4NTEJmOarSWBysrewweycnknRHSZhyF3HMHgQQfRvdtSBAfHNCiQBdpXXZuOmfX04pKomHZ1Nf7dkAuw9qgl67pDyBPo3HmOxbg54zhF4xg7AK3aKmaNXGZ5U5lL1NN+tGRdy2TVF9P+DhTM2osxmNVqi6DXq5GffxgA4O09zOwGSl0NFaaZpQsLj+HU6XuQl8dd64pEEQg1mWasJZgGoTpdedV+3RrUuGI6HtxW42XbImvJrmw1DZGRt7e3TbfX2pw2mJ0wYQL/pfzxxx9j69at2Lp1K/z8qi9a/vnnH8ydOxeTJk3i52gCgLVr16Jfv35YsmQJli9fDpFIhMceewz79+8328fixYvx9NNPQywWY8mSJVi8eDFCQ0Pxzz//8Ots3boVY8aMgZubG1auXIl3330XcXFxuPPOO/nAujbnz5+HRqNBdHS0xXMN2TcA9O/fHwBw4sSJBr1vjz76KPR6Pb766it+mVqtxqZNmzBo0CCalofUqbHjIIhtmV64WJuep7DwGADAzbUb7hj8Jzp1egFyedPu1ranunZ3jwLAQCCQwNdnJADzpC+Aeaucs7FHXde8mSAWe7fo9DcNUfMzAQD+fvfZoSQtpyXr2kPRFwDg4hIB91ZKpOTITHuMFBYe5ZM9+fne1eBtCAQSfh7XvPw/+eSAvj6jkZU5wSYJxOoazWgtULM2r6z111YHdEwLJahqC6wloLJ1Qq668t20BFuPcHXabsZ9+vRBdHQ0du7ciXHjxlkdMxsfH4/Y2Fj07NnTbHlCQgLk8uruea+88gqio6OxZs0ajBkzBgA3FnTJkiUYP348du/eDYGg+r6BsRLLy8sxe/ZsPPfcc2bB4ZQpU9CtWzcsX77cbHlN169fB8C1LJtqyL6NQkJCIJFIEBcXV+t+TA0aNAiPPfYY5s+fj9zcXERERGDLli1ISUnBxo0b698AIcRuRCYX+7oaLbNabRE/lYiPzwi7Z3BsS1xcOmHQwP1gGCE/t66sRjAllzluFy1HJKsRONq7VRbgLjBdXML5eTKjen0Kb+8hdi6V4wgJeRIuLmFwc+vhEFmM7c00mC0p+Y9/7N7IOWElYm9UmvRwCAwch549PsLVqzubXUaBQACNRgOWZa3Wac0WVYFA3ODcG6aBsK1bKtuSlpyGyB64XCt6iMW2OwanDWYbYsSIERaBLACzQLaoqAh6vR7Dhg3Dzp3VJ/7evXthMBjw3nvvmQWTQHWXjz///BPFxcWYPHky8vPz+eeFQiEGDRqEQ4cO1Vm+ggKuO6CXl5fZ8obs25SXl5fZ/uvz7bff4t1338XWrVtRVFSEPn364Ndff8Xw4cMbvA3inHr3prvt9iQWefKPtVrzltmCwuMAuJtd3j7NP5fbW13XTC5Ss2XQmVtm7VHXNVtB7T1e1qhHj5XIy/sDIcGPt4kA29Zasq4FApFdxp46KrNgtvQS/9h0zt6GEEu8UKlK5f/297sfDMPYpK6lUikqKyuRm5sLf39/i2tQs9ZVRggXl84NvpHqPN2MhQAYGH+fAdu3zJrGNS1Jp9MhNzcXer3eInZpDgpm61CzxdPo119/xbJly3Dx4kWo1Wp+uelJeuPGDQgEAqvBsJExZfXo0aOtPq9QNOzuVM3W1obsu+brG3MXVCaTYdWqVVi1qvUmMCftw86dO9tdkONITLthak3mHwSAwgKui7FQ6AJPj/7N3ld7r2uLbsZN7I7dHtijrqWyttcyCwCeHv1tcv60Ve39vHYkpvOLlpVx3b9FIk+IRO6N2o5pEiiBQMInj7JFXQcEBECtVqOwsBAlJSUQCoUW15sGA5fISSCQgGHSG7xtg0EHvV4HABCJcsAwefW8wnFptTqYBrMiUYZNey8olUq4uLjYbHs1sSwLg8EAnY6rL2MuH1uhYLYO1u5UHDt2DA8//DCGDx+Ozz//HEFBQRCLxdi0aRN27NjRqO0bqibp3Lp1KwIDLcfaiER1V4+PD/dFVlRU1KwsZMXFxfD19a1/RUKaqb1kt3VUpmNmTbsZsyyLwkJuPkAvz8E2uevb3uu6ZsusM3cztkdd13z/XdtIMNvetffz2pGYtszq9UoAgFze+B4ipsGsl+fgqhkKbFPXAoEAHTt2RE5ODtRqNX/da75O035vGEYIvb4cjEBikSCuvSktvVyd7VkgsnmCtJYMZAHjzBciyOVyKBQKuLu72zQYd+pgtilv5I8//giZTIbff/8dUml1trhNmzaZrdelSxcYDAbExcXVmuG3Sxdujih/f/9aMxLXpXv37gC4CZFN7541ZN9GGRkZ0Gg06NGjR6P3T0hjjR07Fvv27bN3MZyWQCDn50U17WZcWnoBak0OAMDbZ5hN9tXe65q6GVezR11LJeY3gOUUzLaK9n5eOxKh0I2fd9RI1oSbasbpkADAx7e6p6Ct6logECAoqKWmLXPcuVYbo6R0CUrLqhI0uvVA584zbLp9Rz+v2/etjHq4unJ3n4qLixv8GmMXCb1ezy9LSUnB3r17zdYbN24cBAIBlixZYnEnytgt+L777oNCocDy5cuh1Wot9pWXV3eXif79+0MikeDcuXON3rfR+fPnAQBDhlCSCtLyHPnLsj1gGIbvamzsZsyyLG7cXFP1vBh+vo2/sWZNe69rkcgdQqFxfmXnnWMWsE9dS6V+4MaRAYAALvKOrV4GZ9Tez2tHwjCMWess0LQeIu5u1UPSfE3GLFNdtx0ScXWX8pa4cerode3UwaxxWpq3334bW7duxXfffYeKioo6XzNmzBgolUrcf//92LBhA5YsWYJBgwYhIiLCbL2IiAi8/fbb2LNnD4YNG4bVq1dj3bp1mDJlChYsWACAGxP7xRdf4NixY4iOjsb777+Pr776Cu+88w769euHxYsX11kWmUyGe++9F3/99Vej9230559/omPHjujXr1+D3jNCmiMmJsbeRXB6xq7GxpbZwsLjKCo6BQAICXmi0clDauMMdS2V+lf933nnmAXsU9cCgYQfMyiXdXDq9781OcN57UhM58AGmhbodOw4Hd7ew9A5/FXITW4KUV23Habjo231G23K0evaqbsZ33777Vi6dCk2bNiAgwcPwmAwIDk5mW+xtWb06NHYuHEjVqxYgVdffRXh4eFYuXIlUlJScPnyZbN1lyxZgvDwcHz22Wd4++234eLigj59+uDpp5/m13niiScQHByMFStWYNWqVVCr1QgJCcGwYcPw7LPP1nsM06ZNw8SJE5GWlmY2x2tD9m0wGPDjjz9i+vTplAaftIrNmzfbuwhOzzg+SqPJrWqV5RK5CYWuCA97yWb7cYa6lss7QalMhos8zN5FsSt71bVcHgaNJh+ubl3tsn9n5AzntSOp2TLblER0UmkA+vXdbLGc6rrtEEtatmXW0evaqVtmAeCdd95Beno69Ho9WJbl55tlWRbr1q2z+ppp06YhISEBKpUK165dw9SpU7Fo0SKrkwA/++yz+O+//6BSqVBYWIjDhw9bjI8dOXIkDh48iOLiYlRWViIpKQmbNm3iW47r8vDDDyMyMtLqfLT17fuXX35BcXExXnrJdhewhNRl9erV9i6C05PLOwEAlMoUqFSZKCu7CgAIDZ1qcWHUHM5Q1106/w9BgRMQETHP3kWxK3vVdWTkAgQHxaBL5//ZZf/OyBnOa0di2mIH2DYRHdV12yFp4WDW0eva6YNZRycUCrFkyRKsX78e5eXl9b/AxMqVK/HKK6+04MB8Qszdd9999i6C03Otmo9Tqy1EcfFZfrm311Cb7scZ6trdvSd69lwFhaKPvYtiV/aqaw/FbejR4wO4Uctsq3GG89qRWLTM2rALKtV12yGXVfe8dG2BObUdva6duptxezFp0iRMmjSp0a87depUC5SGkNplZGTYuwhOz8XkhzAv73f+satrhLXVm4zq2nlQXTsPquu2xTSYFYk8Gj3HbF2ortsOT8+BCA9/FSKRG9zcutl8+45e1xTMEkJaTVFRkb2L4PRcXaunMigoPAoAEIu9LbqrNRfVtfOgunYeVNdti2kwa+u5rqmu2w6GYdA5fFaLbd/R65q6GRNCWs3w4cPtXQSnJ5N1AMNw9zGN8xO6ukbafD9U186D6tp5UF23LRJxdTArk9t2LCXVtfNw9LqmYJYQ0mrWr19v7yI4PYFAzCeBMnJztf2YQ6pr50F17TyortsW05ZZmY1bZqmunYej1zUFs4SQVrNmzRp7F8EurGU6t6eaCSRsPV4WcN66dkYff/yxvYtAWsnHznpet7HvcCPTOa7dbNzDxmnr2gk5+nc4BbOEkFbx182/IOohwl83/7J3UVrVXzf/gvx9eZs6bheLYNa2F0HOWtfOauzYsfYuAmkNf/2FsSIR8JeTndd//QXI5W3yuEUiV0T1WovwsNkICHjEdht21rp2Uo7+HU7BLCGkxbEsi7f+eguGyQbM/2t+m2upbCnG41br1W3quF1cWy6Ydda6dmb79u2zdxFIS2NZ4K23sM9gAObPb7MtlTZXddxQq9vscfv53YPOnedAKJTaZoPOWtdOzNG/wymYJYS0uP2J+3E+6zywBziXdQ6/Jf5m7yK1Cv640baO27SbsVjsA4nE22bbdta6dmZTpkyxdxFIS9u/Hzh/HlMA4Nw54DcnOa+rjhuA8xy3s9a1E3P073AKZgkhLYplWSw6vAgMGOA+gAGDRYcXtfsWO7PjRts6btNuxrYcZ+Wsde3sHH28FakHywKLFgEMg48BgGG4v9v7eW1y3ACc47idta6dnKN/h1MwSwhpUcaWOhYscAFgwTpFi53ZcaNtHbdY7MlnvnRX9LbZdp21rp3dxo0b7V0E0pKMrZMsi40AF9g4Q4udyXEDcI7jdta6dnKO/h1OwSwhpMXUbJ1E1TR47b3FzuK4q7Sl4+aShsxCWKcXbbI9Z61rAgwcONDeRSAtpUbrJF/T7b3FrmarrFF7Pm5nrWvi8N/hInsXgDg3tVoNAEhKSrJzSUhLOJxyGOcvna9ekAfAparFLvccvvjtC4wIG2G38rUUi+Ou0raOWwzgHiQkZALIbPbWnLWuCXD9+nX4+vrWvyJxPIcPV48ZBXAdgC9Q3WL3xRfAiHZ4Xtc4bl57Pm5nrWvS5r7DjTGBMUaoD8PS7XJiR1u2bMHUqVPtXQxCCCGEEEJIG7F371488kj9U05Ryyyxq65duwIAdu3ahZ49e9q5NKQlJSUlYdy4cdi7dy8iIiLsXRzSgqiunQfVtfOgunYeVNfOoy3WtVqtRlpaGkY0sCcABbPErhQKBQCgZ8+e6NWrl51LQ1pDREQE1bWToLp2HlTXzoPq2nlQXTuPtlbX0dHRDV6XEkARQgghhBBCCHE4FMwSQgghhBBCCHE4FMwSQgghhBBCCHE4FMwSu/Lz88PChQvh5+dn76KQFkZ17Tyorp0H1bXzoLp2HlTXzqM91DVNzUMIIYQQQgghxOFQyywhhBBCCCGEEIdDwSwhhBBCCCGEEIdDwSwhhBBCCCGEEIdDwSwhhBBCCCGEEIdDwSwhhBBCCCGEEIdDwSwhhBBCCCGEEIdDwSwhhBBCCCGEEIdDwSwhhBBCCCGEEIdDwSwhhBBCCCGEEIdDwSwhhBBCCCGEEIdDwSwhhBBCCCGEEIdDwSwhhBBCCCGEEIdDwSwhhBBCCCGEEIdDwSwhhBBCCCGEEIdDwSwhhBBCCCGEEIcjsncBiHMrLi7GkSNHEBoaCqlUau/iEEIIIYQQQuxErVYjLS0NI0aMgKenZ73rUzBL7OrIkSMYN26cvYtBCCGEEEIIaSP27t2LRx55pN71KJgldhUaGgqA+8BGRETYuTSkpZWUlMDDw8PexSCtoL66ZlkWWm0BlMpb0GqLoNUVQ6ctgU6vBGvQgoUOrEEPA6sHy+oAVgeW1YMFa9yCcUPV27S+J9OdNvewiBU6vR4iodDexSAtTOHRD+5uYxrUUkIcH/1eO4+2VtdJSUkYN24cHyPUh4JZYlfGrsURERHo1auXnUtDWtqqVavwxhtv2LsYpBXUVtdFRaeRk/Mr8vP/gVqTwy8XCACJFJC0ZiEJIY2QgCtXSvHii+vsXRDSCuj32nm01bpu6PBDCmYJIa1m4MCB9i4CaSU161qvVyMhYREys3bV+hqGEUEkUkDAiMEIxGAYEQRV/2cYEQSMCGBM8xYyVf9lTDdi8bzZPqwsI81TXFxMrXXtXGnZZej1SkREXgbL6sEw1BLf3tHvtfNw9LqmYJYQ0moqKyvtXQTSSkzrWq+vxH//PYHSsssAAIYRw9t7CLy87oC7W0/IZMEQi70hEinAMBRsOpqDBw8iOvp+exeDtKCUlA24cXMVgAxkZf2E4ODH7F0k0sLo99p5OHpdUzBLCGk1N27csHcRSCsxrev09K18IOvh0R9RUZ9CJg20V9GIjdF53f6Fhk5FesZWqNXZSE5Zh6CgR+nGUztH57XzcPS6pnlmCQDg8OHDYBjG6r/Tp0+brXvy5EnceeedcHFxQWBgIGbPno3y8nI7lZw4Espc7TyMda3XK3Er9WsAgKtrJKL7badAtp2h87r9EwplCO3wDABApUqHWp1t5xKRlkbntfNw9LqmllliZvbs2bj99tvNlplmGb548SLuuusu9OjRA2vWrEF6ejo++ugjJCYm4sCBA61dXOJgli5dig0bNti7GKQVGOs6PWMHtNpCAEBY2MsQCMR2LhmxNTqvnYNC0Y9/XFZ2BTJZkB1LQ1qarc5rnU6HoqIilJeXg6WM8m3S+fPn0b9//xbdB8MwkEqlUCgUcHV1tWnPDgpmiZlhw4bh0UcfrfX5BQsWwMvLC4cPH4ZCoQAAhIWF4fnnn8cff/yBe++9t7WKShwQXfA6jw0bNsBgUCO1qlXWxaULAvwftHOpSEug89o5uLv3BJdUjUVpWSz8/O6xd5FIC7LFec2yLNLT01FZWQmhUAiRiMKOtqilA1kA0Ov1KCkpQUlJCby9veHv72+zgJY+VcRCWVkZ5HK5xZdOaWkp/vzzT8ydO5cPZAHgmWeewdy5c7Fr1y4KZkmdxo4di3379tm7GKQVjB07Ft98MwcaTT4AIKzTDMqA2k7Ree0cRCI3FBaI4e2jQVlprL2LQ1qYLc7rsrIyVFZWwsPDA0FBQTTOuo1KTExEZGRki+9Ho9EgKysLhYWFcHV1hZubm022S2NmW8jUqVMRFhbW5NfaqoIb69lnn4VCoYBMJsOoUaNw7tw5/rnY2FjodDoMGDDA7DUSiQR9+/bFhQsXWru4xMHQBa/z2LdvH3JyuPoWCOTw96dst+0VndfOo2dPrndFadkV6jLaztnivC4tLQUAm7bCEdtrjUAW4OKFoCBueILxs2ELThXM7tq1CwzDYM+ePRbP3XbbbWAYBocOHbJ4rmPHjhgyZEhrFLFRlEolFi1ahMOHDzd7WxKJBBMnTsTatWvx888/Y9myZYiNjcWwYcP4IDUrKwsA+A+iqaCgIGRmZta5j9zcXFy9etXsX1JSUrPLThzHjBkz7F0E0kpefvl55OX/DQDw870LQqGLnUtEWgqd187jwMFrAACtthBqdZadS0Naki3Oa61WC5FIRN2L27hbt2612r4kEgnEYjHUarXNtulUweydd94JADh+/LjZ8tLSUly5cgUikQgnTpwwey4tLQ1paWn8axvq66+/Rnx8fPMKXA+lUonFixfbJJgdMmQIdu/ejWnTpuHhhx/GW2+9hdOnT4NhGMyfPx9A9TxUUqnU4vUymazeeao+//xzREVFmf0zZlA7fvw4jhw5glWrVqGwsBBTpkwBwHVzAYC5c+ciKSkJ33zzDfbs2YOzZ89i6dKlUCqViImJMVt3wYIFiI2NxY4dO7Bjxw7ExsZiwYIFZuvExMRAqVRi6dKlOHv2LPbs2YNvvvkGSUlJmDt3rtm6U6ZMQWFhIVatWoUjR47g4MGDWL9+PTIyMvgve+O6M2bMQEZGBtavX4+DBw/SMdU4pnfffbfdHVN7rCdbHFN0tBAGA/edEBDwULs4pvZYT7Y4poqKinZ3TO2xnmxxTPff/yKM3po/uV0cU3usJ1sc00MPPdTsYzp27BgEAgFu3boFjUaD3NxclJSUoKysDNnZ2dDpdEhOTgbAdXUFuOtulUqF/Px8FBUVoaKiApmZmdDr9fwUMsZ109PToVQqUVBQgIKCAiiVSqSnp5utc+PGDej1emRmZqKiogJFRUXIz8+HSqVCWlqa2brJycnQ6XTIzs5GWVkZSkpKkJubC41Gwwd8xnXb0zEZA8vWOiaDwYDLly/X+tmLjW3cMAaGdbJ+Ip07d4afnx/OnDnDL/v999/xwAMP4PHHH0dhYSEOHjzIP7dz50488cQT+Pnnn/Hwww+3ShmnTp2K3bt31zvdTX5+Pvz8/LBw4UIsWrSoRcoyefJk/PTTT1AqldizZw8ee+wxHD16FMOGDTNbLyYmBseOHeNbb63Jzc1FXl6e2bKkpCSMGzcOV65cQa9evVrkGEjbsX79erz88sv2LgZpBXt/vhfu7jcgErlj2J1nIBBY3gQj7QOd187j888/Qbfu6wEY0KnTTER0ed3eRSItxBbn9c2bNwFw196k7crNzYW/v3+r7a++z8XVq1cRFRXV4NjAqVpmAa519sKFC2atiCdOnECvXr3wwAMP4PTp0zAYDGbPMQyDoUOH8su2bduG/v37Qy6Xw9vbG48//jh/J8TI2pjZgoICPP3001AoFPD09MSUKVNw6dIlMAyDzZs3W5Q1IyMD48aNg5ubG/z8/PD6669Dr9cDAFJSUuDn5wcAWLx4MT8nrK2D2tDQUGg0GlRUVPDdi60FrFlZWQgODq5zW/7+/ujVq5fZP9Npf0j716VLF3sXgbQCna4Mbm7cHV8/v/sokG3n6Lx2Hp07d4erK1ffpaWX7Fwa0pLovHYe1npcOhKnDGa1Wq1Zy+yJEycwZMgQDBkyBCUlJbhy5YrZc927d4ePjw8A4P3338czzzyDyMhIrFmzBq+++ir+/vtvDB8+HMXFxbXu12AwYOzYsdi5cyemTJmC999/H1lZWXyXkZr0ej3uu+8++Pj44KOPPsKIESOwevVqfPXVVwAAPz8/fPHFFwCA8ePHY+vWrdi6dSsmTJjQ3LfIzM2bNyGTyeDm5oaoqCiIRCKzpFAAl53s4sWL6Nu3r033TdofuVxu7yKQVpCb9zsYRgcACPB/yM6lIS2NzmvnIZfL4enBJYEsLj4LrbbIziUiLYXOa+chEDh2OOjYpW+CmuNmdTodzpw5g6FDh6JLly4ICAjgnysrK0NsbCz/mlu3bmHhwoVYtmwZvvvuO8ycORPvvfceDh06hPT0dHz++ee17nfv3r04deoUVq9ejc8++wwvv/wyDh48yAfJNalUKkyaNAkbN27EjBkzsHv3bvTr1w8bN24EALi6uvLzwfbp0wdPPfUUnnrqKfTp06dJ70vN7r8AcOnSJfzyyy+49957IRAI4OHhgbvvvhvbtm1DWVkZv97WrVtRXl6Oxx57rEn7Js7j7Nmz9i4CaQU5Ob8CAMRib3h53WHn0pCWRue18zh79iwCArgbVCyrQ27uwXpeQRwVndfOo6KiokmvW7duHXr06AGpVIqQkBC89tprTd5WczhdMNujRw/4+PjwAeulS5dQUVHBZyseMmQInwTq1KlT0Ov1fDD7008/wWAwICYmBvn5+fy/wMBAREZGWs2EbHTw4EGIxWI8//zz/DKBQFDneISameSGDRvG9zO3tUmTJmHMmDF4//338fXXX2Pu3LkYMmQIXFxcsGLFCn69999/H4WFhRgxYgQ2bNiAd955B6+88gruvfde3H8/Tb1B6jZ9+nR7F4G0MI2mAEVFJwEA/v4PQiCgLJbtHZ3XzmP69Onw9LwdUkkAACA7h6Zlaq/ovHYevr6+jX7NvHnzMGvWLERFRWHt2rWYOHEiPvvsM5v3EG0Ip7vKYBgGQ4YMwdGjR2EwGHDixAn4+/vzYzeHDBmCdevWAQAf1BqD2cTERLAsW+t8TGKxuNb93rp1C0FBQXBxMZ+eorYxozKZjB8Ta+Tl5YWiopbp0jNu3Dhs374da9asQWlpKfz8/DBhwgQsXLjQrIzR0dH466+/MG/ePMydOxfu7u6YPn06PvjggxYpF2lf5s6diy1btti7GG2aTleBSlUa9Lpy6PTl0OsqYDCowcIAsGzV/w1gwVb9v+bf3P8B++T2Ky+PB8tyY/uNLTikfaPz2nkY6zog4CGkpm1EcfFZqFRZkMksp+wjjo3Oa8eiUqkgkUia1GU4LS0N4eHhDV4/KysLa9aswdNPP41vv/2WX961a1fMmjUL+/bt47MUtwanC2YBLjjdt28fYmNj+fGyRkOGDMEbb7yBjIwMHD9+HMHBwXy2LYPBAIZhcODAAQiFQovturm52ayM1rbfkmbPno3Zs2c3aN0777zTYgojQhqCfhgtGQw6FBQcRn7+3ygsOgmVKt3eRbIJqTQQnh797V0M0grovHYexroOCBiL1LSNAFhkZ+9BWNhL9i0YsTk6r+u2aNEiLF68GImJiVi2bBn27t0LlmUxYcIErF+/3qLxatu2bfj4448RFxcHuVyOe++9F6tWrUJoaCi/TlhYGEaOHGmRFHbkyJEAwE/FefjwYYwaNQo7d+7ElStXsGnTJmRlZaGwsBCenp744YcfsGLFCsTFxcHV1RX3338/Vq5ciZCQEH6bxplT4uPjMXfuXPz111+Qy+WYMmUKVq5cWWcccurUKeh0Ojz++ONmyx9//HHMmjUL3333XasGs07XzRgwHzd74sQJs0zF/fv3h1QqxeHDh/mxtEZdunQBy7IIDw/H3XffbfFv8ODBte6zU6dOyMrKglKpNFuelJTU5ONgGKbJryXEHlrzy62tY1kWmZk/4PTpe3A59kVkZu1qN4Esw4jx228AwzjlT4zTofPaeRjr2t09Ci4uXLbbm8mfoaTkoh1LRVoCndcNExMTg7KyMnzwwQeIiYnB5s2bsXjxYrN1mpo8tj5Lly7F/v378frrr2P58uWQSCTYvHkzYmJiIBQK8cEHH+D555/HTz/9hDvvvNNiX8Zks2Kx2Gqy2doY56WtmSTMGMCfP3++ycfUFE7ZMjtgwADIZDJs374dGRkZZi2zUqkU0dHRWL9+PSoqKvjAFwAmTJiA+fPnY/Hixdi2bZtZMMmyLAoLC2tN6HTffffh66+/xtdff405c+YA4Fp6169f3+TjMH5omnMiENKa9u2j8VUA1xobH/8uMrN28csEAim8vAZDoegLF5dwiMVeEAldIRS6QCCQgWGEVcEhU/V/QdV3kKDG8ur/2wvDCDF6lMRu+yeti85r52Gsa4Zh0L3bUly4+AxYVoPY2JfQv//3kMtD69kCcRR0XjeMaXJWgJuGc+PGjVi5ciUA8+SxCxYs4NebMGEC+vXrh88//9xseWOoVCqcO3eODyq1Wi3mzZuHqKgoHD16FDKZDADXiPfQQw/h448/Ngu0jclm3333XQBcrp7o6Ghs3LgRM2fOrHW/3bp1A8ANxxw1ahS//NixYwC4qUVbk1MGsxKJBLfffjuOHTsGqVSK/v3Nu8INGTIEq1evBgCzYLZLly5YtmwZ5s+fj5SUFIwbNw7u7u5ITk7Gnj178MILL+D1161PID5u3DgMHDgQ//vf/5CUlITu3bvjl19+QWFhIYCmtbLK5XL07NkT33//Pbp27Qpvb29ERUUhKiqq0dsipDXMnTsXH3/8sb2LYVcGgwaxV2YhP/8vAFx33E6dXkRw0KMQCl3qebXjoLp2HlTXzsO0rr28BiEy8m0kJCyGWpODM2cfQvduSxEQ8BD1ymgHWvK8TkhYirLyay2y7aZwd+uBrl3fbdJrrSVr3bNnD0pLS6FQKCySxxqZJo9tajA7ZcoUs9bRc+fOITc3F4sWLeIDWQAYM2YMunfvjv3791u0Gs+YMQNpaWl8d+dhw4Zh69atde43OjoagwYN4rsujxo1CteuXcPMmTMhFotRWVnZpONpKqcMZgEuSD127BjfrdjU0KFDsXr1ari7u+O2224ze+6tt95C165dze5uhIaG4t5778XDDz9c6/6EQiH279+POXPmYMuWLRAIBBg/fjwWLlyIoUOHmn3oGuP//u//MGvWLMydOxcajQYLFy6kYJa0WXVl73YGLKvH1bjX+UDW3a0XbrttI6RSv3pe6Xicva6dCdW186hZ1x1CnoZKlYnU1K+h15fjatxc3Ez+BEGB4+HldQfc3HpAJHK1U2lJc7TkeV1Wfg3FxWdabPutqWPHjmZ/e3l5AQCKioqgUCialTy2PjWTNt26dQtAdcupqe7du/MzuRgZk82qVCqz8jck2eyPP/6ISZMmYdq0aQC4OOe1117DkSNHEB8f3+hjaQ6nDWaXL1+O5cuXW31u/PjxYNnaM4FOmDCh3tTTNQdvA1zq6+3bt5st27t3LwCgQ4cOZq+19vpFixZh0aJFZsvuuOMOnDt3rs6yENJWHD16tNYM3s4gMWkFcnP3AwAUir7o13czRCJ3O5eqZTh7XTsTqmvnUbOuGYZBZMRb8PToj2vX50OrLUJl5S3cTP4ESP4EACASKSAUuoBhxBAIRGAYERhGXO9wCKauoRL19mar6/nG9YQTCMToGDodfn53N+p1jq4lz2t3tx4tst2mak55akuUZIwjGpM8trZemnq93upra45ZbSzjNsvLyxvdqBYSEoLjx48jMTER2dnZiIyMRGBgIIKDg9G1a9dmlauxnDaYtYfKykqzD55er8dnn30GhUKB6OhoO5aMkNZhvGPpjCor05CWtgkA4Ooaib63bWy3gSzg3HXtbKiunUdtde3ndw88PQchO/snZGR+h4qKRP45na4UOl1paxWxRVRUJMHHZ6RTzZvdkud1U7v0OiLT5LH1BXleXl5W8+DcunWLn1mlLp06dQIAxMfHY/To0WbPxcfH88/X1JwZVCIjI/lW57i4OGRlZWHq1KlN3l5TOM9Z2QbMmjULlZWVuOOOO6BWq/HTTz/h5MmTWL58ebPvrhDiCEzTwjubjIwdMM792qvXJxCLPe1anpbmzHXtbKiunUdddS0WKxAaOhWhoVOhVueguOQ8KpW3oFJncXNlG3QwsFqwrK7qn76OPdUxT3YdPee4V9pujm2tthhlZbHQagtRVHQSPj7Dbbbtto7Oa9toTPLYLl264NixY9BoNJBIuCSKv/76K9LS0hoUzA4YMAD+/v7YsGEDpk2bxg+jPHDgAK5du4b33nvP6uuM+2oOg8GAN998Ey4uLhbjiFsaBbOtaPTo0Vi9ejV+/fVXqFQqRERE4LPPPsMrr7xi76IR0ip+//13DBw40N7FaHV6vQoZmVzmYk+P2+Hu1t3OJWp5zlrXzojq2nk0tK6l0gAE+D/YCiVqWTpdGY4dHwiDQYPsnF+cKpil89o2GpM89rnnnsPu3btx//33IyYmBjdu3MC2bdvQpUuXBu1LLBZj5cqVePbZZzFixAhMnjwZOTk5WLt2LcLCwjB37lyrryspKYGra+PGts+ZMwcqlQp9+/aFVqvFjh07cPbsWWzZssViHHFLo2C2FT3xxBN44okn7F0MQuzmf//7n72LYBc5ub9CpysGAHTo8LR9C9NKnLWunRHVtfNwtroWidzh4zMaeXkHkZf3B/R6FYTCpiXsdDTOVtctqaHJY++77z6sXr2an4t2wIAB+PXXXxtVF1OnToWLiwtWrFiBefPmwdXVFePHj8fKlSvh6elp9TUBAQGNPqZ+/frhk08+wfbt2yEQCDBw4ED8/fffZlP1tBaGrSvTESEt7OrVq4iKisKVK1fQq1cvexeHtLCYmBjs2rWr/hXbmXPnY1BSch4SiT+GDjkKgaDp2QsdhbPWtTOiunYezljXubm/I/bKSwCAqKh1CPB/wM4lah22qOubN28CQIO6yBL7uXHjRoNbf22hvs9FY2MDmgisjdi1axe8vb1RXl7erO0cPHgQbm5uyMvLs1HJCLEdZ7sIAgC9Xo3S0ssAgAD/B50ikAWcs66dFdW183DGuvbxGQmhkMs4m5S0EpWV6XYuUetwxrp2Vq0ZyLYEhw9mT548iUWLFlnN/uUo9Ho9Fi5ciFmzZpml6G6K+++/HxEREfjggw8a9bp///0Xr7zyCnr16gVXV1d07NgRMTExSEhIMFtv6tSpYBjG4l/37u1/DCBpvrFjx9q7CK2urCwWLKsFAHh4OE/Wcmesa2dFde08nLGuhUIpOnZ8DgCgUqXhv/8mQ6lMtnOpWp4z1rWzSkxMrH+lNszhx8yePHkSixcvxtSpU2vtC97W7du3D/Hx8XjhhRdssr0XX3wRr7/+OhYvXgx394ZN/bFy5UqcOHECjz32GPr06YPs7GysW7cO0dHROH36NKKiovh1pVIp/u///s/s9R4eHjYpO2nf9u3bZ+8itLqS0gv8Yw+PfnYsSetyxrp2VlTXzsNZ6zo87BXo9eVITf0/qNSZ+PfcBERFfQYf7zvtXbQW46x17YyMU+s4KodvmW0Mg8EAlUpl72JY2LRpE4YOHWqzNOgTJ06EWq3GDz/80ODXvPbaa7h16xY+/fRTPPfcc3jnnXdw7Ngx6HQ6rFixwmxdkUiEp556yuwf3cEjDbFgwQJ7F6HVlZRwwaxUGgiZLNjOpWk9zljXzorq2nk4a10zDIOILm8hPHwOAG7u3IsXn0Vy8mf1TDHkuJy1rp1Rerpjd5136JbZRYsW8VnBwsPD+eXJyckICwsDwzB4+eWXcccdd2D58uVISEjADz/8gHHjxuGjjz7CTz/9hPj4eCiVSvTs2RPz58/Ho48+arGfbdu24dNPP8WVK1cglUrRu3dvvPPOO7j33nv5dQ4cOIDly5fjv//+g0AgwPDhw/Hhhx/WO3BZpVLh4MGDFl8aEyZMQEpKCv777z9+2dixY/Hrr7/i559/5rOfnTlzBoMHD8Zvv/2GBx7gkhL4+/ujT58++PnnnzFt2rQGvZdDhgyxWBYZGYlevXrh2rVrFs/p9XpUVFRAoVA0aPuEAMDkyZPtXYRWxbIsH8x6KJynVRZwvrp2ZlTXzsOZ65phGHQOnw0Xl3BcuzYPBoMaN5M/QUbmdxAK3SASuUEi8a365wOhwAUCoRQCgRRCgRQCgQyMQAQGDFD1j2EEVY9h8pgBGKZqPfswsFqMG+eD9PRtCAqaCKFQbreykJbn7e1t7yI0i0MHsxMmTEBCQgJ27tyJjz/+GL6+vgAAPz8/fp1//vkHu3btwiuvvAJfX1+EhYUBANauXYuHH34YTz75JDQaDb777js89thj+PXXXzFmzBj+9YsXL8aiRYswZMgQLFmyBBKJBGfOnME///zDB7Nbt27FlClTcN9992HlypVQKpX44osvcOedd+LChQv8Pq05f/48NBoNoqPNx9INGzYMP//8M0pLS6FQKMCyLE6cOAGBQIBjx47xweyxY8cgEAgwdOhQs9f3798fe/fubepbC4C7EM/JybEIyJVKJRQKBZRKJby8vDB58mSsXLmy2eN9SfsXGxuL3r1727sYrUalyoRGkwvAuboYA85X186M6tp5UF0DgQFj4eoSgStX50CpvAG1OtveRWox8QlAYdEJ9I76HAzTtOCaJk1p+yorK+Hi4tJq+2NZtsmfJ2scOpjt06cPoqOjsXPnTowbN85q0BgfH4/Y2Fj07NnTbHlCQgLk8uo7Ta+88gqio6OxZs0aPphNSkrCkiVLMH78eOzevRsCQXWvbOPJWV5ejtmzZ+O5557DV199xT8/ZcoUdOvWDcuXLzdbXtP169cBmLcsA1wwazAYcOLECTzwwAO4cuUKioqK8Nhjj+HYsWP8eseOHcNtt91m0ULauXNn5OfnIzc3F/7+/rXuvy7bt29HRkYGlixZwi8LCgrCm2++iejoaBgMBhw8eBCff/45Ll26hMOHD0Mkqv0jlZuba5FlOSkpqUllI87JYFBDp6sAy+rBQg+wBu4xqwfLGqqWtZ0fzsKiE/xjZwtmCSGkvXJ374GBt+/FrdSNqKhIAFgWWl0JNJp8aDT50GqLALSd36LmyMv7AxkZ29Ghw1ONfi3DMNDr22c3bNJ0LMuaxVTN1e7HzI4YMcIikAVgFsgWFRWhpKQEw4YNM+vWu3fvXhgMBrz33nsWb7rxjsKff/6J4uJiTJ48Gfn5+fw/oVCIQYMG4dChQ3WWr6CgAADg5eVltrxfv35wc3PD0aNHAXBBa4cOHfDMM8/gv//+g1KpBMuyOH78OIYNG2axXeP28vPz69x/ba5fv8530Z4yZQq//IMPPsCKFSsQExODxx9/HJs3b8b777+PEydOYPfu3XVu8/PPP0dUVJTZv3HjxgEAjh8/jiNHjmDVqlUoLCzk92kcizt37lwkJSXhm2++wZ49e3D27FksXboUSqUSMTExZusuWLAAsbGx2LFjB3bs2IHY2Fi+G7dxnZiYGCiVSixduhRnz57Fnj178M033yApKQlz5841W3fKlCkoLCz8//buPC6qqv8D+GdmmBn2fRERN3AFy50s1+pJjVwqxcxybdHS0krJHUEtI+PJ3Cu1x1Ifl7THMhcyTVMxFX8uoIACIoLsyDb7+f0xzpVxWHUWZu73/Xrxgrn33Dvfw5cZ5txz7jmIjY3F8ePHcfDgQaxZswbZ2dmYOnWqXtmpU6ciOzsba9aswcGDB6lOD9WpS5cu9daJMQ3eeut5pKd/g2+/64FTpwfj94Oh+ONoR/x5rDNOnOyFk38/hb//fgZ/n+qHU6cH4vSZ53Am4V9ISBiChLNDm8xXaupSAIBAIMGECQutJk/G+NtLS0uzuTrZYp6MUad9+/bZXJ1sMU/GqFNwcLDN1elR8zR27EQ085uCfXt9UVU1HpkZryDp6mg099+OX/e/hIEDrmLd2g7o+8xp/LynJzp2/C+Sk0ZBJFwMpTIS6enj0KrlBsTH90bPHnuwY3tr9OixE0f/6IWWgauRmREBlXIWRMJPcf36CLQL3oiDv3dB9+47sHNnK3TvvgOn/n4Gfr5fIjfnTVSUvwcHh8W4fHkoQjpvwS/72uuVPX/uWbi7LUNR4RQUFU6Bu9synD/3rF6ZX/a1R0jnLbh86UUUFEyHRuMOALieshSLF09udJ72798PlUqF9PR0KBQK5OXlobS0FGVlZcjNzeX2AQ9m1M3KyoJMJkNBQQGKi4tRUVGBO3fuQK1W48aNG3plb9++jcrKShQWFqKwsBCVlZXc/Z+6Mjdu3IBarcadO3dQUVGB4uJiFBQUQCaTISsrS69seno6VCoVcnNzUVZWhtLSUuTl5UGhUCAzM1OvbGZmps3USdfRZI463b17F1VVVTh58mSt7xGXL19GYwiYlff/f/nll5g9ezZ3n2x1AoEAkydPxvfff29w3K+//oqlS5fi4sWLkMvlesdoNBoAwLRp07Bx40ZUVVVBIpHU+PxffPEFIiMja43P1dUVpaWlte7XHZ+VlYUWLVro7XvhhRdQWVmJkydPYuzYsRAIBFi7di28vLxw5MgR+Pn5ITQ0FLt27TK413fdunV47733kJSUhE6dOtX6/DXJzc3FM888A6VSiTNnzqB587onramqqoKzszMmTZpkMMtxdbX1zI4cObLBCyMT6zZv3jwsX768xn2MqZGTuxfp6asgk2WbOTLT8vZ+Dk8+UfsIDVtUV66JbaFc8wflmj/mzZuHOXNewYXE18GYGo6ObdGr5z7Y2Tk1+Bz37t1DdnY23Nzc4O/vb9ShpcR4bt++bdAGMQWFQoGcnBxUVlYiMDCw1tsTr169itDQ0Aa3Dax6mHFDVO+B1dHdc9q/f3+sXbsW/v7+EIvF2Lx5M7Zt29ao8+savlu3bkWzZs0M9tc17BYAvLy8AGh7hx/+Q+rbty+WLVsGmUyGEydOYP78+XB3d0doaChOnDgBPz8/AKixZ7a4uBgAuPuIG6q0tBRDhw5FSUkJTpw4UW9DFtD+jr28vFBUVFRnOV9f30ce8kxsQ20fgpTKEly8OAn3yi7pbXewbwknp2BIJN6wE7tBbOcKkcgJAoEdBAIhBAIRIBBCABEEApF2Ag1B0xpwIhRI4OHRx9JhmB194OUPyjV/UK75Q5frNm0+xM2bX6Gy8iZSUqLQqdMXDW6Uuri4wNHREaWlpSgvL4dIJKIGbRN18+ZNk52bMQbGGJRKJQDthFNOTg2/KFIfq2/MPsqLYs+ePbC3t8ehQ4cglUq57Zs3b9YrFxQUBI1Gg6SkJHTt2rXGcwUFBQHQNtSef/75RsfSsWNHANphAA9PqtCvXz8oFAps374d2dnZXKO1f//+XGO2ffv2XKO2uvT0dHh7e+tNhlUfmUyGYcOGISUlBfHx8TUOz65JWVkZCgoKGvVchJ+GDRtmsHadWl2F/7v0NteQlUr80KrVO/DxGQx7e39LhEmMoKZcE9tEueYPyjV/6HLdutVUFBefQXHxKeTk/gyRyAnt2y/UXkyuh0AgQEBAAIqLi1FeXk6TQTVRJ0+eRN++plszWSAQQCgUwtHREa6urnBycqIJoKrTtexLSkoafIzuylD1m9IzMjIMZv8dOXIkIiMjER0dXeMEUAKBAIMHD4arqyuWL1+OQYMGQSwW650jPz+/zkZejx49IJFIcO7cOW6GYp2wsDCIxWKsWLECnp6eXFd7v379sHnzZri7u2PIkCE1nvf8+fPo06fhvUFqtRpjxozB6dOn8csvv9R4rEwmg1KphIuLi972mJgYMMZqjYUQnYc/BDHGcDXpI5SWau9V9/V9EZ07fUHLANgA+sDLH5Rr/qBc84cu1wKBCCGdV+Kfcy9DLs/F7eytqJLdQvt2i+Do2Lre89jZ2cHHx4c6PJqwtm3bWjqEx9K0xuM9gh49egAA5s+fj61bt2LHjh2oqKio85jw8HBUVlZiyJAhWL9+PaKjoxEWFobg4GC9csHBwZg/fz727t2Lfv36YeXKlVi9ejUmTJjATQTg6uqKdevW4cSJE+jevTuWLVuGjRs3YsGCBejWrRu3Dm5t7O3t8cILLyA+Pt5gn6OjI3r06IHr16/jmWee4a5i9O/fHxUVFXq9tdXl5eXh0qVLGDFiRJ3PXd3HH3+M//3vfxg6dCiKiorw448/6n0B2ntpW7Zsiffeew+rVq3CqlWrEB4ejtjYWAwZMqRRz0f4STfJhk5R0Unk5x8GAHh4PI2Qzl9SQ9ZGPJxrYrso1/xBueaP6rmWSn3Rs8duODt1AAAUFh7HmYTBuHxlBnJy9qCk5BwqKm5AoSiERqOkHlgrY+2va6ufAAoAli5divXr1yMnJwcajYabDEogEOD999/H6tWrDY7ZtGkTPv/8c9y6dQtt2rRBZGQkMjIysGTJEoMX4ebNm/HNN98gKSkJjo6OeOKJJ7BgwQK9YcXHjh3D559/jjNnzkAulyMgIAD9+vXD9OnTuQZ3bfbu3YtXX30VmZmZCAwM1Ns3Z84cxMbGYsWKFZgzZw63vV27dkhLS8ONGzcMrqisX78eH3/8MXJzcw16UWszcOBAHD9+vNb9jDGUlJRgxowZOHPmDDdjWXBwMMaNG4dPPvnEoFe6IRp7kzexbpWVldxaZowx/HPuZZSVXYZI5ISn+/wJicTLwhESY6mea2LbKNf8Qbnmj5pyrVKV4XpKFHJz99VztABCoRgCgeT+d7F2Tot6jnnw00NDUA2GpApq+Zk8CsY06NB+EXx8Gn+7pCk0tm1gE41Za6dWq9G5c2dEREQgJibmsc/XrVs3DBw4EHFxcUaIzrSoMcsvMTExWLhQu0RNXv4hXL78HgCgTesZaNt2pgUjI8ZWPdfEtlGu+YNyzR915bqs7CoyMzeisOg4VKoyM0dGTCGkcxyaNRtef0EzoNmMrZBIJEJ0dDSmTZuGyMjIWqeqboiDBw8iNTUVhw4dMmKEhBjH4MGDAWh7ZdPTvwEA2Nm5o2XLKZYMi5iALtfE9lGu+YNyzR915drFJQShoV9Do1GivOI6lIoiKJUlUCqLoVKVQcOUYBrlg+8aud7xDA/3o1V7bNDHxh56xGrdRx5NQUEhHBxMvzSPqVBjtokYM2YMxowZ89jnGTJkCMrLy40QESHGl52tXT+2rOwyysuTAQAtAyfCzq5hw+GJ9dDlmtg+yjV/UK75oyG5FgrFcHUJNUM0xJT27t0LN7fulg7jkVn9BFCEEOuhW//4zp2d97cI4d98tOUCIiajyzWxfZRr/qBc8wflmj+sPdfUmCWEmE3//v2hVlch9652yn8vrwGwlzazcFTEFPr372/pEIiZUK75g3LNH5Rr/rD2XFNjlhBiNmvWrEFe3u9Qq7VD4ZtTr6zNWrNmjaVDIGZCueYPyjV/UK75w9pzTbMZE4ui2Yz5hTE1zv4zAuXlyRCLvdD3mb8hFDZ+SSdCCCGEEGJ7Gts2oJ5ZQojZREYO5CZ+CmwxnjcNWT5eMxw2bJilQyBmQrnmD97mmt7DiQ2z9lxTY5YQYhbxaQfQbdAtAIBU4seb5Xjib8bDYZkD4m/GWzoUs4m/GY8jYUd4VWc+279/v6VDIOYQH4/9R44A8Tx7XcfHAw4O/Ko3X3PNU9b+Hk6NWUKIyalUVfi/qx/BV6pdDaxNmw8hEjlYOCrTY4zh0/hPIVfLMTd+Li96aLk67+ZPnfluwoQJlg6BmBpjwKefYoJcDsydy5+eyvv1Bp/qzddc85i1v4fTOrOkSUhOnguFwt3SYRATKShLQVcXJQAgrVwOWbkDAiwckzn8lvobzuecBwCcyzmHA6kHEN4+3MJRmRZX58H8qTPfxcXFWToEYmq//QacP484ADh3DjhwAAjnwev6fr0B8KfefM01j1n7ezg1ZkmTUHovEUXFEkuHQUxENwTk/25VITo7D+1yY/Bi+2EQCAQWjcuUGGOIOhYFAQRgYBBAgKhjUXix3Ys2W2+9OicyCJ6x/ToT4Pvvv8fs2bMtHQYxFcaAqChAIMD3jGG2QKB9/OKLgC2/rqvVG4xpv9t6vfmaa56z9vdwasySJsHZuRPc3NwsHQYxgaKqYiTnJyOxtAo/nSiGqiU/euyq98oCAAOz+Xrr1TmAH3UmQO/evS0dAjGlar2TvQFtg4cPPXbVe2UBftSbr7nmOWt/D6fGLLEouVwOALCXvg8H+2ALR0OMjTGGWfvHICn/jnbDXQD22h8jt0Wi1ahWNtljxxhD5O5IIN9wn63W26DO+QActT/aap2J1rVr1+Dt7W3pMIgpMAZERnIPrwHgMh0ZCbRqZZs9dg/VW4+t1puvuSZN7j08LS0NwIM2Qn1onVliUT/88AMmTpxo6TAIIYQQQgghTcS+ffswYsSIestRzyyxqPbt2wMAdu7cic6dO1s4GmJKaWlpGDlyJPbt24fgYOqFt2WUa/6gXPMH5Zo/KNf80RRzLZfLkZWVhQEDBjSoPDVmiUW5uroCADp37oyQkBALR0PMITg4mHLNE5Rr/qBc8wflmj8o1/zR1HLdvXv3BpeldWYJIYQQQgghhFgdaswSQgghhBBCCLE61JglhBBCCCGEEGJ1qDFLLMrHxweLFy+Gj4+PpUMhJka55g/KNX9QrvmDcs0flGv+sIVc09I8hBBCCCGEEEKsDvXMEkIIIYQQQgixOtSYJYQQQgghhBBidagxSwghhBBCCCHE6lBjlhBCCCGEEEKI1aHGLCGEEEIIIYQQq0ONWUIIIYQQQgghVocas4QQQgghhBBCrA41ZgkhhBBCCCGEWB1qzBJCCCGEEEIIsTrUmCWEEEIIIYQQYnWoMUsIIYQQQgghxOpQY5YQQgghhBBCiNWhxiwhhBBCCCGEEKtDjVlCCCGEEEIIIVaHGrOEEEIIIYQQQqyOnaUDIPxWUlKC48ePIzAwEFKp1NLhEEIIIYQQQixELpcjKysLAwYMgLu7e73lqTFLLOr48eMYOXKkpcMghBBCCCGENBH79u3DiBEj6i1HjVliUYGBgQC0f7DBwcEWjoaYklJZjlu3dsLHNwyuLiGWDoeYWGlpKdzc3CwdBjEDyjV/UK75g3LNH00t12lpaRg5ciTXRqgPNWaJRemGFgcHByMkhBo4tiw9Yw2civZBpTqFzp1PQSAQWDokYkKxsbGYPXu2pcMgZkC55g/KNX9Qrvmjqea6obcf0gRQhBCzqKrKAgAoFHlQKPItHA0xtd69e1s6BGImlGv+oFzzB+WaP6w919SYJYSYhUpZwv1cWXnTcoEQs6iqqrJ0CMRMKNf8QbnmD8o1f1h7rqkxSwgxC6WqlPu5ghqzNu/GjRuWDoGYCeWaPyjX/EG55g9rzzU1ZgkhZqHU65lNt1wgxCwGPeuI/7v0Lqqqblk6FGJiNCM9f1Cu+YNyzR/WnmuaAIoQYhYq1T3u58pK674KSOqXkb4CUnslpFI/dOwQbelwiAnFxMRg/fr1lg6DmAHlmj+MlWuVSoXi4mKUl5eDMWaEyIixnT9/Hj169DDpcwgEAkilUri6usLJycmok4BSzywPyeVyREZGonnz5nBwcEBYWBiOHDlS73HXr1/HrFmz8PTTT8Pe3h4CgQAZGRmmD5jYBL2e2QrqmbVlGo0cUnslAKCs7KqFoyGmRo0b/qBc84cxcs0Yw+3bt1FQUAClUmmEqIgpmLohCwBqtRqlpaXIyspCXl6eUS9sUM8sD02cOBG7d+/GzJkz0a5dO2zZsgUvvvgi/vzzT/Tt27fW406fPo1Vq1ahc+fO6NSpEy5evGi+oIlVU6tl0Ghk3OMq2W1oNHIIhQ2bdp1YF4WiiPu5vPwaGFNDIBBZMCJiSsOGDcP+/fstHQYxA8o1fxgj12VlZaiqqoKbmxv8/f1pSb4mKjU1Fe3atTP58ygUCuTk5KCoqAhOTk5wdnY2ynmpZ7YBoqKibOYFePbsWezYsQOfffYZYmNj8c477+Do0aNo1aoV5syZU+exw4cPR0lJCS5fvoxx48aZKWJiC1TVJn/S0qCyMtMisVhCfn48EhPHo7T0oqVDMQuFspD7WaORobIyw3LBEJOjxg1/UK75wxi5vndPe3uRr6+vzXyOtkXmaMgCgEQigb+/P4AHfxvG8EiN2S1btkAgEHBf9vb2aN68OQYPHoxVq1ahrKzMaAES49q9ezdEIhHeeecdbpu9vT2mTJmC06dPIysrq9ZjPT094eLiYo4wiY2pPsRYh0/L89y8+RWKiv/GzZtxlg7FLJSKQr3HZeVJFoqEmMPUqVMtHQIxE8o1fxgj10qlEnZ2drCzo4GgTVlmpvk6FyQSCcRiMeRyudHO+Vg9s9HR0di6dSvWrVuHGTNmAABmzpyJLl264NKlS0YJsClYsGCB1a/BpJOYmIj27dvD1dVVb7tuwWQaOkxMQakyvALHp8ZslSwbAFB6LxEajcrC0Zie4qHGbHn5NQtFQsxh4cKFlg6BmAnlmj+MkWvGGIRCGgTa1Ol6S81FIBAY9Z7Zx/oLGzp0KN544w1MmjQJc+fOxaFDhxAfH4+8vDwMHz7cZhqAdnZ2sLe3t3QYRpGTk1PjH61u2507d0z23Hl5ebh69areV1pamsmejzQdqhp6Zvmy1qxKVQG1uhwAoFZXoKLiuoUjMj2FskjvcXkZ9czasn379lk6BGImlGv+MFauaXhx01dSUmLW5zP234TRL5c8++yzWLhwITIzM/Hjjz/q7Tt69Cj69esHJycnuLu7Y8SIEUhOTtYrk5mZiffeew8dOnSAg4MDvLy8MHr0aINZc3VDnf/66y+8++678PLygqurK8aPH4/i4mK9sq1bt8ZLL72EY8eOoWfPnnBwcECXLl1w7NgxAMDPP/+MLl26wN7eHj169EBiYqLe8TXdMysQCDB9+nTs27cPoaGhkEqlCAkJwcGDBw1+J9nZ2Zg8eTL8/Py4cps2bWrMr9VoqqqqIJUaTrqja6yb8gLE2rVrERoaqvelW9vq5MmTOH78OGJjY1FUVIQJEyYA0E5AAACzZs1CWloaNm3ahL179+Ls2bOIiYlBZWUlIiIi9MrOmzcPly9fxrZt27Bt2zZcvnwZ8+bN0ysTERGByspKxMTE4OzZs9i7dy82bdqEtLQ0zJo1S6/shAkTUFRUhNjYWBw/fhwHDx7EmjVrkJ2dzQ3D0ZWdOnUqsrOzsWbNGhw8eJDqdL9OFRV53N/BvVIxACAl5U+rrlND8/TZ55/qvQ6++up9q69TfXm6evW0Xp3LypOtvk62mCdj1enAgQM2VydbzJMx6hQQEGBzdbLFPBmjTiqV6rHrdPLkSQDaz/YKhQJ5eXkoLS1FWVkZcnNzoVKpkJ6uXd0gNTUVAJCVlQWZTIaCggIUFxejoqICd+7cgVqtxo0bN/TK3r59G5WVlSgsLERhYSEqKytx+/ZtvTI3btyAWq3GnTt3UFFRgeLiYhQUFEAmk3G31unKpqenQ6VSITc3F2VlZSgtLUVeXh4UCgU3FFdX1pbqVFhYaNY6qVQqXL58uda/Pd2+hhKwR+jn3bJlCyZNmoR//vkHPXv2NNh/+/ZtBAYGYtSoUdi1axcAID4+HkOHDkXbtm3x1ltvoaqqCt988w3UajUuXLiA1q1bA9De07l06VKMGDECLVq0QEZGBtatWwdXV1ckJSXB0dFRL4YuXbrA3d0do0ePxvXr17Fu3Tr07dsXx44d4xqgrVu3hr29Pe7du4d3330Xbm5u+PLLL1FaWor169dj3rx5eO+99wAAn332GXx8fHD9+nVuaERUVBSWLFmi1yUuEAjw5JNPIi8vD++99x5cXFywatUq5Obm4tatW/Dy8gIA3L17Fz179oRAIMDbb78NHx8f/P777/jf//6HuLg4zJw5s7G//scSGhoKPz8//PHHH3rbk5KSEBISgvXr1+Pdd9+t9zxffvklZs+ejfT0dC539cnLy0N+fr7etrS0NIwcORJXrlxBSEhIg+tBrEvmre+QlvYZACAgYByys38CIEC/vmchkXhaNjgTKy4+gwuJDyZM8/N9CaGhX1swItNLSpqDnNw9etv69k2AVOJtoYiIKR0/fhwDBgywdBjEDCjX/GGMXN+8qR2B1bZtW2OEREykrKzMrHPi1Pd3cfXqVYSGhja4bWCSO7JbtGgBNzc3rmUOALNnz4anpydOnz4NT0/th9eRI0eiW7duWLx4MX744QcAQHh4OEaNGqV3vmHDhqFPnz7Ys2cP3nzzTb19EokEf/zxB8RibW+Pblbe/fv3Y/jw4Vy569ev49SpU+jTpw8AoHPnzhg8eDDefvttXLt2DS1btgQAeHh44N1338Vff/2FgQMH1lnP5ORkJCUlISgoCAAwaNAgPPnkk9i+fTumT58OAJg/fz7UajUuX77MNXCnTp2KsWPHIioqCu+++y4cHBwa/st9TP7+/sjOzjbYnpOTAwBo3ry5yZ7b19cXvr6+Jjs/abpUSu1sxowJ4Os79H5jlqGo6CSaNRte98FWTi6/q/e4pPS8hSIxnwezGQsAaC8ClpclQ+rVz2IxEdM5e/YsNXB4gnLNH5Rr/qioqHikxuzq1auxZs0a3Lx5E97e3hgzZgxiYmLg5ORkgihrZ7K7sp2dnblZjXNycnDx4kVMnDiRa8gCwBNPPIF//etfOHDgALetesNOqVSisLAQwcHBcHd3x4ULFwye55133uEasgAwbdo02NnZ6Z0T0DZedQ1ZAAgLCwOgHRata8hW3667alCX559/nmvI6urj6urKHcsYw549ezBs2DAwxlBQUMB9DR48GKWlpTXWyZS6du2KlJQUgymxExISuP2EGJvy/tI8Yjs3uLv1gEikfaMrKjphybDMQi7PfehxDmQy092b3hToJoBycXlwRbW4+JSlwiEmNmXKFEuHQMyEcs0flGv+8PZu/KipyMhIzJgxA6Ghofj666/x6quv4ptvvsErr7xiggjrZrLGbHl5OdfK143J7tChg0G5Tp06oaCgABUVFQC092wuWrQIgYGBkEql8Pb2ho+PD0pKSlBa+vBalYZrIzk7O8Pf39/gHtvqDVYAcHNzAwAEBgbWuP3h+25r8vA5AW3Pru7Y/Px8lJSUYOPGjfDx8dH7mjRpEgDt0FtzGjVqFNRqNTZu3Mhtk8vl2Lx5M8LCwrjfx61bt3DtGs1ASoxDtzRPYZEcQqEEHh5P3X980qgz2jVFcrnha9zWe2eV9yeAcnIKhptbdwDA3bwDNp9rvtLdS0dsH+WaPyjX1kUmk0Gj0TzSsXUty1mTnJwcfPXVV3jzzTexa9cuTJ06FatWrUJcXBwOHz5s9vWoTdKYvX37NkpLSxEcHNzoY2fMmIFly5YhIiICO3fuxOHDh3HkyBF4eXk9cpIAQCQSNWp7Qz501XesLt433ngDR44cqfHrmWeeaUj4RhMWFobRo0dj7ty5mDNnDjZu3Ihnn30WGRkZ+OKLL7hy48ePR6dOnfSOLS0txdKlS7F06VLuntvVq1dj6dKlWL16tVnrQayLbphxYGBHAICnp3a4qUKRh3Ibn91XN8zY3j4AQqF28rX8/MOWDMmkGGNcz6xE7AU/33AAgEx2G/fKbGfJNvKA7jYhYvso1/xBua6bbnLYtLQ0TJw4Ee7u7nBzc8OkSZNQWVlpUP7HH39Ejx494ODgAE9PT7z22msGjcjWrVtj4sSJBscOHDhQ79ZH3bxAO3bswIIFCxAQEABHR0du1OWuXbu45/L29sYbb7xhcIvhxIkT4ezsjOzsbMyaNQvOzs7w8fHBJ598ArVaXWfdT58+DZVKhddee01vu+7xjh076jze2Exyz+zWrVsBAIMHDwagvY8V0N63+rBr167B29ubG1+9e/duTJgwAStXruTKyGSyWqeNTk1NxaBBg7jH5eXlyMnJwYsvvmiUujwOHx8fuLi4QK1W4/nnn7d0OJz//Oc/WLhwIbZu3Yri4mI88cQT+PXXX9G/f/86jysuLjZYd0yXp1atWnH3CRPyMKWqBADwf/+Xil49AS/PB39rRYXH4eLc0UKRmZ5coWvMtoC7ey/k5u5Dfv5hyOV5kEpt7x5ytboSGo0MACCReMHXdyhSUpcCYMi7+xvcXJ+0bIDE6IYNG2b2K/HEMijX/EG5bpiIiAi0adMGn332GS5cuIDvvvsOvr6+WLFiBVdm2bJlWLhwISIiIvDWW28hPz8f33zzDfr374/ExES4u7s/0nPHxMRAIpHgk08+gVwuh0Qi4SbI7dWrFz777DPcvXsXX3/9Nf7++2+D51Kr1Rg8eDA6deqEL7/8EvHx8Vi5ciWCgoIwbdq0Wp9XLpcDgMGcP7pJes+fN+/oM6P3zB49ehQxMTFo06YNxo3TzuDp7++Prl274ocfftBrlF65cgWHDx/Wa3iKRCKDXlHdrMc12bhxI5RKJfd43bp1UKlUGDp0qBFr9WhEIhFeffVV7NmzB1euXDHY//DMvuZib2+P2NhY5OTkQCaT4ezZs9yFB51jx44Z5KF169ZgjNX49fCwbkKqUym1Vwv7PPUcAMDRsRUcHFoDAG5nb4NGo7BUaCbH9cxKm6FFwBsAAMZUyL7zX0uGZTJKbvInQCz2glTqB3f3XgB0Q40ffYQNaZroAy9/UK75g3LdMN26dcOePXswbdo0fPvtt3j55Zfx/fffc/szMzOxePFiLF26FDt27MC0adOwaNEi/Pnnn7h9+zbWrl37yM8tk8lw6tQpzJo1C59++inEYjEiIyMRGhqKv/76CzNnzsRnn32GXbt2ISMjA3FxcQbHjxkzhhsqvHv3bnTr1k0v/probhv9+++/9bafOKGdB6WmiWZN6bF6Zn///Xdcu3YNKpUKd+/exdGjR3HkyBG0atUK//vf/7i1SwEgNjYWQ4cORZ8+fTBlyhRuaR43NzdERUVx5V566SVs3boVbm5u6Ny5M06fPo34+HhuJuCHKRQKPPfcc4iIiMD169exdu1a9O3bV28mY0v6/PPP8eeffyIsLAxvv/02OnfujKKiIly4cAHx8fEoKiqydIiEmJyuZ/b06UvQzbLeMnAyrqcsgkx2G3fu7EKLFuNqP4GVYkzD3TMrlfrB1bUrXFxCUFZ2FXeyt6N1q6kQCsX1nMW66IYYA9qeWQDw8w1HSclZyOU5KCiIh4/PC5YKj5jArFmzDD4kEdtEueYPU+Y6JSUGZeXJJjn3o3Bx7oT27RfWX7AGujV1dfr164e9e/fi3r17cHV1xc8//wyNRoOIiAgUFBRw5Zo1a4Z27drhzz//5Nb7bawJEybo9Y6eO3cOeXl5iIqK0muDhYeHo2PHjvjtt9+wZMkSg/izsrK4OXP69evHjbCtTffu3REWFoYVK1YgICAAgwYNQnJyMqZNmwaxWIyqqqpHqs+jeqzG7KJFiwBol8fx9PREly5d8O9//xuTJk0ymOL5+eefx8GDB7F48WIsWrQIYrEYAwYMwIoVK9CmTRuu3Ndffw2RSISffvoJMpkMzzzzDOLj4w16DnVWr16Nn376CYsWLYJSqcTYsWOxatUqbo1ZS/Pz88PZs2cRHR2Nn3/+GWvXroWXlxdCQkL0hiCYk1wux6JFi/SGGS9duhT/+te/6j1WN7b+8OHD0Gg0GDRoEOLi4mgNMVIrxtRQqbQ9s127PrhHvHnz0ci89S1ksiykZ6yGv/8rEInMt0yVOSiVxWBMO3JEIvWFQCBAi4A3kXztU8gVd3E7+0e0DJxk4SiNS6F8cIGOa8z6hePGzZVQqe7hesoSeHj0gZ2d+da0I6b1/vvvWzoEYiaUa/4wZa7LypNRUpJgsvOb08OTwXp4eADQ3prn6uqK1NRUMMYMJqzVqb4iS2NVbz8BdU+427FjR5w8eVJvm729PXx8fCCTyfTib8gkuHv27MGYMWMwefJkANrRqB999BGOHz9e422lpvRIjdmJEyfWeINyfZ577jk899xzdZZxd3fHpk2bDLbXNozV0dERGzZswIYNG2o9Z23H1jTJk24obXVRUVF6vce1HVvbc/n6+mL16tVNZpKkiRMnYvfu3Zg5cybatWuHLVu24MUXX8Sff/6Jvn371npceXk5Bg0ahNLSUsybNw9isRhxcXEYMGAALl68WGvvOeE3XUMWANLT89Czp/ZnoVCCtm0+RFLyJ1Ao8nA9ZQk6dfysyVyIMobqa8xKpc0AAH5+L+Fm+teQy3OQlrYCbq5d4ebWzVIhGp1SoT/MWPvdA8HBn+LatXmQy3ORdiMWHTtEWypEYmR//fXXI034SKwP5Zo/TJlrF+dO9Rcyo8eJpyGTwQoEAvz+++81lnV2duZ+ru3zj1qtrvHYh+9ZbSzdOcvLy/V6chsiICAAJ0+eRGpqKnJzc9GuXTs0a9YMzZs3R/v27R8rrsYyyQRQpOk6e/YsduzYgdjYWHzyyScAtDMXh4aGYs6cOTh1qva1INeuXYvU1FScPXsWvXpp74EbOnQoQkNDsXLlSixfvtwsdSDWRbcsDwA4OOhf8GjWbDiybm9BWdkV5OTsgp2dC9oFz4VAYLJVw8xKvzGrnexJJHJAl9BvcP7CWDCmxOXL76PLE+tsZmIk/WHGD9YVb+4fgdzcX1BSkoDs7J8gEjkgOCjSZnLNZ7qeCGL7KNf8YcpcP+qQXmsUFBQExhjatGlTbyPPw8OjxglvMzMzGzQCsvqEu88++6zevuvXr3P7H1Zbg7wh2rVrx/U6JyUlIScn55E6PB8HfYrgmd27d0MkEuGdd97httnb22PKlCk4ffp0nWtN7d69G7169eIasoB22MJzzz2HnTt3mjRuYr2U1XpmPT1b6O0TCER48onv4OCgfYPNytqEf869cn/92bqnhrcGeo1ZSTPuZze3bmgXPFdbRnEX58+PRlraClRVmXfSBFNQcBNASfWGjQsEAnTq+BnXW3vr1ne4kPgGiopO0fqzVi4gIMDSIRAzoVzzB+XaOF555RWIRCIsWbLE4H8dYwyFhQ8uAAcFBeHMmTNQKB5Mivnrr782eB3Ynj17wtfXF+vXr+dmHAa0cxwlJycjPDy8xuMkEkljqlQjjUaDOXPmwNHR0eA+YlOjnlmeSUxMRPv27eHq6qq3vXfv3gCAixcvcjeBV6fRaHDp0iVubPzDxx4+fBhlZWUG90o3lFJZotejQ2yHrOrBm3DC2at4+mn9/VKpD7p13YoLia9DJruNsrLLuHhxAsRiT7i794KzU3tIpL4Qi90htnOHnZ0LBEIxBBBCILCDQCDS+4KRevqMMdi5qiqT+1kq9dHb16LFeGiYEjdufAnGlMi8tRGZt76Fs3MnuLo+AQf7AEgk3pBIvCEWu0MgEEMgFEMoEEMgsNNOHPVQXQUGUQtq+RnAQ8OZ6nrUGHJZLgBAJjO8D8jRsRV69dyDi//3Fior01BSkoDEiwkQi73g4d4bjk5BcLAPgJ2dK+zsXGBn5wKhUPogtxDe/1nIPX64HqZmmUHwTXvo/R9//IKuXYMsHQYxMbHYE4cOHeI+Lzwu7WoIqvsznKvBmPr+RcyGX9x6tAthjTtGKJQY7R5/bZ3VYEx5v+7VY3k4rrofG9bdeBcFhUKp0XKtW/XiQXyM227NdDPzazQqaDQqbrtGo9bb3qZNK8TERGPevPnIyEjHiBEj4OzsjIyMDOzb9wvefvstfPzxRwCAyZMnYffu3RgyZDBGjRqFmzdv4qeftiEoKAgA457nwXOo9Z5bJBLgs8+WY8qUtzBgQH+89toY3L2bh1WrvkHr1q3x4YczuPLV4793rwSOjg6NGin14YcfQiaToWvXrlAqldi2bRvOnj2LH374weA+YlOz2sbso963y3c5OTnw9/c32K7bdufOnRqPKyoqglwur/fYmm4618nLyzNYjigtLQ0AcP7CaygsevwrQ6RpG/9mzVfrHBwCENb7ADJvbcCtW99Bo5FDqSxCfv4h5OcfMnOUxicWe0Io1P/7FggEaNXyLXh4PIXr1xfj3r2LABjKy5NQXp5kkTiNydu75iFRDg6B6NljJ26m/xt37uyERiODUlmIvPzfAcusVkYeU+8w4MTJHZYOg5iYm1tPfPRR3Ut26CiVJSgs/Atl5UmorLwJhaIIKlUJlMoSqFTlYEwFYza+TK116/cR1PajOsswpkZJ6QXcu3cR5eXXoVAUQKEohFJRCKXq3v3Gq7LOczQVAoEI48bNbVBZhaIQxSUJuFd6EZVVmZDL70KlKoNKVQaJeCI8PPqgrMxweUprp1Bo/2FVVKTA3v7BPy+5POf+9jSUl2tn9X3//WEIDHTA2rVbER2tnU04IKAZBg4Mw3PPdUL5/Zmdn3kmEMuWfYI1a/6Djz76CN26hWDHjn9jwYIvoVZXcuV0F8plstvcNp1Ro3pDKIxFXNz3+PTTuXB0dMBLLw3CkiUzYWeXg/JybXwqVSkADcrLk+HkBKhUThCL3Rtc/27duuHf//43fvrpJwiFQvTu3Rt//PEHBg0a1Mjf5OMTMGu/NEIaJSgoCB06dMCBAwf0tt+8eRNBQUGIi4vDzJkzDY7LyspCy5YtsWLFCsyZM0dv36ZNmzBlyhQkJiaia9eutT53VFSUwZTgOt993wKtW1Nj1pbJ5SL8uPUJlJXJsX//fsybNw9jx47F5cuXAQBdunTB9u3bERX1CRYuGo5x47rgxo1jcHW1/jVovbwGYOGCfOzfvx8RERHYsmULVq5cicGDByM7OxvFxcV46qkAnDj5FXr29MTdu+cglVr3eqxnzkgxJuJ/WLNmDeLi4jBs2DDs378fEyZMQFxcHL7//nv06tUJCsXfqKhMhKdnKZTKPHN3tBJCGmHrfzqistIJO3fu5F7T1d/L7ezuwL95AmSyRAiFtvPxUij0wpHDz2P58uVcvXXv5XFxn6N//yrI5H9AKCy1dKhGk5UlhZvrMhQXF6N///4G7+Uff/Iyxr7mgZLS47W+bzs6zIKn5zPw97favjPecHAIxJ07pfD390dJSQmkUimEQiEqKirg7e2NrKwstGnTBqmpqWjXrh2ysrLg4+OD8vJyiEQiSCQSlJaWws/PDxkZGQgKCuLK3r59G56entySPYWFhUhOTsaIESMMXk8rV65Eu3btMHbsWFy5cgUhuvUc60CNWZ4JDQ2Fn58f/vjjD73tSUlJCAkJwfr16/Huu+8aHFdQUAAfHx9ER0dj4UL9G/fXrl2L999/H9euXXukntmRI0fiSPxydOjQopYjibUTQAAPj6fg5NT4mRHVajmUqmKolKVQKouhUpWBMc39q9wPhqax+8PUYLS3NOOcRyiUwNv7eb3JkBpCra66f2W/AEpVKZhGBQ1Tgmm0w9M0TPlQXR8aglZX/HUMT6vzuAayEznBx+cF2Nk511+4GrVaDoUi7/5V/XKo1GXQaOT386q5n2uNCXLdUOb/d2mMfBDyOCoq0pCd/SMAoFfPvXB1fcKgjEajQmraUty+/SOqv04EAjs4OraBVOIHO7EbxGJ32ImcIRDaQQBRjbeJCBo7nUujr4A1vHxh4Z8oLDwOgUCEQQOT79/e8EBp6QVcvfoxqmS39LZLJD6wl/pDLPHS3ipi56q9PUZgp71VRCiGUGBX720xdd86ghrq/vhXA3NydqOs7AocHdugz1PxBvsZUyM17XNkZemvPCIQSODg0BIO9s25W0UUiqfh4NAaLVt6VYtNwMVOt200HSKRM0QiqVme6+bNmwBQ66RWV69eRWhoaIMbs3SpxEh27tyJqVOn4tatW3rTbDfE+vXrsXz5cqSmpkIqNe0fkr+/P7KzDSeZycnRDjto3rx5jcd5enpCKpVy5RpzrI6vry98fX1rjqvZcAS2qP8Pllg33RW4xhCJpBCJmgHSZvUXtiEikQMcHALh4GB4D7s1eNRcW2t9+exRck2sR0npea4xO2/eh1i9+k+9/YxpkHwtErm5+wBoG7DN/UfD1y8c7m49DG6xsC4MhYXHwZgaCkUBpFI/bk9xcQISL46/P2QacHEJQUDz1+HtPUivnLWprLiBsrIrKCrKNNinVstx5eoHKCjQNnIFAgn8m41Es2Yj4OrazaAxpGu0WPPvgw+0PajWu7ymxWczPnXqFKKiomqcitpaqNVqLF68GDNmzGh0QxbQ3v+rUCjqXCvXWLp27YqUlBTcu3dPb3tCQgK3vyZCoRBdunTBuXPnDPYlJCSgbdu2jzz5E+EP+sDLH5Rr/qBc2zaxnRv384IFswz2p6Yu4xqyzs6dENb7d3TsuBSeHn2svCGr3wirPju9XH4XV65+AMZUEAjEaBc8D7167kNAwGtW33ATS7SNGnt7DTQa/dt80tO/5hqyTk7t0eepw+jU6TN4eDxltl49Yny6pXWsVZNozC5ZssSqG7P79+/H9evX9Za7aQx7e3tMmDABX331lclndxs1ahTUajU2btzIbZPL5di8eTPCwsK4mYxv3bqFa9euGRz7zz//6DVor1+/jqNHj2L06NEmjZvYhnnz5lk6BGImlGv+oFzbNrtqk8Ls+Xmr3r579y4h6/YWAICjYzC6df0BTk71r4dpLaTVRgTJ5dqZ2hnT4MqVD6FQFAAAOnaIQcuWU2xmzWyJ5EEPnVJZzP1cVn4Nt7K+A6Dthe7ZYyeNpLERt2/ftnQIj8WqXnkajQYymczSYRjYvHkznnnmmcdakysiIgKZmZn4888/6y/8GMLCwjB69GjMnTsXc+bMwcaNG/Hss88iIyMDX3zxBVdu/Pjx6NSpk96x7733HoKCghAeHo7Y2Fj8+9//xr/+9S/4+fnh448/NmncxDaMHTvW0iEQM6Fc8wfl2raJ7R4s5deje0e9fTdufgUAEAjE6Prkt3oNIVtQvZdVdr9ntrDoL5SU/gMAaO4fgebNbetivkT8YH4H3ZKJjGlw7dp8MKaGQCBCp44rjLZcEbE8T8/GzenR1Fi0MRsVFYXZs2cDANq0aQOBQACBQICMjAwA2qUrpk+fjp9++gkhISGQSqU4ePAgAODLL7/E008/DS8vLzg4OKBHjx7YvXt3jc/z448/onfv3nB0dISHhwf69++Pw4cP65X5/fff0a9fPzg5OcHFxQXh4eG4evVqvXWQyWQ4ePAgnn/+eYN9uvj37duH0NBQSKVShISEcHWorkePHvD09MQvv/xS73M+rv/85z+YOXMmtm7dig8++ABKpRK//vor+vfvX+dxLi4uOHbsGPr374+lS5di4cKFePLJJ3H8+HH4+PjUeSwhALiZi4nto1zzB+XatgmFEohETgCAvPwMbntx8RkUFZ0AAAQEvAYHB/OuLWkOUokPN+mTbphxVtYWAIBI5IR27WxvVIK42gUJXWO2qOjE/eXjgMDAyXBx6VTToTWieWabPt0sw+Zi7L8Ji04A9corryAlJQXbt29HXFwcvL29AUCvYXT06FHs3LkT06dPh7e3N1q3bg0A+PrrrzF8+HCMGzcOCoUCO3bswOjRo/Hrr78iPDycO37JkiWIiorC008/jejoaEgkEiQkJODo0aN44YUXAABbt27FhAkTMHjwYKxYsQKVlZVYt24d+vbti8TERO45a3L+/HkoFAp07969xv0nT57Ezz//jPfeew8uLi5YtWoVXn31Vdy6dQteXvpXMLt3746///77UX6VjWJvb4/Y2FjExsbWWubYsWM1bm/RogV27dplosgIIYQQ0tSI7dygVldAKHzwoTc9YzUAQCi0R+tW71sqNJMSCESQSHwgl+dCLs9FRcUNrgHv7/+qTfZOSsTVhxkXAQBy72rvixcKJWjTuuG5FggEUKvVxg2QWD3GGIRC4/WnWrQx+8QTT6B79+7Yvn07Ro4cWWOj8fr167h8+TI6d+6stz0lJQUODg7c4+nTp6N79+746quvuMZsWloaoqOj8fLLL2P37t16vzjdVYHy8nJ88MEHeOutt/TuI50wYQI6dOiA5cuX621/mO6+0jZt2tS4Pzk5GUlJSQgKCgIADBo0CE8++SS2b9+O6dOn65Vt27Yttm7dWtNpCLEJXbp0sXQIxEwo1/xBubZ9dmI3QH4Hbm7aj41KZQmKi7UTRzZvHgGp1HZHZ0mlfvcbs3eRdfs/3PbAFuMtGJXpSB7qmVWr5cjPPwIA8PIa1KgGvFgshkwmg0qlgp0dLaDSVFVvT5maQqGAUqmEo6Oj0c7Z5O+ZHTBggEFDFtD/xRcXF6O0tBT9+vXDhQsXuO379u2DRqPBokWLDK4ACO6vzXXkyBGUlJRg7NixKCgo4L5EIhHCwsLqvYe1sFA7BMPDw6PG/c8//zzXkAW0DXhXV1duuvLqPDw8UFVVhcrKyjqfkxBrtX37dkuHQMyEcs0flGvbp5vROO9uOgCgqOhvABoAgI+34W1WtkR336xMdoebtdnLawAcHWvuxLB2dnauEAi0DU+FshCFhcegVpcDAPz8hjXqXK6u2vut8/LyaLhxE1ZUVGSW51EoFNxynrq/DWNo8pdJauvx/PXXX7F06VJcvHgRcrmc2y6otoD0jRs3IBQKa2wM66SmpgIAnn322Rr3N/SXXduLtGVLw3tIPDw8UFxcbLBddw5BoxcAb5ySkhLMmTMHe/fuRWVlJXr37o2VK1fWOlS6urNnz2LLli1ISEjApUuXoFKp6A2KNNjy5cstHQIxE8o1f1CubZ9uRuOAFtoL94WFxwEAIpEj3N17Wioss9A1ZquqMrhtfr7htZS2fgKBAGKxJxSKPCgVRbh7f4ixSOQEb69BjTqXi4sLHB0dUVpaivLycohEIpN/xiWPpqZONmNhjIExBqVSCUA74ZSTk5PRzt/ke2Zr6vo+ceIEhg8fDnt7e6xduxYHDhzAkSNH8Prrrze6YaXRaK8sbt26FUeOHDH4qm9CJt19rzU1TgFAJBLVuL2mOIuLi+Ho6GjS7n6NRoPw8HBs27YN06dPxxdffIG8vDwMHDiQa9jX5cCBA/juu+8gEAjQtq3tTL9PzGPYsMZd1SXWi3LNH5Rr2ycW3++ZzUsHYwyFRX8BADw8+kAotO31RaWSZgbb3Nx6WCAS89ENNZbJslFQeBQA4OP9L4hE9o06j0AgQEBAALy9vSEWi6kh20SdPHnSpOcXCAQQiURwc3NDYGAgfH19jfq3YPGe2UepzJ49e2Bvb49Dhw5BKn3wJrp582a9ckFBQdBoNEhKSkLXrl1rPJduCLCvr2+NMxLXp2NH7TT16enpj33fUHp6usFyOMa2e/dunDp1Crt27cKoUaMAaJcFat++PRYvXoxt27bVefy0adMQGRkJBwcHTJ8+HSkpKSaNl9iW/fv3WzoEYiaUa/6gXNs+sZ07AMDZWYjy8mQoFPkAAC/PuldBsAXVl+cBAInEGw4OrSwUjXnoJoEqKT0HjUY7+tHbu3G9sjp2dnbw8fGhVS+aMGvvnLJ4z6yum7mkpKTBx+iGKVSfIS0jIwP79u3TKzdy5EgIhUJER0dzPbA6up7RwYMHw9XVFcuXL+e6v6vLz8+vM5YePXpAIpHg3LlzDY6/NhcuXMDTTz/92Oepy+7du+Hn54dXXnmF2+bj44OIiAj88ssvekO2a+Ln52fWG8WJbYmIiLB0CMRMKNf8Qbm2fXb3e2YZUyAv/8Hygl5e/GvMurn1sPkeRl3PrK4hCwAuLiGWCoeYmLW/h1u8Mdujh3aoxvz587F161bs2LEDFRUVdR4THh6OyspKDBkyBOvXr0d0dDTCwsIQHBysVy44OBjz58/H3r170a9fP6xcuRKrV6/GhAkTMG+edm0wV1dXrFu3DidOnED37t2xbNkybNy4EQsWLEC3bt2wZMmSOmOxt7fHCy+8gPj4+Mf4LWiX+CkqKsKIESMe6zz1SUxMRPfu3Q0mxOrduzcqKyupp5WY1JYtWywdAjETyjV/UK5tn24CKADczLYODq1scm3Zh0ml+sOM3W18iDEAiCWeeo9FIkde5JqvrP093OKN2V69eiEmJgb/93//h4kTJ2Ls2LH19oY+++yz+P7775Gbm4uZM2di+/btWLFiBV5++WWDstHR0di0aROqqqowf/58LFq0CJmZmXjuuee4Mq+//jr++OMPBAQEIDY2Fh9++CF27NiBrl27YtKkSfXWYfLkyThz5gyysrIa/wu4b9euXWjZsmWtE1EZS05ODvz9/Q2267bduXPHZM+dl5eHq1ev6n2lpaWZ7PlI07Ny5UpLh0DMhHLNH5Rr2ye+PwEUAFRUaOfX4EtPnUHPrI1PeAXorzULAE5OHSAQ1DwHDLF+1v4ebvHGLAAsWLAAt2/fhlqtBmOMW2+WMYbVq1fXeMzkyZORkpICmUyG5ORkTJw4EVFRUTVOrDRp0iRcuHABMpkMRUVFOHbsmMH9sQMHDsTBgwdRUlKCqqoqpKWlYfPmzVzPcV2GDx+Odu3aGaxHW1v8GRkZeldB5HI5fvjhB3z00UeNGrqi0Wggk8ka9KX7vVRVVendZ6xjb2/P7TeVtWvXIjQ0VO9r5MiRALQ3nx8/fhyxsbEoKirChAkTADyYWGTWrFlIS0vDpk2bsHfvXpw9exYxMTGorKzkhkfoys6bNw+XL1/Gtm3bsG3bNly+fJnrideViYiIQGVlJWJiYnD27Fns3bsXmzZtQlpaGmbNmqVXdsKECSgqKkJsbCyOHz+OgwcPYs2aNcjOzsbUqVP1yk6dOhXZ2dlYs2YNDh48SHV6qE6DBw+2uTrZYp6MUSe5XG5zdbLFPBmjTomJiTZXJ1vM0+PUKS1Nu5yGlvbzxP7/nbXqOjU0Tzt3/gKBQLsmplBoj/Fvzrf6OtWXp0OHTqE6jcbf6utki3kyVp0OHz7cpOp0+fJlNIaA0boqRvHf//4X06ZNw61bt+Ds7NyoY9evX4/ly5cjNTW1xoZmbY4dO4ZBgxp2Q35ycjI6duwIZ2dnjBkzBt9//73e/gMHDiA8PBwHDx7E4MGDG3TO6dOnY82aNQ2eQTovL8+g1z0tLQ0jR47ElStXEBLCj6u8fLZ3794aR1AQ20O55g/Kte0rK0vC2X/0Z63u3OlL+PvzI+9nEoaioiIF7u5h6NG97okybUF+wR+4dOkd7nGHDjFoEfC6BSMiptTU3sOvXr2K0NDQBrcNLD6bsa0YM2YMxowZ80jHTp06lbs60hgdO3Y0mMG5NrphxP7+/tyCxdXptjVv3rzRcTSUr68vfH19TXZ+0vTVtoQVsT2Ua/6gXNu+6sOMdRydrHsG1MZo03o6bmVtQts2H1g6FLN4eJixi3NHC0VCzMHa38OpMWvFmjVrhokTJzbqmK5du+LEiRPQaDR6k0AlJCTA0dER7du3N3KUhDzQv7/tz3xJtCjX/EG5tn121SaA0nFy5E9j1s8vHH5+4ZYOw2wkehNACeDk1MFisRDTs/b38CZxzywxn1GjRuHu3bv4+eefuW0FBQXYtWsXhg0bpjfM+caNG7hx44YlwiQ2as2aNZYOgZgJ5Zo/KNe2TyRyhEAg5h5LJN6ws3OxYETElMTVemYdHFrBzs7JgtEQU7P293DqmeWZUaNG4amnnsKkSZOQlJQEb29vrF27Fmq12mAZIt2MzxkZGdy2zMxMbN26FQC4tXWXLl0KAGjVqhXefPNNM9SCWKu4uDhLh0DMhHLNH5Rr2ycQCCAWu0GhKAAAODq0sXBExJREIkcIhfbQaGRwce5k6XCIiVn7ezj1zPKMSCTCgQMHMGbMGKxatQqzZ8+Gt7c3jh49ig4d6h9Gkp6ejoULF2LhwoVISEgAAO7xw5NKEfIw3ax1fMPHefb4mms+olzzQ/Whxo6OPGvM8uw9XCAQ4MoVKQQCOzRrNsLS4RATs/b3cGrM8pCHhwe+++47FBQUoKKiAseOHUPPnobrpmVkZOj1ygLaJYwYYzV+HTt2zDwVIFYp/mY8joQdQfzNeEuHYlbxN+PhsMyBV/Xma675av/+/ZYOgZiBuOLBz3ya/Anx8YCDg/Y7X8THY/onSRig/go+Pv+ydDTExKz9PZwas4QQk2OM4dP4TyHfLcfc+Lm86ank6q3mT735mms+060/SGwYYxAn3+IeOjq0tlws5sQY8OmngFwOzJ3Ljx7a+3WeKJdDNDeKH3XmOWt/D6fGLCHE5H5L/Q3nc84Dg4FzOedwIPWApUMyC67e4E+9+ZprPrP2+61IA/z2G+xuF3EPHf/JsmAwZvTbb8B57Xs4zp0DDvDg/ex+neMA/tSZ56z9PZwas4QQk2KMIepYFAQQAImAAAJEHYuy+R47vXqDH/Xma675juZLsHGMAVFRkJRqAAACFYPDkrW232N3v94QaN/DIRBoH9tyvavV+XuAH3UmVv8eTo1ZQohJ6XrqGBgQADAwXvTY6dUb/Kg3X3PNd71797Z0CMSU7vfUNTtcBtyQo81/iiE8e972e+x0vbK6hhxjtt9TWa3OvQF+1JlY/Xs4Lc1DLEoulwMA0tLSLBwJMQXGGCJ3RwL59zfkA3DU/hi5LRKtRrWCQHfV24YY1LsaW603X3NNgGvXrsHb29vSYRBTYAyIjNT+fFOBtHey0QzAVUC7vVWrBz2XtqR6vR9mq/V+qM7XAHCvalutMwHQ9N7DdW0CXRuhPgJG47+IBf3www+YOHGipcMghBBCCCGENBH79u3DiBH1Lw1FPbPEotq3bw8A2LlzJzp37mzhaIgppaWlYeTIkdi3bx+Cg4MtHQ4xIco1f1Cu+YNyzR+Ua/5oirmWy+XIysrCgAEDGlSeGrPEolxdXQEAnTt3RkhIiIWjIeYQHBxMueYJyjV/UK75g3LNH5Rr/mhque7evXuDy9IEUIQQQgghhBBCrA41ZgkhhBBCCCGEWB1qzBJCCCGEEEIIsTrUmCUW5ePjg8WLF8PHx8fSoRATo1zzB+WaPyjX/EG55g/KNX/YQq5paR5CCCGEEEIIIVaHemYJIYQQQgghhFgdaswSQgghhBBCCLE61JglhBBCCCGEEGJ1qDFLCCGEEEIIIcTqUGOWEEIIIYQQQojVocYssQi5XI7IyEg0b94cDg4OCAsLw5EjRywdFnnIP//8g+nTpyMkJAROTk5o2bIlIiIikJKSYlA2OTkZQ4YMgbOzMzw9PfHmm28iPz/foJxGo8EXX3yBNm3awN7eHk888QS2b99e4/M39JzENJYtWwaBQIDQ0FCDfadOnULfvn3h6OiIZs2a4YMPPkB5eblBuca81ht6TmIcFy5cwPDhw+Hp6QlHR0eEhoZi1apVemUoz9YvNTUVr732Glq0aAFHR0d07NgR0dHRqKys1CtHubYu5eXlWLx4MYYMGQJPT08IBAJs2bKlxrKW/P/cmHOSmjUk1xqNBlu2bMHw4cMRGBgIJycnhIaGYunSpZDJZDWe9/vvv0enTp1gb2+Pdu3a4ZtvvqmxXHZ2NiIiIuDu7g5XV1eMGDECN2/efKxzGhUjxAJee+01Zmdnxz755BO2YcMG1qdPH2ZnZ8dOnDhh6dBINa+++ipr1qwZmzFjBvv2229ZTEwM8/PzY05OTuzy5ctcuaysLObt7c2CgoLY119/zZYtW8Y8PDzYk08+yeRyud45P/30UwaAvf3222zjxo0sPDycAWDbt2/XK9eYcxLjy8rKYo6OjszJyYmFhITo7UtMTGT29vasW7dubN26dWz+/PlMKpWyIUOGGJynoa/1xpyTPL5Dhw4xiUTCwsLC2FdffcU2btzIIiMj2ezZs7kylGfrd+vWLebu7s5atWrFPvvsM7ZhwwY2ceJEBoANHz6cK0e5tj7p6ekMAGvZsiUbOHAgA8A2b95sUM7S/58bek5Su4bkuqysjAFgTz31FFu6dCnbuHEjmzRpEhMKhWzgwIFMo9HolV+/fj0DwF599VW2ceNG9uabbzIA7PPPPzc4b7t27Zivry9bsWIF++qrr1hgYCBr0aIFKygoeKRzGhs1ZonZJSQkMAAsNjaW21ZVVcWCgoJYnz59LBgZedjff/9t8I8pJSWFSaVSNm7cOG7btGnTmIODA8vMzOS2HTlyhAFgGzZs4Lbdvn2bicVi9v7773PbNBoN69evH2vRogVTqVSNPicxjTFjxrBnn32WDRgwwKAxO3ToUObv789KS0u5bd9++y0DwA4dOsRta8xrvaHnJI+vtLSU+fn5sZdffpmp1epay1Gerd+yZcsYAHblyhW97ePHj2cAWFFREWOMcm2NZDIZy8nJYYwx9s8//9TamLXk/+fGnJPUriG5lsvl7O+//zY4dsmSJQwAO3LkCLetsrKSeXl5sfDwcL2y48aNY05OTtz7AmOMrVixggFgZ8+e5bYlJyczkUjE5s6d+0jnNDZqzBKzmz17NhOJRHr/4BhjbPny5QwAu3XrloUiIw3VvXt31r17d+6xr68vGz16tEG59u3bs+eee457vGbNGgaAXb16Va/ctm3bGAC9K/sNPScxvuPHjzORSMQuXbpk0JgtLS1ldnZ2ej14jGn/kTo7O7MpU6Zw2xr6Wm/MOcnjW7duHQPAkpKSGGOMlZeXGzRqKc+2ITIykgFg+fn5BtuFQiErLy+nXNuAuhqzlvz/3JhzkoapK9c1uXTpEgPAVq1axW377bffGAD222+/6ZU9deoUA8C2bt3KbevVqxfr1auXwXlfeOEFFhQU9EjnNDa6Z5aYXWJiItq3bw9XV1e97b179wYAXLx40QJRkYZijOHu3bvw9vYGoL2XIi8vDz179jQo27t3byQmJnKPExMT4eTkhE6dOhmU0+1v7DmJcanVasyYMQNvvfUWunTpYrD/8uXLUKlUBrmRSCTo2rWrQb4b8lpvzDnJ44uPj4erqyuys7PRoUMHODs7w9XVFdOmTePuraI824aBAwcCAKZMmYKLFy8iKysL//3vf7Fu3Tp88MEHcHJyolzbMEv/f27oOYnp5ObmAgD3mQ148Ht/OIc9evSAUCjk9ms0Gly6dKnWXN+4cQNlZWWNOqcpUGOWmF1OTg78/f0Ntuu23blzx9whkUb46aefkJ2djTFjxgDQ5hNArTktKiqCXC7nyvr5+UEgEBiUAx7kvjHnJMa1fv16ZGZmIiYmpsb99eWm+uu3oa/1xpyTPL7U1FSoVCqMGDECgwcPxp49ezB58mSsX78ekyZNAkB5thVDhgxBTEwMjhw5gm7duqFly5Z47bXXMGPGDMTFxQGgXNsyS/9/bug5iel88cUXcHV1xdChQ7ltOTk5EIlE8PX11SsrkUjg5eXF5UWXy4a+5htyTlOwM9mZCalFVVUVpFKpwXZ7e3tuP2marl27hvfffx99+vTBhAkTADzIV305lUqlDc59Y85JjKewsBCLFi3CwoUL4ePjU2OZ+nJT/fVrrHzTe4JxlZeXo7KyElOnTuVmL37llVegUCiwYcMGREdHU55tSOvWrdG/f3+8+uqr8PLywm+//Ybly5ejWbNmmD59OuXahln6/zN93rOs5cuXIz4+HmvXroW7uzu3vaqqChKJpMZjqr8+G5rrxpzTFKgxS8zOwcGhxl413fA2BwcHc4dEGiA3Nxfh4eFwc3PD7t27IRKJADzIV0Ny2tDcN+acxHgWLFgAT09PzJgxo9Yy9eWmel6MlW/KtXHpfp9jx47V2/76669jw4YNOH36NBwdHQFQnq3djh078M477yAlJQUtWrQAoL1wodFoEBkZibFjx9Jr2oZZ+v8zfd6znP/+979YsGABpkyZgmnTpuntc3BwgEKhqPG46q/Pxua6Iec0BRpmTMzO39+fG6ZSnW5b8+bNzR0SqUdpaSmGDh2KkpISHDx4UC9HuqEmteXU09OTu6rn7++P3NxcMMYMygEPct+YcxLjSE1NxcaNG/HBBx/gzp07yMjIQEZGBmQyGZRKJTIyMlBUVFRvbh7+22jIa70x5ySPT/f79PPz09uuGx5WXFxMebYRa9euRbdu3biGrM7w4cNRWVmJxMREyrUNs/T/54aekxjXkSNHMH78eISHh2P9+vUG+/39/aFWq5GXl6e3XaFQoLCwkMuLLpcNfc035JymQI1ZYnZdu3ZFSkoK7t27p7c9ISGB20+aDplMhmHDhiElJQW//vorOnfurLc/ICAAPj4+OHfunMGxZ8+e1ctn165dUVlZieTkZL1yD+e+MeckxpGdnQ2NRoMPPvgAbdq04b4SEhKQkpKCNm3aIDo6GqGhobCzszPIjUKhwMWLFw3y3ZDXemPOSR5fjx49AGhzXp3uniYfHx/Ks424e/cu1Gq1wXalUgkAUKlUlGsbZun/zw09JzGehIQEvPzyy+jZsyd27twJOzvDQbi63/vDOTx37hw0Gg23XygUokuXLjXmOiEhAW3btoWLi0ujzmkSJpsnmZBanDlzxmCdOplMxoKDg1lYWJgFIyMPU6lUbPjw4czOzs5guvXqpk6dyhwcHPSWVYqPj2cA2Lp167htWVlZta45FxAQoLfmXEPPSYwjPz+f7d271+ArJCSEtWzZku3du5ddunSJMcbYkCFDmL+/P7t37x53/HfffccAsN9//53b1pjXekPPSR7fhQsXGAD2+uuv620fO3Yss7OzY9nZ2YwxyrMteOmll5hEImHXr1/X2z5y5EgmFAop1zairuVaLPn/uTHnJA1TV66TkpKYl5cXCwkJqXNd18rKSubp6cleeuklve1vvPEGc3R0ZIWFhdy2zz//nAFg//zzD7ft2rVrTCQSscjIyEc6p7FRY5ZYxOjRo7k16DZs2MCefvppZmdnx44fP27p0Eg1H374IQPAhg0bxrZu3WrwpXPr1i3m5eXFgoKC2KpVq9jy5cuZh4cH69KlC5PJZHrnnD17NgPA3nnnHfbtt9+y8PBwBoD99NNPeuUac05iOg+vM8sYY+fPn2dSqZR169aNrVu3js2fP5/Z29uzF154weD4hr7WG3NO8vgmT57MALCIiAi2Zs0aNnr0aAaAzZ07lytDebZ+ujWjfX19WXR0NFuzZg0bOnQoA8Deeustrhzl2jp98803LCYmhk2bNo0BYK+88gqLiYlhMTExrKSkhDFm+f/PDT0nqVt9ub537x4LDAxkQqGQff755waf106dOqV3Pt0awKNGjWLffvstGz9+PAPAli1bplfu3r17LCgoiPn6+rIvvviCxcXFscDAQNa8eXOWl5f3SOc0NmrMEouoqqpin3zyCWvWrBmTSqWsV69e7ODBg5YOizxkwIABDECtX9VduXKFvfDCC8zR0ZG5u7uzcePGsdzcXINzqtVqtnz5ctaqVSsmkUhYSEgI+/HHH2t8/oaek5hOTY1Zxhg7ceIEe/rpp5m9vT3z8fFh77//vl4PjE5jXusNPSd5fAqFgkVFRbFWrVoxsVjMgoODWVxcnEE5yrP1S0hIYEOHDmXNmjVjYrGYtW/fni1btowplUq9cpRr69OqVata/z+np6dz5Sz5/7kx5yS1qy/X6enpdX5emzBhgsE5N27cyDp06MAkEgkLCgpicXFxTKPRGJTLyspio0aNYq6urszZ2Zm99NJLLDU1tcY4G3pOYxIw9tBd2YQQQgghhBBCSBNHE0ARQgghhBBCCLE61JglhBBCCCGEEGJ1qDFLCCGEEEIIIcTqUGOWEEIIIYQQQojVocYsIYQQQgghhBCrQ41ZQgghhBBCCCFWhxqzhBBCCCGEEEKsDjVmCSGEEEIIIYRYHWrMEkIIIYQQQgixOtSYJYQQQgghhBBidagxSwghhBBCCCHE6lBjlhBCCCGEEEKI1aHGLCGEEEIIIYQQq0ONWUIIIYQQQgghVocas4QQQgghhBBCrM7/A5CdsWyg+E6vAAAAAElFTkSuQmCC", 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\n", 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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -965,46 +1277,366 @@ "name": "stdout", "output_type": "stream", "text": [ - "[11,neuromodulated_stdp6e6abce83c944886bd3262e4ea77c799_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", - "[21,neuromodulated_stdp6e6abce83c944886bd3262e4ea77c799_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", - "[43,neuromodulated_stdp6e6abce83c944886bd3262e4ea77c799_nestml__with_iaf_psc_exp6e6abce83c944886bd3262e4ea77c799_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n" + "[17,neuromodulated_stdp_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[22,neuromodulated_stdp_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[29,neuromodulated_stdp_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[48,neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "WARNING:Under certain conditions, the propagator matrix is singular (contains infinities).\n", - "WARNING:List of all conditions that result in a singular propagator:\n", - "WARNING:\ttau_m = tau_syn_inh\n", - "WARNING:\ttau_m = tau_syn_exc\n", - "WARNING:Under certain conditions, the propagator matrix is singular (contains infinities).\n", - "WARNING:List of all conditions that result in a singular propagator:\n", - "WARNING:\ttau_m = tau_syn_inh\n", - "WARNING:\ttau_m = tau_syn_exc\n" + "WARNING:root:Under certain conditions, the propagator matrix is singular (contains infinities).\n", + "WARNING:root:List of all conditions that result in a singular propagator:\n", + "WARNING:root:\ttau_m = tau_syn_exc\n", + "WARNING:root:\ttau_m = tau_syn_inh\n", + "WARNING:root:Under certain conditions, the propagator matrix is singular (contains infinities).\n", + "WARNING:root:List of all conditions that result in a singular propagator:\n", + "WARNING:root:\ttau_m = tau_syn_exc\n", + "WARNING:root:\ttau_m = tau_syn_inh\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "[56,neuromodulated_stdp6e6abce83c944886bd3262e4ea77c799_nestml__with_iaf_psc_exp6e6abce83c944886bd3262e4ea77c799_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", - "[60,neuromodulated_stdp6e6abce83c944886bd3262e4ea77c799_nestml__with_iaf_psc_exp6e6abce83c944886bd3262e4ea77c799_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n" + "[61,neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "[65,neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml, WARNING, [12:8;12:28]]: Variable 'd' has the same name as a physical unit!\n", + "\u001b[33mCMake Warning (dev) at CMakeLists.txt:95 (project):\n", + " cmake_minimum_required() should be called prior to this top-level project()\n", + " call. Please see the cmake-commands(7) manual for usage documentation of\n", + " both commands.\n", + "This warning is for project developers. Use -Wno-dev to suppress it.\n", + "\u001b[0m\n", + "-- The CXX compiler identification is AppleClang 15.0.0.15000309\n", + "-- Detecting CXX compiler ABI info\n", + "-- Detecting CXX compiler ABI info - done\n", + "-- Check for working CXX compiler: /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++ - skipped\n", + "-- Detecting CXX compile features\n", + "-- Detecting CXX compile features - done\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0mstdp_dopa_balanced_module Configuration Summary\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", + "\u001b[0mBuild static libs : OFF\u001b[0m\n", + "\u001b[0mC++ compiler flags : \u001b[0m\n", + "\u001b[0mNEST compiler flags : -std=c++17 -Wall -Xclang -fopenmp -O2\u001b[0m\n", + "\u001b[0mNEST include dirs : -I/Users/pooja/conda/nestml_dev/include/nest -I/usr/local/include -I/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX14.4.sdk/usr/include -I/usr/local/Cellar/gsl/2.7/include -I/Users/pooja/conda/nestml_dev/include\u001b[0m\n", + "\u001b[0mNEST libraries flags : -L/Users/pooja/conda/nestml_dev/lib/nest -lnest -lsli /usr/local/lib/libltdl.dylib /Users/pooja/conda/nestml_dev/lib/libreadline.dylib /Users/pooja/conda/nestml_dev/lib/libncurses.dylib /usr/local/Cellar/gsl/2.7/lib/libgsl.dylib /usr/local/Cellar/gsl/2.7/lib/libgslcblas.dylib /usr/local/lib/libomp.dylib\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mYou can now build and install 'stdp_dopa_balanced_module' using\u001b[0m\n", + "\u001b[0m make\u001b[0m\n", + "\u001b[0m make install\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mThe library file libstdp_dopa_balanced_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_1bazda9c\u001b[0m\n", + "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", + "\u001b[0m (stdp_dopa_balanced_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(stdp_dopa_balanced_module) (in PyNEST)\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", + " No cmake_minimum_required command is present. A line of code such as\n", + "\n", + " cmake_minimum_required(VERSION 3.28)\n", + "\n", + " should be added at the top of the file. The version specified may be lower\n", + " if you wish to support older CMake versions for this project. For more\n", + " information run \"cmake --help-policy CMP0000\".\n", + "This warning is for project developers. Use -Wno-dev to suppress it.\n", + "\u001b[0m\n", + "-- Configuring done (0.6s)\n", + "-- Generating done (0.0s)\n", + "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target\n", + "[ 25%] \u001b[32mBuilding CXX object CMakeFiles/stdp_dopa_balanced_module_module.dir/stdp_dopa_balanced_module.o\u001b[0m\n", + "[ 50%] \u001b[32mBuilding CXX object CMakeFiles/stdp_dopa_balanced_module_module.dir/iaf_psc_exp_nestml.o\u001b[0m\n", + "[ 75%] \u001b[32mBuilding CXX object CMakeFiles/stdp_dopa_balanced_module_module.dir/iaf_psc_exp_nestml__with_neuromodulated_stdp_nestml.o\u001b[0m\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_nestml.h:252:17: warning: 'iaf_psc_exp_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_nestml__with_neuromodulated_stdp_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_nestml__with_neuromodulated_stdp_nestml.h:305:17: warning: 'iaf_psc_exp_nestml__with_neuromodulated_stdp_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_nestml__with_neuromodulated_stdp_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_nestml__with_neuromodulated_stdp_nestml.h:245:8: warning: 'register_stdp_connection' overrides a member function but is not marked 'override' [-Winconsistent-missing-override]\n", + " void register_stdp_connection( double t_first_read, double delay );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:482:16: note: overridden virtual function is here\n", + " virtual void register_stdp_connection( double, double );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/stdp_dopa_balanced_module.cpp:31:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_nestml.h:252:17: warning: 'iaf_psc_exp_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_nestml.cpp:180:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_nestml.cpp:316:10: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_nestml.cpp:310:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_nestml__with_neuromodulated_stdp_nestml.cpp:190:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_nestml__with_neuromodulated_stdp_nestml.cpp:345:10: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_nestml__with_neuromodulated_stdp_nestml.cpp:339:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/stdp_dopa_balanced_module.cpp:33:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_nestml__with_neuromodulated_stdp_nestml.h:305:17: warning: 'iaf_psc_exp_nestml__with_neuromodulated_stdp_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/stdp_dopa_balanced_module.cpp:33:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/iaf_psc_exp_nestml__with_neuromodulated_stdp_nestml.h:245:8: warning: 'register_stdp_connection' overrides a member function but is not marked 'override' [-Winconsistent-missing-override]\n", + " void register_stdp_connection( double t_first_read, double delay );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:482:16: note: overridden virtual function is here\n", + " virtual void register_stdp_connection( double, double );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/stdp_dopa_balanced_module.cpp:36:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:517:18: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:705:12: warning: unused variable 'cd' [-Wunused-variable]\n", + " double cd;\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:859:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:876:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:1043:18: warning: unused variable '_tr_t' [-Wunused-variable]\n", + " const double _tr_t = start->t_;\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:1025:10: warning: unused variable 'timestep' [-Wunused-variable]\n", + " double timestep = 0;\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:519:10: warning: unused variable 'get_thread' [-Wunused-variable]\n", + " auto get_thread = [tid]()\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:668:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:590:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:615:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:646:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:979:8: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:585:9: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml::update_internal_state_' requested here\n", + " update_internal_state_(t_lastspike_, (start->t_ + __dendritic_delay) - t_lastspike_, cp);\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:668:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:500:7: warning: expression result unused [-Wunused-value]\n", + " dynamic_cast(t);\n", + " ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:316:14: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml::check_connection' requested here\n", + " connection.check_connection( src, tgt, receptor_type, get_common_properties() );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:668:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:519:10: warning: unused variable 'get_thread' [-Wunused-variable]\n", + " auto get_thread = [tid]()\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", + " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:668:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:590:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:615:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:646:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:979:8: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:585:9: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml::update_internal_state_' requested here\n", + " update_internal_state_(t_lastspike_, (start->t_ + __dendritic_delay) - t_lastspike_, cp);\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", + " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:668:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:500:7: warning: expression result unused [-Wunused-value]\n", + " dynamic_cast(t);\n", + " ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:316:14: note: in instantiation of member function 'nest::neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml::check_connection' requested here\n", + " connection.check_connection( src, tgt, receptor_type, get_common_properties() );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", + " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_dopa_synapse/target/neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml.h:668:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< neuromodulated_stdp_nestml__with_iaf_psc_exp_nestml >( name );\n", + " ^\n", + "4 warnings generated.\n", + "5 warnings generated.\n", + "21 warnings generated.\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module stdp_dopa_balanced_module.so\u001b[0m\n", + "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", + "[100%] Built target stdp_dopa_balanced_module_module\n", + "[100%] Built target stdp_dopa_balanced_module_module\n", + "\u001b[36mInstall the project...\u001b[0m\n", + "-- Install configuration: \"\"\n", + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_1bazda9c/stdp_dopa_balanced_module.so\n" ] } ], "source": [ "# generate and build code\n", - "\n", - "\n", - "module_name, neuron_model_name, synapse_model_name = NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_exp.nestml\",\n", - " nestml_stdp_dopa_model,\n", - " post_ports=[\"post_spikes\"],\n", - " mod_ports=[\"mod_spikes\"])\n", - "\n", - "# load dynamic library (NEST extension module) into NEST kernel\n", - "nest.ResetKernel()\n", - "nest.Install(module_name)" + "module_name_bal_network, neuron_model_name, synapse_model_name = NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_exp.nestml\",\n", + " nestml_stdp_dopa_model,\n", + " module_name=\"stdp_dopa_balanced_module\",\n", + " post_ports=[\"post_spikes\"],\n", + " mod_ports=[\"mod_spikes\"])" ] }, { @@ -1111,24 +1743,19 @@ "name": "stdout", "output_type": "stream", "text": [ - "--> Stimuli will be presented at times: [123.0, 142.0, 262.0, 487.0, 680.0, 733.0, 840.0, 978.0, 1004.0, 1230.0, 1867.0, 2061.0, 2163.0, 2505.0, 2764.0, 3102.0, 3195.0, 3770.0, 3780.0, 4008.0, 4054.0, 4420.0, 4450.0, 4767.0, 5080.0, 5688.0, 5949.0, 5959.0, 5986.0, 5996.0, 6515.0, 6663.0, 6685.0, 6766.0, 6816.0, 6875.0, 7151.0, 7395.0, 7501.0, 7896.0, 7935.0, 8246.0, 8260.0, 8553.0, 8739.0, 8852.0, 8984.0, 9068.0, 9200.0, 9329.0, 9693.0, 9959.0, 10227.0]\n", - "--> t_dopa_spikes = [283.0, 513.0, 863.0, 1022.0, 1245.0, 1883.0, 2082.0, 2785.0, 3207.0, 3789.0, 3802.0, 4037.0, 4081.0, 4462.0, 4787.0, 5998.0, 6536.0, 6705.0, 6784.0, 6839.0, 7178.0, 8267.0, 8286.0, 8573.0, 8757.0, 8876.0, 9090.0, 9352.0, 10256.0]\n" + "--> Stimuli will be presented at times: [367.0, 600.0, 811.0, 909.0, 1194.0, 1569.0, 1627.0, 1885.0, 2592.0, 2652.0, 2893.0, 3054.0, 3138.0, 3156.0, 3178.0, 3290.0, 3614.0, 3640.0, 3910.0, 4217.0, 4620.0, 4748.0, 4784.0, 4821.0, 4839.0, 4875.0, 5587.0, 5694.0, 6021.0, 7435.0, 7887.0, 7929.0, 7974.0, 8451.0, 8494.0, 8573.0, 8849.0, 9159.0, 9379.0, 9500.0, 9822.0, 10197.0]\n", + "--> t_dopa_spikes = [393.0, 616.0, 1644.0, 2620.0, 3155.0, 3184.0, 3311.0, 3661.0, 4243.0, 4648.0, 4832.0, 4861.0, 6042.0, 7904.0, 7950.0, 7986.0, 8469.0, 8510.0, 9521.0, 9839.0]\n" ] } ], "source": [ "nest.ResetKernel()\n", - "nest.set_verbosity(\"M_ALL\")\n", - "nest.local_num_threads = 4\n", + "nest.Install(module_name_bal_network)\n", "\n", "nest.resolution = dt\n", "nest.print_time = True\n", "nest.overwrite_files = True\n", - "\n", - "try:\n", - " nest.Install(module_name)\n", - "except Exception:\n", - " pass\n", + "nest.local_num_threads = 4\n", "\n", "nodes_ex = nest.Create(neuron_model_name, NE, params=neuron_params_exc)\n", "nodes_in = nest.Create(neuron_model_name, NI, params=neuron_params_inh)\n", @@ -1326,105 +1953,305 @@ "output_type": "stream", "text": [ "0.0%\n", + "\n", + "[ 100% ] Model time: 100.0 ms, Real-time factor: 9.7313l time: 19.0 ms, Real-time factor: 9.8610\n", "1.0%\n", + "\n", + "[ 100% ] Model time: 200.0 ms, Real-time factor: 19.54213\n", "2.0%\n", + "\n", + "[ 100% ] Model time: 300.0 ms, Real-time factor: 29.410800\n", "3.0%\n", + "\n", + "[ 100% ] Model time: 400.0 ms, Real-time factor: 39.403320\n", "4.0%\n", + "\n", + "[ 100% ] Model time: 500.0 ms, Real-time factor: 49.829150\n", "5.0%\n", + "\n", + "[ 100% ] Model time: 600.0 ms, 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factor: 927.873756\n", "83.0%\n", + "\n", + "[ 100% ] Model time: 8400.0 ms, Real-time factor: 938.672134\n", "84.0%\n", + "\n", + "[ 100% ] Model time: 8500.0 ms, Real-time factor: 949.705972\n", "85.0%\n", + "\n", + "[ 100% ] Model time: 8600.0 ms, Real-time factor: 960.622524\n", "86.0%\n", + "\n", + "[ 100% ] Model time: 8700.0 ms, Real-time factor: 971.461984odel time: 8684.0 ms, Real-time factor: 1154.4391\n", "87.0%\n", + "\n", + "[ 100% ] Model time: 8800.0 ms, Real-time factor: 982.333499\n", "88.0%\n", + "\n", + "[ 100% ] Model time: 8900.0 ms, Real-time factor: 1003.08178993.1546\n", "89.0%\n", + "\n", + "[ 100% ] Model time: 9000.0 ms, Real-time factor: 1004.02253\n", "90.0%\n", + "\n", + "[ 100% ] Model time: 9100.0 ms, Real-time factor: 1015.506620\n", "91.0%\n", + "\n", + "[ 100% ] Model time: 9200.0 ms, Real-time factor: 1027.973470\n", "92.0%\n", + "\n", + "[ 100% ] Model time: 9300.0 ms, Real-time factor: 1040.334210\n", "93.0%\n", + "\n", + "[ 100% ] Model time: 9400.0 ms, Real-time factor: 1053.702700\n", "94.0%\n", + "\n", + "[ 100% ] Model time: 9500.0 ms, Real-time factor: 1066.025630\n", "95.0%\n", + "\n", + "[ 100% ] Model time: 9600.0 ms, Real-time factor: 1078.154360al-time factor: 1627.6174\n", "96.0%\n", + "\n", + "[ 100% ] Model time: 9700.0 ms, Real-time factor: 1091.373340\n", "97.0%\n", + "\n", + "[ 100% ] Model time: 9800.0 ms, Real-time factor: 1104.174520 Model time: 9784.0 ms, Real-time factor: 1311.8843\n", "98.0%\n", - "99.0%\n" + "\n", + "[ 100% ] Model time: 9900.0 ms, Real-time factor: 1116.169360 ms, Real-time factor: 1659.8562\n", + "99.0%\n", + "\n", + "[ 100% ] Model time: 10000.0 ms, Real-time factor: 1129.79500\n" ] } ], @@ -1462,16 +2289,14 @@ "Number of synapses: 100000\n", " Exitatory : 81000\n", " Inhibitory : 20000\n", - "Excitatory rate : 12.43 Hz\n", - "Inhibitory rate : 3.00 Hz\n", - "Actual times of stimulus presentation: [ 124. 143. 681. 734. 979. 2164. 2506. 3103. 4421. 5081. 5689. 5950.\n", - " 5960. 5997. 6664. 6876. 7396. 7502. 7897. 7936. 8985. 9201. 9694. 9960.\n", - " 263. 488. 841. 1005. 1231. 1868. 2062. 2765. 3196. 3771. 3781. 4009.\n", - " 4055. 4451. 4768. 5987. 6516. 6686. 6767. 6817. 7152. 8247. 8261. 8554.\n", - " 8740. 8853. 9069. 9330.]\n", - "Actual t_dopa_spikes = [ 284. 514. 864. 1023. 1246. 1884. 2083. 2786. 3208. 3790. 3803. 4038.\n", - " 4082. 4463. 4788. 5999. 6537. 6706. 6785. 6840. 7179. 8268. 8287. 8574.\n", - " 8758. 8877. 9091. 9353.]\n" + "Excitatory rate : 10.27 Hz\n", + "Inhibitory rate : 2.41 Hz\n", + "Actual times of stimulus presentation: [ 368. 601. 812. 910. 1195. 1570. 1628. 1886. 2593. 2653. 2894. 3055.\n", + " 3139. 3157. 3179. 3291. 3615. 3641. 3911. 4218. 4621. 4749. 4785. 4822.\n", + " 4840. 4876. 5588. 5695. 6022. 7436. 7888. 7930. 7975. 8452. 8495. 8574.\n", + " 8850. 9160. 9380. 9501. 9823.]\n", + "Actual t_dopa_spikes = [ 394. 617. 1645. 2621. 3156. 3185. 3312. 3662. 4244. 4649. 4833. 4862.\n", + " 6043. 7905. 7951. 7987. 8470. 8511. 9522. 9840.]\n" ] } ], @@ -1512,14 +2337,12 @@ "outputs": [ { "data": { - "image/png": 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\n", 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", 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\n", 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", 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\n", + "image/png": 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", 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\n", 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", 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\n", + "image/png": 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", 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\n", 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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -1863,7 +2676,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1877,7 +2690,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.2" + "version": "3.11.8" } }, "nbformat": 4, diff --git a/doc/tutorials/stdp_windows/stdp_windows.ipynb b/doc/tutorials/stdp_windows/stdp_windows.ipynb index 620101dcb..58d5ecda3 100644 --- a/doc/tutorials/stdp_windows/stdp_windows.ipynb +++ b/doc/tutorials/stdp_windows/stdp_windows.ipynb @@ -13,29 +13,7 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " -- N E S T --\n", - " Copyright (C) 2004 The NEST Initiative\n", - "\n", - " Version: 3.6.0-post0.dev0\n", - " Built: Mar 26 2024 10:08:21\n", - "\n", - " This program is provided AS IS and comes with\n", - " NO WARRANTY. See the file LICENSE for details.\n", - "\n", - " Problems or suggestions?\n", - " Visit https://www.nest-simulator.org\n", - "\n", - " Type 'nest.help()' to find out more about NEST.\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "%matplotlib inline\n", "import matplotlib as mpl\n", @@ -46,7 +24,10 @@ "import os\n", "import re\n", "\n", - "from pynestml.codegeneration.nest_code_generator_utils import NESTCodeGeneratorUtils" + "from pynestml.codegeneration.nest_code_generator_utils import NESTCodeGeneratorUtils\n", + "\n", + "# Set the verbosity in NEST to ERROR\n", + "nest.set_verbosity(\"M_ERROR\")" ] }, { @@ -284,21 +265,6 @@ "name": "stdout", "output_type": "stream", "text": [ - "\n", - " -- N E S T --\n", - " Copyright (C) 2004 The NEST Initiative\n", - "\n", - " Version: 3.6.0-post0.dev0\n", - " Built: Mar 26 2024 10:08:21\n", - "\n", - " This program is provided AS IS and comes with\n", - " NO WARRANTY. See the file LICENSE for details.\n", - "\n", - " Problems or suggestions?\n", - " Visit https://www.nest-simulator.org\n", - "\n", - " Type 'nest.help()' to find out more about NEST.\n", - "\n", "[13,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", "[14,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", "[19,stdp_nestml, WARNING, [8:8;8:28]]: Variable 'd' has the same name as a physical unit!\n", @@ -329,7 +295,7 @@ "-- Detecting CXX compile features - done\n", "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", - "\u001b[0mnestml_module Configuration Summary\u001b[0m\n", + "\u001b[0mnestml_stdp_module Configuration Summary\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", @@ -341,15 +307,15 @@ "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mYou can now build and install 'nestml_module' using\u001b[0m\n", + "\u001b[0mYou can now build and install 'nestml_stdp_module' using\u001b[0m\n", "\u001b[0m make\u001b[0m\n", "\u001b[0m make install\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mThe library file libnestml_module.so will be installed to\u001b[0m\n", - "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_90apod2z\u001b[0m\n", + "\u001b[0mThe library file libnestml_stdp_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_hru10kht\u001b[0m\n", "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", - "\u001b[0m (nestml_module) Install (in SLI)\u001b[0m\n", - "\u001b[0m nest.Install(nestml_module) (in PyNEST)\u001b[0m\n", + "\u001b[0m (nestml_stdp_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(nestml_stdp_module) (in PyNEST)\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -364,16 +330,9 @@ "-- Configuring done (0.7s)\n", "-- Generating done (0.0s)\n", "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target\n", - "[ 25%] \u001b[32mBuilding CXX object CMakeFiles/nestml_module_module.dir/nestml_module.o\u001b[0m\n", - "[ 50%] \u001b[32mBuilding CXX object CMakeFiles/nestml_module_module.dir/iaf_psc_delta_nestml.o\u001b[0m\n", - "[ 75%] \u001b[32mBuilding CXX object CMakeFiles/nestml_module_module.dir/iaf_psc_delta_nestml__with_stdp_nestml.o\u001b[0m\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_module.cpp:31:\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.h:267:17: warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", - " inline double get_C_m() const\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", - " virtual double get_C_m( int comp );\n", - " ^\n", + "[ 50%] \u001b[32mBuilding CXX object CMakeFiles/nestml_stdp_module_module.dir/nestml_stdp_module.o\u001b[0m\n", + "[ 50%] \u001b[32mBuilding CXX object CMakeFiles/nestml_stdp_module_module.dir/iaf_psc_delta_nestml.o\u001b[0m\n", + "[ 75%] \u001b[32mBuilding CXX object CMakeFiles/nestml_stdp_module_module.dir/iaf_psc_delta_nestml__with_stdp_nestml.o\u001b[0m\n", "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.cpp:44:\n", "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.h:267:17: warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", " inline double get_C_m() const\n", @@ -404,30 +363,37 @@ "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.cpp:283:16: warning: unused variable '__resolution' [-Wunused-variable]\n", " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_module.cpp:33:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_nestml.cpp:181:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_nestml.cpp:318:10: warning: In file included from unused variable 'get_t' [-Wunused-variable]/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_stdp_module.cpp:31:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.h:267:17:\n", + " warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " ^\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_nestml.cpp:312:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^ virtual double get_C_m( int comp );\n", + "\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_stdp_module.cpp:33:\n", "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_nestml.h:319:17: warning: 'iaf_psc_delta_nestml__with_stdp_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", " inline double get_C_m() const\n", " ^\n", "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", " virtual double get_C_m( int comp );\n", " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_module.cpp:33:\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_stdp_module.cpp:33:\n", "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_nestml.h:259:8: warning: 'register_stdp_connection' overrides a member function but is not marked 'override' [-Winconsistent-missing-override]\n", " void register_stdp_connection( double t_first_read, double delay );\n", " ^\n", "/Users/pooja/conda/nestml_dev/include/nest/node.h:482:16: note: overridden virtual function is here\n", " virtual void register_stdp_connection( double, double );\n", " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_nestml.cpp:181:16: warning: unused variable '__resolution' [-Wunused-variable]\n", - " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_nestml.cpp:318:10: warning: unused variable 'get_t' [-Wunused-variable]\n", - " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_nestml.cpp:312:16: warning: unused variable '__resolution' [-Wunused-variable]\n", - " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_module.cpp:36:\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_stdp_module.cpp:36:\n", "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_nestml__with_iaf_psc_delta_nestml.h:417:18: warning: unused variable '__resolution' [-Wunused-variable]\n", " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " ^\n", @@ -626,13 +592,13 @@ "4 warnings generated.\n", "5 warnings generated.\n", "19 warnings generated.\n", - "[100%] \u001b[32m\u001b[1mLinking CXX shared module nestml_module.so\u001b[0m\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module nestml_stdp_module.so\u001b[0m\n", "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", - "[100%] Built target nestml_module_module\n", - "[100%] Built target nestml_module_module\n", + "[100%] Built target nestml_stdp_module_module\n", + "[100%] Built target nestml_stdp_module_module\n", "\u001b[36mInstall the project...\u001b[0m\n", "-- Install configuration: \"\"\n", - "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_90apod2z/nestml_module.so\n" + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_hru10kht/nestml_stdp_module.so\n" ] } ], @@ -640,6 +606,7 @@ "module_name, neuron_model_name, synapse_model_name = NESTCodeGeneratorUtils.generate_code_for(\n", " \"../../../models/neurons/iaf_psc_delta.nestml\",\n", " nestml_stdp_model,\n", + " module_name=\"nestml_stdp_module\",\n", " post_ports=[\"post_spikes\"])" ] }, @@ -669,9 +636,6 @@ " synapse_parameters=None, # optional dictionary passed to the synapse\n", " fname_snip=\"\"):\n", "\n", - " nest.set_verbosity(\"M_WARNING\")\n", - " #nest.set_verbosity(\"M_ALL\")\n", - "\n", " nest.ResetKernel()\n", " \n", " # load dynamic library (NEST extension module) into NEST kernel\n", @@ -798,4133 +762,501 @@ "cell_type": "code", "execution_count": 7, "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dt_vec, dw_vec, delay = stdp_window(neuron_model_name, synapse_model_name, module_name,\n", + " synapse_parameters={\"alpha\": .5})\n", + "\n", + "plot_stdp_window(dt_vec, dw_vec, delay)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Symmetric LTP or LTD-only\n", + "----------------------\n", + "\n", + "Depending on the frequency at which the spike pairing protocol is repeated, a symmetric potentiation-only window can occur for high repetition rates, whereas for low rates, a depression-only window is observed.\n", + "\n", + "Facilitation-only is easy to obtain without even changing the model:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "dt_vec, dw_vec, delay = stdp_window(neuron_model_name, synapse_model_name, module_name,\n", + " synapse_parameters={\"alpha\": -1.})\n", + "plot_stdp_window(dt_vec, dw_vec, delay)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Adapt the model to obtain the symmetric depression-only window." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Windowed STDP\n", + "------------\n", + "\n", + "In this variant of the original STDP rule, we allow only spikes more than a few milliseconds apart to cause the weight to change. If the pre-post absolute $|\\Delta t|$ is smaller than some threshold, the weight change should be zero." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "nestml_windowed_stdp_model = \"\"\"\n", + "synapse stdp_windowed:\n", + "\n", + " state:\n", + " w real = 1.\n", + " pre_nn_trace real = 0.\n", + " post_nn_trace real = 0.\n", + "\n", + " parameters:\n", + " d ms = 1 ms @nest::delay\n", + " lambda real = .01\n", + " tau_tr_pre ms = 20 ms\n", + " tau_tr_post ms = 20 ms\n", + " alpha real = 1\n", + " mu_plus real = 1\n", + " mu_minus real = 1\n", + " Wmax real = 100.\n", + " Wmin real = 0.\n", + " tau_recency_window_pre ms = 10 ms\n", + " tau_recency_window_post ms = 10 ms\n", + "\n", + " equations:\n", + " kernel pre_trace_kernel = exp(-t / tau_tr_pre)\n", + " inline pre_trace real = convolve(pre_trace_kernel, pre_spikes)\n", + "\n", + " # all-to-all trace of postsynaptic neuron\n", + " kernel post_trace_kernel = exp(-t / tau_tr_post)\n", + " inline post_trace real = convolve(post_trace_kernel, post_spikes)\n", + "\n", + " pre_nn_trace' = -pre_nn_trace / tau_recency_window_pre\n", + " post_nn_trace' = -post_nn_trace / tau_recency_window_post\n", + "\n", + " input:\n", + " pre_spikes <- spike\n", + " post_spikes <- spike\n", + "\n", + " output:\n", + " spike\n", + "\n", + " onReceive(post_spikes):\n", + " post_nn_trace = 1\n", + "\n", + " if pre_nn_trace < .7:\n", + " # potentiate synapse\n", + " w_ real = Wmax * ( w / Wmax + (lambda * ( 1. - ( w / Wmax ) )**mu_plus * pre_trace ))\n", + " w = min(Wmax, w_)\n", + "\n", + " onReceive(pre_spikes):\n", + " pre_nn_trace = 1\n", + "\n", + " if post_nn_trace < .7:\n", + " # depress synapse\n", + " w_ real = Wmax * ( w / Wmax - ( alpha * lambda * ( w / Wmax )**mu_minus * post_trace ))\n", + " w = max(Wmin, w_)\n", + "\n", + " # deliver spike to postsynaptic partner\n", + " deliver_spike(w, d)\n", + "\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ + "[13,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[14,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[19,stdp_windowed_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n", + "[26,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[27,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[29,stdp_windowed_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n", + "[36,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[37,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[41,stdp_windowed_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n", + "[72,iaf_psc_delta_nestml__with_stdp_windowed_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[73,iaf_psc_delta_nestml__with_stdp_windowed_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[75,stdp_windowed_nestml__with_iaf_psc_delta_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n", + "[84,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[88,iaf_psc_delta_nestml__with_stdp_windowed_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[92,stdp_windowed_nestml__with_iaf_psc_delta_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n", + "[98,stdp_windowed_nestml__with_iaf_psc_delta_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n", + "\u001b[33mCMake Warning (dev) at CMakeLists.txt:95 (project):\n", + " cmake_minimum_required() should be called prior to this top-level project()\n", + " call. Please see the cmake-commands(7) manual for usage documentation of\n", + " both commands.\n", + "This warning is for project developers. Use -Wno-dev to suppress it.\n", + "\u001b[0m\n", + "-- The CXX compiler identification is AppleClang 15.0.0.15000309\n", + "-- Detecting CXX compiler ABI info\n", + "-- Detecting CXX compiler ABI info - done\n", + "-- Check for working CXX compiler: /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++ - skipped\n", + "-- Detecting CXX compile features\n", + "-- Detecting CXX compile features - done\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0mstdp_windowed_module Configuration Summary\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", + "\u001b[0mBuild static libs : OFF\u001b[0m\n", + "\u001b[0mC++ compiler flags : \u001b[0m\n", + "\u001b[0mNEST compiler flags : -std=c++17 -Wall -Xclang -fopenmp -O2\u001b[0m\n", + "\u001b[0mNEST include dirs : -I/Users/pooja/conda/nestml_dev/include/nest -I/usr/local/include -I/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX14.4.sdk/usr/include -I/usr/local/Cellar/gsl/2.7/include -I/Users/pooja/conda/nestml_dev/include\u001b[0m\n", + "\u001b[0mNEST libraries flags : -L/Users/pooja/conda/nestml_dev/lib/nest -lnest -lsli /usr/local/lib/libltdl.dylib /Users/pooja/conda/nestml_dev/lib/libreadline.dylib /Users/pooja/conda/nestml_dev/lib/libncurses.dylib /usr/local/Cellar/gsl/2.7/lib/libgsl.dylib /usr/local/Cellar/gsl/2.7/lib/libgslcblas.dylib /usr/local/lib/libomp.dylib\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mYou can now build and install 'stdp_windowed_module' using\u001b[0m\n", + "\u001b[0m make\u001b[0m\n", + "\u001b[0m make install\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mThe library file libstdp_windowed_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_vbp6k7be\u001b[0m\n", + "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", + "\u001b[0m (stdp_windowed_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(stdp_windowed_module) (in PyNEST)\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", + " No cmake_minimum_required command is present. A line of code such as\n", "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. 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Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:27 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:28 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "dt_vec, dw_vec, delay = stdp_window(neuron_model_name, synapse_model_name, module_name,\n", - " synapse_parameters={\"alpha\": .5})\n", - "\n", - "plot_stdp_window(dt_vec, dw_vec, delay)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Symmetric LTP or LTD-only\n", - "----------------------\n", - "\n", - "Depending on the frequency at which the spike pairing protocol is repeated, a symmetric potentiation-only window can occur for high repetition rates, whereas for low rates, a depression-only window is observed.\n", - "\n", - "Facilitation-only is easy to obtain without even changing the model:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. 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Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:29 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:30 iaf_psc_delta_nestml__with_stdp_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "dt_vec, dw_vec, delay = stdp_window(neuron_model_name, synapse_model_name, module_name,\n", - " synapse_parameters={\"alpha\": -1.})\n", - "plot_stdp_window(dt_vec, dw_vec, delay)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Adapt the model to obtain the symmetric depression-only window." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Windowed STDP\n", - "------------\n", - "\n", - "In this variant of the original STDP rule, we allow only spikes more than a few milliseconds apart to cause the weight to change. If the pre-post absolute $|\\Delta t|$ is smaller than some threshold, the weight change should be zero." - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "nestml_windowed_stdp_model = \"\"\"\n", - "synapse stdp_windowed:\n", - "\n", - " state:\n", - " w real = 1.\n", - " pre_nn_trace real = 0.\n", - " post_nn_trace real = 0.\n", - "\n", - " parameters:\n", - " d ms = 1 ms @nest::delay\n", - " lambda real = .01\n", - " tau_tr_pre ms = 20 ms\n", - " tau_tr_post ms = 20 ms\n", - " alpha real = 1\n", - " mu_plus real = 1\n", - " mu_minus real = 1\n", - " Wmax real = 100.\n", - " Wmin real = 0.\n", - " tau_recency_window_pre ms = 10 ms\n", - " tau_recency_window_post ms = 10 ms\n", - "\n", - " equations:\n", - " kernel pre_trace_kernel = exp(-t / tau_tr_pre)\n", - " inline pre_trace real = convolve(pre_trace_kernel, pre_spikes)\n", - "\n", - " # all-to-all trace of postsynaptic neuron\n", - " kernel post_trace_kernel = exp(-t / tau_tr_post)\n", - " inline post_trace real = convolve(post_trace_kernel, post_spikes)\n", - "\n", - " pre_nn_trace' = -pre_nn_trace / tau_recency_window_pre\n", - " post_nn_trace' = -post_nn_trace / tau_recency_window_post\n", - "\n", - " input:\n", - " pre_spikes <- spike\n", - " post_spikes <- spike\n", - "\n", - " output:\n", - " spike\n", - "\n", - " onReceive(post_spikes):\n", - " post_nn_trace = 1\n", - "\n", - " if pre_nn_trace < .7:\n", - " # potentiate synapse\n", - " w_ real = Wmax * ( w / Wmax + (lambda * ( 1. - ( w / Wmax ) )**mu_plus * pre_trace ))\n", - " w = min(Wmax, w_)\n", - "\n", - " onReceive(pre_spikes):\n", - " pre_nn_trace = 1\n", - "\n", - " if post_nn_trace < .7:\n", - " # depress synapse\n", - " w_ real = Wmax * ( w / Wmax - ( alpha * lambda * ( w / Wmax )**mu_minus * post_trace ))\n", - " w = max(Wmin, w_)\n", - "\n", - " # deliver spike to postsynaptic partner\n", - " deliver_spike(w, d)\n", - "\"\"\"" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " -- N E S T --\n", - " Copyright (C) 2004 The NEST Initiative\n", - "\n", - " Version: 3.6.0-post0.dev0\n", - " Built: Mar 26 2024 10:08:21\n", - "\n", - " This program is provided AS IS and comes with\n", - " NO WARRANTY. See the file LICENSE for details.\n", - "\n", - " Problems or suggestions?\n", - " Visit https://www.nest-simulator.org\n", - "\n", - " Type 'nest.help()' to find out more about NEST.\n", - "\n", - "[13,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", - "[14,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[19,stdp_windowed_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n", - "[26,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", - "[27,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[29,stdp_windowed_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n", - "[36,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", - "[37,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[41,stdp_windowed_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n", - "[72,iaf_psc_delta_nestml__with_stdp_windowed_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", - "[73,iaf_psc_delta_nestml__with_stdp_windowed_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[75,stdp_windowed_nestml__with_iaf_psc_delta_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n", - "[84,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[88,iaf_psc_delta_nestml__with_stdp_windowed_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[92,stdp_windowed_nestml__with_iaf_psc_delta_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n", - "[98,stdp_windowed_nestml__with_iaf_psc_delta_nestml, WARNING, [10:8;10:28]]: Variable 'd' has the same name as a physical unit!\n", - "\u001b[33mCMake Warning (dev) at CMakeLists.txt:95 (project):\n", - " cmake_minimum_required() should be called prior to this top-level project()\n", - " call. Please see the cmake-commands(7) manual for usage documentation of\n", - " both commands.\n", - "This warning is for project developers. Use -Wno-dev to suppress it.\n", - "\u001b[0m\n", - "-- The CXX compiler identification is AppleClang 15.0.0.15000309\n", - "-- Detecting CXX compiler ABI info\n", - "-- Detecting CXX compiler ABI info - done\n", - "-- Check for working CXX compiler: /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++ - skipped\n", - "-- Detecting CXX compile features\n", - "-- Detecting CXX compile features - done\n", - "\u001b[0m\u001b[0m\n", - "\u001b[0m-------------------------------------------------------\u001b[0m\n", - "\u001b[0mnestml_module Configuration Summary\u001b[0m\n", - "\u001b[0m-------------------------------------------------------\u001b[0m\n", - "\u001b[0m\u001b[0m\n", - "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", - "\u001b[0mBuild static libs : OFF\u001b[0m\n", - "\u001b[0mC++ compiler flags : \u001b[0m\n", - "\u001b[0mNEST compiler flags : -std=c++17 -Wall -Xclang -fopenmp -O2\u001b[0m\n", - "\u001b[0mNEST include dirs : -I/Users/pooja/conda/nestml_dev/include/nest -I/usr/local/include -I/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX14.4.sdk/usr/include -I/usr/local/Cellar/gsl/2.7/include -I/Users/pooja/conda/nestml_dev/include\u001b[0m\n", - "\u001b[0mNEST libraries flags : -L/Users/pooja/conda/nestml_dev/lib/nest -lnest -lsli /usr/local/lib/libltdl.dylib /Users/pooja/conda/nestml_dev/lib/libreadline.dylib /Users/pooja/conda/nestml_dev/lib/libncurses.dylib /usr/local/Cellar/gsl/2.7/lib/libgsl.dylib /usr/local/Cellar/gsl/2.7/lib/libgslcblas.dylib /usr/local/lib/libomp.dylib\u001b[0m\n", - "\u001b[0m\u001b[0m\n", - "\u001b[0m-------------------------------------------------------\u001b[0m\n", - "\u001b[0m\u001b[0m\n", - "\u001b[0mYou can now build and install 'nestml_module' using\u001b[0m\n", - "\u001b[0m make\u001b[0m\n", - "\u001b[0m make install\u001b[0m\n", - "\u001b[0m\u001b[0m\n", - "\u001b[0mThe library file libnestml_module.so will be installed to\u001b[0m\n", - "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_ygzdr009\u001b[0m\n", - "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", - "\u001b[0m (nestml_module) Install (in SLI)\u001b[0m\n", - "\u001b[0m nest.Install(nestml_module) (in PyNEST)\u001b[0m\n", - "\u001b[0m\u001b[0m\n", - "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", - " No cmake_minimum_required command is present. A line of code such as\n", - "\n", - " cmake_minimum_required(VERSION 3.28)\n", - "\n", - " should be added at the top of the file. The version specified may be lower\n", - " if you wish to support older CMake versions for this project. For more\n", - " information run \"cmake --help-policy CMP0000\".\n", - "This warning is for project developers. Use -Wno-dev to suppress it.\n", - "\u001b[0m\n", - "-- Configuring done (0.6s)\n", - "-- Generating done (0.0s)\n", - "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target\n", - "[ 25%] \u001b[32mBuilding CXX object CMakeFiles/nestml_module_module.dir/nestml_module.o\u001b[0m\n", - "[ 50%] \u001b[32mBuilding CXX object CMakeFiles/nestml_module_module.dir/iaf_psc_delta_nestml.o\u001b[0m\n", - "[ 75%] \u001b[32mBuilding CXX object CMakeFiles/nestml_module_module.dir/iaf_psc_delta_nestml__with_stdp_windowed_nestml.o\u001b[0m\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.cpp:44:\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.h:267:17: warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", - " inline double get_C_m() const\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", - " virtual double get_C_m( int comp );\n", - " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.cpp:44:\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.h:334:17: warning: 'iaf_psc_delta_nestml__with_stdp_windowed_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", - " inline double get_C_m() const\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", - " virtual double get_C_m( int comp );\n", - " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.cpp:44:\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.h:264:8: warning: 'register_stdp_connection' overrides a member function but is not marked 'override' [-Winconsistent-missing-override]\n", - " void register_stdp_connection( double t_first_read, double delay );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/node.h:482:16: note: overridden virtual function is here\n", - " virtual void register_stdp_connection( double, double );\n", - " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_module.cpp:31:\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.h:267:17: warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", - " inline double get_C_m() const\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", - " virtual double get_C_m( int comp );\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.cpp:171:16: warning: unused variable '__resolution' [-Wunused-variable]\n", - " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.cpp:289:10: warning: unused variable 'get_t' [-Wunused-variable]\n", - " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.cpp:283:16: warning: unused variable '__resolution' [-Wunused-variable]\n", - " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.cpp:186:16: warning: unused variable '__resolution' [-Wunused-variable]\n", - " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.cpp:336:10: warning: unused variable 'get_t' [-Wunused-variable]\n", - " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.cpp:330:16: warning: unused variable '__resolution' [-Wunused-variable]\n", - " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_module.cpp:33:\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.h:334:17: warning: 'iaf_psc_delta_nestml__with_stdp_windowed_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", - " inline double get_C_m() const\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", - " virtual double get_C_m( int comp );\n", - " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_module.cpp:33:\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.h:264:8: warning: 'register_stdp_connection' overrides a member function but is not marked 'override' [-Winconsistent-missing-override]\n", - " void register_stdp_connection( double t_first_read, double delay );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/node.h:482:16: note: overridden virtual function is here\n", - " virtual void register_stdp_connection( double, double );\n", - " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_module.cpp:36:\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:450:18: warning: unused variable '__resolution' [-Wunused-variable]\n", - " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:722:16: warning: unused variable '__resolution' [-Wunused-variable]\n", - " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:739:16: warning: unused variable '__resolution' [-Wunused-variable]\n", - " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:835:16: warning: unused variable '__resolution' [-Wunused-variable]\n", - " const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:452:10: warning: unused variable 'get_thread' [-Wunused-variable]\n", - " auto get_thread = [tid]()\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::send' requested here\n", - " C_[ lcid ].send( e, tid, cp );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", - " explicit Connector( const synindex syn_id )\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", - " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", - " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", - " GenericConnectorModel( const std::string name )\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", - " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", - " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:608:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", - " nest::register_connection_model< stdp_windowed_nestml__with_iaf_psc_delta_nestml >( name );\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:518:14: warning: unused variable 'get_t' [-Wunused-variable]\n", - " auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:546:14: warning: unused variable 'get_t' [-Wunused-variable]\n", - " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:582:14: warning: unused variable 'get_t' [-Wunused-variable]\n", - " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:836:8: warning: unused variable 'get_t' [-Wunused-variable]\n", - " auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:513:9: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::update_internal_state_' requested here\n", - " update_internal_state_(t_lastspike_, (start->t_ + __dendritic_delay) - t_lastspike_, cp);\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::send' requested here\n", - " C_[ lcid ].send( e, tid, cp );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", - " explicit Connector( const synindex syn_id )\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", - " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", - " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", - " GenericConnectorModel( const std::string name )\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", - " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", - " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:608:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", - " nest::register_connection_model< stdp_windowed_nestml__with_iaf_psc_delta_nestml >( name );\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:438:7: warning: expression result unused [-Wunused-value]\n", - " dynamic_cast(t);\n", - " ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:316:14: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::check_connection' requested here\n", - " connection.check_connection( src, tgt, receptor_type, get_common_properties() );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", - " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", - " GenericConnectorModel( const std::string name )\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", - " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", - " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:608:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", - " nest::register_connection_model< stdp_windowed_nestml__with_iaf_psc_delta_nestml >( name );\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:452:10: warning: unused variable 'get_thread' [-Wunused-variable]\n", - " auto get_thread = [tid]()\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::send' requested here\n", - " C_[ lcid ].send( e, tid, cp );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", - " explicit Connector( const synindex syn_id )\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", - " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", - " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", - " GenericConnectorModel( const std::string name )\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", - " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", - " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", - " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:608:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", - " nest::register_connection_model< stdp_windowed_nestml__with_iaf_psc_delta_nestml >( name );\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:518:14: warning: unused variable 'get_t' [-Wunused-variable]\n", - " auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:546:14: warning: unused variable 'get_t' [-Wunused-variable]\n", - " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:582:14: warning: unused variable 'get_t' [-Wunused-variable]\n", - " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:836:8: warning: unused variable 'get_t' [-Wunused-variable]\n", - " auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:513:9: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::update_internal_state_' requested here\n", - " update_internal_state_(t_lastspike_, (start->t_ + __dendritic_delay) - t_lastspike_, cp);\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::send' requested here\n", - " C_[ lcid ].send( e, tid, cp );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", - " explicit Connector( const synindex syn_id )\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", - " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", - " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", - " GenericConnectorModel( const std::string name )\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", - " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", - " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", - " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:608:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", - " nest::register_connection_model< stdp_windowed_nestml__with_iaf_psc_delta_nestml >( name );\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:438:7: warning: expression result unused [-Wunused-value]\n", - " dynamic_cast(t);\n", - " ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:316:14: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::check_connection' requested here\n", - " connection.check_connection( src, tgt, receptor_type, get_common_properties() );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", - " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", - " GenericConnectorModel( const std::string name )\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", - " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", - " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", - " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", - " ^\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:608:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", - " nest::register_connection_model< stdp_windowed_nestml__with_iaf_psc_delta_nestml >( name );\n", - " ^\n", - "4 warnings generated.\n", - "5 warnings generated.\n", - "19 warnings generated.\n", - "[100%] \u001b[32m\u001b[1mLinking CXX shared module nestml_module.so\u001b[0m\n", - "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", - "[100%] Built target nestml_module_module\n", - "[100%] Built target nestml_module_module\n", - "\u001b[36mInstall the project...\u001b[0m\n", - "-- Install configuration: \"\"\n", - "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_ygzdr009/nestml_module.so\n" - ] - } - ], - "source": [ - "module_name, neuron_model_name, synapse_model_name = NESTCodeGeneratorUtils.generate_code_for(\n", - " \"../../../models/neurons/iaf_psc_delta.nestml\",\n", - " nestml_windowed_stdp_model,\n", - " post_ports=[\"post_spikes\"])" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:51 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:52 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:48:53 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n" + " should be added at the top of the file. The version specified may be lower\n", + " if you wish to support older CMake versions for this project. For more\n", + " information run \"cmake --help-policy CMP0000\".\n", + "This warning is for project developers. Use -Wno-dev to suppress it.\n", + "\u001b[0m\n", + "-- Configuring done (0.8s)\n", + "-- Generating done (0.0s)\n", + "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target\n", + "[ 25%] \u001b[32mBuilding CXX object CMakeFiles/stdp_windowed_module_module.dir/stdp_windowed_module.o\u001b[0m\n", + "[ 50%] \u001b[32mBuilding CXX object CMakeFiles/stdp_windowed_module_module.dir/iaf_psc_delta_nestml.o\u001b[0m\n", + "[ 75%] \u001b[32mBuilding CXX object CMakeFiles/stdp_windowed_module_module.dir/iaf_psc_delta_nestml__with_stdp_windowed_nestml.o\u001b[0m\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.h:267:17: warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.h:334:17: warning: 'iaf_psc_delta_nestml__with_stdp_windowed_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.h:264:8: warning: 'register_stdp_connection' overrides a member function but is not marked 'override' [-Winconsistent-missing-override]\n", + " void register_stdp_connection( double t_first_read, double delay );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:482:16: note: overridden virtual function is here\n", + " virtual void register_stdp_connection( double, double );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.cpp:171:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.cpp:289:10: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.cpp:283:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.cpp:186:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.cpp:336:10: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.cpp:330:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_module.cpp:31:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.h:267:17: warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_module.cpp:33:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.h:334:17: warning: 'iaf_psc_delta_nestml__with_stdp_windowed_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_module.cpp:33:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_windowed_nestml.h:264:8: warning: 'register_stdp_connection' overrides a member function but is not marked 'override' [-Winconsistent-missing-override]\n", + " void register_stdp_connection( double t_first_read, double delay );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:482:16: note: overridden virtual function is here\n", + " virtual void register_stdp_connection( double, double );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_module.cpp:36:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:450:18: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:722:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:739:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:835:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:452:10: warning: unused variable 'get_thread' [-Wunused-variable]\n", + " auto get_thread = [tid]()\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:608:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_windowed_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:518:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:546:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:582:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:836:8: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:513:9: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::update_internal_state_' requested here\n", + " update_internal_state_(t_lastspike_, (start->t_ + __dendritic_delay) - t_lastspike_, cp);\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:608:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_windowed_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:438:7: warning: expression result unused [-Wunused-value]\n", + " dynamic_cast(t);\n", + " ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:316:14: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::check_connection' requested here\n", + " connection.check_connection( src, tgt, receptor_type, get_common_properties() );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:608:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_windowed_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:452:10: warning: unused variable 'get_thread' [-Wunused-variable]\n", + " auto get_thread = [tid]()\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", + " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:608:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_windowed_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:518:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:546:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:582:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:836:8: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:513:9: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::update_internal_state_' requested here\n", + " update_internal_state_(t_lastspike_, (start->t_ + __dendritic_delay) - t_lastspike_, cp);\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", + " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:608:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_windowed_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:438:7: warning: expression result unused [-Wunused-value]\n", + " dynamic_cast(t);\n", + " ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:316:14: note: in instantiation of member function 'nest::stdp_windowed_nestml__with_iaf_psc_delta_nestml::check_connection' requested here\n", + " connection.check_connection( src, tgt, receptor_type, get_common_properties() );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", + " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_windowed_nestml__with_iaf_psc_delta_nestml.h:608:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_windowed_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "4 warnings generated.\n", + "5 warnings generated.\n", + "19 warnings generated.\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module stdp_windowed_module.so\u001b[0m\n", + "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", + "[100%] Built target stdp_windowed_module_module\n", + "[100%] Built target stdp_windowed_module_module\n", + "\u001b[36mInstall the project...\u001b[0m\n", + "-- Install configuration: \"\"\n", + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_vbp6k7be/stdp_windowed_module.so\n" ] - }, + } + ], + "source": [ + "module_name_windowed, neuron_model_name, synapse_model_name = NESTCodeGeneratorUtils.generate_code_for(\n", + " \"../../../models/neurons/iaf_psc_delta.nestml\",\n", + " nestml_windowed_stdp_model,\n", + " module_name=\"stdp_windowed_module\",\n", + " post_ports=[\"post_spikes\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ { "data": { "image/png": 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", @@ -4937,7 +1269,7 @@ } ], "source": [ - "dt_vec, dw_vec, delay = stdp_window(neuron_model_name, synapse_model_name, module_name)\n", + "dt_vec, dw_vec, delay = stdp_window(neuron_model_name, synapse_model_name, module_name_windowed)\n", "plot_stdp_window(dt_vec, dw_vec, delay)" ] }, @@ -5031,21 +1363,6 @@ "name": "stdout", "output_type": "stream", "text": [ - "\n", - " -- N E S T --\n", - " Copyright (C) 2004 The NEST Initiative\n", - "\n", - " Version: 3.6.0-post0.dev0\n", - " Built: Mar 26 2024 10:08:21\n", - "\n", - " This program is provided AS IS and comes with\n", - " NO WARRANTY. See the file LICENSE for details.\n", - "\n", - " Problems or suggestions?\n", - " Visit https://www.nest-simulator.org\n", - "\n", - " Type 'nest.help()' to find out more about NEST.\n", - "\n", "[13,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", "[14,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", "[19,stdp_vogels_nestml, WARNING, [8:8;8:28]]: Variable 'd' has the same name as a physical unit!\n", @@ -5076,7 +1393,7 @@ "-- Detecting CXX compile features - done\n", "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", - "\u001b[0mnestml_module Configuration Summary\u001b[0m\n", + "\u001b[0mstdp_vogels_module Configuration Summary\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", @@ -5088,15 +1405,15 @@ "\u001b[0m\u001b[0m\n", "\u001b[0m-------------------------------------------------------\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mYou can now build and install 'nestml_module' using\u001b[0m\n", + "\u001b[0mYou can now build and install 'stdp_vogels_module' using\u001b[0m\n", "\u001b[0m make\u001b[0m\n", "\u001b[0m make install\u001b[0m\n", "\u001b[0m\u001b[0m\n", - "\u001b[0mThe library file libnestml_module.so will be installed to\u001b[0m\n", - "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_z3768a0z\u001b[0m\n", + "\u001b[0mThe library file libstdp_vogels_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_fz6hkibd\u001b[0m\n", "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", - "\u001b[0m (nestml_module) Install (in SLI)\u001b[0m\n", - "\u001b[0m nest.Install(nestml_module) (in PyNEST)\u001b[0m\n", + "\u001b[0m (stdp_vogels_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(stdp_vogels_module) (in PyNEST)\u001b[0m\n", "\u001b[0m\u001b[0m\n", "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", " No cmake_minimum_required command is present. A line of code such as\n", @@ -5108,12 +1425,12 @@ " information run \"cmake --help-policy CMP0000\".\n", "This warning is for project developers. Use -Wno-dev to suppress it.\n", "\u001b[0m\n", - "-- Configuring done (0.8s)\n", + "-- Configuring done (0.6s)\n", "-- Generating done (0.0s)\n", "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target\n", - "[ 25%] \u001b[32mBuilding CXX object CMakeFiles/nestml_module_module.dir/nestml_module.o\u001b[0m\n", - "[ 50%] \u001b[32mBuilding CXX object CMakeFiles/nestml_module_module.dir/iaf_psc_delta_nestml.o\u001b[0m\n", - "[ 75%] \u001b[32mBuilding CXX object CMakeFiles/nestml_module_module.dir/iaf_psc_delta_nestml__with_stdp_vogels_nestml.o\u001b[0m\n", + "[ 50%] \u001b[32mBuilding CXX object CMakeFiles/stdp_vogels_module_module.dir/iaf_psc_delta_nestml.o\u001b[0m\n", + "[ 50%] \u001b[32mBuilding CXX object CMakeFiles/stdp_vogels_module_module.dir/stdp_vogels_module.o\u001b[0m\n", + "[ 75%] \u001b[32mBuilding CXX object CMakeFiles/stdp_vogels_module_module.dir/iaf_psc_delta_nestml__with_stdp_vogels_nestml.o\u001b[0m\n", "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.cpp:44:\n", "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.h:267:17: warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", " inline double get_C_m() const\n", @@ -5135,6 +1452,13 @@ "/Users/pooja/conda/nestml_dev/include/nest/node.h:482:16: note: overridden virtual function is here\n", " virtual void register_stdp_connection( double, double );\n", " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_vogels_module.cpp:31:\n", + "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.h:267:17: warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.cpp:171:16: warning: unused variable '__resolution' [-Wunused-variable]\n", " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " ^\n", @@ -5153,28 +1477,21 @@ "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_vogels_nestml.cpp:312:16: warning: unused variable '__resolution' [-Wunused-variable]\n", " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_module.cpp:31:\n", - "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml.h:267:17: warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", - " inline double get_C_m() const\n", - " ^\n", - "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", - " virtual double get_C_m( int comp );\n", - " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_module.cpp:33:\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_vogels_module.cpp:33:\n", "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_vogels_nestml.h:319:17: warning: 'iaf_psc_delta_nestml__with_stdp_vogels_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", " inline double get_C_m() const\n", " ^\n", "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", " virtual double get_C_m( int comp );\n", " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_module.cpp:33:\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_vogels_module.cpp:33:\n", "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/iaf_psc_delta_nestml__with_stdp_vogels_nestml.h:259:8: warning: 'register_stdp_connection' overrides a member function but is not marked 'override' [-Winconsistent-missing-override]\n", " void register_stdp_connection( double t_first_read, double delay );\n", " ^\n", "/Users/pooja/conda/nestml_dev/include/nest/node.h:482:16: note: overridden virtual function is here\n", " virtual void register_stdp_connection( double, double );\n", " ^\n", - "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/nestml_module.cpp:36:\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_vogels_module.cpp:36:\n", "/Users/pooja/nestml/master/doc/tutorials/stdp_windows/target/stdp_vogels_nestml__with_iaf_psc_delta_nestml.h:428:18: warning: unused variable '__resolution' [-Wunused-variable]\n", " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", " ^\n", @@ -5373,20 +1690,21 @@ "4 warnings generated.\n", "5 warnings generated.\n", "19 warnings generated.\n", - "[100%] \u001b[32m\u001b[1mLinking CXX shared module nestml_module.so\u001b[0m\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module stdp_vogels_module.so\u001b[0m\n", "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", - "[100%] Built target nestml_module_module\n", - "[100%] Built target nestml_module_module\n", + "[100%] Built target stdp_vogels_module_module\n", + "[100%] Built target stdp_vogels_module_module\n", "\u001b[36mInstall the project...\u001b[0m\n", "-- Install configuration: \"\"\n", - "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_z3768a0z/nestml_module.so\n" + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_fz6hkibd/stdp_vogels_module.so\n" ] } ], "source": [ - "module_name, neuron_model_name, synapse_model_name = NESTCodeGeneratorUtils.generate_code_for(\n", + "module_name_vogels, neuron_model_name, synapse_model_name = NESTCodeGeneratorUtils.generate_code_for(\n", " \"../../../models/neurons/iaf_psc_delta.nestml\",\n", " nestml_stdp_vogels_model,\n", + " module_name=\"stdp_vogels_module\",\n", " post_ports=[\"post_spikes\"])" ] }, @@ -5396,55 +1714,24 @@ "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Mar 26 10:49:14 iaf_psc_delta_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n", - "\n", - "Mar 26 10:49:14 iaf_psc_delta_nestml__with_stdp_windowed_nestml [Warning]: \n", - " Simulation resolution has changed. Internal state and parameters of the \n", - " model have been reset!\n" - ] - }, - { - "ename": "NESTErrors.UnknownModelName", - "evalue": "UnknownModelName in SLI function CopyModel_l_l_D: /stdp_vogels_nestml__with_iaf_psc_delta_nestml is not a known model name.", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNESTErrors.UnknownModelName\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m dt_vec, dw_vec, delay \u001b[38;5;241m=\u001b[39m \u001b[43mstdp_window\u001b[49m\u001b[43m(\u001b[49m\u001b[43mneuron_model_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2\u001b[0m \u001b[43m \u001b[49m\u001b[43msynapse_model_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3\u001b[0m \u001b[43m \u001b[49m\u001b[43mmodule_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4\u001b[0m \u001b[43m \u001b[49m\u001b[43msynapse_parameters\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43moffset\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m.6\u001b[39;49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 5\u001b[0m plot_stdp_window(dt_vec, dw_vec, delay)\n", - "Cell \u001b[0;32mIn[5], line 9\u001b[0m, in \u001b[0;36mstdp_window\u001b[0;34m(neuron_model_name, synapse_model_name, module_name, synapse_parameters)\u001b[0m\n\u001b[1;32m 7\u001b[0m dw_vec \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m 8\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m post_spike_time \u001b[38;5;129;01min\u001b[39;00m np\u001b[38;5;241m.\u001b[39marange(\u001b[38;5;241m25\u001b[39m, \u001b[38;5;241m175\u001b[39m)\u001b[38;5;241m.\u001b[39mastype(\u001b[38;5;28mfloat\u001b[39m):\n\u001b[0;32m----> 9\u001b[0m dt, dw \u001b[38;5;241m=\u001b[39m \u001b[43mrun_network\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpre_spike_time\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpost_spike_time\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 10\u001b[0m \u001b[43m \u001b[49m\u001b[43mneuron_model_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 11\u001b[0m \u001b[43m \u001b[49m\u001b[43msynapse_model_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 12\u001b[0m \u001b[43m \u001b[49m\u001b[43mmodule_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 13\u001b[0m \u001b[43m \u001b[49m\u001b[43mresolution\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1.\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# [ms]\u001b[39;49;00m\n\u001b[1;32m 14\u001b[0m \u001b[43m \u001b[49m\u001b[43mdelay\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdelay\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# [ms]\u001b[39;49;00m\n\u001b[1;32m 15\u001b[0m \u001b[43m \u001b[49m\u001b[43msynapse_parameters\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msynapse_parameters\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 16\u001b[0m \u001b[43m \u001b[49m\u001b[43msim_time\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msim_time\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 17\u001b[0m dt_vec\u001b[38;5;241m.\u001b[39mappend(dt)\n\u001b[1;32m 18\u001b[0m dw_vec\u001b[38;5;241m.\u001b[39mappend(dw)\n", - "Cell \u001b[0;32mIn[4], line 23\u001b[0m, in \u001b[0;36mrun_network\u001b[0;34m(pre_spike_time, post_spike_time, neuron_model_name, synapse_model_name, module_name, resolution, delay, lmbda, sim_time, synapse_parameters, fname_snip)\u001b[0m\n\u001b[1;32m 20\u001b[0m nest\u001b[38;5;241m.\u001b[39mSetKernelStatus({\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mresolution\u001b[39m\u001b[38;5;124m'\u001b[39m: resolution})\n\u001b[1;32m 22\u001b[0m wr \u001b[38;5;241m=\u001b[39m nest\u001b[38;5;241m.\u001b[39mCreate(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mweight_recorder\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m---> 23\u001b[0m \u001b[43mnest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mCopyModel\u001b[49m\u001b[43m(\u001b[49m\u001b[43msynapse_model_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstdp_nestml_rec\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 24\u001b[0m \u001b[43m \u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mweight_recorder\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mwr\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 25\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mw\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1.\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 26\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43md\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mdelay\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 27\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mreceptor_type\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 28\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmu_minus\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0.\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 29\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmu_plus\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0.\u001b[39;49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 31\u001b[0m \u001b[38;5;66;03m# create spike_generators with these times\u001b[39;00m\n\u001b[1;32m 32\u001b[0m pre_sg \u001b[38;5;241m=\u001b[39m nest\u001b[38;5;241m.\u001b[39mCreate(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mspike_generator\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 33\u001b[0m params\u001b[38;5;241m=\u001b[39m{\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mspike_times\u001b[39m\u001b[38;5;124m\"\u001b[39m: [pre_spike_time, sim_time \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m10.\u001b[39m]})\n", - "File \u001b[0;32m~/conda/nestml_dev/lib/python3.11/site-packages/nest/ll_api.py:216\u001b[0m, in \u001b[0;36mstack_checker..stack_checker_func\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 213\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(f)\n\u001b[1;32m 214\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mstack_checker_func\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 215\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m get_debug():\n\u001b[0;32m--> 216\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mf\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 217\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 218\u001b[0m sr(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcount\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "File \u001b[0;32m~/conda/nestml_dev/lib/python3.11/site-packages/nest/lib/hl_api_models.py:211\u001b[0m, in \u001b[0;36mCopyModel\u001b[0;34m(existing, new, params)\u001b[0m\n\u001b[1;32m 209\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m params \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 210\u001b[0m sps(params)\n\u001b[0;32m--> 211\u001b[0m \u001b[43msr\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m/\u001b[39;49m\u001b[38;5;132;43;01m%s\u001b[39;49;00m\u001b[38;5;124;43m /\u001b[39;49m\u001b[38;5;132;43;01m%s\u001b[39;49;00m\u001b[38;5;124;43m 3 2 roll CopyModel\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m%\u001b[39;49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mexisting\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnew\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 212\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 213\u001b[0m sr(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m/\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m /\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m CopyModel\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m%\u001b[39m (existing, new))\n", - "File \u001b[0;32m~/conda/nestml_dev/lib/python3.11/site-packages/nest/ll_api.py:103\u001b[0m, in \u001b[0;36mcatching_sli_run\u001b[0;34m(cmd)\u001b[0m\n\u001b[1;32m 100\u001b[0m engine\u001b[38;5;241m.\u001b[39mrun(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mclear\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 102\u001b[0m exceptionCls \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(kernel\u001b[38;5;241m.\u001b[39mNESTErrors, errorname)\n\u001b[0;32m--> 103\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m exceptionCls(commandname, message)\n", - "\u001b[0;31mNESTErrors.UnknownModelName\u001b[0m: UnknownModelName in SLI function CopyModel_l_l_D: /stdp_vogels_nestml__with_iaf_psc_delta_nestml is not a known model name." - ] + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ "dt_vec, dw_vec, delay = stdp_window(neuron_model_name,\n", " synapse_model_name,\n", - " module_name,\n", + " module_name_vogels,\n", " synapse_parameters={\"offset\": .6})\n", "plot_stdp_window(dt_vec, dw_vec, delay)" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "nest.ResetKernel()\n", - "nest.Install(module_name)\n", - "nest.synapse_models" - ] - }, { "attachments": { "image.png": { diff --git a/doc/tutorials/triplet_stdp_synapse/triplet_stdp_synapse.ipynb b/doc/tutorials/triplet_stdp_synapse/triplet_stdp_synapse.ipynb index a6e1bad16..349b6d26e 100644 --- a/doc/tutorials/triplet_stdp_synapse/triplet_stdp_synapse.ipynb +++ b/doc/tutorials/triplet_stdp_synapse/triplet_stdp_synapse.ipynb @@ -32,7 +32,10 @@ "\n", "from pynestml.codegeneration.nest_code_generator_utils import NESTCodeGeneratorUtils\n", "\n", - "np.set_printoptions(suppress=True)" + "np.set_printoptions(suppress=True)\n", + "\n", + "# Set the verbosity in NEST to ERROR\n", + "nest.set_verbosity(\"M_ERROR\")" ] }, { @@ -215,29 +218,360 @@ "cell_type": "code", "execution_count": 3, "id": "colonial-serve", - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:root:PyGSL is not available. The stiffness test will be skipped.\n", + "WARNING:root:Error when importing: No module named 'pygsl'\n" + ] + }, { "name": "stdout", "output_type": "stream", "text": [ - "[7,iaf_psc_deltaf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", - "[8,iaf_psc_deltaf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[14,stdp_tripletf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", - "[17,stdp_tripletf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [47:16;47:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", - "[20,stdp_tripletf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [56:16;56:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", - "[27,iaf_psc_deltaf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", - "[28,iaf_psc_deltaf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[31,stdp_tripletf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", - "[61,iaf_psc_deltaf626ae1d8042411a8b394014f08dca4a_nestml__with_stdp_tripletf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", - "[62,iaf_psc_deltaf626ae1d8042411a8b394014f08dca4a_nestml__with_stdp_tripletf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[67,stdp_tripletf626ae1d8042411a8b394014f08dca4a_nestml__with_iaf_psc_deltaf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", - "[68,stdp_tripletf626ae1d8042411a8b394014f08dca4a_nestml__with_iaf_psc_deltaf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [47:16;47:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", - "[71,stdp_tripletf626ae1d8042411a8b394014f08dca4a_nestml__with_iaf_psc_deltaf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [56:16;56:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", - "[76,iaf_psc_deltaf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[80,iaf_psc_deltaf626ae1d8042411a8b394014f08dca4a_nestml__with_stdp_tripletf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[85,stdp_tripletf626ae1d8042411a8b394014f08dca4a_nestml__with_iaf_psc_deltaf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", - "[90,stdp_tripletf626ae1d8042411a8b394014f08dca4a_nestml__with_iaf_psc_deltaf626ae1d8042411a8b394014f08dca4a_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n" + "[13,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[14,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[20,stdp_triplet_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[23,stdp_triplet_nestml, WARNING, [47:16;47:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", + "[26,stdp_triplet_nestml, WARNING, [56:16;56:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", + "[28,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[29,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[32,stdp_triplet_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[38,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[39,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[44,stdp_triplet_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[47,stdp_triplet_nestml, WARNING, [47:16;47:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", + "[50,stdp_triplet_nestml, WARNING, [56:16;56:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", + "[74,iaf_psc_delta_nestml__with_stdp_triplet_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[75,iaf_psc_delta_nestml__with_stdp_triplet_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[78,stdp_triplet_nestml__with_iaf_psc_delta_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[85,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[89,iaf_psc_delta_nestml__with_stdp_triplet_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[94,stdp_triplet_nestml__with_iaf_psc_delta_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[99,stdp_triplet_nestml__with_iaf_psc_delta_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "\u001b[33mCMake Warning (dev) at CMakeLists.txt:95 (project):\n", + " cmake_minimum_required() should be called prior to this top-level project()\n", + " call. Please see the cmake-commands(7) manual for usage documentation of\n", + " both commands.\n", + "This warning is for project developers. Use -Wno-dev to suppress it.\n", + "\u001b[0m\n", + "-- The CXX compiler identification is AppleClang 15.0.0.15000309\n", + "-- Detecting CXX compiler ABI info\n", + "-- Detecting CXX compiler ABI info - done\n", + "-- Check for working CXX compiler: /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++ - skipped\n", + "-- Detecting CXX compile features\n", + "-- Detecting CXX compile features - done\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0mtriplet_syn_module Configuration Summary\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", + "\u001b[0mBuild static libs : OFF\u001b[0m\n", + "\u001b[0mC++ compiler flags : \u001b[0m\n", + "\u001b[0mNEST compiler flags : -std=c++17 -Wall -Xclang -fopenmp -O2\u001b[0m\n", + "\u001b[0mNEST include dirs : -I/Users/pooja/conda/nestml_dev/include/nest -I/usr/local/include -I/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX14.4.sdk/usr/include -I/usr/local/Cellar/gsl/2.7/include -I/Users/pooja/conda/nestml_dev/include\u001b[0m\n", + "\u001b[0mNEST libraries flags : -L/Users/pooja/conda/nestml_dev/lib/nest -lnest -lsli /usr/local/lib/libltdl.dylib /Users/pooja/conda/nestml_dev/lib/libreadline.dylib /Users/pooja/conda/nestml_dev/lib/libncurses.dylib /usr/local/Cellar/gsl/2.7/lib/libgsl.dylib /usr/local/Cellar/gsl/2.7/lib/libgslcblas.dylib /usr/local/lib/libomp.dylib\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mYou can now build and install 'triplet_syn_module' using\u001b[0m\n", + "\u001b[0m make\u001b[0m\n", + "\u001b[0m make install\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mThe library file libtriplet_syn_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_8w1ykd82\u001b[0m\n", + "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", + "\u001b[0m (triplet_syn_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(triplet_syn_module) (in PyNEST)\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", + " No cmake_minimum_required command is present. A line of code such as\n", + "\n", + " cmake_minimum_required(VERSION 3.28)\n", + "\n", + " should be added at the top of the file. The version specified may be lower\n", + " if you wish to support older CMake versions for this project. For more\n", + " information run \"cmake --help-policy CMP0000\".\n", + "This warning is for project developers. Use -Wno-dev to suppress it.\n", + "\u001b[0m\n", + "-- Configuring done (0.9s)\n", + "-- Generating done (0.0s)\n", + "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn\n", + "[ 25%] \u001b[32mBuilding CXX object CMakeFiles/triplet_syn_module_module.dir/triplet_syn_module.o\u001b[0m\n", + "[ 50%] \u001b[32mBuilding CXX object CMakeFiles/triplet_syn_module_module.dir/iaf_psc_delta_nestml.o\u001b[0m\n", + "[ 75%] \u001b[32mBuilding CXX object CMakeFiles/triplet_syn_module_module.dir/iaf_psc_delta_nestml__with_stdp_triplet_nestml.o\u001b[0m\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/triplet_syn_module.cpp:31:\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/iaf_psc_delta_nestml.h:267:17: warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/iaf_psc_delta_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/iaf_psc_delta_nestml.h:267:17: warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/iaf_psc_delta_nestml__with_stdp_triplet_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/iaf_psc_delta_nestml__with_stdp_triplet_nestml.h:336:17: warning: 'iaf_psc_delta_nestml__with_stdp_triplet_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/iaf_psc_delta_nestml__with_stdp_triplet_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/iaf_psc_delta_nestml__with_stdp_triplet_nestml.h:266:8: warning: 'register_stdp_connection' overrides a member function but is not marked 'override' [-Winconsistent-missing-override]\n", + " void register_stdp_connection( double t_first_read, double delay );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:482:16: note: overridden virtual function is here\n", + " virtual void register_stdp_connection( double, double );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/iaf_psc_delta_nestml.cpp:171:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/iaf_psc_delta_nestml.cpp:289:10: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/iaf_psc_delta_nestml.cpp:283:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/triplet_syn_module.cpp:33:\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/iaf_psc_delta_nestml__with_stdp_triplet_nestml.h:336:17: warning: 'iaf_psc_delta_nestml__with_stdp_triplet_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/triplet_syn_module.cpp:33:\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/iaf_psc_delta_nestml__with_stdp_triplet_nestml.h:266:8: warning: 'register_stdp_connection' overrides a member function but is not marked 'override' [-Winconsistent-missing-override]\n", + " void register_stdp_connection( double t_first_read, double delay );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:482:16: note: overridden virtual function is here\n", + " virtual void register_stdp_connection( double, double );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/iaf_psc_delta_nestml__with_stdp_triplet_nestml.cpp:186:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/iaf_psc_delta_nestml__with_stdp_triplet_nestml.cpp:336:10: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/iaf_psc_delta_nestml__with_stdp_triplet_nestml.cpp:330:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/triplet_syn_module.cpp:36:\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:451:18: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:714:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:731:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:827:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:453:10: warning: unused variable 'get_thread' [-Wunused-variable]\n", + " auto get_thread = [tid]()\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_triplet_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:600:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_triplet_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:519:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:544:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:577:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:828:8: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:514:9: note: in instantiation of member function 'nest::stdp_triplet_nestml__with_iaf_psc_delta_nestml::update_internal_state_' requested here\n", + " update_internal_state_(t_lastspike_, (start->t_ + __dendritic_delay) - t_lastspike_, cp);\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_triplet_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:600:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_triplet_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:439:7: warning: expression result unused [-Wunused-value]\n", + " dynamic_cast(t);\n", + " ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:316:14: note: in instantiation of member function 'nest::stdp_triplet_nestml__with_iaf_psc_delta_nestml::check_connection' requested here\n", + " connection.check_connection( src, tgt, receptor_type, get_common_properties() );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:600:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_triplet_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:453:10: warning: unused variable 'get_thread' [-Wunused-variable]\n", + " auto get_thread = [tid]()\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_triplet_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", + " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:600:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_triplet_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:519:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:544:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:577:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:828:8: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:514:9: note: in instantiation of member function 'nest::stdp_triplet_nestml__with_iaf_psc_delta_nestml::update_internal_state_' requested here\n", + " update_internal_state_(t_lastspike_, (start->t_ + __dendritic_delay) - t_lastspike_, cp);\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_triplet_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", + " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:600:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_triplet_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:439:7: warning: expression result unused [-Wunused-value]\n", + " dynamic_cast(t);\n", + " ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:316:14: note: in instantiation of member function 'nest::stdp_triplet_nestml__with_iaf_psc_delta_nestml::check_connection' requested here\n", + " connection.check_connection( src, tgt, receptor_type, get_common_properties() );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", + " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn/stdp_triplet_nestml__with_iaf_psc_delta_nestml.h:600:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_triplet_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "4 warnings generated.\n", + "5 warnings generated.\n", + "19 warnings generated.\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module triplet_syn_module.so\u001b[0m\n", + "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", + "[100%] Built target triplet_syn_module_module\n", + "[100%] Built target triplet_syn_module_module\n", + "\u001b[36mInstall the project...\u001b[0m\n", + "-- Install configuration: \"\"\n", + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_8w1ykd82/triplet_syn_module.so\n" ] } ], @@ -245,8 +579,9 @@ "# Generate code for All-to-All spike interaction\n", "module_name, neuron_model_name, synapse_model_name = NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_delta.nestml\",\n", " nestml_triplet_stdp_model,\n", - " post_ports=[\"post_spikes\"])\n", - "nest.Install(module_name)" + " module_name=\"triplet_syn_module\",\n", + " target_path=\"target_triplet_syn\",\n", + " post_ports=[\"post_spikes\"])" ] }, { @@ -342,36 +677,361 @@ "cell_type": "code", "execution_count": 5, "id": "civic-xerox", - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[7,iaf_psc_delta07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", - "[8,iaf_psc_delta07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[14,stdp_triplet_nn07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", - "[17,stdp_triplet_nn07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [48:16;48:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", - "[20,stdp_triplet_nn07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [58:16;58:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", - "[27,iaf_psc_delta07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", - "[28,iaf_psc_delta07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[31,stdp_triplet_nn07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", - "[61,iaf_psc_delta07edd451bf704570a7deb433b776f7ab_nestml__with_stdp_triplet_nn07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", - "[62,iaf_psc_delta07edd451bf704570a7deb433b776f7ab_nestml__with_stdp_triplet_nn07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[67,stdp_triplet_nn07edd451bf704570a7deb433b776f7ab_nestml__with_iaf_psc_delta07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", - "[68,stdp_triplet_nn07edd451bf704570a7deb433b776f7ab_nestml__with_iaf_psc_delta07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [48:16;48:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", - "[71,stdp_triplet_nn07edd451bf704570a7deb433b776f7ab_nestml__with_iaf_psc_delta07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [58:16;58:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", - "[76,iaf_psc_delta07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[80,iaf_psc_delta07edd451bf704570a7deb433b776f7ab_nestml__with_stdp_triplet_nn07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", - "[85,stdp_triplet_nn07edd451bf704570a7deb433b776f7ab_nestml__with_iaf_psc_delta07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", - "[90,stdp_triplet_nn07edd451bf704570a7deb433b776f7ab_nestml__with_iaf_psc_delta07edd451bf704570a7deb433b776f7ab_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n" + "[13,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[14,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[20,stdp_triplet_nn_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[23,stdp_triplet_nn_nestml, WARNING, [48:16;48:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", + "[26,stdp_triplet_nn_nestml, WARNING, [58:16;58:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", + "[28,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[29,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[32,stdp_triplet_nn_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[38,iaf_psc_delta_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[39,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[44,stdp_triplet_nn_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[47,stdp_triplet_nn_nestml, WARNING, [48:16;48:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", + "[50,stdp_triplet_nn_nestml, WARNING, [58:16;58:16]]: Implicit casting from (compatible) type 'nS' to 'real'.\n", + "[74,iaf_psc_delta_nestml__with_stdp_triplet_nn_nestml, WARNING, [59:8;60:8]]: Variable 'G' has the same name as a physical unit!\n", + "[75,iaf_psc_delta_nestml__with_stdp_triplet_nn_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[78,stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[85,iaf_psc_delta_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[89,iaf_psc_delta_nestml__with_stdp_triplet_nn_nestml, WARNING, [77:8;77:26]]: Variable 'h' has the same name as a physical unit!\n", + "[94,stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "[99,stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml, WARNING, [13:8;13:28]]: Variable 'd' has the same name as a physical unit!\n", + "\u001b[33mCMake Warning (dev) at CMakeLists.txt:95 (project):\n", + " cmake_minimum_required() should be called prior to this top-level project()\n", + " call. Please see the cmake-commands(7) manual for usage documentation of\n", + " both commands.\n", + "This warning is for project developers. Use -Wno-dev to suppress it.\n", + "\u001b[0m\n", + "-- The CXX compiler identification is AppleClang 15.0.0.15000309\n", + "-- Detecting CXX compiler ABI info\n", + "-- Detecting CXX compiler ABI info - done\n", + "-- Check for working CXX compiler: /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++ - skipped\n", + "-- Detecting CXX compile features\n", + "-- Detecting CXX compile features - done\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0mtriplet_syn_nn_module Configuration Summary\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mC++ compiler : /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/c++\u001b[0m\n", + "\u001b[0mBuild static libs : OFF\u001b[0m\n", + "\u001b[0mC++ compiler flags : \u001b[0m\n", + "\u001b[0mNEST compiler flags : -std=c++17 -Wall -Xclang -fopenmp -O2\u001b[0m\n", + "\u001b[0mNEST include dirs : -I/Users/pooja/conda/nestml_dev/include/nest -I/usr/local/include -I/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX14.4.sdk/usr/include -I/usr/local/Cellar/gsl/2.7/include -I/Users/pooja/conda/nestml_dev/include\u001b[0m\n", + "\u001b[0mNEST libraries flags : -L/Users/pooja/conda/nestml_dev/lib/nest -lnest -lsli /usr/local/lib/libltdl.dylib /Users/pooja/conda/nestml_dev/lib/libreadline.dylib /Users/pooja/conda/nestml_dev/lib/libncurses.dylib /usr/local/Cellar/gsl/2.7/lib/libgsl.dylib /usr/local/Cellar/gsl/2.7/lib/libgslcblas.dylib /usr/local/lib/libomp.dylib\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0m-------------------------------------------------------\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mYou can now build and install 'triplet_syn_nn_module' using\u001b[0m\n", + "\u001b[0m make\u001b[0m\n", + "\u001b[0m make install\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[0mThe library file libtriplet_syn_nn_module.so will be installed to\u001b[0m\n", + "\u001b[0m /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_8z3ju6xq\u001b[0m\n", + "\u001b[0mThe module can be loaded into NEST using\u001b[0m\n", + "\u001b[0m (triplet_syn_nn_module) Install (in SLI)\u001b[0m\n", + "\u001b[0m nest.Install(triplet_syn_nn_module) (in PyNEST)\u001b[0m\n", + "\u001b[0m\u001b[0m\n", + "\u001b[33mCMake Warning (dev) in CMakeLists.txt:\n", + " No cmake_minimum_required command is present. A line of code such as\n", + "\n", + " cmake_minimum_required(VERSION 3.28)\n", + "\n", + " should be added at the top of the file. The version specified may be lower\n", + " if you wish to support older CMake versions for this project. For more\n", + " information run \"cmake --help-policy CMP0000\".\n", + "This warning is for project developers. Use -Wno-dev to suppress it.\n", + "\u001b[0m\n", + "-- Configuring done (0.7s)\n", + "-- Generating done (0.0s)\n", + "-- Build files have been written to: /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn\n", + "[ 25%] \u001b[32mBuilding CXX object CMakeFiles/triplet_syn_nn_module_module.dir/triplet_syn_nn_module.o\u001b[0m\n", + "[ 50%] \u001b[32mBuilding CXX object CMakeFiles/triplet_syn_nn_module_module.dir/iaf_psc_delta_nestml.o\u001b[0m\n", + "[ 75%] \u001b[32mBuilding CXX object CMakeFiles/triplet_syn_nn_module_module.dir/iaf_psc_delta_nestml__with_stdp_triplet_nn_nestml.o\u001b[0m\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/iaf_psc_delta_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/iaf_psc_delta_nestml.h:267:17: warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/iaf_psc_delta_nestml__with_stdp_triplet_nn_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/iaf_psc_delta_nestml__with_stdp_triplet_nn_nestml.h:336:17: warning: 'iaf_psc_delta_nestml__with_stdp_triplet_nn_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/iaf_psc_delta_nestml__with_stdp_triplet_nn_nestml.cpp:44:\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/iaf_psc_delta_nestml__with_stdp_triplet_nn_nestml.h:266:8: warning: 'register_stdp_connection' overrides a member function but is not marked 'override' [-Winconsistent-missing-override]\n", + " void register_stdp_connection( double t_first_read, double delay );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:482:16: note: overridden virtual function is here\n", + " virtual void register_stdp_connection( double, double );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/iaf_psc_delta_nestml.cpp:171:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/iaf_psc_delta_nestml.cpp:289:10: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/iaf_psc_delta_nestml.cpp:283:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/iaf_psc_delta_nestml__with_stdp_triplet_nn_nestml.cpp:186:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/iaf_psc_delta_nestml__with_stdp_triplet_nn_nestml.cpp:336:10: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [origin, lag](){ return nest::Time( nest::Time::step( origin.get_steps() + lag + 1) ).get_ms(); };\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/iaf_psc_delta_nestml__with_stdp_triplet_nn_nestml.cpp:330:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/triplet_syn_nn_module.cpp:31:\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/iaf_psc_delta_nestml.h:267:17: warning: 'iaf_psc_delta_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/triplet_syn_nn_module.cpp:33:\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/iaf_psc_delta_nestml__with_stdp_triplet_nn_nestml.h:336:17: warning: 'iaf_psc_delta_nestml__with_stdp_triplet_nn_nestml::get_C_m' hides overloaded virtual function [-Woverloaded-virtual]\n", + " inline double get_C_m() const\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:797:18: note: hidden overloaded virtual function 'nest::Node::get_C_m' declared here: different number of parameters (1 vs 0)\n", + " virtual double get_C_m( int comp );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/triplet_syn_nn_module.cpp:33:\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/iaf_psc_delta_nestml__with_stdp_triplet_nn_nestml.h:266:8: warning: 'register_stdp_connection' overrides a member function but is not marked 'override' [-Winconsistent-missing-override]\n", + " void register_stdp_connection( double t_first_read, double delay );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/node.h:482:16: note: overridden virtual function is here\n", + " virtual void register_stdp_connection( double, double );\n", + " ^\n", + "In file included from /Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/triplet_syn_nn_module.cpp:36:\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:451:18: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:714:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:731:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = nest::Time::get_resolution().get_ms(); // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:827:16: warning: unused variable '__resolution' [-Wunused-variable]\n", + " const double __resolution = timestep; // do not remove, this is necessary for the resolution() function\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:453:10: warning: unused variable 'get_thread' [-Wunused-variable]\n", + " auto get_thread = [tid]()\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:600:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:519:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:544:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:577:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:828:8: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:514:9: note: in instantiation of member function 'nest::stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml::update_internal_state_' requested here\n", + " update_internal_state_(t_lastspike_, (start->t_ + __dendritic_delay) - t_lastspike_, cp);\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:600:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:439:7: warning: expression result unused [-Wunused-value]\n", + " dynamic_cast(t);\n", + " ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:316:14: note: in instantiation of member function 'nest::stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml::check_connection' requested here\n", + " connection.check_connection( src, tgt, receptor_type, get_common_properties() );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:62:9: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " new GenericConnectorModel< ConnectionT< TargetIdentifierPtrRport > >( \"dummy\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:600:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:453:10: warning: unused variable 'get_thread' [-Wunused-variable]\n", + " auto get_thread = [tid]()\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", + " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:600:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:519:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [_tr_t](){ return _tr_t; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:544:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:577:14: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [__t_spike](){ return __t_spike; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model \n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:828:8: warning: unused variable 'get_t' [-Wunused-variable]\n", + " auto get_t = [t_start](){ return t_start; }; // do not remove, this is in case the predefined time variable ``t`` is used in the NESTML model\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:514:9: note: in instantiation of member function 'nest::stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml::update_internal_state_' requested here\n", + " update_internal_state_(t_lastspike_, (start->t_ + __dendritic_delay) - t_lastspike_, cp);\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:391:18: note: in instantiation of member function 'nest::stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml::send' requested here\n", + " C_[ lcid ].send( e, tid, cp );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_base.h:227:12: note: in instantiation of member function 'nest::Connector>::send_to_all' requested here\n", + " explicit Connector( const synindex syn_id )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:311:45: note: in instantiation of member function 'nest::Connector>::Connector' requested here\n", + " thread_local_connectors[ syn_id ] = new Connector< ConnectionT >( syn_id );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", + " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:600:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:439:7: warning: expression result unused [-Wunused-value]\n", + " dynamic_cast(t);\n", + " ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:316:14: note: in instantiation of member function 'nest::stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml::check_connection' requested here\n", + " connection.check_connection( src, tgt, receptor_type, get_common_properties() );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model_impl.h:292:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection_' requested here\n", + " add_connection_( src, tgt, thread_local_connectors, syn_id, connection, actual_receptor_type );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/connector_model.h:162:3: note: in instantiation of member function 'nest::GenericConnectorModel>::add_connection' requested here\n", + " GenericConnectorModel( const std::string name )\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:103:38: note: in instantiation of member function 'nest::GenericConnectorModel>::GenericConnectorModel' requested here\n", + " ConnectorModel* conn_model = new GenericConnectorModel< CompleteConnectionT >( name );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/model_manager_impl.h:67:5: note: in instantiation of function template specialization 'nest::ModelManager::register_specific_connection_model_>' requested here\n", + " register_specific_connection_model_< ConnectionT< TargetIdentifierIndex > >( name + \"_hpc\" );\n", + " ^\n", + "/Users/pooja/conda/nestml_dev/include/nest/nest_impl.h:37:26: note: in instantiation of function template specialization 'nest::ModelManager::register_connection_model' requested here\n", + " kernel().model_manager.register_connection_model< ConnectorModelT >( name );\n", + " ^\n", + "/Users/pooja/nestml/master/doc/tutorials/triplet_stdp_synapse/target_triplet_syn_nn/stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml.h:600:9: note: in instantiation of function template specialization 'nest::register_connection_model' requested here\n", + " nest::register_connection_model< stdp_triplet_nn_nestml__with_iaf_psc_delta_nestml >( name );\n", + " ^\n", + "4 warnings generated.\n", + "5 warnings generated.\n", + "19 warnings generated.\n", + "[100%] \u001b[32m\u001b[1mLinking CXX shared module triplet_syn_nn_module.so\u001b[0m\n", + "ld: warning: install name of a reexported library '@rpath/libtinfo.6.dylib' found at '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' is different from install name '/Users/pooja/conda/nestml_dev/lib/libtinfo.6.dylib' found in its parent library '/Users/pooja/conda/nestml_dev/lib/libncurses.6.dylib'\n", + "[100%] Built target triplet_syn_nn_module_module\n", + "[100%] Built target triplet_syn_nn_module_module\n", + "\u001b[36mInstall the project...\u001b[0m\n", + "-- Install configuration: \"\"\n", + "-- Installing: /var/folders/2j/fb047q1177v9f56f_jktrb4c0000gn/T/nestml_target_8z3ju6xq/triplet_syn_nn_module.so\n" ] } ], "source": [ "# Generate code for nearest spike interaction model\n", - "module_name, neuron_model_name_nn, synapse_model_name_nn = NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_delta.nestml\",\n", + "module_name_nn, neuron_model_name_nn, synapse_model_name_nn = NESTCodeGeneratorUtils.generate_code_for(\"../../../models/neurons/iaf_psc_delta.nestml\",\n", " nestml_triplet_stdp_nn_model,\n", + " module_name=\"triplet_syn_nn_module\",\n", + " target_path=\"target_triplet_syn_nn\",\n", " post_ports=[\"post_spikes\"])" ] }, @@ -436,13 +1096,12 @@ "metadata": {}, "outputs": [], "source": [ - "def run_triplet_stdp_network(neuron_model_name, synapse_model_name, neuron_opts,\n", + "def run_triplet_stdp_network(neuron_model_name, synapse_model_name, module_name, neuron_opts,\n", " nest_syn_opts, pre_spike_times, post_spike_times, \n", " resolution=1., delay=1., sim_time=None):\n", " \"\"\"\n", " Runs the triplet stdp synapse model\n", " \"\"\"\n", - " nest.set_verbosity(\"M_ALL\")\n", " nest.ResetKernel()\n", " \n", " # load dynamic library (NEST extension module) into NEST kernel\n", @@ -529,7 +1188,7 @@ "outputs": [], "source": [ "# Simulate the network\n", - "def run_frequency_simulation(neuron_model_name, synapse_model_name,\n", + "def run_frequency_simulation(neuron_model_name, synapse_model_name, module_name,\n", " neuron_opts, nest_syn_opts,\n", " freqs, delta_t, n_spikes):\n", " \"\"\"\n", @@ -547,7 +1206,7 @@ "\n", " sim_time = max(np.amax(pre_spike_times), np.amax(post_spike_times)) + 10. + 3 * syn_opts[\"delay\"]\n", "\n", - " dw = run_triplet_stdp_network(neuron_model_name, synapse_model_name, \n", + " dw = run_triplet_stdp_network(neuron_model_name, synapse_model_name, module_name,\n", " neuron_opts, nest_syn_opts,\n", " pre_spike_times=pre_spike_times,\n", " post_spike_times=post_spike_times,\n", @@ -579,14 +1238,6 @@ "n_spikes = 60" ] }, - { - "cell_type": "code", - "execution_count": null, - "id": "f80eae4e-0749-449c-a2b8-dcb2248d1fb0", - "metadata": {}, - "outputs": [], - "source": [] - }, { "cell_type": "code", "execution_count": 10, @@ -636,7 +1287,7 @@ "nest_syn_opts.pop('tau_minus')\n", "nest_syn_opts.pop('tau_y')\n", "\n", - "dw_dict = run_frequency_simulation(neuron_model_name, synapse_model_name, \n", + "dw_dict = run_frequency_simulation(neuron_model_name, synapse_model_name, module_name,\n", " neuron_opts, nest_syn_opts,\n", " freqs, delta_t, n_spikes)" ] @@ -698,7 +1349,7 @@ "nest_syn_opts_nn.pop('tau_minus')\n", "nest_syn_opts_nn.pop('tau_y')\n", "\n", - "dw_dict_nn = run_frequency_simulation(neuron_model_name_nn, synapse_model_name_nn,\n", + "dw_dict_nn = run_frequency_simulation(neuron_model_name_nn, synapse_model_name_nn, module_name_nn,\n", " neuron_opts_nn, nest_syn_opts_nn,\n", " freqs, delta_t, n_spikes)" ] @@ -720,7 +1371,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 12, @@ -729,14 +1380,12 @@ }, { "data": { - "image/png": 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\n", 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", 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\n", 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MDtY6ZDYABC/XxxslSdWdE6TPPrN5mvalLfLaYQXZm8q8Xq9iY2Pl8XgUExPz3W6MDyTBN3E84DKOhSYaGhpUV1dn9xj2qTsvvXhn489z35Eio6+7S0RExDUfMW/TLAtgoXI//Ya/TQCa842/DfWPntIlR6TNA7UfbZXXAf+ebgBAYAsLC1NUVJTdY9gnrF4699cPBItySpEhvBYAgIAWHh6ucHLK70L0DXgAAAAAAJhH6QYAAAAAwBBKNwAAAAAAhlC6AQAAAAAwhNINAAAAAIAhlG4AAAAAAAyhdAMAAAAAYAilGwAAAAAAQyjdAAAAAAAYQukGAAAAAMAQSjcAAAAAAIZQugEAAAAAMITSDQAAAACAIZRuAAAAAAAMoXQDAAAAAGAIpRsAAAAAAEMo3QAAAAAAGELpBgAAAADAEEo3AAAAAACGULoBAAAAADCE0g0AAAAAgCGUbgAAAAAADKF0AwAAAABgCKUbAAAAAABDKN0AAAAAABhitHS/8847uu+++5SUlCSHw6EtW7Zcd5+ioiKNHDlSTqdT/fv314YNG0yOCAAARGYDAGCK0dJdU1OjtLQ0rV27tkXbl5eX695779Xdd9+t0tJSLViwQLNnz9af//xnk2MCABDyyGwAAMzoYPLGJ06cqIkTJ7Z4+3Xr1iklJUXLly+XJA0aNEh79uzRypUrlZ2dbWpMAABCHpkNAIAZAfWe7uLiYmVlZTW5LDs7W8XFxTZNBAAAmkNmAwDQMkaf6W4tt9uthISEJpclJCTI6/XqwoUL6tix4xX71NbWqra21nfe6/UanxMAgFBHZgMA0DIB9Uz3jSgsLFRsbKzvlJycbPdIAACgGWQ2ACAUBVTpdrlcqqqqanJZVVWVYmJimn3EXJIKCgrk8Xh8p1OnTvljVAAAQhqZDQBAywTUy8szMjL05ptvNrls+/btysjIuOo+TqdTTqfT9GgAAOAbyGwAAFrG6DPd586dU2lpqUpLSyU1fr1IaWmpKioqJDU+4p2Tk+Pbft68efrLX/6in/3sZzp69Kh++ctf6ne/+51+/OMfmxwTAICQR2YDAGCG0dK9b98+jRgxQiNGjJAk5efna8SIEVqyZIkkqbKy0hfmkpSSkqL/+q//0vbt25WWlqbly5dr/fr1fPUIAACGkdkAAJhh9OXlmZmZsizrqtdv2LCh2X0OHjxocCoAAPBtZDYAAGYE1AepAQAAAAAQTCjdAAAAAAAYQukGAAAAAMAQSjcAAAAAAIZQugEAAAAAMITSDQAAAACAIZRuAAAAAAAMoXQDAAAAAGAIpRsAAAAAAEMo3QAAAAAAGELpBgAAAADAEEo3AAAAAACGULoBAAAAADCE0g0AAAAAgCGUbgAAAAAADKF0AwAAAABgCKUbAAAAAABDKN0AAAAAABhC6QYAAAAAwBBKNwAAAAAAhlC6AQAAAAAwhNINAAAAAIAhlG4AAAAAAAyhdAMAAAAAYAilGwAAAAAAQyjdAAAAAAAYQukGAAAAAMAQv5TutWvXqm/fvoqKilJ6err27t171W03bNggh8PR5BQVFeWPMQEACGnkNQAAbc946d60aZPy8/O1dOlSHThwQGlpacrOzlZ1dfVV94mJiVFlZaXvdPLkSdNjAgAQ0shrAADMMF66V6xYoTlz5mjWrFkaPHiw1q1bp+joaL300ktX3cfhcMjlcvlOCQkJpscEACCkkdcAAJhhtHTX1dVp//79ysrK+voXhoUpKytLxcXFV93v3Llz6tOnj5KTkzV58mR9+OGHV922trZWXq+3yQkAALScP/JaIrMBAKGpg8kb/+yzz1RfX3/FI98JCQk6evRos/ukpqbqpZde0rBhw+TxePTcc89p3Lhx+vDDD9WrV68rti8sLNSyZcuMzK/ITtLjHjO33Y6cr/tKg5f8WZJ05IlsRUcaPWwCF8cDLuNYkMTfBp8gOB78kdeS2czmeFRQHIttgWMB38TxIP42/JWdx0LAfXp5RkaGcnJyNHz4cN111116/fXX1b17d73wwgvNbl9QUCCPx+M7nTp1ys8TAwAQelqb1xKZDQAITUbrfXx8vMLDw1VVVdXk8qqqKrlcrhbdRkREhEaMGKFjx441e73T6ZTT6fzOswIAEKr8kdcSmQ0ACE1Gn+mOjIzUqFGjtGPHDt9lDQ0N2rFjhzIyMlp0G/X19Tp8+LASExNNjQkAQEgjrwEAMMf4C9nz8/M1Y8YMjR49WmPGjNGqVatUU1OjWbNmSZJycnLUs2dPFRYWSpKeeOIJjR07Vv3799eZM2f07LPP6uTJk5o9e7bpUQEACFnkNQAAZhgv3dOnT9enn36qJUuWyO12a/jw4dq2bZvvw1oqKioUFvb1E+5ffvml5syZI7fbra5du2rUqFF67733NHjwYNOjAgAQsshrAADM8MtHtuXl5SkvL6/Z64qKipqcX7lypVauXOmHqQAAwDeR1wAAtL2A+/RyAAAAAACCBaUbAAAAAABDKN0AAAAAABhC6QYAAAAAwBBKNwAAAAAAhlC6AQAAAAAwhNINAAAAAIAhlG4AAAAAAAyhdAMAAAAAYAilGwAAAAAAQyjdAAAAAAAYQukGAAAAAMAQSjcAAAAAAIZQugEAAAAAMITSDQAAAACAIZRuAAAAAAAMoXQDAAAAAGAIpRsAAAAAAEMo3QAAAAAAGELpBgAAAADAEEo3AAAAAACGULoBAAAAADCE0g0AAAAAgCGUbgAAAAAADKF0AwAAAABgCKUbAAAAAABD/FK6165dq759+yoqKkrp6enau3fvNbd/7bXXNHDgQEVFRWno0KF68803/TEmAAAhjbwGAKDtGS/dmzZtUn5+vpYuXaoDBw4oLS1N2dnZqq6ubnb79957Tz/84Q/14IMP6uDBg5oyZYqmTJmiDz74wPSoAACELPIaAAAzjJfuFStWaM6cOZo1a5YGDx6sdevWKTo6Wi+99FKz269evVoTJkzQT3/6Uw0aNEhPPvmkRo4cqV/84hemRwUAIGSR1wAAmGG0dNfV1Wn//v3Kysr6+heGhSkrK0vFxcXN7lNcXNxke0nKzs6+6va1tbXyer1NTgAAoOX8kdcSmQ0ACE1GS/dnn32m+vp6JSQkNLk8ISFBbre72X3cbnerti8sLFRsbKzvlJyc3DbDAwAQIvyR1xKZDQAITe3+08sLCgrk8Xh8p1OnTtk9EgAAaAaZDQAIRR1M3nh8fLzCw8NVVVXV5PKqqiq5XK5m93G5XK3a3ul0yul0ts3AAACEIH/ktURmAwBCk9FnuiMjIzVq1Cjt2LHDd1lDQ4N27NihjIyMZvfJyMhosr0kbd++/arbAwCA74a8BgDAHKPPdEtSfn6+ZsyYodGjR2vMmDFatWqVampqNGvWLElSTk6OevbsqcLCQknS/Pnzddddd2n58uW699579eqrr2rfvn168cUXTY8KAEDIIq8BADDDeOmePn26Pv30Uy1ZskRut1vDhw/Xtm3bfB++UlFRobCwr59wHzdunDZu3Kh//ud/1mOPPaYBAwZoy5YtGjJkiOlRAQAIWeQ1AABmGC/dkpSXl6e8vLxmrysqKrrismnTpmnatGmGpwIAAN9EXgMA0Pba/aeXAwAAAAAQqCjdAAAAAAAYQukGAAAAAMAQSjcAAAAAAIZQugEAAAAAMITSDQAAAACAIZRuAAAAAAAMoXQDAAAAAGAIpRsAAAAAAEMo3QAAAAAAGELpBgAAAADAEEo3AAAAAACGULoBAAAAADCE0g0AAAAAgCGUbgAAAAAADKF0AwAAAABgCKUbAAAAAABDKN0AAAAAABhC6QYAAAAAwBBKNwAAAAAAhlC6AQAAAAAwhNINAAAAAIAhlG4AAAAAAAyhdAMAAAAAYAilGwAAAAAAQyjdAAAAAAAYYrR0f/HFF3rggQcUExOjuLg4Pfjggzp37tw198nMzJTD4WhymjdvnskxAQAIaeQ1AADmdDB54w888IAqKyu1fft2Xbp0SbNmzdLcuXO1cePGa+43Z84cPfHEE77z0dHRJscEACCkkdcAAJhjrHR/9NFH2rZtm/77v/9bo0ePliStWbNGkyZN0nPPPaekpKSr7hsdHS2Xy2VqNAAA8FfkNQAAZhl7eXlxcbHi4uJ8AS5JWVlZCgsLU0lJyTX3feWVVxQfH68hQ4aooKBA58+fNzUmAAAhjbwGAMAsY890u91u9ejRo+kv69BB3bp1k9vtvup+P/rRj9SnTx8lJSXp0KFDevTRR1VWVqbXX3+92e1ra2tVW1vrO+/1etvmDgAAEAL8ldcSmQ0ACE2tLt2LFi3S008/fc1tPvrooxseaO7cub6fhw4dqsTERI0fP17Hjx/XzTfffMX2hYWFWrZs2Q3/PlxfdGQHnXjqXrvHABBg+NsQ2AItryWzmc3xiMs4FvBNHA+4zM5jodWle+HChZo5c+Y1t+nXr59cLpeqq6ubXP7VV1/piy++aNX7v9LT0yVJx44dazbECwoKlJ+f7zvv9XqVnJzc4tsHACAYBVpeS2Q2ACA0tbp0d+/eXd27d7/udhkZGTpz5oz279+vUaNGSZJ27typhoYGXzC3RGlpqSQpMTGx2eudTqecTmeLbw8AgFAQaHktkdkAgNBk7IPUBg0apAkTJmjOnDnau3ev3n33XeXl5en+++/3fRLqJ598ooEDB2rv3r2SpOPHj+vJJ5/U/v37deLECW3dulU5OTm68847NWzYMFOjAgAQsshrAADMMla6pcZPNR04cKDGjx+vSZMm6Xvf+55efPFF3/WXLl1SWVmZ79NOIyMj9fbbb+uee+7RwIEDtXDhQk2dOlV//OMfTY4JAEBII68BADDHYVmWZfcQbcnr9So2NlYej0cxMTF2jwMAQKuFSpaFyv0EAASnluaY0We6AQAAAAAIZZRuAAAAAAAMoXQDAAAAAGAIpRsAAAAAAEMo3QAAAAAAGELpBgAAAADAEEo3AAAAAACGULoBAAAAADCE0g0AAAA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"text/plain": [ - "
" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -875,7 +1522,7 @@ "outputs": [], "source": [ "# Simulation\n", - "def run_triplet_protocol_simulation(neuron_model_name, synapse_model_name,\n", + "def run_triplet_protocol_simulation(neuron_model_name, synapse_model_name, module_name,\n", " neuron_opts, nest_syn_opts,\n", " spike_delays, n_triplets = 1, triplet_delay = 1000,\n", " pre_post_pre=True):\n", @@ -890,7 +1537,7 @@ " sim_time = max(np.amax(pre_spike_times), np.amax(post_spike_times)) + 10. + 3 * syn_opts[\"delay\"]\n", "\n", " print('Simulating for (delta_t1, delta_t2) = ({}, {})'.format(_delays[0], _delays[1]))\n", - " dw = run_triplet_stdp_network(neuron_model_name, synapse_model_name,\n", + " dw = run_triplet_stdp_network(neuron_model_name, synapse_model_name, module_name,\n", " neuron_opts, nest_syn_opts,\n", " pre_spike_times=pre_spike_times,\n", " post_spike_times=post_spike_times,\n", @@ -1027,14 +1674,14 @@ "pre_post_pre_delays = [(5, -5), (10, -10), (15, -5), (5, -15)]\n", "\n", "# All-to-All interation\n", - "dw_vec = run_triplet_protocol_simulation(neuron_model_name, synapse_model_name,\n", + "dw_vec = run_triplet_protocol_simulation(neuron_model_name, synapse_model_name, module_name,\n", " neuron_opts, nest_syn_opts,\n", " pre_post_pre_delays,\n", " n_triplets=1,\n", " triplet_delay=1000)\n", "\n", "# Nearest spike interaction\n", - "dw_vec_nn = run_triplet_protocol_simulation(neuron_model_name_nn, synapse_model_name_nn,\n", + "dw_vec_nn = run_triplet_protocol_simulation(neuron_model_name_nn, synapse_model_name_nn, module_name_nn,\n", " neuron_opts_nn, nest_syn_opts_nn,\n", " pre_post_pre_delays,\n", " n_triplets=1,\n", @@ -1045,18 +1692,18 @@ "cell_type": "code", "execution_count": 19, "id": "alpine-consultancy", - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [ { "data": { - "image/png": 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\n", 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" + "
" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -1116,7 +1763,7 @@ "post_pre_post_delays = [(-5, 5), (-10, 10), (-5, 15), (-15, 5)]\n", "\n", "# All-to-All interaction\n", - "dw_vec = run_triplet_protocol_simulation(neuron_model_name, synapse_model_name,\n", + "dw_vec = run_triplet_protocol_simulation(neuron_model_name, synapse_model_name, module_name,\n", " neuron_opts, nest_syn_opts,\n", " post_pre_post_delays,\n", " n_triplets=10,\n", @@ -1124,7 +1771,7 @@ " pre_post_pre=False)\n", "\n", "# Nearest spike interaction\n", - "dw_vec_nn = run_triplet_protocol_simulation(neuron_model_name_nn, synapse_model_name_nn,\n", + "dw_vec_nn = run_triplet_protocol_simulation(neuron_model_name_nn, synapse_model_name_nn, module_name_nn,\n", " neuron_opts_nn, nest_syn_opts_nn,\n", " post_pre_post_delays,\n", " n_triplets=10,\n", @@ -1140,14 +1787,12 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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", "text/plain": [ - "
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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -1214,7 +1859,9 @@ { "cell_type": "markdown", "id": "shared-spice", - "metadata": {}, + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, "source": [ "Acknowledgements\n", "----------------\n", @@ -1232,7 +1879,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -1246,7 +1893,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.2" + "version": "3.11.8" } }, "nbformat": 4, diff --git a/pynestml/codegeneration/nest_builder.py b/pynestml/codegeneration/nest_builder.py index 5ee0bf0ae..e00841aa0 100644 --- a/pynestml/codegeneration/nest_builder.py +++ b/pynestml/codegeneration/nest_builder.py @@ -41,7 +41,6 @@ def __add_library_to_sli(lib_path): lib_path = os.path.abspath(lib_path) system = platform.system() - lib_key = "" if system == "Linux": lib_key = "LD_LIBRARY_PATH" @@ -51,8 +50,7 @@ def __add_library_to_sli(lib_path): if lib_key in os.environ: current = os.environ[lib_key].split(os.pathsep) if lib_path not in current: - current.append(lib_path) - os.environ[lib_key] += os.pathsep.join(current) + os.environ[lib_key] = os.pathsep.join([os.environ[lib_key], lib_path]) else: os.environ[lib_key] = lib_path diff --git a/pynestml/codegeneration/nest_code_generator_utils.py b/pynestml/codegeneration/nest_code_generator_utils.py index 969aaecea..66f5c0fd9 100644 --- a/pynestml/codegeneration/nest_code_generator_utils.py +++ b/pynestml/codegeneration/nest_code_generator_utils.py @@ -63,6 +63,7 @@ def generate_code_for(cls, nestml_neuron_model: str, nestml_synapse_model: Optional[str] = None, module_name: Optional[str] = None, + target_path: str = "target", post_ports: Optional[List[str]] = None, mod_ports: Optional[List[str]] = None, logging_level: str = "WARNING"): @@ -119,16 +120,14 @@ def generate_code_for(cls, mangled_neuron_name = neuron_model_name + "_nestml__with_" + synapse_model_name + "_nestml" mangled_synapse_name = synapse_model_name + "_nestml__with_" + neuron_model_name + "_nestml" - # generate the code for neuron and optionally synapse - if module_name: - module_name = "nestml_" + module_name + "_module" - else: + if not module_name: module_name = "nestml_module" generate_nest_target(input_path=input_fns, install_path=install_path, logging_level=logging_level, module_name=module_name, + target_path=target_path, suffix="_nestml", codegen_opts=codegen_opts)