From 83c5cd2d8241ac09dc4500de1b3585784aa757a4 Mon Sep 17 00:00:00 2001
From: bonochof <ryos427@yahoo.co.jp>
Date: Tue, 28 Mar 2023 14:16:21 +0900
Subject: [PATCH 1/5] add shock_transfer notebook

---
 examples/shock_transfer.ipynb | 274 ++++++++++++++++++++++++++++++++++
 1 file changed, 274 insertions(+)
 create mode 100644 examples/shock_transfer.ipynb

diff --git a/examples/shock_transfer.ipynb b/examples/shock_transfer.ipynb
new file mode 100644
index 00000000..981ec5fa
--- /dev/null
+++ b/examples/shock_transfer.ipynb
@@ -0,0 +1,274 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "KCI4qIU_pa-1"
+      },
+      "source": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "58xSRq9jpa-2"
+      },
+      "source": [
+        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](http://colab.research.google.com/github/masanorihirano/pams/blob/main/examples/shock_transfer.ipynb)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "id": "OwaI8_xbpa-5"
+      },
+      "outputs": [],
+      "source": [
+        "# Please remove comment-out if necessary\n",
+        "#! pip install pams matplotlib"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "id": "ixLeaU7Epa-5"
+      },
+      "outputs": [],
+      "source": [
+        "config = {\n",
+        "\t\"simulation\": {\n",
+        "\t\t\"markets\": [\"SpotMarket-1\", \"SpotMarket-2\", \"IndexMarket-I\"],\n",
+        "\t\t\"agents\": [\"FCNAgents-1\", \"FCNAgents-2\", \"FCNAgents-I\", \"ArbitrageAgents\"],\n",
+        "\t\t\"sessions\": [\n",
+        "\t\t\t{\t\"sessionName\": 0,\n",
+        "\t\t\t\t\"iterationSteps\": 100,\n",
+        "\t\t\t\t\"withOrderPlacement\": True,\n",
+        "\t\t\t\t\"withOrderExecution\": False,\n",
+        "\t\t\t\t\"withPrint\": True,\n",
+        "\t\t\t\t\"maxNormalOrders\": 3, \"MEMO\": \"The same number as #markets\",\n",
+        "\t\t\t\t\"maxHifreqOrders\": 0\n",
+        "\t\t\t},\n",
+        "\t\t\t{\t\"sessionName\": 1,\n",
+        "\t\t\t\t\"iterationSteps\": 500,\n",
+        "\t\t\t\t\"withOrderPlacement\": True,\n",
+        "\t\t\t\t\"withOrderExecution\": True,\n",
+        "\t\t\t\t\"withPrint\": True,\n",
+        "\t\t\t\t\"maxNormalOrders\": 3, \"MEMO\": \"The same number as #markets\",\n",
+        "\t\t\t\t\"maxHifreqOrders\": 5,\n",
+        "\t\t\t\t\"events\": [\"FundamentalPriceShock\"]\n",
+        "\t\t\t}\n",
+        "\t\t]\n",
+        "\t},\n",
+        "\n",
+        "\t\"FundamentalPriceShock\": {\n",
+        "\t\t\"class\": \"FundamentalPriceShock\",\n",
+        "\t\t\"target\": \"SpotMarket-1\",\n",
+        "\t\t\"triggerTime\": 0,\n",
+        "\t\t\"priceChangeRate\": -0.1,\n",
+        "\t\t\"enabled\": True\n",
+        "\t},\n",
+        "\t\"SpotMarket\": {\n",
+        "\t\t\"class\": \"Market\",\n",
+        "\t\t\"tickSize\": 0.00001,\n",
+        "\t\t\"marketPrice\": 300.0,\n",
+        "\t\t\"outstandingShares\": 25000\n",
+        "\t},\n",
+        "\t\"SpotMarket-1\": {\n",
+        "\t\t\"extends\": \"SpotMarket\"\n",
+        "\t},\n",
+        "\t\"SpotMarket-2\": {\n",
+        "\t\t\"extends\": \"SpotMarket\"\n",
+        "\t},\n",
+        "\t\"IndexMarket-I\": {\n",
+        "\t\t\"class\": \"IndexMarket\",\n",
+        "\t\t\"tickSize\": 0.00001,\n",
+        "\t\t\"marketPrice\": 300.0,\n",
+        "\t\t\"outstandingShares\": 25000,\n",
+        "\t\t\"markets\": [\"SpotMarket-1\", \"SpotMarket-2\"]\n",
+        "\t},\n",
+        "\t\"FCNAgent\": {\n",
+        "\t\t\"class\": \"FCNAgent\",\n",
+        "\t\t\"numAgents\": 100,\n",
+        "\t\t\"markets\": [\"Market\"],\n",
+        "\t\t\"assetVolume\": 50,\n",
+        "\t\t\"cashAmount\": 10000,\n",
+        "\n",
+        "\t\t\"fundamentalWeight\": {\"expon\": [1.0]},\n",
+        "\t\t\"chartWeight\": {\"expon\": [0.0]},\n",
+        "\t\t\"noiseWeight\": {\"expon\": [1.0]},\n",
+        "\t\t\"noiseScale\": 0.001,\n",
+        "\t\t\"timeWindowSize\": [100, 200],\n",
+        "\t\t\"orderMargin\": [0.0, 0.1]\n",
+        "\t},\n",
+        "\n",
+        "\t\"FCNAgents-1\": {\n",
+        "\t\t\"extends\": \"FCNAgent\",\n",
+        "\t\t\"markets\": [\"SpotMarket-1\"],\n",
+        "\t\t\"fundamentalWeight\": {\"expon\": [1.0]},\n",
+        "\t\t\"chartWeight\": {\"expon\": [0.0]},\n",
+        "\t\t\"noiseWeight\": {\"expon\": [1.0]}\n",
+        "\t},\n",
+        "\t\"FCNAgents-2\": {\n",
+        "\t\t\"extends\": \"FCNAgent\",\n",
+        "\t\t\"markets\": [\"SpotMarket-2\"],\n",
+        "\t\t\"fundamentalWeight\": {\"expon\": [0.0]},\n",
+        "\t\t\"chartWeight\": {\"expon\": [0.0]},\n",
+        "\t\t\"noiseWeight\": {\"expon\": [0.2]}\n",
+        "\t},\n",
+        "\t\"FCNAgents-I\": {\n",
+        "\t\t\"extends\": \"FCNAgent\",\n",
+        "\t\t\"markets\": [\"IndexMarket-I\"],\n",
+        "\t\t\"fundamentalWeight\": {\"expon\": [0.5]},\n",
+        "\t\t\"chartWeight\": {\"expon\": [0.0]},\n",
+        "\t\t\"noiseWeight\": {\"expon\": [1.0]}\n",
+        "\t},\n",
+        "\t\"ArbitrageAgents\": {\n",
+        "\t\t\"class\": \"ArbitrageAgent\",\n",
+        "\t\t\"numAgents\": 100,\n",
+        "\t\t\"markets\": [\"IndexMarket-I\", \"SpotMarket-1\", \"SpotMarket-2\"],\n",
+        "\t\t\"assetVolume\": 50,\n",
+        "\t\t\"cashAmount\": 150000,\n",
+        "\t\t\"orderVolume\": 1,\n",
+        "\t\t\"orderThresholdPrice\": 1.0\n",
+        "\t}\n",
+        "}"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "metadata": {
+        "id": "xUUUfulSpa-6"
+      },
+      "outputs": [],
+      "source": [
+        "import random\n",
+        "import numpy as np\n",
+        "import matplotlib.pyplot as plt\n",
+        "from pams.runners import SequentialRunner\n",
+        "from pams.logs.market_step_loggers import MarketStepSaver#PrintLogger"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "3QXSkEw2pa-6",
+        "outputId": "255e80ff-e174-4f96-dbd8-12b3cc8e3835"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "/usr/local/lib/python3.9/dist-packages/pams/market.py:446: UserWarning: order price does not accord to the tick size. price will be modified\n",
+            "  warnings.warn(\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "# INITIALIZATION TIME 0.007541969\n",
+            "# EXECUTION TIME 0.535983768\n"
+          ]
+        }
+      ],
+      "source": [
+        "saver = MarketStepSaver() #PrintLogger()\n",
+        "\n",
+        "runner = SequentialRunner(\n",
+        "    settings=config,\n",
+        "    prng=random.Random(42),\n",
+        "    logger=saver,\n",
+        ")\n",
+        "runner.main()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 5,
+      "metadata": {
+        "id": "P5_pyTa9pa-6"
+      },
+      "outputs": [],
+      "source": [
+        "market_prices_indexmarket_i = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"market_price\"]), filter(lambda x: x[\"market_time\"] >= 100 and x[\"market_name\"] == \"IndexMarket-I\", saver.market_step_logs))))\n",
+        "market_prices_spotmarket_1 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"market_price\"]), filter(lambda x: x[\"market_time\"] >= 100 and x[\"market_name\"] == \"SpotMarket-1\", saver.market_step_logs))))\n",
+        "market_prices_spotmarket_2 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"market_price\"]), filter(lambda x: x[\"market_time\"] >= 100 and x[\"market_name\"] == \"SpotMarket-2\", saver.market_step_logs))))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 279
+        },
+        "id": "c__AgWzapa-7",
+        "outputId": "241b483b-6eb9-4aac-a06b-805367c1a3b9"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 432x288 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {
+            "needs_background": "light"
+          }
+        }
+      ],
+      "source": [
+        "plt.plot(list(market_prices_indexmarket_i.keys()), list(market_prices_indexmarket_i.values()), label=\"IndexMarket-I\")\n",
+        "plt.plot(list(market_prices_spotmarket_1.keys()), list(market_prices_spotmarket_1.values()), label=\"SpotMarket-1\")\n",
+        "plt.plot(list(market_prices_spotmarket_2.keys()), list(market_prices_spotmarket_2.values()), label=\"SpotMarket-2\")\n",
+        "plt.xlabel(\"ticks\")\n",
+        "plt.ylabel(\"market price\")\n",
+        "plt.legend()\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "aVsDnfX7pa-7"
+      },
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "kernelspec": {
+      "display_name": "Python 3 (ipykernel)",
+      "language": "python",
+      "name": "python3"
+    },
+    "language_info": {
+      "codemirror_mode": {
+        "name": "ipython",
+        "version": 3
+      },
+      "file_extension": ".py",
+      "mimetype": "text/x-python",
+      "name": "python",
+      "nbconvert_exporter": "python",
+      "pygments_lexer": "ipython3",
+      "version": "3.9.12"
+    },
+    "colab": {
+      "provenance": []
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
\ No newline at end of file

From 786a0e7ea74605468cf4a34dcfd96621a4619699 Mon Sep 17 00:00:00 2001
From: bonochof <ryos427@yahoo.co.jp>
Date: Tue, 11 Apr 2023 16:45:16 +0900
Subject: [PATCH 2/5] [wip] fix config

---
 examples/shock_transfer.ipynb | 92 ++++++++++++++++++++++-------------
 1 file changed, 58 insertions(+), 34 deletions(-)

diff --git a/examples/shock_transfer.ipynb b/examples/shock_transfer.ipynb
index 981ec5fa..a57a82c1 100644
--- a/examples/shock_transfer.ipynb
+++ b/examples/shock_transfer.ipynb
@@ -20,9 +20,37 @@
       "cell_type": "code",
       "execution_count": 1,
       "metadata": {
-        "id": "OwaI8_xbpa-5"
+        "id": "OwaI8_xbpa-5",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "1df64bd6-6e6b-4365-8f03-c6f3fc583f5e"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
+            "Requirement already satisfied: pams in /usr/local/lib/python3.9/dist-packages (0.0.10)\n",
+            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.9/dist-packages (3.7.1)\n",
+            "Requirement already satisfied: numpy<2.0.0,>=1.23.4 in /usr/local/lib/python3.9/dist-packages (from pams) (1.24.2)\n",
+            "Requirement already satisfied: tqdm<5.0.0,>=4.64.1 in /usr/local/lib/python3.9/dist-packages (from pams) (4.65.0)\n",
+            "Requirement already satisfied: scipy<2.0.0,>=1.9.2 in /usr/local/lib/python3.9/dist-packages (from pams) (1.10.1)\n",
+            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (1.0.7)\n",
+            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (23.0)\n",
+            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (2.8.2)\n",
+            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (0.11.0)\n",
+            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (4.39.3)\n",
+            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (3.0.9)\n",
+            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (1.4.4)\n",
+            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (8.4.0)\n",
+            "Requirement already satisfied: importlib-resources>=3.2.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (5.12.0)\n",
+            "Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.9/dist-packages (from importlib-resources>=3.2.0->matplotlib) (3.15.0)\n",
+            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.9/dist-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\n"
+          ]
+        }
+      ],
       "source": [
         "# Please remove comment-out if necessary\n",
         "#! pip install pams matplotlib"
@@ -47,7 +75,7 @@
         "\t\t\t\t\"withOrderExecution\": False,\n",
         "\t\t\t\t\"withPrint\": True,\n",
         "\t\t\t\t\"maxNormalOrders\": 3, \"MEMO\": \"The same number as #markets\",\n",
-        "\t\t\t\t\"maxHifreqOrders\": 0\n",
+        "\t\t\t\t\"maxHighFrequencyOrders\": 0\n",
         "\t\t\t},\n",
         "\t\t\t{\t\"sessionName\": 1,\n",
         "\t\t\t\t\"iterationSteps\": 500,\n",
@@ -55,7 +83,7 @@
         "\t\t\t\t\"withOrderExecution\": True,\n",
         "\t\t\t\t\"withPrint\": True,\n",
         "\t\t\t\t\"maxNormalOrders\": 3, \"MEMO\": \"The same number as #markets\",\n",
-        "\t\t\t\t\"maxHifreqOrders\": 5,\n",
+        "\t\t\t\t\"maxHighFrequencyOrders\": 5,\n",
         "\t\t\t\t\"events\": [\"FundamentalPriceShock\"]\n",
         "\t\t\t}\n",
         "\t\t]\n",
@@ -65,7 +93,7 @@
         "\t\t\"class\": \"FundamentalPriceShock\",\n",
         "\t\t\"target\": \"SpotMarket-1\",\n",
         "\t\t\"triggerTime\": 0,\n",
-        "\t\t\"priceChangeRate\": -0.1,\n",
+        "\t\t\"priceChangeRate\": -0.3,\n",
         "\t\t\"enabled\": True\n",
         "\t},\n",
         "\t\"SpotMarket\": {\n",
@@ -104,24 +132,15 @@
         "\n",
         "\t\"FCNAgents-1\": {\n",
         "\t\t\"extends\": \"FCNAgent\",\n",
-        "\t\t\"markets\": [\"SpotMarket-1\"],\n",
-        "\t\t\"fundamentalWeight\": {\"expon\": [1.0]},\n",
-        "\t\t\"chartWeight\": {\"expon\": [0.0]},\n",
-        "\t\t\"noiseWeight\": {\"expon\": [1.0]}\n",
+        "\t\t\"markets\": [\"SpotMarket-1\"]\n",
         "\t},\n",
         "\t\"FCNAgents-2\": {\n",
         "\t\t\"extends\": \"FCNAgent\",\n",
-        "\t\t\"markets\": [\"SpotMarket-2\"],\n",
-        "\t\t\"fundamentalWeight\": {\"expon\": [0.0]},\n",
-        "\t\t\"chartWeight\": {\"expon\": [0.0]},\n",
-        "\t\t\"noiseWeight\": {\"expon\": [0.2]}\n",
+        "\t\t\"markets\": [\"SpotMarket-2\"]\n",
         "\t},\n",
         "\t\"FCNAgents-I\": {\n",
         "\t\t\"extends\": \"FCNAgent\",\n",
-        "\t\t\"markets\": [\"IndexMarket-I\"],\n",
-        "\t\t\"fundamentalWeight\": {\"expon\": [0.5]},\n",
-        "\t\t\"chartWeight\": {\"expon\": [0.0]},\n",
-        "\t\t\"noiseWeight\": {\"expon\": [1.0]}\n",
+        "\t\t\"markets\": [\"IndexMarket-I\"]\n",
         "\t},\n",
         "\t\"ArbitrageAgents\": {\n",
         "\t\t\"class\": \"ArbitrageAgent\",\n",
@@ -147,7 +166,7 @@
         "import numpy as np\n",
         "import matplotlib.pyplot as plt\n",
         "from pams.runners import SequentialRunner\n",
-        "from pams.logs.market_step_loggers import MarketStepSaver#PrintLogger"
+        "from pams.logs.market_step_loggers import MarketStepSaver"
       ]
     },
     {
@@ -158,14 +177,14 @@
           "base_uri": "https://localhost:8080/"
         },
         "id": "3QXSkEw2pa-6",
-        "outputId": "255e80ff-e174-4f96-dbd8-12b3cc8e3835"
+        "outputId": "fb454d0c-57b3-4cb6-d6ad-4512dbe429c1"
       },
       "outputs": [
         {
           "output_type": "stream",
           "name": "stderr",
           "text": [
-            "/usr/local/lib/python3.9/dist-packages/pams/market.py:446: UserWarning: order price does not accord to the tick size. price will be modified\n",
+            "/usr/local/lib/python3.9/dist-packages/pams/market.py:735: UserWarning: order price does not accord to the tick size. price will be modified\n",
             "  warnings.warn(\n"
           ]
         },
@@ -173,13 +192,13 @@
           "output_type": "stream",
           "name": "stdout",
           "text": [
-            "# INITIALIZATION TIME 0.007541969\n",
-            "# EXECUTION TIME 0.535983768\n"
+            "# INITIALIZATION TIME 0.012723214\n",
+            "# EXECUTION TIME 1.689226608\n"
           ]
         }
       ],
       "source": [
-        "saver = MarketStepSaver() #PrintLogger()\n",
+        "saver = MarketStepSaver()\n",
         "\n",
         "runner = SequentialRunner(\n",
         "    settings=config,\n",
@@ -197,9 +216,13 @@
       },
       "outputs": [],
       "source": [
-        "market_prices_indexmarket_i = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"market_price\"]), filter(lambda x: x[\"market_time\"] >= 100 and x[\"market_name\"] == \"IndexMarket-I\", saver.market_step_logs))))\n",
-        "market_prices_spotmarket_1 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"market_price\"]), filter(lambda x: x[\"market_time\"] >= 100 and x[\"market_name\"] == \"SpotMarket-1\", saver.market_step_logs))))\n",
-        "market_prices_spotmarket_2 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"market_price\"]), filter(lambda x: x[\"market_time\"] >= 100 and x[\"market_name\"] == \"SpotMarket-2\", saver.market_step_logs))))"
+        "market_prices_indexmarket_i = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"market_price\"]), filter(lambda x: x[\"market_name\"] == \"IndexMarket-I\", saver.market_step_logs))))\n",
+        "market_prices_spotmarket_1 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"market_price\"]), filter(lambda x: x[\"market_name\"] == \"SpotMarket-1\", saver.market_step_logs))))\n",
+        "market_prices_spotmarket_2 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"market_price\"]), filter(lambda x: x[\"market_name\"] == \"SpotMarket-2\", saver.market_step_logs))))\n",
+        "\n",
+        "fundamental_prices_indexmarket_i = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"fundamental_price\"]), filter(lambda x: x[\"market_name\"] == \"IndexMarket-I\", saver.market_step_logs))))\n",
+        "fundamental_prices_spotmarket_1 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"fundamental_price\"]), filter(lambda x: x[\"market_name\"] == \"SpotMarket-1\", saver.market_step_logs))))\n",
+        "fundamental_prices_spotmarket_2 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"fundamental_price\"]), filter(lambda x: x[\"market_name\"] == \"SpotMarket-2\", saver.market_step_logs))))"
       ]
     },
     {
@@ -208,29 +231,30 @@
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 279
+          "height": 449
         },
         "id": "c__AgWzapa-7",
-        "outputId": "241b483b-6eb9-4aac-a06b-805367c1a3b9"
+        "outputId": "456ed7cb-0b14-4774-845c-da50b68a7031"
       },
       "outputs": [
         {
           "output_type": "display_data",
           "data": {
             "text/plain": [
-              "<Figure size 432x288 with 1 Axes>"
+              "<Figure size 640x480 with 1 Axes>"
             ],
-            "image/png": 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\n"
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\n"
           },
-          "metadata": {
-            "needs_background": "light"
-          }
+          "metadata": {}
         }
       ],
       "source": [
         "plt.plot(list(market_prices_indexmarket_i.keys()), list(market_prices_indexmarket_i.values()), label=\"IndexMarket-I\")\n",
         "plt.plot(list(market_prices_spotmarket_1.keys()), list(market_prices_spotmarket_1.values()), label=\"SpotMarket-1\")\n",
         "plt.plot(list(market_prices_spotmarket_2.keys()), list(market_prices_spotmarket_2.values()), label=\"SpotMarket-2\")\n",
+        "plt.plot(list(fundamental_prices_indexmarket_i.keys()), list(fundamental_prices_indexmarket_i.values()), color='black')\n",
+        "plt.plot(list(fundamental_prices_spotmarket_1.keys()), list(fundamental_prices_spotmarket_1.values()), color='black')\n",
+        "plt.plot(list(fundamental_prices_spotmarket_2.keys()), list(fundamental_prices_spotmarket_2.values()), color='black')\n",
         "plt.xlabel(\"ticks\")\n",
         "plt.ylabel(\"market price\")\n",
         "plt.legend()\n",
@@ -239,7 +263,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 6,
       "metadata": {
         "id": "aVsDnfX7pa-7"
       },

From 9e32e650cc5b04f4049926d7e09c57459bb9c2a3 Mon Sep 17 00:00:00 2001
From: Masanori HIRANO <masa.hirano.1996@gmail.com>
Date: Wed, 26 Apr 2023 21:07:00 +0900
Subject: [PATCH 3/5] update parameter

---
 samples/shock_transfer/config.json | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/samples/shock_transfer/config.json b/samples/shock_transfer/config.json
index e4bc9e81..d0423f9e 100644
--- a/samples/shock_transfer/config.json
+++ b/samples/shock_transfer/config.json
@@ -27,7 +27,7 @@
 		"class": "FundamentalPriceShock",
 		"target": "SpotMarket-1",
 		"triggerTime": 0,
-		"priceChangeRate": -0.3,
+		"priceChangeRate": -0.1,
 		"enabled": true
 	},
 	"SpotMarket": {

From 6574613618196e1b90d03af8ce346443c68cd629 Mon Sep 17 00:00:00 2001
From: Masanori HIRANO <masa.hirano.1996@gmail.com>
Date: Wed, 26 Apr 2023 21:08:42 +0900
Subject: [PATCH 4/5] update notebook

---
 examples/shock_transfer.ipynb | 524 +++++++++++++++-------------------
 1 file changed, 231 insertions(+), 293 deletions(-)

diff --git a/examples/shock_transfer.ipynb b/examples/shock_transfer.ipynb
index a57a82c1..21d2a8e6 100644
--- a/examples/shock_transfer.ipynb
+++ b/examples/shock_transfer.ipynb
@@ -1,298 +1,236 @@
 {
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "KCI4qIU_pa-1"
-      },
-      "source": []
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "58xSRq9jpa-2"
-      },
-      "source": [
-        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](http://colab.research.google.com/github/masanorihirano/pams/blob/main/examples/shock_transfer.ipynb)"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 1,
-      "metadata": {
-        "id": "OwaI8_xbpa-5",
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "outputId": "1df64bd6-6e6b-4365-8f03-c6f3fc583f5e"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
-            "Requirement already satisfied: pams in /usr/local/lib/python3.9/dist-packages (0.0.10)\n",
-            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.9/dist-packages (3.7.1)\n",
-            "Requirement already satisfied: numpy<2.0.0,>=1.23.4 in /usr/local/lib/python3.9/dist-packages (from pams) (1.24.2)\n",
-            "Requirement already satisfied: tqdm<5.0.0,>=4.64.1 in /usr/local/lib/python3.9/dist-packages (from pams) (4.65.0)\n",
-            "Requirement already satisfied: scipy<2.0.0,>=1.9.2 in /usr/local/lib/python3.9/dist-packages (from pams) (1.10.1)\n",
-            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (1.0.7)\n",
-            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (23.0)\n",
-            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (2.8.2)\n",
-            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (0.11.0)\n",
-            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (4.39.3)\n",
-            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (3.0.9)\n",
-            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (1.4.4)\n",
-            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (8.4.0)\n",
-            "Requirement already satisfied: importlib-resources>=3.2.0 in /usr/local/lib/python3.9/dist-packages (from matplotlib) (5.12.0)\n",
-            "Requirement already satisfied: zipp>=3.1.0 in /usr/local/lib/python3.9/dist-packages (from importlib-resources>=3.2.0->matplotlib) (3.15.0)\n",
-            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.9/dist-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\n"
-          ]
-        }
-      ],
-      "source": [
-        "# Please remove comment-out if necessary\n",
-        "#! pip install pams matplotlib"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 2,
-      "metadata": {
-        "id": "ixLeaU7Epa-5"
-      },
-      "outputs": [],
-      "source": [
-        "config = {\n",
-        "\t\"simulation\": {\n",
-        "\t\t\"markets\": [\"SpotMarket-1\", \"SpotMarket-2\", \"IndexMarket-I\"],\n",
-        "\t\t\"agents\": [\"FCNAgents-1\", \"FCNAgents-2\", \"FCNAgents-I\", \"ArbitrageAgents\"],\n",
-        "\t\t\"sessions\": [\n",
-        "\t\t\t{\t\"sessionName\": 0,\n",
-        "\t\t\t\t\"iterationSteps\": 100,\n",
-        "\t\t\t\t\"withOrderPlacement\": True,\n",
-        "\t\t\t\t\"withOrderExecution\": False,\n",
-        "\t\t\t\t\"withPrint\": True,\n",
-        "\t\t\t\t\"maxNormalOrders\": 3, \"MEMO\": \"The same number as #markets\",\n",
-        "\t\t\t\t\"maxHighFrequencyOrders\": 0\n",
-        "\t\t\t},\n",
-        "\t\t\t{\t\"sessionName\": 1,\n",
-        "\t\t\t\t\"iterationSteps\": 500,\n",
-        "\t\t\t\t\"withOrderPlacement\": True,\n",
-        "\t\t\t\t\"withOrderExecution\": True,\n",
-        "\t\t\t\t\"withPrint\": True,\n",
-        "\t\t\t\t\"maxNormalOrders\": 3, \"MEMO\": \"The same number as #markets\",\n",
-        "\t\t\t\t\"maxHighFrequencyOrders\": 5,\n",
-        "\t\t\t\t\"events\": [\"FundamentalPriceShock\"]\n",
-        "\t\t\t}\n",
-        "\t\t]\n",
-        "\t},\n",
-        "\n",
-        "\t\"FundamentalPriceShock\": {\n",
-        "\t\t\"class\": \"FundamentalPriceShock\",\n",
-        "\t\t\"target\": \"SpotMarket-1\",\n",
-        "\t\t\"triggerTime\": 0,\n",
-        "\t\t\"priceChangeRate\": -0.3,\n",
-        "\t\t\"enabled\": True\n",
-        "\t},\n",
-        "\t\"SpotMarket\": {\n",
-        "\t\t\"class\": \"Market\",\n",
-        "\t\t\"tickSize\": 0.00001,\n",
-        "\t\t\"marketPrice\": 300.0,\n",
-        "\t\t\"outstandingShares\": 25000\n",
-        "\t},\n",
-        "\t\"SpotMarket-1\": {\n",
-        "\t\t\"extends\": \"SpotMarket\"\n",
-        "\t},\n",
-        "\t\"SpotMarket-2\": {\n",
-        "\t\t\"extends\": \"SpotMarket\"\n",
-        "\t},\n",
-        "\t\"IndexMarket-I\": {\n",
-        "\t\t\"class\": \"IndexMarket\",\n",
-        "\t\t\"tickSize\": 0.00001,\n",
-        "\t\t\"marketPrice\": 300.0,\n",
-        "\t\t\"outstandingShares\": 25000,\n",
-        "\t\t\"markets\": [\"SpotMarket-1\", \"SpotMarket-2\"]\n",
-        "\t},\n",
-        "\t\"FCNAgent\": {\n",
-        "\t\t\"class\": \"FCNAgent\",\n",
-        "\t\t\"numAgents\": 100,\n",
-        "\t\t\"markets\": [\"Market\"],\n",
-        "\t\t\"assetVolume\": 50,\n",
-        "\t\t\"cashAmount\": 10000,\n",
-        "\n",
-        "\t\t\"fundamentalWeight\": {\"expon\": [1.0]},\n",
-        "\t\t\"chartWeight\": {\"expon\": [0.0]},\n",
-        "\t\t\"noiseWeight\": {\"expon\": [1.0]},\n",
-        "\t\t\"noiseScale\": 0.001,\n",
-        "\t\t\"timeWindowSize\": [100, 200],\n",
-        "\t\t\"orderMargin\": [0.0, 0.1]\n",
-        "\t},\n",
-        "\n",
-        "\t\"FCNAgents-1\": {\n",
-        "\t\t\"extends\": \"FCNAgent\",\n",
-        "\t\t\"markets\": [\"SpotMarket-1\"]\n",
-        "\t},\n",
-        "\t\"FCNAgents-2\": {\n",
-        "\t\t\"extends\": \"FCNAgent\",\n",
-        "\t\t\"markets\": [\"SpotMarket-2\"]\n",
-        "\t},\n",
-        "\t\"FCNAgents-I\": {\n",
-        "\t\t\"extends\": \"FCNAgent\",\n",
-        "\t\t\"markets\": [\"IndexMarket-I\"]\n",
-        "\t},\n",
-        "\t\"ArbitrageAgents\": {\n",
-        "\t\t\"class\": \"ArbitrageAgent\",\n",
-        "\t\t\"numAgents\": 100,\n",
-        "\t\t\"markets\": [\"IndexMarket-I\", \"SpotMarket-1\", \"SpotMarket-2\"],\n",
-        "\t\t\"assetVolume\": 50,\n",
-        "\t\t\"cashAmount\": 150000,\n",
-        "\t\t\"orderVolume\": 1,\n",
-        "\t\t\"orderThresholdPrice\": 1.0\n",
-        "\t}\n",
-        "}"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 3,
-      "metadata": {
-        "id": "xUUUfulSpa-6"
-      },
-      "outputs": [],
-      "source": [
-        "import random\n",
-        "import numpy as np\n",
-        "import matplotlib.pyplot as plt\n",
-        "from pams.runners import SequentialRunner\n",
-        "from pams.logs.market_step_loggers import MarketStepSaver"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 4,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "3QXSkEw2pa-6",
-        "outputId": "fb454d0c-57b3-4cb6-d6ad-4512dbe429c1"
-      },
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stderr",
-          "text": [
-            "/usr/local/lib/python3.9/dist-packages/pams/market.py:735: UserWarning: order price does not accord to the tick size. price will be modified\n",
-            "  warnings.warn(\n"
-          ]
-        },
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "# INITIALIZATION TIME 0.012723214\n",
-            "# EXECUTION TIME 1.689226608\n"
-          ]
-        }
-      ],
-      "source": [
-        "saver = MarketStepSaver()\n",
-        "\n",
-        "runner = SequentialRunner(\n",
-        "    settings=config,\n",
-        "    prng=random.Random(42),\n",
-        "    logger=saver,\n",
-        ")\n",
-        "runner.main()"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 5,
-      "metadata": {
-        "id": "P5_pyTa9pa-6"
-      },
-      "outputs": [],
-      "source": [
-        "market_prices_indexmarket_i = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"market_price\"]), filter(lambda x: x[\"market_name\"] == \"IndexMarket-I\", saver.market_step_logs))))\n",
-        "market_prices_spotmarket_1 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"market_price\"]), filter(lambda x: x[\"market_name\"] == \"SpotMarket-1\", saver.market_step_logs))))\n",
-        "market_prices_spotmarket_2 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"market_price\"]), filter(lambda x: x[\"market_name\"] == \"SpotMarket-2\", saver.market_step_logs))))\n",
-        "\n",
-        "fundamental_prices_indexmarket_i = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"fundamental_price\"]), filter(lambda x: x[\"market_name\"] == \"IndexMarket-I\", saver.market_step_logs))))\n",
-        "fundamental_prices_spotmarket_1 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"fundamental_price\"]), filter(lambda x: x[\"market_name\"] == \"SpotMarket-1\", saver.market_step_logs))))\n",
-        "fundamental_prices_spotmarket_2 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"fundamental_price\"]), filter(lambda x: x[\"market_name\"] == \"SpotMarket-2\", saver.market_step_logs))))"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 6,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 449
-        },
-        "id": "c__AgWzapa-7",
-        "outputId": "456ed7cb-0b14-4774-845c-da50b68a7031"
-      },
-      "outputs": [
-        {
-          "output_type": "display_data",
-          "data": {
-            "text/plain": [
-              "<Figure size 640x480 with 1 Axes>"
-            ],
-            "image/png": 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\n"
-          },
-          "metadata": {}
-        }
-      ],
-      "source": [
-        "plt.plot(list(market_prices_indexmarket_i.keys()), list(market_prices_indexmarket_i.values()), label=\"IndexMarket-I\")\n",
-        "plt.plot(list(market_prices_spotmarket_1.keys()), list(market_prices_spotmarket_1.values()), label=\"SpotMarket-1\")\n",
-        "plt.plot(list(market_prices_spotmarket_2.keys()), list(market_prices_spotmarket_2.values()), label=\"SpotMarket-2\")\n",
-        "plt.plot(list(fundamental_prices_indexmarket_i.keys()), list(fundamental_prices_indexmarket_i.values()), color='black')\n",
-        "plt.plot(list(fundamental_prices_spotmarket_1.keys()), list(fundamental_prices_spotmarket_1.values()), color='black')\n",
-        "plt.plot(list(fundamental_prices_spotmarket_2.keys()), list(fundamental_prices_spotmarket_2.values()), color='black')\n",
-        "plt.xlabel(\"ticks\")\n",
-        "plt.ylabel(\"market price\")\n",
-        "plt.legend()\n",
-        "plt.show()"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 6,
-      "metadata": {
-        "id": "aVsDnfX7pa-7"
-      },
-      "outputs": [],
-      "source": []
-    }
-  ],
-  "metadata": {
-    "kernelspec": {
-      "display_name": "Python 3 (ipykernel)",
-      "language": "python",
-      "name": "python3"
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "KCI4qIU_pa-1"
+   },
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "58xSRq9jpa-2"
+   },
+   "source": [
+    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](http://colab.research.google.com/github/masanorihirano/pams/blob/main/examples/shock_transfer.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "OwaI8_xbpa-5",
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
-    "language_info": {
-      "codemirror_mode": {
-        "name": "ipython",
-        "version": 3
-      },
-      "file_extension": ".py",
-      "mimetype": "text/x-python",
-      "name": "python",
-      "nbconvert_exporter": "python",
-      "pygments_lexer": "ipython3",
-      "version": "3.9.12"
+    "outputId": "1df64bd6-6e6b-4365-8f03-c6f3fc583f5e"
+   },
+   "outputs": [],
+   "source": [
+    "# Please remove comment-out if necessary\n",
+    "#! pip install pams matplotlib"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "ixLeaU7Epa-5"
+   },
+   "outputs": [],
+   "source": [
+    "config = {\n",
+    "\t\"simulation\": {\n",
+    "\t\t\"markets\": [\"SpotMarket-1\", \"SpotMarket-2\", \"IndexMarket-I\"],\n",
+    "\t\t\"agents\": [\"FCNAgents-1\", \"FCNAgents-2\", \"FCNAgents-I\", \"ArbitrageAgents\"],\n",
+    "\t\t\"sessions\": [\n",
+    "\t\t\t{\t\"sessionName\": 0,\n",
+    "\t\t\t\t\"iterationSteps\": 100,\n",
+    "\t\t\t\t\"withOrderPlacement\": True,\n",
+    "\t\t\t\t\"withOrderExecution\": False,\n",
+    "\t\t\t\t\"withPrint\": True,\n",
+    "\t\t\t\t\"maxNormalOrders\": 3, \"MEMO\": \"The same number as #markets\",\n",
+    "\t\t\t\t\"maxHighFrequencyOrders\": 0\n",
+    "\t\t\t},\n",
+    "\t\t\t{\t\"sessionName\": 1,\n",
+    "\t\t\t\t\"iterationSteps\": 500,\n",
+    "\t\t\t\t\"withOrderPlacement\": True,\n",
+    "\t\t\t\t\"withOrderExecution\": True,\n",
+    "\t\t\t\t\"withPrint\": True,\n",
+    "\t\t\t\t\"maxNormalOrders\": 3, \"MEMO\": \"The same number as #markets\",\n",
+    "\t\t\t\t\"maxHighFrequencyOrders\": 5,\n",
+    "\t\t\t\t\"events\": [\"FundamentalPriceShock\"]\n",
+    "\t\t\t}\n",
+    "\t\t]\n",
+    "\t},\n",
+    "\n",
+    "\t\"FundamentalPriceShock\": {\n",
+    "\t\t\"class\": \"FundamentalPriceShock\",\n",
+    "\t\t\"target\": \"SpotMarket-1\",\n",
+    "\t\t\"triggerTime\": 0,\n",
+    "\t\t\"priceChangeRate\": -0.1\n",
+    "\t},\n",
+    "\t\"SpotMarket\": {\n",
+    "\t\t\"class\": \"Market\",\n",
+    "\t\t\"tickSize\": 0.00001,\n",
+    "\t\t\"marketPrice\": 300.0,\n",
+    "\t\t\"outstandingShares\": 25000\n",
+    "\t},\n",
+    "\t\"SpotMarket-1\": {\n",
+    "\t\t\"extends\": \"SpotMarket\"\n",
+    "\t},\n",
+    "\t\"SpotMarket-2\": {\n",
+    "\t\t\"extends\": \"SpotMarket\"\n",
+    "\t},\n",
+    "\t\"IndexMarket-I\": {\n",
+    "\t\t\"class\": \"IndexMarket\",\n",
+    "\t\t\"tickSize\": 0.00001,\n",
+    "\t\t\"marketPrice\": 300.0,\n",
+    "\t\t\"outstandingShares\": 25000,\n",
+    "\t\t\"markets\": [\"SpotMarket-1\", \"SpotMarket-2\"]\n",
+    "\t},\n",
+    "\t\"FCNAgent\": {\n",
+    "\t\t\"class\": \"FCNAgent\",\n",
+    "\t\t\"numAgents\": 100,\n",
+    "\t\t\"markets\": [\"Market\"],\n",
+    "\t\t\"assetVolume\": 50,\n",
+    "\t\t\"cashAmount\": 10000,\n",
+    "\n",
+    "\t\t\"fundamentalWeight\": {\"expon\": [1.0]},\n",
+    "\t\t\"chartWeight\": {\"expon\": [0.0]},\n",
+    "\t\t\"noiseWeight\": {\"expon\": [1.0]},\n",
+    "\t\t\"noiseScale\": 0.001,\n",
+    "\t\t\"timeWindowSize\": [100, 200],\n",
+    "\t\t\"orderMargin\": [0.0, 0.1]\n",
+    "\t},\n",
+    "\n",
+    "\t\"FCNAgents-1\": {\n",
+    "\t\t\"extends\": \"FCNAgent\",\n",
+    "\t\t\"markets\": [\"SpotMarket-1\"]\n",
+    "\t},\n",
+    "\t\"FCNAgents-2\": {\n",
+    "\t\t\"extends\": \"FCNAgent\",\n",
+    "\t\t\"markets\": [\"SpotMarket-2\"]\n",
+    "\t},\n",
+    "\t\"FCNAgents-I\": {\n",
+    "\t\t\"extends\": \"FCNAgent\",\n",
+    "\t\t\"markets\": [\"IndexMarket-I\"]\n",
+    "\t},\n",
+    "\t\"ArbitrageAgents\": {\n",
+    "\t\t\"class\": \"ArbitrageAgent\",\n",
+    "\t\t\"numAgents\": 100,\n",
+    "\t\t\"markets\": [\"IndexMarket-I\", \"SpotMarket-1\", \"SpotMarket-2\"],\n",
+    "\t\t\"assetVolume\": 50,\n",
+    "\t\t\"cashAmount\": 150000,\n",
+    "\t\t\"orderVolume\": 1,\n",
+    "\t\t\"orderThresholdPrice\": 1.0\n",
+    "\t}\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "xUUUfulSpa-6"
+   },
+   "outputs": [],
+   "source": [
+    "import random\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "from pams.runners import SequentialRunner\n",
+    "from pams.logs.market_step_loggers import MarketStepSaver"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
     },
+    "id": "3QXSkEw2pa-6",
+    "outputId": "fb454d0c-57b3-4cb6-d6ad-4512dbe429c1"
+   },
+   "outputs": [],
+   "source": [
+    "saver = MarketStepSaver()\n",
+    "\n",
+    "runner = SequentialRunner(\n",
+    "    settings=config,\n",
+    "    prng=random.Random(42),\n",
+    "    logger=saver,\n",
+    ")\n",
+    "runner.main()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "P5_pyTa9pa-6"
+   },
+   "outputs": [],
+   "source": [
+    "market_prices_indexmarket_i = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"market_price\"]), filter(lambda x: x[\"market_name\"] == \"IndexMarket-I\", saver.market_step_logs))))\n",
+    "market_prices_spotmarket_1 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"market_price\"]), filter(lambda x: x[\"market_name\"] == \"SpotMarket-1\", saver.market_step_logs))))\n",
+    "market_prices_spotmarket_2 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"market_price\"]), filter(lambda x: x[\"market_name\"] == \"SpotMarket-2\", saver.market_step_logs))))\n",
+    "\n",
+    "fundamental_prices_indexmarket_i = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"fundamental_price\"]), filter(lambda x: x[\"market_name\"] == \"IndexMarket-I\", saver.market_step_logs))))\n",
+    "fundamental_prices_spotmarket_1 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"fundamental_price\"]), filter(lambda x: x[\"market_name\"] == \"SpotMarket-1\", saver.market_step_logs))))\n",
+    "fundamental_prices_spotmarket_2 = dict(sorted(map(lambda x: (x[\"market_time\"], x[\"fundamental_price\"]), filter(lambda x: x[\"market_name\"] == \"SpotMarket-2\", saver.market_step_logs))))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
     "colab": {
-      "provenance": []
-    }
+     "base_uri": "https://localhost:8080/",
+     "height": 449
+    },
+    "id": "c__AgWzapa-7",
+    "outputId": "456ed7cb-0b14-4774-845c-da50b68a7031"
+   },
+   "outputs": [],
+   "source": [
+    "plt.plot(list(market_prices_indexmarket_i.keys()), list(market_prices_indexmarket_i.values()), label=\"IndexMarket-I\")\n",
+    "plt.plot(list(market_prices_spotmarket_1.keys()), list(market_prices_spotmarket_1.values()), label=\"SpotMarket-1\")\n",
+    "plt.plot(list(market_prices_spotmarket_2.keys()), list(market_prices_spotmarket_2.values()), label=\"SpotMarket-2\")\n",
+    "plt.plot(list(fundamental_prices_indexmarket_i.keys()), list(fundamental_prices_indexmarket_i.values()), color='black')\n",
+    "plt.plot(list(fundamental_prices_spotmarket_1.keys()), list(fundamental_prices_spotmarket_1.values()), color='black')\n",
+    "plt.plot(list(fundamental_prices_spotmarket_2.keys()), list(fundamental_prices_spotmarket_2.values()), color='black')\n",
+    "plt.xlabel(\"ticks\")\n",
+    "plt.ylabel(\"market price\")\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.12"
   },
-  "nbformat": 4,
-  "nbformat_minor": 0
-}
\ No newline at end of file
+  "colab": {
+   "provenance": []
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}

From 7d5d5a01b728a383d9b24afbf2f4629729b5f90e Mon Sep 17 00:00:00 2001
From: Masanori HIRANO <masa.hirano.1996@gmail.com>
Date: Wed, 26 Apr 2023 21:10:43 +0900
Subject: [PATCH 5/5] drop exception in ci (trial)

---
 .github/workflows/ci-python.yml | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/.github/workflows/ci-python.yml b/.github/workflows/ci-python.yml
index 328c1855..bc8dfcfa 100644
--- a/.github/workflows/ci-python.yml
+++ b/.github/workflows/ci-python.yml
@@ -24,9 +24,6 @@ jobs:
       matrix:
         platform: [ubuntu-latest, macos-latest, windows-latest]
         python-version: [3.8, 3.9, "3.10", "3.11"]
-        exclude:
-          - platform: windows-latest
-            python-version: "3.11"
 
     # Steps represent a sequence of tasks that will be executed as part of the job
     steps: