playground.copy. copy 2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import trackhhl.toy.simple_generator as toy\n",
    "import trackhhl.event_model.q_event_model as em\n",
    "import numpy as np\n",
    "import itertools\n",
    "import copy\n",
    "from dwave.samplers import SimulatedAnnealingSampler\n",
    "import dimod\n",
    "import psutil\n",
    "import time\n",
    "from scipy.sparse import lil_matrix, csc_matrix, block_diag\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Hit(hit_id=0, x=0.11221702536854823, y=-0.12363750426032506, z=1.0, module_id=0, track_id=0),\n",
       " Hit(hit_id=5, x=0.31566674107241505, y=0.2642494914083945, z=1.0, module_id=0, track_id=1),\n",
       " Hit(hit_id=10, x=0.11935245628820933, y=-0.022624644383053453, z=1.0, module_id=0, track_id=2),\n",
       " Hit(hit_id=15, x=-0.003545093135268213, y=-0.34873708078914595, z=1.0, module_id=0, track_id=3),\n",
       " Hit(hit_id=20, x=0.4595849318488096, y=0.15432267234414968, z=1.0, module_id=0, track_id=4),\n",
       " Hit(hit_id=25, x=-0.1407502694333988, y=0.291324542869651, z=1.0, module_id=0, track_id=5),\n",
       " Hit(hit_id=30, x=-0.549209564584994, y=0.0803825439389368, z=1.0, module_id=0, track_id=6),\n",
       " Hit(hit_id=35, x=0.3614989525828391, y=0.27121839454504104, z=1.0, module_id=0, track_id=7),\n",
       " Hit(hit_id=40, x=0.4610412824645188, y=0.09561057534852499, z=1.0, module_id=0, track_id=8),\n",
       " Hit(hit_id=45, x=0.15883321846100013, y=0.2022803886035029, z=1.0, module_id=0, track_id=9),\n",
       " Hit(hit_id=50, x=-0.1572711365143559, y=-0.34868582847248825, z=1.0, module_id=0, track_id=10),\n",
       " Hit(hit_id=55, x=-0.05508752637283623, y=0.5677306698959763, z=1.0, module_id=0, track_id=11),\n",
       " Hit(hit_id=60, x=0.1718181533673422, y=0.2693722936245774, z=1.0, module_id=0, track_id=12),\n",
       " Hit(hit_id=65, x=0.27335656155854, y=0.0067230266736834545, z=1.0, module_id=0, track_id=13),\n",
       " Hit(hit_id=70, x=0.26138714347787934, y=0.3559548638088299, z=1.0, module_id=0, track_id=14),\n",
       " Hit(hit_id=75, x=-0.19160361555434408, y=-0.3790824801440376, z=1.0, module_id=0, track_id=15),\n",
       " Hit(hit_id=80, x=0.008417507973712738, y=0.0952729793717641, z=1.0, module_id=0, track_id=16),\n",
       " Hit(hit_id=85, x=-0.02288974143524525, y=0.18118847904574864, z=1.0, module_id=0, track_id=17),\n",
       " Hit(hit_id=90, x=0.3071745807982158, y=0.24366045578842976, z=1.0, module_id=0, track_id=18),\n",
       " Hit(hit_id=95, x=-0.046210939484170016, y=0.42018669457583663, z=1.0, module_id=0, track_id=19),\n",
       " Hit(hit_id=100, x=-0.1560699284114197, y=-0.49963231801218994, z=1.0, module_id=0, track_id=20),\n",
       " Hit(hit_id=105, x=-0.20418924450229825, y=0.2990868106880941, z=1.0, module_id=0, track_id=21),\n",
       " Hit(hit_id=110, x=-0.23832986096083336, y=0.12025236365395614, z=1.0, module_id=0, track_id=22),\n",
       " Hit(hit_id=115, x=-0.2793159567540756, y=0.03966592939660256, z=1.0, module_id=0, track_id=23),\n",
       " Hit(hit_id=120, x=-0.06788937309274573, y=-0.34907489278850573, z=1.0, module_id=0, track_id=24),\n",
       " Hit(hit_id=125, x=0.18368054714087365, y=-0.001284116239201023, z=1.0, module_id=0, track_id=25),\n",
       " Hit(hit_id=130, x=-0.40331153401277053, y=0.30556359996605065, z=1.0, module_id=0, track_id=26),\n",
       " Hit(hit_id=135, x=-0.34095408475607303, y=0.0575279406487537, z=1.0, module_id=0, track_id=27),\n",
       " Hit(hit_id=140, x=-0.08069863597098309, y=-0.26059291630807463, z=1.0, module_id=0, track_id=28),\n",
       " Hit(hit_id=145, x=-0.03219409267438363, y=-0.24012943456578087, z=1.0, module_id=0, track_id=29),\n",
       " Hit(hit_id=150, x=-0.3389815802090363, y=0.19176104261230517, z=1.0, module_id=0, track_id=30),\n",
       " Hit(hit_id=155, x=0.18966000051926057, y=-0.19694308299008176, z=1.0, module_id=0, track_id=31),\n",
       " Hit(hit_id=160, x=-0.15827010650421822, y=0.07535375501593942, z=1.0, module_id=0, track_id=32),\n",
       " Hit(hit_id=165, x=0.5080635303568407, y=-0.2399522220759539, z=1.0, module_id=0, track_id=33),\n",
       " Hit(hit_id=170, x=-0.04587663400421564, y=-0.27063060444306736, z=1.0, module_id=0, track_id=34),\n",
       " Hit(hit_id=175, x=-0.535038994961842, y=-0.10236724246387394, z=1.0, module_id=0, track_id=35),\n",
       " Hit(hit_id=180, x=0.3090407292266182, y=-0.3417334257705834, z=1.0, module_id=0, track_id=36),\n",
       " Hit(hit_id=185, x=0.10608683777312723, y=0.5613283394233131, z=1.0, module_id=0, track_id=37),\n",
       " Hit(hit_id=190, x=-0.3301032382337359, y=-0.43416422772306057, z=1.0, module_id=0, track_id=38),\n",
       " Hit(hit_id=195, x=-0.5234983445663758, y=0.2283183101434765, z=1.0, module_id=0, track_id=39),\n",
       " Hit(hit_id=200, x=-0.5580056372889952, y=0.04006468916645024, z=1.0, module_id=0, track_id=40),\n",
       " Hit(hit_id=205, x=-0.4312836057823598, y=0.0513566648846819, z=1.0, module_id=0, track_id=41),\n",
       " Hit(hit_id=210, x=-0.052785114400999, y=0.400474626442253, z=1.0, module_id=0, track_id=42),\n",
       " Hit(hit_id=215, x=0.4382690427715241, y=-0.17078187230420266, z=1.0, module_id=0, track_id=43),\n",
       " Hit(hit_id=220, x=-0.20383543545244304, y=0.23878561655226216, z=1.0, module_id=0, track_id=44),\n",
       " Hit(hit_id=225, x=-0.29405140164498483, y=-0.2721821018216738, z=1.0, module_id=0, track_id=45),\n",
       " Hit(hit_id=230, x=-0.08948288509110923, y=0.16172245402326427, z=1.0, module_id=0, track_id=46),\n",
       " Hit(hit_id=235, x=-0.04352725158513084, y=0.4804429390660812, z=1.0, module_id=0, track_id=47),\n",
       " Hit(hit_id=240, x=-0.3301581425804875, y=0.0977856349536458, z=1.0, module_id=0, track_id=48),\n",
       " Hit(hit_id=245, x=-0.2596179189302145, y=-0.1683133449457496, z=1.0, module_id=0, track_id=49),\n",
       " Hit(hit_id=250, x=-0.5479748726205712, y=0.08511722828205182, z=1.0, module_id=0, track_id=50),\n",
       " Hit(hit_id=255, x=0.1724535003472892, y=-0.025143907478188596, z=1.0, module_id=0, track_id=51),\n",
       " Hit(hit_id=260, x=0.2635404996688358, y=-0.433549150869509, z=1.0, module_id=0, track_id=52),\n",
       " Hit(hit_id=265, x=-0.05489045232629334, y=-0.026226348450103285, z=1.0, module_id=0, track_id=53),\n",
       " Hit(hit_id=270, x=-0.08766664294601965, y=0.07785568185853323, z=1.0, module_id=0, track_id=54),\n",
       " Hit(hit_id=275, x=-0.31406176545999054, y=-0.2557190614121293, z=1.0, module_id=0, track_id=55),\n",
       " Hit(hit_id=280, x=0.049516856072464185, y=0.49297653985292395, z=1.0, module_id=0, track_id=56),\n",
       " Hit(hit_id=285, x=-0.4440833725127946, y=0.12549130421465202, z=1.0, module_id=0, track_id=57),\n",
       " Hit(hit_id=290, x=0.35237773102702363, y=-0.03982695433692835, z=1.0, module_id=0, track_id=58),\n",
       " Hit(hit_id=295, x=0.014902577405207434, y=-0.3405500071216952, z=1.0, module_id=0, track_id=59),\n",
       " Hit(hit_id=300, x=0.3083784143478401, y=0.016352325577603043, z=1.0, module_id=0, track_id=60),\n",
       " Hit(hit_id=305, x=-0.5027289288434851, y=-0.010834974142402918, z=1.0, module_id=0, track_id=61),\n",
       " Hit(hit_id=310, x=0.2854851068050417, y=0.48782418390803123, z=1.0, module_id=0, track_id=62),\n",
       " Hit(hit_id=315, x=-0.36532124168713537, y=-0.04867573261447113, z=1.0, module_id=0, track_id=63),\n",
       " Hit(hit_id=320, x=-0.541809882167066, y=0.06635661965449996, z=1.0, module_id=0, track_id=64),\n",
       " Hit(hit_id=325, x=0.1254313563399504, y=-0.15895281113316456, z=1.0, module_id=0, track_id=65),\n",
       " Hit(hit_id=330, x=-0.08820426818172906, y=0.3922569434305272, z=1.0, module_id=0, track_id=66),\n",
       " Hit(hit_id=335, x=-0.22382726558671048, y=0.21410784375611028, z=1.0, module_id=0, track_id=67),\n",
       " Hit(hit_id=340, x=-0.5357266330096279, y=0.17249085650281992, z=1.0, module_id=0, track_id=68),\n",
       " Hit(hit_id=345, x=-0.3138017020019872, y=0.37106129215614786, z=1.0, module_id=0, track_id=69),\n",
       " Hit(hit_id=350, x=-0.44919689052016915, y=0.1444738862863025, z=1.0, module_id=0, track_id=70),\n",
       " Hit(hit_id=355, x=0.4700644006492627, y=-0.2191429862788865, z=1.0, module_id=0, track_id=71),\n",
       " Hit(hit_id=360, x=-0.03541862816669384, y=-0.502418717049214, z=1.0, module_id=0, track_id=72),\n",
       " Hit(hit_id=365, x=0.16967755290780984, y=-0.1543208023959946, z=1.0, module_id=0, track_id=73),\n",
       " Hit(hit_id=370, x=-0.025472990737733636, y=-0.3197062582190676, z=1.0, module_id=0, track_id=74),\n",
       " Hit(hit_id=375, x=-0.1447578477391597, y=0.5514145550753681, z=1.0, module_id=0, track_id=75),\n",
       " Hit(hit_id=380, x=-0.36013431847527166, y=0.4445120101190552, z=1.0, module_id=0, track_id=76),\n",
       " Hit(hit_id=385, x=-0.20295864270013553, y=0.08345759635321218, z=1.0, module_id=0, track_id=77),\n",
       " Hit(hit_id=390, x=-0.2571275850162457, y=0.09929224333120734, z=1.0, module_id=0, track_id=78),\n",
       " Hit(hit_id=395, x=0.3799408304883781, y=-0.23207586834774022, z=1.0, module_id=0, track_id=79),\n",
       " Hit(hit_id=400, x=0.07546219892529243, y=-0.11227441513129698, z=1.0, module_id=0, track_id=80),\n",
       " Hit(hit_id=405, x=0.19966928691222174, y=0.13478758756198017, z=1.0, module_id=0, track_id=81),\n",
       " Hit(hit_id=410, x=-0.05796090334544434, y=-0.3501868114634479, z=1.0, module_id=0, track_id=82),\n",
       " Hit(hit_id=415, x=-0.23454887355125167, y=0.06475437602291723, z=1.0, module_id=0, track_id=83),\n",
       " Hit(hit_id=420, x=0.33749342000975757, y=0.043554689124216665, z=1.0, module_id=0, track_id=84),\n",
       " Hit(hit_id=425, x=-0.1263479448126649, y=-0.5470444314163326, z=1.0, module_id=0, track_id=85),\n",
       " Hit(hit_id=430, x=-0.2638114801686351, y=0.23359701506929645, z=1.0, module_id=0, track_id=86),\n",
       " Hit(hit_id=435, x=0.2037456165662624, y=-0.21824074729693693, z=1.0, module_id=0, track_id=87),\n",
       " Hit(hit_id=440, x=-0.04293250548768841, y=0.5268923132950202, z=1.0, module_id=0, track_id=88),\n",
       " Hit(hit_id=445, x=0.011826509142939064, y=-0.22940794681795748, z=1.0, module_id=0, track_id=89),\n",
       " Hit(hit_id=450, x=-0.47846651614569113, y=-0.03737819247144874, z=1.0, module_id=0, track_id=90),\n",
       " Hit(hit_id=455, x=0.027932562452374837, y=-0.3779697086662221, z=1.0, module_id=0, track_id=91),\n",
       " Hit(hit_id=460, x=0.12921542810665446, y=-0.36792669062246436, z=1.0, module_id=0, track_id=92),\n",
       " Hit(hit_id=465, x=-0.2008079166798372, y=-0.18664328236896086, z=1.0, module_id=0, track_id=93),\n",
       " Hit(hit_id=470, x=-0.20472445725020277, y=0.2365970380945222, z=1.0, module_id=0, track_id=94),\n",
       " Hit(hit_id=475, x=0.39599787678340986, y=0.16595834706336815, z=1.0, module_id=0, track_id=95),\n",
       " Hit(hit_id=480, x=-0.004726986897576606, y=0.3414538056559767, z=1.0, module_id=0, track_id=96),\n",
       " Hit(hit_id=485, x=0.039754288287390874, y=-0.41316234531829654, z=1.0, module_id=0, track_id=97),\n",
       " Hit(hit_id=490, x=-0.06525196139314539, y=0.38805531846632657, z=1.0, module_id=0, track_id=98),\n",
       " Hit(hit_id=495, x=-0.08817314067948238, y=0.27341809827202396, z=1.0, module_id=0, track_id=99),\n",
       " Hit(hit_id=500, x=0.3910375858081971, y=0.3156838348569084, z=1.0, module_id=0, track_id=100),\n",
       " Hit(hit_id=505, x=-0.3037997577975121, y=-0.06740907802591638, z=1.0, module_id=0, track_id=101),\n",
       " Hit(hit_id=510, x=-0.22654491932837872, y=0.2838667753072747, z=1.0, module_id=0, track_id=102),\n",
       " Hit(hit_id=515, x=-0.40374750592432274, y=-0.35829514879662466, z=1.0, module_id=0, track_id=103),\n",
       " Hit(hit_id=520, x=0.334734231484137, y=0.2509227124882182, z=1.0, module_id=0, track_id=104),\n",
       " Hit(hit_id=525, x=0.20587619057839696, y=-0.23772298167255404, z=1.0, module_id=0, track_id=105),\n",
       " Hit(hit_id=530, x=-0.16759083310126424, y=-0.07622973491263142, z=1.0, module_id=0, track_id=106),\n",
       " Hit(hit_id=535, x=-0.41973297248902425, y=-0.19135024157836678, z=1.0, module_id=0, track_id=107),\n",
       " Hit(hit_id=540, x=0.2904300608671837, y=-0.22565544583833058, z=1.0, module_id=0, track_id=108),\n",
       " Hit(hit_id=545, x=-0.021888863964532865, y=-0.4859856870440612, z=1.0, module_id=0, track_id=109),\n",
       " Hit(hit_id=550, x=-0.21593191857635613, y=0.03902622934601699, z=1.0, module_id=0, track_id=110),\n",
       " Hit(hit_id=555, x=-0.06803809576652027, y=0.5703187312374306, z=1.0, module_id=0, track_id=111),\n",
       " Hit(hit_id=560, x=-0.06302745894604642, y=0.21203953772796727, z=1.0, module_id=0, track_id=112),\n",
       " Hit(hit_id=565, x=-0.5191122720431562, y=0.15497669776018147, z=1.0, module_id=0, track_id=113),\n",
       " Hit(hit_id=570, x=0.042171638282970415, y=-0.04072573774048353, z=1.0, module_id=0, track_id=114),\n",
       " Hit(hit_id=575, x=-0.008255756665126287, y=-0.04121079436683359, z=1.0, module_id=0, track_id=115),\n",
       " Hit(hit_id=580, x=0.4090997235421744, y=0.18406131982354798, z=1.0, module_id=0, track_id=116),\n",
       " Hit(hit_id=585, x=0.34179432962057965, y=-0.4594331150229259, z=1.0, module_id=0, track_id=117),\n",
       " Hit(hit_id=590, x=0.39795310577528503, y=-0.3914695284178241, z=1.0, module_id=0, track_id=118),\n",
       " Hit(hit_id=595, x=0.5381611538045384, y=0.08753420264349976, z=1.0, module_id=0, track_id=119),\n",
       " Hit(hit_id=600, x=0.44446477339683726, y=0.19137676934283004, z=1.0, module_id=0, track_id=120),\n",
       " Hit(hit_id=605, x=0.09214083943751959, y=0.21810068094665563, z=1.0, module_id=0, track_id=121),\n",
       " Hit(hit_id=610, x=0.09627604006348618, y=-0.3094521036496598, z=1.0, module_id=0, track_id=122),\n",
       " Hit(hit_id=615, x=-0.5185061401619333, y=-0.18685135020893365, z=1.0, module_id=0, track_id=123),\n",
       " Hit(hit_id=620, x=0.4542584130013233, y=0.31976280332986823, z=1.0, module_id=0, track_id=124),\n",
       " Hit(hit_id=625, x=-0.36927073308720865, y=-0.05122684456487577, z=1.0, module_id=0, track_id=125),\n",
       " Hit(hit_id=630, x=0.1468446540862582, y=-0.017423461965316613, z=1.0, module_id=0, track_id=126),\n",
       " Hit(hit_id=635, x=-0.016194761422083048, y=0.3074981984897467, z=1.0, module_id=0, track_id=127),\n",
       " Hit(hit_id=640, x=0.4355328692048425, y=-0.060990447721221475, z=1.0, module_id=0, track_id=128),\n",
       " Hit(hit_id=645, x=0.103462846063519, y=0.0400299167962115, z=1.0, module_id=0, track_id=129),\n",
       " Hit(hit_id=650, x=0.15568756119442761, y=0.07139004096998636, z=1.0, module_id=0, track_id=130),\n",
       " Hit(hit_id=655, x=-0.2685281853182783, y=0.06309494451492503, z=1.0, module_id=0, track_id=131),\n",
       " Hit(hit_id=660, x=0.4593848357327718, y=-0.010163329973074743, z=1.0, module_id=0, track_id=132),\n",
       " Hit(hit_id=665, x=0.14836898635314003, y=-0.24045317688655587, z=1.0, module_id=0, track_id=133),\n",
       " Hit(hit_id=670, x=-0.5018810771255559, y=-0.038097711853924424, z=1.0, module_id=0, track_id=134),\n",
       " Hit(hit_id=675, x=0.1328949962105608, y=-0.2584233422757893, z=1.0, module_id=0, track_id=135),\n",
       " Hit(hit_id=680, x=-0.34110388169416767, y=0.4566814720788013, z=1.0, module_id=0, track_id=136),\n",
       " Hit(hit_id=685, x=0.5194072708350342, y=-0.17794593576448225, z=1.0, module_id=0, track_id=137),\n",
       " Hit(hit_id=690, x=0.1529015614518755, y=0.16323575873085586, z=1.0, module_id=0, track_id=138),\n",
       " Hit(hit_id=695, x=0.2548722498640423, y=-0.5169123502698671, z=1.0, module_id=0, track_id=139),\n",
       " Hit(hit_id=700, x=-0.014885324106142557, y=-0.1321206830632251, z=1.0, module_id=0, track_id=140),\n",
       " Hit(hit_id=705, x=-0.4722910034765616, y=0.09802088536230726, z=1.0, module_id=0, track_id=141),\n",
       " Hit(hit_id=710, x=0.4204513315828656, y=0.3798923102884942, z=1.0, module_id=0, track_id=142),\n",
       " Hit(hit_id=715, x=-0.18606246304027932, y=0.48385287072743155, z=1.0, module_id=0, track_id=143),\n",
       " Hit(hit_id=720, x=0.4040694480114922, y=0.34590300162320015, z=1.0, module_id=0, track_id=144),\n",
       " Hit(hit_id=725, x=0.0937501681399461, y=-0.1374601130548611, z=1.0, module_id=0, track_id=145),\n",
       " Hit(hit_id=730, x=0.32316305346430163, y=-0.4657062959652357, z=1.0, module_id=0, track_id=146),\n",
       " Hit(hit_id=735, x=0.5144798220126015, y=0.22754461551932106, z=1.0, module_id=0, track_id=147),\n",
       " Hit(hit_id=740, x=0.3145287152593325, y=-0.12209033300417761, z=1.0, module_id=0, track_id=148),\n",
       " Hit(hit_id=745, x=-0.15145121560481692, y=0.16304281863956854, z=1.0, module_id=0, track_id=149),\n",
       " Hit(hit_id=1, x=0.22443405073709646, y=-0.24727500852065012, z=2.0, module_id=1, track_id=0),\n",
       " Hit(hit_id=6, x=0.6313334821448301, y=0.528498982816789, z=2.0, module_id=1, track_id=1),\n",
       " Hit(hit_id=11, x=0.23870491257641865, y=-0.045249288766106906, z=2.0, module_id=1, track_id=2),\n",
       " Hit(hit_id=16, x=-0.007090186270536426, y=-0.6974741615782919, z=2.0, module_id=1, track_id=3),\n",
       " Hit(hit_id=21, x=0.9191698636976192, y=0.30864534468829935, z=2.0, module_id=1, track_id=4),\n",
       " Hit(hit_id=26, x=-0.2815005388667976, y=0.582649085739302, z=2.0, module_id=1, track_id=5),\n",
       " Hit(hit_id=31, x=-1.098419129169988, y=0.1607650878778736, z=2.0, module_id=1, track_id=6),\n",
       " Hit(hit_id=36, x=0.7229979051656782, y=0.5424367890900821, z=2.0, module_id=1, track_id=7),\n",
       " Hit(hit_id=41, x=0.9220825649290376, y=0.19122115069704998, z=2.0, module_id=1, track_id=8),\n",
       " Hit(hit_id=46, x=0.31766643692200025, y=0.4045607772070058, z=2.0, module_id=1, track_id=9),\n",
       " Hit(hit_id=51, x=-0.3145422730287118, y=-0.6973716569449765, z=2.0, module_id=1, track_id=10),\n",
       " Hit(hit_id=56, x=-0.11017505274567246, y=1.1354613397919526, z=2.0, module_id=1, track_id=11),\n",
       " Hit(hit_id=61, x=0.3436363067346844, y=0.5387445872491547, z=2.0, module_id=1, track_id=12),\n",
       " Hit(hit_id=66, x=0.54671312311708, y=0.013446053347366909, z=2.0, module_id=1, track_id=13),\n",
       " Hit(hit_id=71, x=0.5227742869557587, y=0.7119097276176598, z=2.0, module_id=1, track_id=14),\n",
       " Hit(hit_id=76, x=-0.38320723110868815, y=-0.7581649602880752, z=2.0, module_id=1, track_id=15),\n",
       " Hit(hit_id=81, x=0.016835015947425477, y=0.1905459587435282, z=2.0, module_id=1, track_id=16),\n",
       " Hit(hit_id=86, x=-0.0457794828704905, y=0.3623769580914973, z=2.0, module_id=1, track_id=17),\n",
       " Hit(hit_id=91, x=0.6143491615964316, y=0.48732091157685953, z=2.0, module_id=1, track_id=18),\n",
       " Hit(hit_id=96, x=-0.09242187896834003, y=0.8403733891516733, z=2.0, module_id=1, track_id=19),\n",
       " Hit(hit_id=101, x=-0.3121398568228394, y=-0.9992646360243799, z=2.0, module_id=1, track_id=20),\n",
       " Hit(hit_id=106, x=-0.4083784890045965, y=0.5981736213761882, z=2.0, module_id=1, track_id=21),\n",
       " Hit(hit_id=111, x=-0.4766597219216667, y=0.24050472730791228, z=2.0, module_id=1, track_id=22),\n",
       " Hit(hit_id=116, x=-0.5586319135081512, y=0.07933185879320512, z=2.0, module_id=1, track_id=23),\n",
       " Hit(hit_id=121, x=-0.13577874618549146, y=-0.6981497855770115, z=2.0, module_id=1, track_id=24),\n",
       " Hit(hit_id=126, x=0.3673610942817473, y=-0.002568232478402046, z=2.0, module_id=1, track_id=25),\n",
       " Hit(hit_id=131, x=-0.8066230680255411, y=0.6111271999321013, z=2.0, module_id=1, track_id=26),\n",
       " Hit(hit_id=136, x=-0.6819081695121461, y=0.1150558812975074, z=2.0, module_id=1, track_id=27),\n",
       " Hit(hit_id=141, x=-0.16139727194196618, y=-0.5211858326161493, z=2.0, module_id=1, track_id=28),\n",
       " Hit(hit_id=146, x=-0.06438818534876727, y=-0.48025886913156174, z=2.0, module_id=1, track_id=29),\n",
       " Hit(hit_id=151, x=-0.6779631604180726, y=0.38352208522461034, z=2.0, module_id=1, track_id=30),\n",
       " Hit(hit_id=156, x=0.37932000103852115, y=-0.3938861659801635, z=2.0, module_id=1, track_id=31),\n",
       " Hit(hit_id=161, x=-0.31654021300843643, y=0.15070751003187885, z=2.0, module_id=1, track_id=32),\n",
       " Hit(hit_id=166, x=1.0161270607136814, y=-0.4799044441519078, z=2.0, module_id=1, track_id=33),\n",
       " Hit(hit_id=171, x=-0.09175326800843128, y=-0.5412612088861347, z=2.0, module_id=1, track_id=34),\n",
       " Hit(hit_id=176, x=-1.070077989923684, y=-0.20473448492774787, z=2.0, module_id=1, track_id=35),\n",
       " Hit(hit_id=181, x=0.6180814584532364, y=-0.6834668515411668, z=2.0, module_id=1, track_id=36),\n",
       " Hit(hit_id=186, x=0.21217367554625446, y=1.1226566788466261, z=2.0, module_id=1, track_id=37),\n",
       " Hit(hit_id=191, x=-0.6602064764674718, y=-0.8683284554461211, z=2.0, module_id=1, track_id=38),\n",
       " Hit(hit_id=196, x=-1.0469966891327516, y=0.456636620286953, z=2.0, module_id=1, track_id=39),\n",
       " Hit(hit_id=201, x=-1.1160112745779904, y=0.08012937833290049, z=2.0, module_id=1, track_id=40),\n",
       " Hit(hit_id=206, x=-0.8625672115647196, y=0.1027133297693638, z=2.0, module_id=1, track_id=41),\n",
       " Hit(hit_id=211, x=-0.105570228801998, y=0.800949252884506, z=2.0, module_id=1, track_id=42),\n",
       " Hit(hit_id=216, x=0.8765380855430482, y=-0.34156374460840533, z=2.0, module_id=1, track_id=43),\n",
       " Hit(hit_id=221, x=-0.4076708709048861, y=0.4775712331045243, z=2.0, module_id=1, track_id=44),\n",
       " Hit(hit_id=226, x=-0.5881028032899697, y=-0.5443642036433476, z=2.0, module_id=1, track_id=45),\n",
       " Hit(hit_id=231, x=-0.17896577018221846, y=0.32344490804652853, z=2.0, module_id=1, track_id=46),\n",
       " Hit(hit_id=236, x=-0.08705450317026169, y=0.9608858781321624, z=2.0, module_id=1, track_id=47),\n",
       " Hit(hit_id=241, x=-0.660316285160975, y=0.1955712699072916, z=2.0, module_id=1, track_id=48),\n",
       " Hit(hit_id=246, x=-0.519235837860429, y=-0.3366266898914992, z=2.0, module_id=1, track_id=49),\n",
       " Hit(hit_id=251, x=-1.0959497452411424, y=0.17023445656410363, z=2.0, module_id=1, track_id=50),\n",
       " Hit(hit_id=256, x=0.3449070006945784, y=-0.05028781495637719, z=2.0, module_id=1, track_id=51),\n",
       " Hit(hit_id=261, x=0.5270809993376716, y=-0.867098301739018, z=2.0, module_id=1, track_id=52),\n",
       " Hit(hit_id=266, x=-0.10978090465258668, y=-0.05245269690020657, z=2.0, module_id=1, track_id=53),\n",
       " Hit(hit_id=271, x=-0.1753332858920393, y=0.15571136371706645, z=2.0, module_id=1, track_id=54),\n",
       " Hit(hit_id=276, x=-0.6281235309199811, y=-0.5114381228242586, z=2.0, module_id=1, track_id=55),\n",
       " Hit(hit_id=281, x=0.09903371214492837, y=0.9859530797058479, z=2.0, module_id=1, track_id=56),\n",
       " Hit(hit_id=286, x=-0.8881667450255892, y=0.25098260842930403, z=2.0, module_id=1, track_id=57),\n",
       " Hit(hit_id=291, x=0.7047554620540473, y=-0.0796539086738567, z=2.0, module_id=1, track_id=58),\n",
       " Hit(hit_id=296, x=0.029805154810414868, y=-0.6811000142433904, z=2.0, module_id=1, track_id=59),\n",
       " Hit(hit_id=301, x=0.6167568286956802, y=0.032704651155206085, z=2.0, module_id=1, track_id=60),\n",
       " Hit(hit_id=306, x=-1.0054578576869702, y=-0.021669948284805837, z=2.0, module_id=1, track_id=61),\n",
       " Hit(hit_id=311, x=0.5709702136100834, y=0.9756483678160625, z=2.0, module_id=1, track_id=62),\n",
       " Hit(hit_id=316, x=-0.7306424833742707, y=-0.09735146522894227, z=2.0, module_id=1, track_id=63),\n",
       " Hit(hit_id=321, x=-1.083619764334132, y=0.13271323930899992, z=2.0, module_id=1, track_id=64),\n",
       " Hit(hit_id=326, x=0.2508627126799008, y=-0.3179056222663291, z=2.0, module_id=1, track_id=65),\n",
       " Hit(hit_id=331, x=-0.17640853636345813, y=0.7845138868610544, z=2.0, module_id=1, track_id=66),\n",
       " Hit(hit_id=336, x=-0.44765453117342097, y=0.42821568751222056, z=2.0, module_id=1, track_id=67),\n",
       " Hit(hit_id=341, x=-1.0714532660192557, y=0.34498171300563985, z=2.0, module_id=1, track_id=68),\n",
       " Hit(hit_id=346, x=-0.6276034040039744, y=0.7421225843122957, z=2.0, module_id=1, track_id=69),\n",
       " Hit(hit_id=351, x=-0.8983937810403383, y=0.288947772572605, z=2.0, module_id=1, track_id=70),\n",
       " Hit(hit_id=356, x=0.9401288012985254, y=-0.438285972557773, z=2.0, module_id=1, track_id=71),\n",
       " Hit(hit_id=361, x=-0.07083725633338768, y=-1.004837434098428, z=2.0, module_id=1, track_id=72),\n",
       " Hit(hit_id=366, x=0.3393551058156197, y=-0.3086416047919892, z=2.0, module_id=1, track_id=73),\n",
       " Hit(hit_id=371, x=-0.05094598147546727, y=-0.6394125164381352, z=2.0, module_id=1, track_id=74),\n",
       " Hit(hit_id=376, x=-0.2895156954783194, y=1.1028291101507361, z=2.0, module_id=1, track_id=75),\n",
       " Hit(hit_id=381, x=-0.7202686369505433, y=0.8890240202381104, z=2.0, module_id=1, track_id=76),\n",
       " Hit(hit_id=386, x=-0.40591728540027106, y=0.16691519270642435, z=2.0, module_id=1, track_id=77),\n",
       " Hit(hit_id=391, x=-0.5142551700324914, y=0.19858448666241468, z=2.0, module_id=1, track_id=78),\n",
       " Hit(hit_id=396, x=0.7598816609767562, y=-0.46415173669548043, z=2.0, module_id=1, track_id=79),\n",
       " Hit(hit_id=401, x=0.15092439785058487, y=-0.22454883026259395, z=2.0, module_id=1, track_id=80),\n",
       " Hit(hit_id=406, x=0.3993385738244435, y=0.26957517512396034, z=2.0, module_id=1, track_id=81),\n",
       " Hit(hit_id=411, x=-0.11592180669088868, y=-0.7003736229268958, z=2.0, module_id=1, track_id=82),\n",
       " Hit(hit_id=416, x=-0.46909774710250335, y=0.12950875204583445, z=2.0, module_id=1, track_id=83),\n",
       " Hit(hit_id=421, x=0.6749868400195151, y=0.08710937824843333, z=2.0, module_id=1, track_id=84),\n",
       " Hit(hit_id=426, x=-0.2526958896253298, y=-1.0940888628326653, z=2.0, module_id=1, track_id=85),\n",
       " Hit(hit_id=431, x=-0.5276229603372702, y=0.4671940301385929, z=2.0, module_id=1, track_id=86),\n",
       " Hit(hit_id=436, x=0.4074912331325248, y=-0.43648149459387386, z=2.0, module_id=1, track_id=87),\n",
       " Hit(hit_id=441, x=-0.08586501097537683, y=1.0537846265900404, z=2.0, module_id=1, track_id=88),\n",
       " Hit(hit_id=446, x=0.023653018285878128, y=-0.45881589363591496, z=2.0, module_id=1, track_id=89),\n",
       " Hit(hit_id=451, x=-0.9569330322913823, y=-0.07475638494289748, z=2.0, module_id=1, track_id=90),\n",
       " Hit(hit_id=456, x=0.05586512490474967, y=-0.7559394173324442, z=2.0, module_id=1, track_id=91),\n",
       " Hit(hit_id=461, x=0.2584308562133089, y=-0.7358533812449287, z=2.0, module_id=1, track_id=92),\n",
       " Hit(hit_id=466, x=-0.4016158333596744, y=-0.3732865647379217, z=2.0, module_id=1, track_id=93),\n",
       " Hit(hit_id=471, x=-0.40944891450040555, y=0.4731940761890444, z=2.0, module_id=1, track_id=94),\n",
       " Hit(hit_id=476, x=0.7919957535668197, y=0.3319166941267363, z=2.0, module_id=1, track_id=95),\n",
       " Hit(hit_id=481, x=-0.009453973795153212, y=0.6829076113119534, z=2.0, module_id=1, track_id=96),\n",
       " Hit(hit_id=486, x=0.07950857657478175, y=-0.8263246906365931, z=2.0, module_id=1, track_id=97),\n",
       " Hit(hit_id=491, x=-0.13050392278629078, y=0.7761106369326531, z=2.0, module_id=1, track_id=98),\n",
       " Hit(hit_id=496, x=-0.17634628135896477, y=0.5468361965440479, z=2.0, module_id=1, track_id=99),\n",
       " Hit(hit_id=501, x=0.7820751716163942, y=0.6313676697138167, z=2.0, module_id=1, track_id=100),\n",
       " Hit(hit_id=506, x=-0.6075995155950242, y=-0.13481815605183275, z=2.0, module_id=1, track_id=101),\n",
       " Hit(hit_id=511, x=-0.45308983865675745, y=0.5677335506145494, z=2.0, module_id=1, track_id=102),\n",
       " Hit(hit_id=516, x=-0.8074950118486455, y=-0.7165902975932493, z=2.0, module_id=1, track_id=103),\n",
       " Hit(hit_id=521, x=0.669468462968274, y=0.5018454249764364, z=2.0, module_id=1, track_id=104),\n",
       " Hit(hit_id=526, x=0.4117523811567939, y=-0.4754459633451081, z=2.0, module_id=1, track_id=105),\n",
       " Hit(hit_id=531, x=-0.3351816662025285, y=-0.15245946982526284, z=2.0, module_id=1, track_id=106),\n",
       " Hit(hit_id=536, x=-0.8394659449780485, y=-0.38270048315673355, z=2.0, module_id=1, track_id=107),\n",
       " Hit(hit_id=541, x=0.5808601217343674, y=-0.45131089167666116, z=2.0, module_id=1, track_id=108),\n",
       " Hit(hit_id=546, x=-0.04377772792906573, y=-0.9719713740881224, z=2.0, module_id=1, track_id=109),\n",
       " Hit(hit_id=551, x=-0.43186383715271226, y=0.07805245869203398, z=2.0, module_id=1, track_id=110),\n",
       " Hit(hit_id=556, x=-0.13607619153304054, y=1.1406374624748612, z=2.0, module_id=1, track_id=111),\n",
       " Hit(hit_id=561, x=-0.12605491789209283, y=0.42407907545593454, z=2.0, module_id=1, track_id=112),\n",
       " Hit(hit_id=566, x=-1.0382245440863125, y=0.30995339552036294, z=2.0, module_id=1, track_id=113),\n",
       " Hit(hit_id=571, x=0.08434327656594083, y=-0.08145147548096705, z=2.0, module_id=1, track_id=114),\n",
       " Hit(hit_id=576, x=-0.016511513330252574, y=-0.08242158873366719, z=2.0, module_id=1, track_id=115),\n",
       " Hit(hit_id=581, x=0.8181994470843488, y=0.36812263964709596, z=2.0, module_id=1, track_id=116),\n",
       " Hit(hit_id=586, x=0.6835886592411593, y=-0.9188662300458518, z=2.0, module_id=1, track_id=117),\n",
       " Hit(hit_id=591, x=0.7959062115505701, y=-0.7829390568356482, z=2.0, module_id=1, track_id=118),\n",
       " Hit(hit_id=596, x=1.0763223076090769, y=0.17506840528699952, z=2.0, module_id=1, track_id=119),\n",
       " Hit(hit_id=601, x=0.8889295467936745, y=0.3827535386856601, z=2.0, module_id=1, track_id=120),\n",
       " Hit(hit_id=606, x=0.18428167887503918, y=0.43620136189331127, z=2.0, module_id=1, track_id=121),\n",
       " Hit(hit_id=611, x=0.19255208012697236, y=-0.6189042072993196, z=2.0, module_id=1, track_id=122),\n",
       " Hit(hit_id=616, x=-1.0370122803238666, y=-0.3737027004178673, z=2.0, module_id=1, track_id=123),\n",
       " Hit(hit_id=621, x=0.9085168260026466, y=0.6395256066597365, z=2.0, module_id=1, track_id=124),\n",
       " Hit(hit_id=626, x=-0.7385414661744173, y=-0.10245368912975154, z=2.0, module_id=1, track_id=125),\n",
       " Hit(hit_id=631, x=0.2936893081725164, y=-0.034846923930633225, z=2.0, module_id=1, track_id=126),\n",
       " Hit(hit_id=636, x=-0.032389522844166095, y=0.6149963969794934, z=2.0, module_id=1, track_id=127),\n",
       " Hit(hit_id=641, x=0.871065738409685, y=-0.12198089544244295, z=2.0, module_id=1, track_id=128),\n",
       " Hit(hit_id=646, x=0.206925692127038, y=0.080059833592423, z=2.0, module_id=1, track_id=129),\n",
       " Hit(hit_id=651, x=0.31137512238885523, y=0.14278008193997271, z=2.0, module_id=1, track_id=130),\n",
       " Hit(hit_id=656, x=-0.5370563706365566, y=0.12618988902985007, z=2.0, module_id=1, track_id=131),\n",
       " Hit(hit_id=661, x=0.9187696714655436, y=-0.020326659946149486, z=2.0, module_id=1, track_id=132),\n",
       " Hit(hit_id=666, x=0.29673797270628005, y=-0.48090635377311175, z=2.0, module_id=1, track_id=133),\n",
       " Hit(hit_id=671, x=-1.0037621542511117, y=-0.07619542370784885, z=2.0, module_id=1, track_id=134),\n",
       " Hit(hit_id=676, x=0.2657899924211216, y=-0.5168466845515786, z=2.0, module_id=1, track_id=135),\n",
       " Hit(hit_id=681, x=-0.6822077633883353, y=0.9133629441576026, z=2.0, module_id=1, track_id=136),\n",
       " Hit(hit_id=686, x=1.0388145416700685, y=-0.3558918715289645, z=2.0, module_id=1, track_id=137),\n",
       " Hit(hit_id=691, x=0.305803122903751, y=0.3264715174617117, z=2.0, module_id=1, track_id=138),\n",
       " Hit(hit_id=696, x=0.5097444997280846, y=-1.0338247005397343, z=2.0, module_id=1, track_id=139),\n",
       " Hit(hit_id=701, x=-0.029770648212285113, y=-0.2642413661264502, z=2.0, module_id=1, track_id=140),\n",
       " Hit(hit_id=706, x=-0.9445820069531232, y=0.1960417707246145, z=2.0, module_id=1, track_id=141),\n",
       " Hit(hit_id=711, x=0.8409026631657311, y=0.7597846205769884, z=2.0, module_id=1, track_id=142),\n",
       " Hit(hit_id=716, x=-0.37212492608055864, y=0.9677057414548631, z=2.0, module_id=1, track_id=143),\n",
       " Hit(hit_id=721, x=0.8081388960229844, y=0.6918060032464003, z=2.0, module_id=1, track_id=144),\n",
       " Hit(hit_id=726, x=0.1875003362798922, y=-0.2749202261097222, z=2.0, module_id=1, track_id=145),\n",
       " Hit(hit_id=731, x=0.6463261069286033, y=-0.9314125919304714, z=2.0, module_id=1, track_id=146),\n",
       " Hit(hit_id=736, x=1.028959644025203, y=0.45508923103864213, z=2.0, module_id=1, track_id=147),\n",
       " Hit(hit_id=741, x=0.629057430518665, y=-0.24418066600835522, z=2.0, module_id=1, track_id=148),\n",
       " Hit(hit_id=746, x=-0.30290243120963384, y=0.3260856372791371, z=2.0, module_id=1, track_id=149),\n",
       " Hit(hit_id=2, x=0.33665107610564465, y=-0.37091251278097515, z=3.0, module_id=2, track_id=0),\n",
       " Hit(hit_id=7, x=0.9470002232172451, y=0.7927484742251834, z=3.0, module_id=2, track_id=1),\n",
       " Hit(hit_id=12, x=0.35805736886462797, y=-0.06787393314916035, z=3.0, module_id=2, track_id=2),\n",
       " Hit(hit_id=17, x=-0.010635279405804639, y=-1.0462112423674377, z=3.0, module_id=2, track_id=3),\n",
       " Hit(hit_id=22, x=1.378754795546429, y=0.46296801703244905, z=3.0, module_id=2, track_id=4),\n",
       " Hit(hit_id=27, x=-0.42225080830019646, y=0.8739736286089529, z=3.0, module_id=2, track_id=5),\n",
       " Hit(hit_id=32, x=-1.647628693754982, y=0.24114763181681043, z=3.0, module_id=2, track_id=6),\n",
       " Hit(hit_id=37, x=1.0844968577485172, y=0.8136551836351231, z=3.0, module_id=2, track_id=7),\n",
       " Hit(hit_id=42, x=1.3831238473935563, y=0.286831726045575, z=3.0, module_id=2, track_id=8),\n",
       " Hit(hit_id=47, x=0.4764996553830003, y=0.6068411658105086, z=3.0, module_id=2, track_id=9),\n",
       " Hit(hit_id=52, x=-0.47181340954306766, y=-1.046057485417465, z=3.0, module_id=2, track_id=10),\n",
       " Hit(hit_id=57, x=-0.1652625791185087, y=1.703192009687929, z=3.0, module_id=2, track_id=11),\n",
       " Hit(hit_id=62, x=0.5154544601020267, y=0.8081168808737322, z=3.0, module_id=2, track_id=12),\n",
       " Hit(hit_id=67, x=0.8200696846756201, y=0.020169080021050365, z=3.0, module_id=2, track_id=13),\n",
       " Hit(hit_id=72, x=0.7841614304336381, y=1.0678645914264897, z=3.0, module_id=2, track_id=14),\n",
       " Hit(hit_id=77, x=-0.5748108466630323, y=-1.137247440432113, z=3.0, module_id=2, track_id=15),\n",
       " Hit(hit_id=82, x=0.02525252392113822, y=0.28581893811529235, z=3.0, module_id=2, track_id=16),\n",
       " Hit(hit_id=87, x=-0.06866922430573574, y=0.5435654371372459, z=3.0, module_id=2, track_id=17),\n",
       " Hit(hit_id=92, x=0.9215237423946473, y=0.7309813673652892, z=3.0, module_id=2, track_id=18),\n",
       " Hit(hit_id=97, x=-0.13863281845251005, y=1.26056008372751, z=3.0, module_id=2, track_id=19),\n",
       " Hit(hit_id=102, x=-0.46820978523425905, y=-1.49889695403657, z=3.0, module_id=2, track_id=20),\n",
       " Hit(hit_id=107, x=-0.6125677335068949, y=0.8972604320642824, z=3.0, module_id=2, track_id=21),\n",
       " Hit(hit_id=112, x=-0.7149895828825, y=0.36075709096186837, z=3.0, module_id=2, track_id=22),\n",
       " Hit(hit_id=117, x=-0.8379478702622267, y=0.11899778818980766, z=3.0, module_id=2, track_id=23),\n",
       " Hit(hit_id=122, x=-0.2036681192782372, y=-1.047224678365517, z=3.0, module_id=2, track_id=24),\n",
       " Hit(hit_id=127, x=0.5510416414226209, y=-0.0038523487176030688, z=3.0, module_id=2, track_id=25),\n",
       " Hit(hit_id=132, x=-1.2099346020383115, y=0.916690799898152, z=3.0, module_id=2, track_id=26),\n",
       " Hit(hit_id=137, x=-1.022862254268219, y=0.1725838219462611, z=3.0, module_id=2, track_id=27),\n",
       " Hit(hit_id=142, x=-0.24209590791294927, y=-0.7817787489242238, z=3.0, module_id=2, track_id=28),\n",
       " Hit(hit_id=147, x=-0.0965822780231509, y=-0.7203883036973426, z=3.0, module_id=2, track_id=29),\n",
       " Hit(hit_id=152, x=-1.0169447406271088, y=0.5752831278369155, z=3.0, module_id=2, track_id=30),\n",
       " Hit(hit_id=157, x=0.5689800015577817, y=-0.5908292489702454, z=3.0, module_id=2, track_id=31),\n",
       " Hit(hit_id=162, x=-0.4748103195126546, y=0.22606126504781823, z=3.0, module_id=2, track_id=32),\n",
       " Hit(hit_id=167, x=1.5241905910705222, y=-0.7198566662278617, z=3.0, module_id=2, track_id=33),\n",
       " Hit(hit_id=172, x=-0.1376299020126469, y=-0.8118918133292021, z=3.0, module_id=2, track_id=34),\n",
       " Hit(hit_id=177, x=-1.605116984885526, y=-0.3071017273916218, z=3.0, module_id=2, track_id=35),\n",
       " Hit(hit_id=182, x=0.9271221876798545, y=-1.0252002773117501, z=3.0, module_id=2, track_id=36),\n",
       " Hit(hit_id=187, x=0.3182605133193817, y=1.6839850182699392, z=3.0, module_id=2, track_id=37),\n",
       " Hit(hit_id=192, x=-0.9903097147012078, y=-1.3024926831691817, z=3.0, module_id=2, track_id=38),\n",
       " Hit(hit_id=197, x=-1.5704950336991275, y=0.6849549304304295, z=3.0, module_id=2, track_id=39),\n",
       " Hit(hit_id=202, x=-1.6740169118669854, y=0.1201940674993507, z=3.0, module_id=2, track_id=40),\n",
       " Hit(hit_id=207, x=-1.2938508173470795, y=0.1540699946540457, z=3.0, module_id=2, track_id=41),\n",
       " Hit(hit_id=212, x=-0.158355343202997, y=1.2014238793267589, z=3.0, module_id=2, track_id=42),\n",
       " Hit(hit_id=217, x=1.3148071283145724, y=-0.512345616912608, z=3.0, module_id=2, track_id=43),\n",
       " Hit(hit_id=222, x=-0.6115063063573292, y=0.7163568496567866, z=3.0, module_id=2, track_id=44),\n",
       " Hit(hit_id=227, x=-0.8821542049349546, y=-0.8165463054650214, z=3.0, module_id=2, track_id=45),\n",
       " Hit(hit_id=232, x=-0.2684486552733277, y=0.4851673620697928, z=3.0, module_id=2, track_id=46),\n",
       " Hit(hit_id=237, x=-0.13058175475539252, y=1.4413288171982435, z=3.0, module_id=2, track_id=47),\n",
       " Hit(hit_id=242, x=-0.9904744277414624, y=0.29335690486093735, z=3.0, module_id=2, track_id=48),\n",
       " Hit(hit_id=247, x=-0.7788537567906436, y=-0.5049400348372488, z=3.0, module_id=2, track_id=49),\n",
       " Hit(hit_id=252, x=-1.6439246178617137, y=0.25535168484615545, z=3.0, module_id=2, track_id=50),\n",
       " Hit(hit_id=257, x=0.5173605010418676, y=-0.07543172243456578, z=3.0, module_id=2, track_id=51),\n",
       " Hit(hit_id=262, x=0.7906214990065074, y=-1.300647452608527, z=3.0, module_id=2, track_id=52),\n",
       " Hit(hit_id=267, x=-0.16467135697888, y=-0.07867904535030985, z=3.0, module_id=2, track_id=53),\n",
       " Hit(hit_id=272, x=-0.26299992883805895, y=0.2335670455755997, z=3.0, module_id=2, track_id=54),\n",
       " Hit(hit_id=277, x=-0.9421852963799715, y=-0.7671571842363878, z=3.0, module_id=2, track_id=55),\n",
       " Hit(hit_id=282, x=0.14855056821739257, y=1.4789296195587718, z=3.0, module_id=2, track_id=56),\n",
       " Hit(hit_id=287, x=-1.332250117538384, y=0.3764739126439561, z=3.0, module_id=2, track_id=57),\n",
       " Hit(hit_id=292, x=1.057133193081071, y=-0.11948086301078505, z=3.0, module_id=2, track_id=58),\n",
       " Hit(hit_id=297, x=0.044707732215622305, y=-1.0216500213650856, z=3.0, module_id=2, track_id=59),\n",
       " Hit(hit_id=302, x=0.92513524304352, y=0.04905697673280912, z=3.0, module_id=2, track_id=60),\n",
       " Hit(hit_id=307, x=-1.5081867865304555, y=-0.03250492242720876, z=3.0, module_id=2, track_id=61),\n",
       " Hit(hit_id=312, x=0.856455320415125, y=1.4634725517240936, z=3.0, module_id=2, track_id=62),\n",
       " Hit(hit_id=317, x=-1.0959637250614063, y=-0.14602719784341342, z=3.0, module_id=2, track_id=63),\n",
       " Hit(hit_id=322, x=-1.625429646501198, y=0.19906985896349985, z=3.0, module_id=2, track_id=64),\n",
       " Hit(hit_id=327, x=0.3762940690198512, y=-0.47685843339949363, z=3.0, module_id=2, track_id=65),\n",
       " Hit(hit_id=332, x=-0.2646128045451872, y=1.1767708302915816, z=3.0, module_id=2, track_id=66),\n",
       " Hit(hit_id=337, x=-0.6714817967601314, y=0.6423235312683307, z=3.0, module_id=2, track_id=67),\n",
       " Hit(hit_id=342, x=-1.6071798990288835, y=0.5174725695084598, z=3.0, module_id=2, track_id=68),\n",
       " Hit(hit_id=347, x=-0.9414051060059615, y=1.1131838764684436, z=3.0, module_id=2, track_id=69),\n",
       " Hit(hit_id=352, x=-1.3475906715605073, y=0.4334216588589075, z=3.0, module_id=2, track_id=70),\n",
       " Hit(hit_id=357, x=1.410193201947788, y=-0.6574289588366595, z=3.0, module_id=2, track_id=71),\n",
       " Hit(hit_id=362, x=-0.10625588450008151, y=-1.5072561511476419, z=3.0, module_id=2, track_id=72),\n",
       " Hit(hit_id=367, x=0.5090326587234295, y=-0.4629624071879837, z=3.0, module_id=2, track_id=73),\n",
       " Hit(hit_id=372, x=-0.0764189722132009, y=-0.9591187746572027, z=3.0, module_id=2, track_id=74),\n",
       " Hit(hit_id=377, x=-0.4342735432174791, y=1.6542436652261039, z=3.0, module_id=2, track_id=75),\n",
       " Hit(hit_id=382, x=-1.080402955425815, y=1.3335360303571657, z=3.0, module_id=2, track_id=76),\n",
       " Hit(hit_id=387, x=-0.6088759281004065, y=0.2503727890596365, z=3.0, module_id=2, track_id=77),\n",
       " Hit(hit_id=392, x=-0.7713827550487371, y=0.297876729993622, z=3.0, module_id=2, track_id=78),\n",
       " Hit(hit_id=397, x=1.1398224914651345, y=-0.6962276050432207, z=3.0, module_id=2, track_id=79),\n",
       " Hit(hit_id=402, x=0.22638659677587725, y=-0.33682324539389086, z=3.0, module_id=2, track_id=80),\n",
       " Hit(hit_id=407, x=0.5990078607366652, y=0.40436276268594057, z=3.0, module_id=2, track_id=81),\n",
       " Hit(hit_id=412, x=-0.17388271003633304, y=-1.0505604343903436, z=3.0, module_id=2, track_id=82),\n",
       " Hit(hit_id=417, x=-0.703646620653755, y=0.19426312806875168, z=3.0, module_id=2, track_id=83),\n",
       " Hit(hit_id=422, x=1.0124802600292726, y=0.13066406737265, z=3.0, module_id=2, track_id=84),\n",
       " Hit(hit_id=427, x=-0.37904383443799466, y=-1.6411332942489978, z=3.0, module_id=2, track_id=85),\n",
       " Hit(hit_id=432, x=-0.7914344405059054, y=0.7007910452078894, z=3.0, module_id=2, track_id=86),\n",
       " Hit(hit_id=437, x=0.6112368496987871, y=-0.6547222418908107, z=3.0, module_id=2, track_id=87),\n",
       " Hit(hit_id=442, x=-0.12879751646306525, y=1.5806769398850606, z=3.0, module_id=2, track_id=88),\n",
       " Hit(hit_id=447, x=0.035479527428817194, y=-0.6882238404538725, z=3.0, module_id=2, track_id=89),\n",
       " Hit(hit_id=452, x=-1.4353995484370734, y=-0.11213457741434621, z=3.0, module_id=2, track_id=90),\n",
       " Hit(hit_id=457, x=0.08379768735712452, y=-1.1339091259986662, z=3.0, module_id=2, track_id=91),\n",
       " Hit(hit_id=462, x=0.3876462843199634, y=-1.1037800718673931, z=3.0, module_id=2, track_id=92),\n",
       " Hit(hit_id=467, x=-0.6024237500395115, y=-0.5599298471068826, z=3.0, module_id=2, track_id=93),\n",
       " Hit(hit_id=472, x=-0.6141733717506084, y=0.7097911142835667, z=3.0, module_id=2, track_id=94),\n",
       " Hit(hit_id=477, x=1.1879936303502296, y=0.49787504119010445, z=3.0, module_id=2, track_id=95),\n",
       " Hit(hit_id=482, x=-0.014180960692729819, y=1.02436141696793, z=3.0, module_id=2, track_id=96),\n",
       " Hit(hit_id=487, x=0.11926286486217262, y=-1.2394870359548897, z=3.0, module_id=2, track_id=97),\n",
       " Hit(hit_id=492, x=-0.19575588417943615, y=1.1641659553989796, z=3.0, module_id=2, track_id=98),\n",
       " Hit(hit_id=497, x=-0.26451942203844714, y=0.8202542948160718, z=3.0, module_id=2, track_id=99),\n",
       " Hit(hit_id=502, x=1.1731127574245912, y=0.9470515045707252, z=3.0, module_id=2, track_id=100),\n",
       " Hit(hit_id=507, x=-0.9113992733925363, y=-0.20222723407774915, z=3.0, module_id=2, track_id=101),\n",
       " Hit(hit_id=512, x=-0.6796347579851362, y=0.8516003259218242, z=3.0, module_id=2, track_id=102),\n",
       " Hit(hit_id=517, x=-1.2112425177729682, y=-1.074885446389874, z=3.0, module_id=2, track_id=103),\n",
       " Hit(hit_id=522, x=1.0042026944524112, y=0.7527681374646547, z=3.0, module_id=2, track_id=104),\n",
       " Hit(hit_id=527, x=0.6176285717351908, y=-0.713168945017662, z=3.0, module_id=2, track_id=105),\n",
       " Hit(hit_id=532, x=-0.5027724993037929, y=-0.2286892047378943, z=3.0, module_id=2, track_id=106),\n",
       " Hit(hit_id=537, x=-1.2591989174670728, y=-0.5740507247351003, z=3.0, module_id=2, track_id=107),\n",
       " Hit(hit_id=542, x=0.8712901826015512, y=-0.6769663375149918, z=3.0, module_id=2, track_id=108),\n",
       " Hit(hit_id=547, x=-0.0656665918935986, y=-1.4579570611321835, z=3.0, module_id=2, track_id=109),\n",
       " Hit(hit_id=552, x=-0.6477957557290684, y=0.11707868803805095, z=3.0, module_id=2, track_id=110),\n",
       " Hit(hit_id=557, x=-0.20411428729956085, y=1.710956193712292, z=3.0, module_id=2, track_id=111),\n",
       " Hit(hit_id=562, x=-0.18908237683813925, y=0.6361186131839018, z=3.0, module_id=2, track_id=112),\n",
       " Hit(hit_id=567, x=-1.557336816129469, y=0.4649300932805444, z=3.0, module_id=2, track_id=113),\n",
       " Hit(hit_id=572, x=0.12651491484891125, y=-0.1221772132214506, z=3.0, module_id=2, track_id=114),\n",
       " Hit(hit_id=577, x=-0.024767269995378864, y=-0.1236323831005008, z=3.0, module_id=2, track_id=115),\n",
       " Hit(hit_id=582, x=1.2272991706265233, y=0.5521839594706439, z=3.0, module_id=2, track_id=116),\n",
       " Hit(hit_id=587, x=1.025382988861739, y=-1.3782993450687775, z=3.0, module_id=2, track_id=117),\n",
       " Hit(hit_id=592, x=1.1938593173258552, y=-1.1744085852534725, z=3.0, module_id=2, track_id=118),\n",
       " Hit(hit_id=597, x=1.614483461413615, y=0.2626026079304993, z=3.0, module_id=2, track_id=119),\n",
       " Hit(hit_id=602, x=1.3333943201905119, y=0.5741303080284901, z=3.0, module_id=2, track_id=120),\n",
       " Hit(hit_id=607, x=0.27642251831255876, y=0.654302042839967, z=3.0, module_id=2, track_id=121),\n",
       " Hit(hit_id=612, x=0.28882812019045856, y=-0.9283563109489793, z=3.0, module_id=2, track_id=122),\n",
       " Hit(hit_id=617, x=-1.5555184204858, y=-0.560554050626801, z=3.0, module_id=2, track_id=123),\n",
       " Hit(hit_id=622, x=1.36277523900397, y=0.9592884099896049, z=3.0, module_id=2, track_id=124),\n",
       " Hit(hit_id=627, x=-1.1078121992616259, y=-0.1536805336946273, z=3.0, module_id=2, track_id=125),\n",
       " Hit(hit_id=632, x=0.4405339622587746, y=-0.05227038589594984, z=3.0, module_id=2, track_id=126),\n",
       " Hit(hit_id=637, x=-0.048584284266249146, y=0.92249459546924, z=3.0, module_id=2, track_id=127),\n",
       " Hit(hit_id=642, x=1.3065986076145275, y=-0.1829713431636644, z=3.0, module_id=2, track_id=128),\n",
       " Hit(hit_id=647, x=0.31038853819055706, y=0.1200897503886345, z=3.0, module_id=2, track_id=129),\n",
       " Hit(hit_id=652, x=0.46706268358328284, y=0.2141701229099591, z=3.0, module_id=2, track_id=130),\n",
       " Hit(hit_id=657, x=-0.805584555954835, y=0.18928483354477507, z=3.0, module_id=2, track_id=131),\n",
       " Hit(hit_id=662, x=1.3781545071983152, y=-0.03048998991922423, z=3.0, module_id=2, track_id=132),\n",
       " Hit(hit_id=667, x=0.4451069590594201, y=-0.7213595306596677, z=3.0, module_id=2, track_id=133),\n",
       " Hit(hit_id=672, x=-1.5056432313766677, y=-0.11429313556177327, z=3.0, module_id=2, track_id=134),\n",
       " Hit(hit_id=677, x=0.3986849886316824, y=-0.7752700268273678, z=3.0, module_id=2, track_id=135),\n",
       " Hit(hit_id=682, x=-1.023311645082503, y=1.3700444162364038, z=3.0, module_id=2, track_id=136),\n",
       " Hit(hit_id=687, x=1.5582218125051026, y=-0.5338378072934468, z=3.0, module_id=2, track_id=137),\n",
       " Hit(hit_id=692, x=0.45870468435562656, y=0.4897072761925676, z=3.0, module_id=2, track_id=138),\n",
       " Hit(hit_id=697, x=0.764616749592127, y=-1.5507370508096014, z=3.0, module_id=2, track_id=139),\n",
       " Hit(hit_id=702, x=-0.044655972318427675, y=-0.3963620491896754, z=3.0, module_id=2, track_id=140),\n",
       " Hit(hit_id=707, x=-1.4168730104296847, y=0.2940626560869217, z=3.0, module_id=2, track_id=141),\n",
       " Hit(hit_id=712, x=1.2613539947485968, y=1.1396769308654826, z=3.0, module_id=2, track_id=142),\n",
       " Hit(hit_id=717, x=-0.5581873891208379, y=1.4515586121822945, z=3.0, module_id=2, track_id=143),\n",
       " Hit(hit_id=722, x=1.2122083440344766, y=1.0377090048696005, z=3.0, module_id=2, track_id=144),\n",
       " Hit(hit_id=727, x=0.2812505044198383, y=-0.41238033916458333, z=3.0, module_id=2, track_id=145),\n",
       " Hit(hit_id=732, x=0.9694891603929048, y=-1.397118887895707, z=3.0, module_id=2, track_id=146),\n",
       " Hit(hit_id=737, x=1.5434394660378041, y=0.6826338465579631, z=3.0, module_id=2, track_id=147),\n",
       " Hit(hit_id=742, x=0.9435861457779976, y=-0.36627099901253285, z=3.0, module_id=2, track_id=148),\n",
       " Hit(hit_id=747, x=-0.4543536468144508, y=0.4891284559187056, z=3.0, module_id=2, track_id=149),\n",
       " Hit(hit_id=3, x=0.4488681014741929, y=-0.49455001704130025, z=4.0, module_id=3, track_id=0),\n",
       " Hit(hit_id=8, x=1.2626669642896602, y=1.056997965633578, z=4.0, module_id=3, track_id=1),\n",
       " Hit(hit_id=13, x=0.4774098251528373, y=-0.09049857753221381, z=4.0, module_id=3, track_id=2),\n",
       " Hit(hit_id=18, x=-0.014180372541072852, y=-1.3949483231565838, z=4.0, module_id=3, track_id=3),\n",
       " Hit(hit_id=23, x=1.8383397273952384, y=0.6172906893765987, z=4.0, module_id=3, track_id=4),\n",
       " Hit(hit_id=28, x=-0.5630010777335952, y=1.165298171478604, z=4.0, module_id=3, track_id=5),\n",
       " Hit(hit_id=33, x=-2.196838258339976, y=0.3215301757557472, z=4.0, module_id=3, track_id=6),\n",
       " Hit(hit_id=38, x=1.4459958103313564, y=1.0848735781801642, z=4.0, module_id=3, track_id=7),\n",
       " Hit(hit_id=43, x=1.8441651298580752, y=0.38244230139409996, z=4.0, module_id=3, track_id=8),\n",
       " Hit(hit_id=48, x=0.6353328738440005, y=0.8091215544140116, z=4.0, module_id=3, track_id=9),\n",
       " Hit(hit_id=53, x=-0.6290845460574236, y=-1.394743313889953, z=4.0, module_id=3, track_id=10),\n",
       " Hit(hit_id=58, x=-0.22035010549134493, y=2.2709226795839053, z=4.0, module_id=3, track_id=11),\n",
       " Hit(hit_id=63, x=0.6872726134693689, y=1.0774891744983095, z=4.0, module_id=3, track_id=12),\n",
       " Hit(hit_id=68, x=1.09342624623416, y=0.026892106694733818, z=4.0, module_id=3, track_id=13),\n",
       " Hit(hit_id=73, x=1.0455485739115173, y=1.4238194552353196, z=4.0, module_id=3, track_id=14),\n",
       " Hit(hit_id=78, x=-0.7664144622173763, y=-1.5163299205761505, z=4.0, module_id=3, track_id=15),\n",
       " Hit(hit_id=83, x=0.03367003189485095, y=0.3810919174870564, z=4.0, module_id=3, track_id=16),\n",
       " Hit(hit_id=88, x=-0.091558965740981, y=0.7247539161829946, z=4.0, module_id=3, track_id=17),\n",
       " Hit(hit_id=93, x=1.2286983231928632, y=0.9746418231537191, z=4.0, module_id=3, track_id=18),\n",
       " Hit(hit_id=98, x=-0.18484375793668006, y=1.6807467783033465, z=4.0, module_id=3, track_id=19),\n",
       " Hit(hit_id=103, x=-0.6242797136456788, y=-1.9985292720487597, z=4.0, module_id=3, track_id=20),\n",
       " Hit(hit_id=108, x=-0.816756978009193, y=1.1963472427523765, z=4.0, module_id=3, track_id=21),\n",
       " Hit(hit_id=113, x=-0.9533194438433334, y=0.48100945461582456, z=4.0, module_id=3, track_id=22),\n",
       " Hit(hit_id=118, x=-1.1172638270163024, y=0.15866371758641024, z=4.0, module_id=3, track_id=23),\n",
       " Hit(hit_id=123, x=-0.2715574923709829, y=-1.396299571154023, z=4.0, module_id=3, track_id=24),\n",
       " Hit(hit_id=128, x=0.7347221885634946, y=-0.005136464956804092, z=4.0, module_id=3, track_id=25),\n",
       " Hit(hit_id=133, x=-1.6132461360510821, y=1.2222543998642026, z=4.0, module_id=3, track_id=26),\n",
       " Hit(hit_id=138, x=-1.3638163390242921, y=0.2301117625950148, z=4.0, module_id=3, track_id=27),\n",
       " Hit(hit_id=143, x=-0.32279454388393236, y=-1.0423716652322985, z=4.0, module_id=3, track_id=28),\n",
       " Hit(hit_id=148, x=-0.12877637069753453, y=-0.9605177382631235, z=4.0, module_id=3, track_id=29),\n",
       " Hit(hit_id=153, x=-1.3559263208361452, y=0.7670441704492207, z=4.0, module_id=3, track_id=30),\n",
       " Hit(hit_id=158, x=0.7586400020770423, y=-0.787772331960327, z=4.0, module_id=3, track_id=31),\n",
       " Hit(hit_id=163, x=-0.6330804260168729, y=0.3014150200637577, z=4.0, module_id=3, track_id=32),\n",
       " Hit(hit_id=168, x=2.032254121427363, y=-0.9598088883038156, z=4.0, module_id=3, track_id=33),\n",
       " Hit(hit_id=173, x=-0.18350653601686256, y=-1.0825224177722694, z=4.0, module_id=3, track_id=34),\n",
       " Hit(hit_id=178, x=-2.140155979847368, y=-0.40946896985549575, z=4.0, module_id=3, track_id=35),\n",
       " Hit(hit_id=183, x=1.2361629169064727, y=-1.3669337030823336, z=4.0, module_id=3, track_id=36),\n",
       " Hit(hit_id=188, x=0.42434735109250893, y=2.2453133576932522, z=4.0, module_id=3, track_id=37),\n",
       " Hit(hit_id=193, x=-1.3204129529349435, y=-1.7366569108922423, z=4.0, module_id=3, track_id=38),\n",
       " Hit(hit_id=198, x=-2.093993378265503, y=0.913273240573906, z=4.0, module_id=3, track_id=39),\n",
       " Hit(hit_id=203, x=-2.232022549155981, y=0.16025875666580097, z=4.0, module_id=3, track_id=40),\n",
       " Hit(hit_id=208, x=-1.7251344231294392, y=0.2054266595387276, z=4.0, module_id=3, track_id=41),\n",
       " Hit(hit_id=213, x=-0.211140457603996, y=1.601898505769012, z=4.0, module_id=3, track_id=42),\n",
       " Hit(hit_id=218, x=1.7530761710860965, y=-0.6831274892168107, z=4.0, module_id=3, track_id=43),\n",
       " Hit(hit_id=223, x=-0.8153417418097721, y=0.9551424662090486, z=4.0, module_id=3, track_id=44),\n",
       " Hit(hit_id=228, x=-1.1762056065799393, y=-1.0887284072866952, z=4.0, module_id=3, track_id=45),\n",
       " Hit(hit_id=233, x=-0.3579315403644369, y=0.6468898160930571, z=4.0, module_id=3, track_id=46),\n",
       " Hit(hit_id=238, x=-0.17410900634052337, y=1.9217717562643248, z=4.0, module_id=3, track_id=47),\n",
       " Hit(hit_id=243, x=-1.32063257032195, y=0.3911425398145832, z=4.0, module_id=3, track_id=48),\n",
       " Hit(hit_id=248, x=-1.038471675720858, y=-0.6732533797829984, z=4.0, module_id=3, track_id=49),\n",
       " Hit(hit_id=253, x=-2.191899490482285, y=0.34046891312820726, z=4.0, module_id=3, track_id=50),\n",
       " Hit(hit_id=258, x=0.6898140013891568, y=-0.10057562991275439, z=4.0, module_id=3, track_id=51),\n",
       " Hit(hit_id=263, x=1.0541619986753432, y=-1.734196603478036, z=4.0, module_id=3, track_id=52),\n",
       " Hit(hit_id=268, x=-0.21956180930517336, y=-0.10490539380041314, z=4.0, module_id=3, track_id=53),\n",
       " Hit(hit_id=273, x=-0.3506665717840786, y=0.3114227274341329, z=4.0, module_id=3, track_id=54),\n",
       " Hit(hit_id=278, x=-1.2562470618399622, y=-1.0228762456485172, z=4.0, module_id=3, track_id=55),\n",
       " Hit(hit_id=283, x=0.19806742428985674, y=1.9719061594116958, z=4.0, module_id=3, track_id=56),\n",
       " Hit(hit_id=288, x=-1.7763334900511785, y=0.5019652168586081, z=4.0, module_id=3, track_id=57),\n",
       " Hit(hit_id=293, x=1.4095109241080945, y=-0.1593078173477134, z=4.0, module_id=3, track_id=58),\n",
       " Hit(hit_id=298, x=0.059610309620829735, y=-1.3622000284867808, z=4.0, module_id=3, track_id=59),\n",
       " Hit(hit_id=303, x=1.2335136573913603, y=0.06540930231041217, z=4.0, module_id=3, track_id=60),\n",
       " Hit(hit_id=308, x=-2.0109157153739403, y=-0.04333989656961167, z=4.0, module_id=3, track_id=61),\n",
       " Hit(hit_id=313, x=1.1419404272201668, y=1.951296735632125, z=4.0, module_id=3, track_id=62),\n",
       " Hit(hit_id=318, x=-1.4612849667485415, y=-0.19470293045788453, z=4.0, module_id=3, track_id=63),\n",
       " Hit(hit_id=323, x=-2.167239528668264, y=0.26542647861799984, z=4.0, module_id=3, track_id=64),\n",
       " Hit(hit_id=328, x=0.5017254253598016, y=-0.6358112445326582, z=4.0, module_id=3, track_id=65),\n",
       " Hit(hit_id=333, x=-0.35281707272691626, y=1.5690277737221088, z=4.0, module_id=3, track_id=66),\n",
       " Hit(hit_id=338, x=-0.8953090623468419, y=0.8564313750244411, z=4.0, module_id=3, track_id=67),\n",
       " Hit(hit_id=343, x=-2.1429065320385114, y=0.6899634260112797, z=4.0, module_id=3, track_id=68),\n",
       " Hit(hit_id=348, x=-1.2552068080079488, y=1.4842451686245914, z=4.0, module_id=3, track_id=69),\n",
       " Hit(hit_id=353, x=-1.7967875620806766, y=0.57789554514521, z=4.0, module_id=3, track_id=70),\n",
       " Hit(hit_id=358, x=1.8802576025970508, y=-0.876571945115546, z=4.0, module_id=3, track_id=71),\n",
       " Hit(hit_id=363, x=-0.14167451266677536, y=-2.009674868196856, z=4.0, module_id=3, track_id=72),\n",
       " Hit(hit_id=368, x=0.6787102116312393, y=-0.6172832095839784, z=4.0, module_id=3, track_id=73),\n",
       " Hit(hit_id=373, x=-0.10189196295093454, y=-1.2788250328762705, z=4.0, module_id=3, track_id=74),\n",
       " Hit(hit_id=378, x=-0.5790313909566388, y=2.2056582203014723, z=4.0, module_id=3, track_id=75),\n",
       " Hit(hit_id=383, x=-1.4405372739010867, y=1.778048040476221, z=4.0, module_id=3, track_id=76),\n",
       " Hit(hit_id=388, x=-0.8118345708005421, y=0.3338303854128487, z=4.0, module_id=3, track_id=77),\n",
       " Hit(hit_id=393, x=-1.0285103400649829, y=0.39716897332482937, z=4.0, module_id=3, track_id=78),\n",
       " Hit(hit_id=398, x=1.5197633219535125, y=-0.9283034733909609, z=4.0, module_id=3, track_id=79),\n",
       " Hit(hit_id=403, x=0.30184879570116974, y=-0.4490976605251879, z=4.0, module_id=3, track_id=80),\n",
       " Hit(hit_id=408, x=0.798677147648887, y=0.5391503502479207, z=4.0, module_id=3, track_id=81),\n",
       " Hit(hit_id=413, x=-0.23184361338177736, y=-1.4007472458537915, z=4.0, module_id=3, track_id=82),\n",
       " Hit(hit_id=418, x=-0.9381954942050067, y=0.2590175040916689, z=4.0, module_id=3, track_id=83),\n",
       " Hit(hit_id=423, x=1.3499736800390303, y=0.17421875649686666, z=4.0, module_id=3, track_id=84),\n",
       " Hit(hit_id=428, x=-0.5053917792506596, y=-2.1881777256653305, z=4.0, module_id=3, track_id=85),\n",
       " Hit(hit_id=433, x=-1.0552459206745404, y=0.9343880602771858, z=4.0, module_id=3, track_id=86),\n",
       " Hit(hit_id=438, x=0.8149824662650496, y=-0.8729629891877477, z=4.0, module_id=3, track_id=87),\n",
       " Hit(hit_id=443, x=-0.17173002195075365, y=2.1075692531800807, z=4.0, module_id=3, track_id=88),\n",
       " Hit(hit_id=448, x=0.047306036571756256, y=-0.9176317872718299, z=4.0, module_id=3, track_id=89),\n",
       " Hit(hit_id=453, x=-1.9138660645827645, y=-0.14951276988579495, z=4.0, module_id=3, track_id=90),\n",
       " Hit(hit_id=458, x=0.11173024980949935, y=-1.5118788346648884, z=4.0, module_id=3, track_id=91),\n",
       " Hit(hit_id=463, x=0.5168617124266178, y=-1.4717067624898574, z=4.0, module_id=3, track_id=92),\n",
       " Hit(hit_id=468, x=-0.8032316667193488, y=-0.7465731294758434, z=4.0, module_id=3, track_id=93),\n",
       " Hit(hit_id=473, x=-0.8188978290008111, y=0.9463881523780888, z=4.0, module_id=3, track_id=94),\n",
       " Hit(hit_id=478, x=1.5839915071336395, y=0.6638333882534726, z=4.0, module_id=3, track_id=95),\n",
       " Hit(hit_id=483, x=-0.018907947590306423, y=1.3658152226239069, z=4.0, module_id=3, track_id=96),\n",
       " Hit(hit_id=488, x=0.1590171531495635, y=-1.6526493812731862, z=4.0, module_id=3, track_id=97),\n",
       " Hit(hit_id=493, x=-0.26100784557258155, y=1.5522212738653063, z=4.0, module_id=3, track_id=98),\n",
       " Hit(hit_id=498, x=-0.35269256271792954, y=1.0936723930880958, z=4.0, module_id=3, track_id=99),\n",
       " Hit(hit_id=503, x=1.5641503432327883, y=1.2627353394276335, z=4.0, module_id=3, track_id=100),\n",
       " Hit(hit_id=508, x=-1.2151990311900485, y=-0.2696363121036655, z=4.0, module_id=3, track_id=101),\n",
       " Hit(hit_id=513, x=-0.9061796773135149, y=1.1354671012290989, z=4.0, module_id=3, track_id=102),\n",
       " Hit(hit_id=518, x=-1.614990023697291, y=-1.4331805951864987, z=4.0, module_id=3, track_id=103),\n",
       " Hit(hit_id=523, x=1.338936925936548, y=1.0036908499528727, z=4.0, module_id=3, track_id=104),\n",
       " Hit(hit_id=528, x=0.8235047623135878, y=-0.9508919266902162, z=4.0, module_id=3, track_id=105),\n",
       " Hit(hit_id=533, x=-0.670363332405057, y=-0.3049189396505257, z=4.0, module_id=3, track_id=106),\n",
       " Hit(hit_id=538, x=-1.678931889956097, y=-0.7654009663134671, z=4.0, module_id=3, track_id=107),\n",
       " Hit(hit_id=543, x=1.1617202434687348, y=-0.9026217833533223, z=4.0, module_id=3, track_id=108),\n",
       " Hit(hit_id=548, x=-0.08755545585813146, y=-1.9439427481762448, z=4.0, module_id=3, track_id=109),\n",
       " Hit(hit_id=553, x=-0.8637276743054245, y=0.15610491738406795, z=4.0, module_id=3, track_id=110),\n",
       " Hit(hit_id=558, x=-0.2721523830660811, y=2.2812749249497224, z=4.0, module_id=3, track_id=111),\n",
       " Hit(hit_id=563, x=-0.25210983578418567, y=0.8481581509118691, z=4.0, module_id=3, track_id=112),\n",
       " Hit(hit_id=568, x=-2.076449088172625, y=0.6199067910407259, z=4.0, module_id=3, track_id=113),\n",
       " Hit(hit_id=573, x=0.16868655313188166, y=-0.1629029509619341, z=4.0, module_id=3, track_id=114),\n",
       " Hit(hit_id=578, x=-0.03302302666050515, y=-0.16484317746733437, z=4.0, module_id=3, track_id=115),\n",
       " Hit(hit_id=583, x=1.6363988941686975, y=0.7362452792941919, z=4.0, module_id=3, track_id=116),\n",
       " Hit(hit_id=588, x=1.3671773184823186, y=-1.8377324600917035, z=4.0, module_id=3, track_id=117),\n",
       " Hit(hit_id=593, x=1.5918124231011401, y=-1.5658781136712965, z=4.0, module_id=3, track_id=118),\n",
       " Hit(hit_id=598, x=2.1526446152181538, y=0.35013681057399904, z=4.0, module_id=3, track_id=119),\n",
       " Hit(hit_id=603, x=1.777859093587349, y=0.7655070773713202, z=4.0, module_id=3, track_id=120),\n",
       " Hit(hit_id=608, x=0.36856335775007837, y=0.8724027237866225, z=4.0, module_id=3, track_id=121),\n",
       " Hit(hit_id=613, x=0.3851041602539447, y=-1.2378084145986392, z=4.0, module_id=3, track_id=122),\n",
       " Hit(hit_id=618, x=-2.074024560647733, y=-0.7474054008357346, z=4.0, module_id=3, track_id=123),\n",
       " Hit(hit_id=623, x=1.8170336520052932, y=1.279051213319473, z=4.0, module_id=3, track_id=124),\n",
       " Hit(hit_id=628, x=-1.4770829323488346, y=-0.2049073782595031, z=4.0, module_id=3, track_id=125),\n",
       " Hit(hit_id=633, x=0.5873786163450327, y=-0.06969384786126645, z=4.0, module_id=3, track_id=126),\n",
       " Hit(hit_id=638, x=-0.06477904568833219, y=1.2299927939589868, z=4.0, module_id=3, track_id=127),\n",
       " Hit(hit_id=643, x=1.74213147681937, y=-0.2439617908848859, z=4.0, module_id=3, track_id=128),\n",
       " Hit(hit_id=648, x=0.413851384254076, y=0.160119667184846, z=4.0, module_id=3, track_id=129),\n",
       " Hit(hit_id=653, x=0.6227502447777105, y=0.28556016387994543, z=4.0, module_id=3, track_id=130),\n",
       " Hit(hit_id=658, x=-1.0741127412731133, y=0.25237977805970013, z=4.0, module_id=3, track_id=131),\n",
       " Hit(hit_id=663, x=1.8375393429310871, y=-0.04065331989229897, z=4.0, module_id=3, track_id=132),\n",
       " Hit(hit_id=668, x=0.5934759454125601, y=-0.9618127075462235, z=4.0, module_id=3, track_id=133),\n",
       " Hit(hit_id=673, x=-2.0075243085022234, y=-0.1523908474156977, z=4.0, module_id=3, track_id=134),\n",
       " Hit(hit_id=678, x=0.5315799848422432, y=-1.0336933691031571, z=4.0, module_id=3, track_id=135),\n",
       " Hit(hit_id=683, x=-1.3644155267766707, y=1.826725888315205, z=4.0, module_id=3, track_id=136),\n",
       " Hit(hit_id=688, x=2.077629083340137, y=-0.711783743057929, z=4.0, module_id=3, track_id=137),\n",
       " Hit(hit_id=693, x=0.611606245807502, y=0.6529430349234234, z=4.0, module_id=3, track_id=138),\n",
       " Hit(hit_id=698, x=1.019488999456169, y=-2.0676494010794686, z=4.0, module_id=3, track_id=139),\n",
       " Hit(hit_id=703, x=-0.05954129642457023, y=-0.5284827322529004, z=4.0, module_id=3, track_id=140),\n",
       " Hit(hit_id=708, x=-1.8891640139062464, y=0.392083541449229, z=4.0, module_id=3, track_id=141),\n",
       " Hit(hit_id=713, x=1.6818053263314623, y=1.5195692411539767, z=4.0, module_id=3, track_id=142),\n",
       " Hit(hit_id=718, x=-0.7442498521611173, y=1.9354114829097262, z=4.0, module_id=3, track_id=143),\n",
       " Hit(hit_id=723, x=1.6162777920459688, y=1.3836120064928006, z=4.0, module_id=3, track_id=144),\n",
       " Hit(hit_id=728, x=0.3750006725597844, y=-0.5498404522194444, z=4.0, module_id=3, track_id=145),\n",
       " Hit(hit_id=733, x=1.2926522138572065, y=-1.8628251838609429, z=4.0, module_id=3, track_id=146),\n",
       " Hit(hit_id=738, x=2.057919288050406, y=0.9101784620772843, z=4.0, module_id=3, track_id=147),\n",
       " Hit(hit_id=743, x=1.25811486103733, y=-0.48836133201671045, z=4.0, module_id=3, track_id=148),\n",
       " Hit(hit_id=748, x=-0.6058048624192677, y=0.6521712745582742, z=4.0, module_id=3, track_id=149),\n",
       " Hit(hit_id=4, x=0.5610851268427411, y=-0.6181875213016252, z=5.0, module_id=4, track_id=0),\n",
       " Hit(hit_id=9, x=1.5783337053620752, y=1.3212474570419723, z=5.0, module_id=4, track_id=1),\n",
       " Hit(hit_id=14, x=0.5967622814410466, y=-0.11312322191526726, z=5.0, module_id=4, track_id=2),\n",
       " Hit(hit_id=19, x=-0.017725465676341066, y=-1.7436854039457297, z=5.0, module_id=4, track_id=3),\n",
       " Hit(hit_id=24, x=2.2979246592440483, y=0.7716133617207485, z=5.0, module_id=4, track_id=4),\n",
       " Hit(hit_id=29, x=-0.7037513471669941, y=1.4566227143482549, z=5.0, module_id=4, track_id=5),\n",
       " Hit(hit_id=34, x=-2.7460478229249703, y=0.401912719694684, z=5.0, module_id=4, track_id=6),\n",
       " Hit(hit_id=39, x=1.8074947629141955, y=1.3560919727252052, z=5.0, module_id=4, track_id=7),\n",
       " Hit(hit_id=44, x=2.3052064123225944, y=0.478052876742625, z=5.0, module_id=4, track_id=8),\n",
       " Hit(hit_id=49, x=0.7941660923050006, y=1.0114019430175143, z=5.0, module_id=4, track_id=9),\n",
       " Hit(hit_id=54, x=-0.7863556825717796, y=-1.7434291423624415, z=5.0, module_id=4, track_id=10),\n",
       " Hit(hit_id=59, x=-0.2754376318641812, y=2.838653349479882, z=5.0, module_id=4, track_id=11),\n",
       " Hit(hit_id=64, x=0.8590907668367112, y=1.3468614681228872, z=5.0, module_id=4, track_id=12),\n",
       " Hit(hit_id=69, x=1.3667828077927, y=0.033615133368417274, z=5.0, module_id=4, track_id=13),\n",
       " Hit(hit_id=74, x=1.3069357173893967, y=1.7797743190441495, z=5.0, module_id=4, track_id=14),\n",
       " Hit(hit_id=79, x=-0.9580180777717205, y=-1.8954124007201882, z=5.0, module_id=4, track_id=15),\n",
       " Hit(hit_id=84, x=0.04208753986856369, y=0.4763648968588205, z=5.0, module_id=4, track_id=16),\n",
       " Hit(hit_id=89, x=-0.11444870717622624, y=0.9059423952287432, z=5.0, module_id=4, track_id=17),\n",
       " Hit(hit_id=94, x=1.5358729039910788, y=1.2183022789421487, z=5.0, module_id=4, track_id=18),\n",
       " Hit(hit_id=99, x=-0.23105469742085008, y=2.1009334728791833, z=5.0, module_id=4, track_id=19),\n",
       " Hit(hit_id=104, x=-0.7803496420570984, y=-2.49816159006095, z=5.0, module_id=4, track_id=20),\n",
       " Hit(hit_id=109, x=-1.0209462225114914, y=1.4954340534404706, z=5.0, module_id=4, track_id=21),\n",
       " Hit(hit_id=114, x=-1.1916493048041668, y=0.6012618182697806, z=5.0, module_id=4, track_id=22),\n",
       " Hit(hit_id=119, x=-1.396579783770378, y=0.1983296469830128, z=5.0, module_id=4, track_id=23),\n",
       " Hit(hit_id=124, x=-0.33944686546372865, y=-1.7453744639425286, z=5.0, module_id=4, track_id=24),\n",
       " Hit(hit_id=129, x=0.9184027357043683, y=-0.006420581196005115, z=5.0, module_id=4, track_id=25),\n",
       " Hit(hit_id=134, x=-2.0165576700638526, y=1.5278179998302535, z=5.0, module_id=4, track_id=26),\n",
       " Hit(hit_id=139, x=-1.7047704237803651, y=0.28763970324376853, z=5.0, module_id=4, track_id=27),\n",
       " Hit(hit_id=144, x=-0.40349317985491545, y=-1.302964581540373, z=5.0, module_id=4, track_id=28),\n",
       " Hit(hit_id=149, x=-0.16097046337191817, y=-1.2006471728289043, z=5.0, module_id=4, track_id=29),\n",
       " Hit(hit_id=154, x=-1.6949079010451813, y=0.9588052130615258, z=5.0, module_id=4, track_id=30),\n",
       " Hit(hit_id=159, x=0.948300002596303, y=-0.9847154149504089, z=5.0, module_id=4, track_id=31),\n",
       " Hit(hit_id=164, x=-0.791350532521091, y=0.376768775079697, z=5.0, module_id=4, track_id=32),\n",
       " Hit(hit_id=169, x=2.540317651784204, y=-1.1997611103797694, z=5.0, module_id=4, track_id=33),\n",
       " Hit(hit_id=174, x=-0.22938317002107822, y=-1.353153022215337, z=5.0, module_id=4, track_id=34),\n",
       " Hit(hit_id=179, x=-2.67519497480921, y=-0.5118362123193696, z=5.0, module_id=4, track_id=35),\n",
       " Hit(hit_id=184, x=1.545203646133091, y=-1.7086671288529172, z=5.0, module_id=4, track_id=36),\n",
       " Hit(hit_id=189, x=0.5304341888656362, y=2.8066416971165653, z=5.0, module_id=4, track_id=37),\n",
       " Hit(hit_id=194, x=-1.6505161911686796, y=-2.170821138615303, z=5.0, module_id=4, track_id=38),\n",
       " Hit(hit_id=199, x=-2.617491722831879, y=1.1415915507173824, z=5.0, module_id=4, track_id=39),\n",
       " Hit(hit_id=204, x=-2.790028186444976, y=0.20032344583225117, z=5.0, module_id=4, track_id=40),\n",
       " Hit(hit_id=209, x=-2.156418028911799, y=0.2567833244234095, z=5.0, module_id=4, track_id=41),\n",
       " Hit(hit_id=214, x=-0.263925572004995, y=2.002373132211265, z=5.0, module_id=4, track_id=42),\n",
       " Hit(hit_id=219, x=2.1913452138576206, y=-0.8539093615210133, z=5.0, module_id=4, track_id=43),\n",
       " Hit(hit_id=224, x=-1.0191771772622151, y=1.1939280827613108, z=5.0, module_id=4, track_id=44),\n",
       " Hit(hit_id=229, x=-1.4702570082249242, y=-1.360910509108369, z=5.0, module_id=4, track_id=45),\n",
       " Hit(hit_id=234, x=-0.4474144254555461, y=0.8086122701163212, z=5.0, module_id=4, track_id=46),\n",
       " Hit(hit_id=239, x=-0.21763625792565416, y=2.402214695330406, z=5.0, module_id=4, track_id=47),\n",
       " Hit(hit_id=244, x=-1.6507907129024375, y=0.488928174768229, z=5.0, module_id=4, track_id=48),\n",
       " Hit(hit_id=249, x=-1.2980895946510727, y=-0.8415667247287479, z=5.0, module_id=4, track_id=49),\n",
       " Hit(hit_id=254, x=-2.739874363102856, y=0.425586141410259, z=5.0, module_id=4, track_id=50),\n",
       " Hit(hit_id=259, x=0.862267501736446, y=-0.12571953739094296, z=5.0, module_id=4, track_id=51),\n",
       " Hit(hit_id=264, x=1.317702498344179, y=-2.167745754347545, z=5.0, module_id=4, track_id=52),\n",
       " Hit(hit_id=269, x=-0.2744522616314667, y=-0.1311317422505164, z=5.0, module_id=4, track_id=53),\n",
       " Hit(hit_id=274, x=-0.43833321473009823, y=0.3892784092926661, z=5.0, module_id=4, track_id=54),\n",
       " Hit(hit_id=279, x=-1.5703088272999526, y=-1.2785953070606464, z=5.0, module_id=4, track_id=55),\n",
       " Hit(hit_id=284, x=0.24758428036232094, y=2.46488269926462, z=5.0, module_id=4, track_id=56),\n",
       " Hit(hit_id=289, x=-2.2204168625639733, y=0.6274565210732601, z=5.0, module_id=4, track_id=57),\n",
       " Hit(hit_id=294, x=1.7618886551351183, y=-0.19913477168464175, z=5.0, module_id=4, track_id=58),\n",
       " Hit(hit_id=299, x=0.07451288702603717, y=-1.7027500356084762, z=5.0, module_id=4, track_id=59),\n",
       " Hit(hit_id=304, x=1.5418920717392002, y=0.0817616278880152, z=5.0, module_id=4, track_id=60),\n",
       " Hit(hit_id=309, x=-2.5136446442174254, y=-0.05417487071201459, z=5.0, module_id=4, track_id=61),\n",
       " Hit(hit_id=314, x=1.4274255340252084, y=2.439120919540156, z=5.0, module_id=4, track_id=62),\n",
       " Hit(hit_id=319, x=-1.8266062084356771, y=-0.2433786630723557, z=5.0, module_id=4, track_id=63),\n",
       " Hit(hit_id=324, x=-2.70904941083533, y=0.33178309827249974, z=5.0, module_id=4, track_id=64),\n",
       " Hit(hit_id=329, x=0.627156781699752, y=-0.7947640556658228, z=5.0, module_id=4, track_id=65),\n",
       " Hit(hit_id=334, x=-0.44102134090864537, y=1.961284717152636, z=5.0, module_id=4, track_id=66),\n",
       " Hit(hit_id=339, x=-1.1191363279335524, y=1.0705392187805514, z=5.0, module_id=4, track_id=67),\n",
       " Hit(hit_id=344, x=-2.678633165048139, y=0.8624542825140997, z=5.0, module_id=4, track_id=68),\n",
       " Hit(hit_id=349, x=-1.5690085100099358, y=1.8553064607807395, z=5.0, module_id=4, track_id=69),\n",
       " Hit(hit_id=354, x=-2.2459844526008457, y=0.7223694314315124, z=5.0, module_id=4, track_id=70),\n",
       " Hit(hit_id=359, x=2.3503220032463137, y=-1.0957149313944328, z=5.0, module_id=4, track_id=71),\n",
       " Hit(hit_id=364, x=-0.1770931408334692, y=-2.5120935852460695, z=5.0, module_id=4, track_id=72),\n",
       " Hit(hit_id=369, x=0.8483877645390491, y=-0.7716040119799729, z=5.0, module_id=4, track_id=73),\n",
       " Hit(hit_id=374, x=-0.12736495368866818, y=-1.598531291095338, z=5.0, module_id=4, track_id=74),\n",
       " Hit(hit_id=379, x=-0.7237892386957985, y=2.7570727753768396, z=5.0, module_id=4, track_id=75),\n",
       " Hit(hit_id=384, x=-1.8006715923763585, y=2.222560050595276, z=5.0, module_id=4, track_id=76),\n",
       " Hit(hit_id=389, x=-1.0147932135006776, y=0.41728798176606086, z=5.0, module_id=4, track_id=77),\n",
       " Hit(hit_id=394, x=-1.2856379250812286, y=0.4964612166560367, z=5.0, module_id=4, track_id=78),\n",
       " Hit(hit_id=399, x=1.8997041524418907, y=-1.1603793417387012, z=5.0, module_id=4, track_id=79),\n",
       " Hit(hit_id=404, x=0.37731099462646206, y=-0.5613720756564848, z=5.0, module_id=4, track_id=80),\n",
       " Hit(hit_id=409, x=0.9983464345611086, y=0.6739379378099009, z=5.0, module_id=4, track_id=81),\n",
       " Hit(hit_id=414, x=-0.28980451672722174, y=-1.7509340573172394, z=5.0, module_id=4, track_id=82),\n",
       " Hit(hit_id=419, x=-1.1727443677562583, y=0.32377188011458613, z=5.0, module_id=4, track_id=83),\n",
       " Hit(hit_id=424, x=1.6874671000487877, y=0.21777344562108333, z=5.0, module_id=4, track_id=84),\n",
       " Hit(hit_id=429, x=-0.6317397240633243, y=-2.7352221570816626, z=5.0, module_id=4, track_id=85),\n",
       " Hit(hit_id=434, x=-1.3190574008431757, y=1.1679850753464824, z=5.0, module_id=4, track_id=86),\n",
       " Hit(hit_id=439, x=1.0187280828313119, y=-1.0912037364846845, z=5.0, module_id=4, track_id=87),\n",
       " Hit(hit_id=444, x=-0.21466252743844208, y=2.634461566475101, z=5.0, module_id=4, track_id=88),\n",
       " Hit(hit_id=449, x=0.05913254571469532, y=-1.1470397340897873, z=5.0, module_id=4, track_id=89),\n",
       " Hit(hit_id=454, x=-2.3923325807284557, y=-0.18689096235724367, z=5.0, module_id=4, track_id=90),\n",
       " Hit(hit_id=459, x=0.1396628122618742, y=-1.8898485433311103, z=5.0, module_id=4, track_id=91),\n",
       " Hit(hit_id=464, x=0.6460771405332724, y=-1.839633453112322, z=5.0, module_id=4, track_id=92),\n",
       " Hit(hit_id=469, x=-1.004039583399186, y=-0.9332164118448044, z=5.0, module_id=4, track_id=93),\n",
       " Hit(hit_id=474, x=-1.023622286251014, y=1.1829851904726112, z=5.0, module_id=4, track_id=94),\n",
       " Hit(hit_id=479, x=1.9799893839170493, y=0.8297917353168407, z=5.0, module_id=4, track_id=95),\n",
       " Hit(hit_id=484, x=-0.023634934487883032, y=1.7072690282798835, z=5.0, module_id=4, track_id=96),\n",
       " Hit(hit_id=489, x=0.19877144143695438, y=-2.065811726591483, z=5.0, module_id=4, track_id=97),\n",
       " Hit(hit_id=494, x=-0.32625980696572693, y=1.9402765923316327, z=5.0, module_id=4, track_id=98),\n",
       " Hit(hit_id=499, x=-0.44086570339741193, y=1.3670904913601196, z=5.0, module_id=4, track_id=99),\n",
       " Hit(hit_id=504, x=1.9551879290409855, y=1.578419174284542, z=5.0, module_id=4, track_id=100),\n",
       " Hit(hit_id=509, x=-1.5189987889875607, y=-0.3370453901295819, z=5.0, module_id=4, track_id=101),\n",
       " Hit(hit_id=514, x=-1.1327245966418937, y=1.4193338765363739, z=5.0, module_id=4, track_id=102),\n",
       " Hit(hit_id=519, x=-2.0187375296216135, y=-1.7914757439831233, z=5.0, module_id=4, track_id=103),\n",
       " Hit(hit_id=524, x=1.673671157420685, y=1.254613562441091, z=5.0, module_id=4, track_id=104),\n",
       " Hit(hit_id=529, x=1.0293809528919846, y=-1.18861490836277, z=5.0, module_id=4, track_id=105),\n",
       " Hit(hit_id=534, x=-0.8379541655063213, y=-0.38114867456315715, z=5.0, module_id=4, track_id=106),\n",
       " Hit(hit_id=539, x=-2.098664862445121, y=-0.9567512078918339, z=5.0, module_id=4, track_id=107),\n",
       " Hit(hit_id=544, x=1.4521503043359187, y=-1.128277229191653, z=5.0, module_id=4, track_id=108),\n",
       " Hit(hit_id=549, x=-0.10944431982266432, y=-2.429928435220306, z=5.0, module_id=4, track_id=109),\n",
       " Hit(hit_id=554, x=-1.0796595928817807, y=0.19513114673008494, z=5.0, module_id=4, track_id=110),\n",
       " Hit(hit_id=559, x=-0.3401904788326014, y=2.851593656187153, z=5.0, module_id=4, track_id=111),\n",
       " Hit(hit_id=564, x=-0.3151372947302321, y=1.0601976886398365, z=5.0, module_id=4, track_id=112),\n",
       " Hit(hit_id=569, x=-2.5955613602157817, y=0.7748834888009074, z=5.0, module_id=4, track_id=113),\n",
       " Hit(hit_id=574, x=0.21085819141485207, y=-0.20362868870241763, z=5.0, module_id=4, track_id=114),\n",
       " Hit(hit_id=579, x=-0.04127878332563143, y=-0.20605397183416796, z=5.0, module_id=4, track_id=115),\n",
       " Hit(hit_id=584, x=2.045498617710872, y=0.9203065991177398, z=5.0, module_id=4, track_id=116),\n",
       " Hit(hit_id=589, x=1.708971648102898, y=-2.2971655751146294, z=5.0, module_id=4, track_id=117),\n",
       " Hit(hit_id=594, x=1.989765528876425, y=-1.9573476420891207, z=5.0, module_id=4, track_id=118),\n",
       " Hit(hit_id=599, x=2.690805769022692, y=0.4376710132174988, z=5.0, module_id=4, track_id=119),\n",
       " Hit(hit_id=604, x=2.2223238669841865, y=0.9568838467141502, z=5.0, module_id=4, track_id=120),\n",
       " Hit(hit_id=609, x=0.4607041971875979, y=1.0905034047332782, z=5.0, module_id=4, track_id=121),\n",
       " Hit(hit_id=614, x=0.48138020031743095, y=-1.547260518248299, z=5.0, module_id=4, track_id=122),\n",
       " Hit(hit_id=619, x=-2.5925307008096667, y=-0.9342567510446683, z=5.0, module_id=4, track_id=123),\n",
       " Hit(hit_id=624, x=2.2712920650066164, y=1.5988140166493412, z=5.0, module_id=4, track_id=124),\n",
       " Hit(hit_id=629, x=-1.846353665436043, y=-0.2561342228243788, z=5.0, module_id=4, track_id=125),\n",
       " Hit(hit_id=634, x=0.7342232704312911, y=-0.08711730982658307, z=5.0, module_id=4, track_id=126),\n",
       " Hit(hit_id=639, x=-0.08097380711041526, y=1.5374909924487334, z=5.0, module_id=4, track_id=127),\n",
       " Hit(hit_id=644, x=2.177664346024213, y=-0.3049522386061074, z=5.0, module_id=4, track_id=128),\n",
       " Hit(hit_id=649, x=0.517314230317595, y=0.20014958398105748, z=5.0, module_id=4, track_id=129),\n",
       " Hit(hit_id=654, x=0.778437805972138, y=0.3569502048499318, z=5.0, module_id=4, track_id=130),\n",
       " Hit(hit_id=659, x=-1.3426409265913917, y=0.31547472257462517, z=5.0, module_id=4, track_id=131),\n",
       " Hit(hit_id=664, x=2.2969241786638586, y=-0.050816649865373716, z=5.0, module_id=4, track_id=132),\n",
       " Hit(hit_id=669, x=0.7418449317657002, y=-1.2022658844327796, z=5.0, module_id=4, track_id=133),\n",
       " Hit(hit_id=674, x=-2.5094053856277796, y=-0.1904885592696221, z=5.0, module_id=4, track_id=134),\n",
       " Hit(hit_id=679, x=0.664474981052804, y=-1.2921167113789465, z=5.0, module_id=4, track_id=135),\n",
       " Hit(hit_id=684, x=-1.7055194084708383, y=2.283407360394006, z=5.0, module_id=4, track_id=136),\n",
       " Hit(hit_id=689, x=2.597036354175171, y=-0.8897296788224113, z=5.0, module_id=4, track_id=137),\n",
       " Hit(hit_id=694, x=0.7645078072593776, y=0.8161787936542794, z=5.0, module_id=4, track_id=138),\n",
       " Hit(hit_id=699, x=1.2743612493202117, y=-2.584561751349336, z=5.0, module_id=4, track_id=139),\n",
       " Hit(hit_id=704, x=-0.07442662053071278, y=-0.6606034153161255, z=5.0, module_id=4, track_id=140),\n",
       " Hit(hit_id=709, x=-2.361455017382808, y=0.49010442681153626, z=5.0, module_id=4, track_id=141),\n",
       " Hit(hit_id=714, x=2.102256657914328, y=1.8994615514424709, z=5.0, module_id=4, track_id=142),\n",
       " Hit(hit_id=719, x=-0.9303123152013965, y=2.4192643536371574, z=5.0, module_id=4, track_id=143),\n",
       " Hit(hit_id=724, x=2.020347240057461, y=1.729515008116001, z=5.0, module_id=4, track_id=144),\n",
       " Hit(hit_id=729, x=0.46875084069973055, y=-0.6873005652743056, z=5.0, module_id=4, track_id=145),\n",
       " Hit(hit_id=734, x=1.615815267321508, y=-2.3285314798261783, z=5.0, module_id=4, track_id=146),\n",
       " Hit(hit_id=739, x=2.5723991100630075, y=1.1377230775966054, z=5.0, module_id=4, track_id=147),\n",
       " Hit(hit_id=744, x=1.5726435762966626, y=-0.610451665020888, z=5.0, module_id=4, track_id=148),\n",
       " Hit(hit_id=749, x=-0.7572560780240846, y=0.8152140931978425, z=5.0, module_id=4, track_id=149)]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "N_MODULES = 5\n",
    "LX = float(\"+inf\")\n",
    "LY = float(\"+inf\")\n",
    "Z_SPACING = 1.0\n",
    "\n",
    "detector = toy.SimpleDetectorGeometry(\n",
    "    module_id=list(range(N_MODULES)),\n",
    "    lx=[LX] * N_MODULES,\n",
    "    ly=[LY] * N_MODULES,\n",
    "    z=[i + Z_SPACING for i in range(N_MODULES)]\n",
    ")\n",
    "\n",
    "generator = toy.SimpleGenerator(\n",
    "    detector_geometry=detector,\n",
    "    theta_max=np.pi / 6\n",
    ")\n",
    "\n",
    "N_PARTICLES = 150\n",
    "event = generator.generate_event(N_PARTICLES)\n",
    "event.hits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Memory used: 312.61 MB\n",
      "Time taken: 353.534856 seconds\n"
     ]
    }
   ],
   "source": [
    "params = {\n",
    "    'alpha': 1.0,\n",
    "    'beta': 1.0,\n",
    "    'lambda': 100.0,} \n",
    "\n",
    "def generate_hamiltonian_optimized(event, params):\n",
    "    lambda_val = params.get('lambda')\n",
    "    alpha = params.get('alpha')\n",
    "    beta = params.get('beta')\n",
    "\n",
    "    modules = sorted(event.modules, key=lambda module: module.z)\n",
    "\n",
    "    \n",
    "    segments = [\n",
    "        em.segment(from_hit, to_hit)\n",
    "        for idx in range(len(modules) - 1)\n",
    "        for from_hit, to_hit in itertools.product(modules[idx].hits, modules[idx + 1].hits)\n",
    "    ]\n",
    "\n",
    "    N = len(segments)  \n",
    "\n",
    "    #initialize sparse block matrices for effviciency\n",
    "    A_ang_blocks = []\n",
    "    A_bif_blocks = []\n",
    "    A_inh_blocks = []\n",
    "    b = np.zeros(N)\n",
    "\n",
    "    #total Hamiltonian into smaller blocks->> better for memory\n",
    "    block_size = 500  \n",
    "    num_blocks = (N + block_size - 1) // block_size  \n",
    "\n",
    "    for block_idx in range(num_blocks):\n",
    "        start_idx = block_idx * block_size\n",
    "        end_idx = min(start_idx + block_size, N)\n",
    "        A_ang_block = lil_matrix((end_idx - start_idx, end_idx - start_idx), dtype=np.float32)\n",
    "        A_bif_block = lil_matrix((end_idx - start_idx, end_idx - start_idx), dtype=np.float32)\n",
    "        A_inh_block = lil_matrix((end_idx - start_idx, end_idx - start_idx), dtype=np.float32)\n",
    "\n",
    "        for i in range(start_idx, end_idx):\n",
    "            seg_i = segments[i]\n",
    "            vect_i = seg_i.to_vect()\n",
    "            norm_i = np.linalg.norm(vect_i)\n",
    "\n",
    "            for j in range(i + 1, end_idx):  #\n",
    "                seg_j = segments[j]\n",
    "                vect_j = seg_j.to_vect()\n",
    "                norm_j = np.linalg.norm(vect_j)\n",
    "\n",
    "                cosine = np.dot(vect_i, vect_j) / (norm_i * norm_j)\n",
    "                if np.abs(cosine - 1) < 1e-9:\n",
    "                    A_ang_block[i - start_idx, j - start_idx] = 1\n",
    "                    A_ang_block[j - start_idx, i - start_idx] = 1  # Symmetry with positive sign\n",
    "\n",
    "                if seg_i.from_hit == seg_j.from_hit and seg_i.to_hit != seg_j.to_hit:\n",
    "                    A_bif_block[i - start_idx, j - start_idx] = -alpha\n",
    "                    A_bif_block[j - start_idx, i - start_idx] = -alpha  # Symmetry with negative sign\n",
    "\n",
    "                if seg_i.from_hit != seg_j.from_hit and seg_i.to_hit == seg_j.to_hit:\n",
    "                    A_bif_block[i - start_idx, j - start_idx] = -alpha\n",
    "                    A_bif_block[j - start_idx, i - start_idx] = -alpha  # Symmetry with negative sign\n",
    "\n",
    "                s_ab = int(seg_i.from_hit.module_id == 1 and seg_j.to_hit.module_id == 1)\n",
    "                if s_ab > 0:\n",
    "                    A_inh_block[i - start_idx, j - start_idx] = beta * s_ab * s_ab\n",
    "                    A_inh_block[j - start_idx, i - start_idx] = beta * s_ab * s_ab  # Symmetry with positive sign\n",
    "\n",
    "        A_ang_blocks.append(A_ang_block)\n",
    "        A_bif_blocks.append(A_bif_block)\n",
    "        A_inh_blocks.append(A_inh_block)\n",
    "\n",
    "\n",
    "    A_ang = block_diag(A_ang_blocks, format='csc')\n",
    "    A_bif = block_diag(A_bif_blocks, format='csc')\n",
    "    A_inh = block_diag(A_inh_blocks, format='csc')\n",
    "\n",
    "    A = -1 * (A_ang + A_bif + A_inh)\n",
    "\n",
    "    return A, b, segments\n",
    "\n",
    "\n",
    "process = psutil.Process()\n",
    "\n",
    "start_memory = process.memory_info().rss / (1024 ** 2)  \n",
    "start_time = time.time()\n",
    "\n",
    "A, b, segments = generate_hamiltonian_optimized(event, params)\n",
    "end_memory = process.memory_info().rss / (1024 ** 2)  \n",
    "end_time = time.time()\n",
    "\n",
    "memory_used = end_memory - start_memory\n",
    "time_taken = end_time - start_time\n",
    "\n",
    "print(f\"Memory used: {memory_used:.2f} MB\")\n",
    "print(f\"Time taken: {time_taken:.6f} seconds\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: ace_tools in c:\\users\\vita\\anaconda3\\lib\\site-packages (0.0)\n"
     ]
    }
   ],
   "source": [
    "!pip install ace_tools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matrix size: 100, Density: 0.01, Memory used: 0.01 MB, Sparsity: 0.9900, Time: 0.0220s\n",
      "Matrix size: 100, Density: 0.05, Memory used: 0.01 MB, Sparsity: 0.9500, Time: 0.0090s\n",
      "Matrix size: 100, Density: 0.10, Memory used: 0.02 MB, Sparsity: 0.9000, Time: 0.0100s\n",
      "Matrix size: 100, Density: 0.20, Memory used: 0.03 MB, Sparsity: 0.8000, Time: 0.0140s\n",
      "Matrix size: 500, Density: 0.01, Memory used: 0.17 MB, Sparsity: 0.9900, Time: 0.0439s\n",
      "Matrix size: 500, Density: 0.05, Memory used: 0.11 MB, Sparsity: 0.9500, Time: 0.0649s\n",
      "Matrix size: 500, Density: 0.10, Memory used: 0.34 MB, Sparsity: 0.9000, Time: 0.1043s\n",
      "Matrix size: 500, Density: 0.20, Memory used: 0.39 MB, Sparsity: 0.8000, Time: 0.1600s\n",
      "Matrix size: 1000, Density: 0.01, Memory used: 0.23 MB, Sparsity: 0.9900, Time: 0.1192s\n",
      "Matrix size: 1000, Density: 0.05, Memory used: 0.54 MB, Sparsity: 0.9500, Time: 0.2313s\n",
      "Matrix size: 1000, Density: 0.10, Memory used: 0.92 MB, Sparsity: 0.9000, Time: 0.3849s\n",
      "Matrix size: 1000, Density: 0.20, Memory used: 1.68 MB, Sparsity: 0.8000, Time: 0.7004s\n",
      "Matrix size: 1500, Density: 0.01, Memory used: 0.33 MB, Sparsity: 0.9900, Time: 0.2436s\n",
      "Matrix size: 1500, Density: 0.05, Memory used: 1.01 MB, Sparsity: 0.9500, Time: 0.5419s\n",
      "Matrix size: 1500, Density: 0.10, Memory used: 1.87 MB, Sparsity: 0.9000, Time: 0.8965s\n",
      "Matrix size: 1500, Density: 0.20, Memory used: 3.59 MB, Sparsity: 0.8000, Time: 1.7708s\n",
      "Matrix size: 2000, Density: 0.01, Memory used: 0.46 MB, Sparsity: 0.9900, Time: 0.4338s\n",
      "Matrix size: 2000, Density: 0.05, Memory used: 1.68 MB, Sparsity: 0.9500, Time: 0.9844s\n",
      "Matrix size: 2000, Density: 0.10, Memory used: 3.21 MB, Sparsity: 0.9000, Time: 1.7573s\n",
      "Matrix size: 2000, Density: 0.20, Memory used: 6.26 MB, Sparsity: 0.8000, Time: 2.9528s\n",
      "Matrix size: 5000, Density: 0.01, Memory used: 2.08 MB, Sparsity: 0.9900, Time: 3.0017s\n",
      "Matrix size: 5000, Density: 0.05, Memory used: 9.71 MB, Sparsity: 0.9500, Time: 6.5993s\n",
      "Matrix size: 5000, Density: 0.10, Memory used: 19.24 MB, Sparsity: 0.9000, Time: 11.1352s\n",
      "Matrix size: 5000, Density: 0.20, Memory used: 38.32 MB, Sparsity: 0.8000, Time: 19.5543s\n",
      "Matrix size: 10000, Density: 0.01, Memory used: 7.82 MB, Sparsity: 0.9900, Time: 13.2972s\n",
      "Matrix size: 10000, Density: 0.05, Memory used: 38.34 MB, Sparsity: 0.9500, Time: 27.5903s\n",
      "Matrix size: 10000, Density: 0.10, Memory used: 76.48 MB, Sparsity: 0.9000, Time: 45.2619s\n",
      "Matrix size: 10000, Density: 0.20, Memory used: 152.78 MB, Sparsity: 0.8000, Time: 86.0106s\n",
      "Matrix size: 15000, Density: 0.01, Memory used: 17.37 MB, Sparsity: 0.9900, Time: 32.2719s\n",
      "Matrix size: 15000, Density: 0.05, Memory used: 86.04 MB, Sparsity: 0.9500, Time: 65.8977s\n",
      "Matrix size: 15000, Density: 0.10, Memory used: 171.87 MB, Sparsity: 0.9000, Time: 111.3692s\n",
      "Matrix size: 15000, Density: 0.20, Memory used: 343.39 MB, Sparsity: 0.8000, Time: 973.7768s\n"
     ]
    },
    {
     "data": {
      "image/png": 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iwoQJFCxYMMFrBwcHM3fuXBo1asTIkSPJnz8/ixYt4siRI/H9AfOarY8++ohOnTpx+fJlWrduTb58+fjrr7/Yt28ff/31FzNmzHjo79q1a1d69uzJuXPnqFmzZqLAW716dZo2bUqFChXIlSsXhw8f5vPPP39oYO3RowdXr16lVatW+Pv74+zszJEjR5g8eTJOTk4MGjQowfo8efLw2muvcerUKUqVKsW3337LrFmzeO211yhcuDAATZo0YdKkSbRv354ePXpw6dIlJk6cmCiAPsiwYcM4c+YM9erVo2DBgly9epWpU6fi6upKYGDgfX+ufPnyAEydOpVOnTrh6upK6dKl4+8RlTNnTl5++WVmzJhBkSJFHumMm4hIqrJ4mISISLrz76l3D3LvZDfDMIyYmBhj4sSJRsWKFY0sWbIY2bNnN8qUKWP07NnTOHbsWPy6IkWKGE2aNEn0nIDRu3fvBMfuThibMGFCguNfffWVUb16dSNLlixGtmzZjHr16hmbN29OsOZh0+kMwzCio6MNd3d349lnn33g73uvuLg4Y8aMGUZAQIDh4eFhuLm5GSVLljQGDRqUaJLZBx98YNSsWdPImzev4ebmZhQuXNjo1q2bceLEifg1V65cMbp162bky5fP8PDwMJ566ilj06ZNRmBgYKI+HzhwwKhfv76RJUsWI3fu3Ea3bt2MBQsWGICxb9++BGvDwsKMJk2aGLlz5zZcXV2NAgUKGE2aNDGWL1+erN/z2rVrRtasWQ3AmDVrVqLvv/3220ZAQICRK1cuw93d3ShevLjxxhtvGBcvXnzg865fv97o2rWr4efnZ+TIkcNwcXExfHx8jJYtWxpbtmxJsDYwMNAoV66csXHjRiMgIMBwd3c3fHx8jHfeeceIiYlJsHbu3LlG6dKl42t5//33jTlz5iSaSHe/9+CaNWuMRo0aGQUKFDDc3NyMfPnyGY0bNzY2bdoUvyapqXeGYRiDBw82fH19DScnpwQTCO/auHGjARhjx459YG9ERBzBZhgW3NpbRETSjW+++YbnnnuOtWvX0rhxY6vLeWQ9evRg8eLFXLp06aFb6tKbOnXqcPHixUTXLaU3AwYMYMaMGZw+fTr+uioREato652IiCTp0KFDnDx5kgEDBlCpUiUaNWpkdUnJNnLkSHx9fSlevDg3b95kzZo1zJ49m3fffTfDhaSMYOvWrRw9epSPP/6Ynj17KiSJSJqgoCQiIknq1asXmzdvpkqVKixYsOC+E9DSIldXVyZMmMCZM2e4c+cOJUuWZNKkSfTr18/q0iQJd6/Xatq0KaNHj7a6HBERALT1TkRERERE5B4aDy4iIiIiInIPBSUREREREZF7KCiJiIiIiIjcI8MPc4iLi+PcuXN4enqmqwuRRUREREQkdRmGwY0bN/D19Y2/Afn9ZPigdO7cOQoVKmR1GSIiIiIikkacPn2aggULPnBNhg9Knp6egNkMLy8vS2uJiYlhw4YNNGjQAFdXV0trySzUc8dTzx1L/XY89dzx1HPHUr8dTz13nOvXr1OoUKH4jPAgGT4o3d1u5+XllSaCkoeHB15eXvo/gYOo546nnjuW+u146rnjqeeOpX47nnrueMm5JEfDHERERERERO6hoCQiIiIiInIPBSUREREREZF7WBqUihYtis1mS/TVu3dvwBzfFxISgq+vL1mzZqVOnTocPHjQypJFRERERCQTsDQo7dixg8jIyPiv0NBQAF544QUAxo8fz6RJk5g2bRo7duzA29uboKAgbty4YWXZIiIiIiKSwVkalB577DG8vb3jv9asWUOJEiUIDAzEMAymTJnCkCFDaNmyJf7+/ixYsICoqCgWLVpkZdkiIiIiIpLBpZnx4Ldv3+aLL76gf//+2Gw2/vjjD86fP0+DBg3i17i7uxMYGEh4eDg9e/ZM8nmio6OJjo6Of3z9+nXAHLsYExNj31/iIe6+vtV1ZCbqueOp546lfjueeu546rljqd+Op547Tkp6bDMMw7BjLcm2bNky2rdvz6lTp/D19SU8PJxatWpx9uxZfH1949f16NGDkydPsn79+iSfJyQkhBEjRiQ6vmjRIjw8POxWv4iIiIiIpG1RUVG0b9+ea9euPfQeq2nmjNKcOXNo1KhRglAEiW8GZRjGA28QNXjwYPr37x//+O7ddxs0aJAmbjgbGhpKUFCQbibmIOq546nnjqV+O5567njquWOp346nnjvO3d1myZEmgtLJkyf5/vvvWblyZfwxb29vAM6fP4+Pj0/88QsXLpA/f/77Ppe7uzvu7u6Jjru6uqaZN15aqiWzUM8dTz13LPXb8dRzx1PPHUv9djz13P5S0t80cR+lefPmkS9fPpo0aRJ/rFixYnh7e8dPwgPzOqawsDBq1qxpRZkiIiIiIpJJWH5GKS4ujnnz5tGpUydcXP5Xjs1mIzg4mDFjxlCyZElKlizJmDFj8PDwoH379hZWLCIiIiIiGZ3lQen777/n1KlTdO3aNdH3Bg4cyD///EOvXr24cuUK1atXZ8OGDXh6elpQqYiIiIiIZBaWB6UGDRpwv8F7NpuNkJAQQkJCHFuUHcTGQliYjZ9/LkC2bDaeeQacna2uSkREREREkpImrlHK6FauhKJFISjIhUmTAggKcqFoUfO4iIiIiIikPQpKdrZyJbRuDWfOJDx+9qx5XGFJRERERCTtUVCyo9hY6NcPktpZePdYcLC5TkRERERE0g4FJTvatCnxmaR/Mww4fdpcJyIiIiIiaYeCkh1FRqbuOhERERERcQwFJTvy8Uneun37IC7OvrWIiIiIiEjyKSjZUe3aULAg2GwPXjdunLl2716HlCUiIiIiIg+hoGRHzs4wdar553vDks1mfnXsCNmyQXg4PPEE9O4Nly87vlYREREREfkfBSU7a9kSvvwSChRIeLxgQfP4Z5/BkSPQpo25/e7jj6F0aZg9W9vxRERERESsoqDkAC1bwokTEBp6h/79dxIaeofjx83jYIamJUvgxx/Bzw8uXoTu3eHJJ2HHDktLFxERERHJlBSUHMTZGQIDDZ5++iyBgQbOzonXPPOMeZ3SpEng6WmGpOrVoUcPMzyJiIiIiIhjKCilMa6u8MYbcPSoef2SYcCsWVCqFMyYoZvTioiIiIg4goJSGuXtbV6/tGkTVKgAV65Ar15QtSps2WJ1dSIiIiIiGZuCUhr31FOwaxdMmwY5c8KePVCzJnTuDH/+aXV1IiIiIiIZk4JSOuDiYo4Nj4iArl3NYwsWmNPxPvwQ7tyxtj4RERERkYxGQSkdyZcP5syBrVvNey5duwb9+kGVKvDzz1ZXJyIiIiKScSgopUPVq8O2bfDJJ5A7N+zfD4GB0KEDnDtndXUiIiIiIumfglI65exsjg0/ehRefRVsNli0yNyON3EixMRYXaGIiIiISPqloJTO5cljjg2/e8+lmzfhrbegYkX44QerqxMRERERSZ8UlDKIJ56A8HCYOxceewwOH4b69eHFF+H0aaurExERERFJXxSUMhAnJ+jSxdyO9/rr5uPly6FMGXj/fYiOtrpCEREREZH0QUEpA8qZ0xwbvnu3eR+mqCh45x0oXx7WrbO6OhERERGRtE9BKQOrWNEcG/7FF+DtDceOQaNG0KIFnDhhdXUiIiIiImmXglIGZ7OZY8MjIqB/f3Na3tdfQ9myMHIk/POP1RWKiIiIiKQ9CkqZhJcXfPAB7NsHzzwDt27B8OFQrhysXg2GYXWFIiIiIiJph4JSJlOunDk2fOlSKFAAjh+H5s2haVP47TerqxMRERERSRsUlDIhm80cG37kCLz9Nri6wrffmiHq3XfN4Q8iIiIiIpmZglImlj27OTZ8/35o0ABu34b33jOvX1qxQtvxRERERCTzUlASSpc2x4avXAmFC8OpU9C6NTRsaA6BEBERERHJbBSUBDC34z3/PBw+DEOHgrs7hIaa914aNAhu3LC6QhERERERx1FQkgQ8PMyx4QcPmgMeYmJg/HgoUwaWLNF2PBERERHJHBSUJEklSsA335hfxYvDuXPQrh3UrQsHDlhdnYiIiIiIfSkoyQM1bWqeXRo5ErJkgY0boVIl8+a1165ZXZ2IiIiIiH0oKMlDZcliXrd0+LB5HVNsLEyebA6B+PxzbccTERERkYxHQUmSrWhRczLeunVQqhT8+Se8/DLUrg1791pdnYiIiIhI6lFQkhRr2BB+/RXGjoVs2WDzZnjiCejTB65csbo6EREREZH/TkFJHom7uzk2/MgRaNMG4uJg+nTzTNOcOeZjEREREZH0SkFJ/pOCBc2x4T/8AH5+cPEivPIK1KgBO3daXZ2IiIiIyKNRUJJUUbeueZ3SBx+Apyds3w7VqkHPnmZ4EhERERFJTxSUJNW4uppjwyMi4KWXzGl4n35qTsebOdOcliciIiIikh4oKEmq8/Exx4b//DNUqACXL8Nrr5lnmLZssbo6EREREZGHU1ASu6ldG3btgg8/hBw5YPduqFkTunaFCxesrk5ERERE5P4UlMSuXFzg9dfh6FEzIAHMm2dOx/voI7hzx9r6RERERESSoqAkDpEvnzk2fMsWqFIFrl2Dvn3N+y9t2mR1dSIiIiIiCSkoiUM9+aQ5EW/mTMid27xx7dNPm8MfIiOtrk5ERERExKSgJA7n7GyODT96FHr0AJsNFi40p+NNmgQxMVZXKCIiIiKZnYKSWCZPHvjkE/MMU/XqcOMGDBgAFSvCjz9aXZ2IiIiIZGYKSmK5gAAIDzevYcqbFw4fhnr1oE0bOHPG6upEREREJDNSUJI0wcnJnIp39Cj06WM+XrbM3I43dixER1tdoYiIiIhkJgpKkqbkymWODd+1C2rVgqgoGDzYvHHt+vVWVyciIiIimYWCkqRJlSqZY8M/+wzy5zfPND37LDz/PJw4YXV1IiIiIpLRKShJmmWzQceOZkh64w1zWt5XX0HZsjBqFNy6ZXWFIiIiIpJRKShJmuflZY4N37cP6tQxA9KwYVCuHKxZY3V1IiIiIpIRKShJulGunDk2fMkSKFAA/vgDmjWDpk3h99+trk5EREREMhLLg9LZs2d56aWXyJMnDx4eHlSqVIldu3bFf98wDEJCQvD19SVr1qzUqVOHgwcPWlixWMlmM8eGHzkCAweCqyusXWuGqGHDzOEPIiIiIiL/laVB6cqVK9SqVQtXV1e+++47Dh06xAcffEDOnDnj14wfP55JkyYxbdo0duzYgbe3N0FBQdy4ccO6wsVy2bPDuHHw668QFGSODx81yrx+aeVKMAyrKxQRERGR9MzSoDRu3DgKFSrEvHnzqFatGkWLFqVevXqUKFECMM8mTZkyhSFDhtCyZUv8/f1ZsGABUVFRLFq0yMrSJY0oU8YcG75iBRQuDKdOQatW5oS8iAirqxMRERGR9MrFyhdfvXo1DRs25IUXXiAsLIwCBQrQq1cvunfvDsDx48c5f/48DRo0iP8Zd3d3AgMDCQ8Pp2fPnomeMzo6muh/3Z30+vXrAMTExBATE2Pn3+jB7r6+1XVkRM2aQb16MG6cEx984MSGDTbKlzd4/XWoWtVZPXcgvc8dS/12PPXc8dRzx1K/HU89d5yU9NhmGNZtUsqSJQsA/fv354UXXmD79u0EBwfzySef8PLLLxMeHk6tWrU4e/Ysvr6+8T/Xo0cPTp48yfok7kAaEhLCiBEjEh1ftGgRHh4e9vtlJM2IjMzG7Nn+7NrlDUCePP/QpcsBatU6h81mcXEiIiIiYpmoqCjat2/PtWvX8PLyeuBaS4OSm5sbAQEBhIeHxx/r27cvO3bsYMuWLfFB6dy5c/j4+MSv6d69O6dPn2bdunWJnjOpM0qFChXi4sWLD22GvcXExBAaGkpQUBCurq6W1pIZrFljo39/J06cMHeY1qkTx+TJsZQrZ3FhGZze546lfjueeu546rljqd+Op547zvXr18mbN2+ygpKlW+98fHzw8/NLcKxs2bKsWLECAG9v84zA+fPnEwSlCxcukD9//iSf093dHXd390THXV1d08wbLy3VkpE9/zzUrx9Dz54RrFpVho0bnaha1Ym+fWH4cPP+TGI/ep87lvrteOq546nnjqV+O556bn8p6a+lwxxq1apFxD1X3B89epQiRYoAUKxYMby9vQkNDY3//u3btwkLC6NmzZoOrVXSpyxZoE2bo/z66x1atIA7d8yb15YuDV98oel4IiIiIpI0S4PSG2+8wdatWxkzZgy//fYbixYt4tNPP6V3794A2Gw2goODGTNmDKtWreLAgQN07twZDw8P2rdvb2Xpks4ULQqrVsF330HJknD+PHTsCE8/Dfv2WV2diIiIiKQ1lgalqlWrsmrVKhYvXoy/vz+jRo1iypQpdOjQIX7NwIEDCQ4OplevXgQEBHD27Fk2bNiAp6enhZVLevXss7B/P4wZAx4e8MsvUKUKvP46XL1qdXUiIiIiklZYGpQAmjZtyv79+7l16xaHDx+OHw1+l81mIyQkhMjISG7dukVYWBj+/v4WVSsZgbs7DB4MR47Aiy9CXBxMmwalSsHcueZjEREREcncLA9KIlYpVAiWLoXvv4eyZeGvv6BbN6hVC3btsro6EREREbGSgpJkevXqwd69MHEiZM8OW7dC1arw6qtw6ZLV1YmIiIiIFRSURAA3NxgwACIioEMHcxreJ5+Y2/E++QRiY62uUEREREQcSUFJ5F98fc2x4WFhUL48XL5snlmqXt080yQiIiIimYOCkkgSnn4adu+GqVPNG9Pu2gU1apjXMF24YHV1IiIiImJvCkoi9+HiAn37wtGj0LmzeWzuXPNmtdOmmTevFREREZGMSUFJ5CHy54d58yA8HCpXNu+39PrrEBBg3odJRERERDIeBSWRZKpRA3bsgBkzIFcu2LcPateGjh0hMtLq6kREREQkNSkoiaSAs7M53OHoUejRA2w2c/hD6dIwaRLExFhdoYiIiIikBgUlkUeQN685NnzbNqhWDW7cMMeLV64MP/1kdXUiIiIi8l8pKIn8B1WrwpYtMHu2GZ4OHoS6daFtWzhzxurqRERERORRKSiJ/EdOTubY8IgI6N3bfLx0KZQpA+PGwe3bVlcoIiIiIimloCSSSnLnNseG79oFNWvC33/D22+bN67dsMHq6kREREQkJRSURFJZpUrm2PAFC8zR4kePQsOG0KoVnDxpdXUiIiIikhwKSiJ2YLPByy+b2/GCg81peStXQtmyMHo03LpldYUiIiIi8iAKSiJ2lCMHTJ4Me/dCYCD88w8MHQr+/rB2rdXViYiIiMj9KCiJOIC/vzk2fPFi8PWF33+Hpk2hWTP44w+rqxMRERGReykoiTiIzWaODT9yBN56C1xcYM0a8POD4cMhKsrqCkVERETkLgUlEQfz9ITx42H/fqhfH6KjYeRIMzB99RUYhtUVioiIiIiCkohFypQxx4Z/+SUUKmROxHv+eWjUyJyUJyIiIiLWUVASsZDNZo4NP3wYhgwBNzdYv968pmnwYPNeTCIiIiLieApKImlAtmzm2PADB8wzSjExMHasedZp2TJtxxMRERFxNAUlkTSkZElzbPjXX0OxYnDmDLRpY17LdOiQ1dWJiIiIZB4KSiJpjM0Gzz0HBw9CSAhkyQI//ggVK8Kbb8L161ZXKCIiIpLxKSiJpFFZs5pjww8dgubN4c4d+OADczvewoXajiciIiJiTwpKImlcsWLm2PBvv4XHH4fISHjpJQgMhF9/tbo6ERERkYxJQUkknWjUyBz28N575tmmTZugShXo1w+uXrW6OhEREZGMRUFJJB1xd4d33oEjR6B1a4iNhQ8/hFKlYN48iIuzukIRERGRjEFBSSQdKlwYli+H0FDzmqW//oKuXaFWLdi92+rqRERERNI/BSWRdKx+fdi3DyZMgOzZYetWCAiA116Dy5etrk5EREQk/VJQEknn3NzMseFHjkD79uY0vJkzze14n35qbs8TERERkZRRUBLJIAoUMMeGb9wI/v5w6RL07AlPPgnbtlldnYiIiEj6oqAkksEEBsKePTBlCnh5wc6dZlh65RXzWiYREREReTgFJZEMyMXFHBt+9Ch06mQemzPH3I43fbq244mIiIg8jIKSSAaWPz/Mnw+bN0OlSub9lvr0MQc+bN5scXEiIiIiaZiCkkgmULOmuQVv+nTImRP27oWnnjLPNp0/b3V1IiIiImmPgpJIJuHsDL16mdvxuncHmw0++wxKlzavZ4qJsbpCERERkbRDQUkkk3nsMXNs+NatULUqXL8Ob7wBVaqYE/NEREREREFJJNOqVs0MS7NmQZ48cOAAPPMMtGsHZ89aXZ2IiIiItRSURDIxJydzbPjRo+a2PCcnWLLE3I43fjzcvm11hSIiIiLWUFASEXLnNgc97NwJNWrA33/DoEFQoQKEhlpdnYiIiIjjKSiJSLzKleGXX8yR4vnyQUQENGgArVvDqVNWVyciIiLiOApKIpKAk5M5NvzoUfOmtc7OsGIFlCkD770H0dFWVygiIiJifwpKIpKkHDnMseF79sDTT8M//8C774K/P3z7rdXViYiIiNiXgpKIPFD58ubY8IULwccHfvsNmjSB556DP/6wujoRERER+1BQEpGHstmgfXvzmqW33gIXF/jmG/Dzg+HDzbNNIiIiIhmJgpKIJJunpzk2/NdfoV4983qlkSPNwPT112AYVlcoIiIikjoUlEQkxcqWNceGL18OhQrBiRPQogU0bgzHjlldnYiIiMh/p6AkIo/EZjPHhh8+DO+8A25usG4dVK7swuefl+Xvv62uUEREROTRKSiJyH+SLZs5NvzAAXj2Wbh928aKFaUoX96F5cu1HU9ERETSJwUlEUkVJUuaY8O//PIO+fL9zZkzNl58EYKCzLNOIiIiIumJgpKIpBqbDZ57zuCjj37k3XdjcXeHH36AChXMaXk3blhdoYiIiEjyKCiJSKpzd49j2LA4Dh0y77d05w5MnAilS8OiRdqOJyIiImmfgpKI2E3x4ubY8LVroUQJiIyEDh2gTh3Yv9/q6kRERETuz9KgFBISgs1mS/Dl7e0d/33DMAgJCcHX15esWbNSp04dDh48aGHFIvIoGjc2hz2MHg1Zs8LPP0PlyhAcDFevWl2diIiISGKWn1EqV64ckZGR8V/7//XXzOPHj2fSpElMmzaNHTt24O3tTVBQEDd0oYNIupMlCwwZAkeOQKtWEBsLU6ea2/EWLIC4OKsrFBEREfkfF8sLcHFJcBbpLsMwmDJlCkOGDKFly5YALFiwgPz587No0SJ69uyZ5PNFR0cTHR0d//j69esAxMTEEBMTY4ffIPnuvr7VdWQm6rnjPaznPj6weDF8/72N4GBnjh610bkzzJwZx9SpsVSu7MBiMwC9xx1PPXc89dyx1G/HU88dJyU9thmGdZdVh4SEMGHCBHLkyIG7uzvVq1dnzJgxFC9enD/++IMSJUqwe/duKv/rv5yaN29Ozpw5WbBgwX2fc8SIEYmOL1q0CA8PD7v9LiKScjExNtasKcHSpaW5dcsFJyeDBg1O0KHDYTw99S8LERERSV1RUVG0b9+ea9eu4eXl9cC1lgal7777jqioKEqVKsWff/7J6NGjOXLkCAcPHiQiIoJatWpx9uxZfH1943+mR48enDx5kvXr1yf5nEmdUSpUqBAXL158aDPsLSYmhtDQUIKCgnB1dbW0lsxCPXe8R+n52bPw9tvOLF1q7gbOk8dg9OhYunQxcLJ8g3Dapve446nnjqeeO5b67XjqueNcv36dvHnzJisoWbr1rlGjRvF/Ll++PDVq1KBEiRIsWLCAJ598EgCbzZbgZwzDSHTs39zd3XF3d0903NXVNc288dJSLZmFeu54Kel50aKwZAm8+ir06QMHD9p47TUX5s6FadOgWjX71poR6D3ueOq546nnjqV+O556bn8p6W+a+rvabNmyUb58eY4dOxZ/3dL58+cTrLlw4QL58+e3ojwRsbM6dWDPHpg8Gby8YMcOePJJ6N4dLl60ujoRERHJTNJUUIqOjubw4cP4+PhQrFgxvL29CQ0Njf/+7du3CQsLo2bNmhZWKSL25Opqjg2PiICXXzZvTjt7NpQqBR9/bE7LExEREbE3S4PSm2++SVhYGMePH2fbtm20bt2a69ev06lTJ2w2G8HBwYwZM4ZVq1Zx4MABOnfujIeHB+3bt7eybBFxAG9vc2z4L79ApUpw5Qr07g0BARAebnV1IiIiktFZGpTOnDlDu3btKF26NC1btsTNzY2tW7dSpEgRAAYOHEhwcDC9evUiICCAs2fPsmHDBjw9Pa0sW0QcqFYt2LnTvFYpZ07Yu9c81rkz/PmnxcWJiIhIhmVpUFqyZAnnzp3j9u3bnD17lhUrVuDn5xf/fZvNRkhICJGRkdy6dYuwsDD8/f0trFhErODsbJ5NOnoUunUzjy1YYG7HmzoV7tyxtj4RERHJeNLUNUoiIg/y2GPm9Urbtplb8K5fN69nqlwZwsKsrk5EREQyEgUlEUl3qlWDrVvh008hTx44cMCcmNe+PZw7Z3V1IiIikhEoKIlIuuTsbI4Nj4iA114Dmw0WL4bSpWHCBLh92+oKRUREJD1TUBKRdC1PHnNs+M6d5j2Xbt6EgQOhYkX4/nurqxMREZH0SkFJRDKEKlVg82aYN8+8lunIEQgKghdegFOnrK5ORERE0hsFJRHJMJyczLHhR49C377m4y+/hLJlYcwYiI62ukIRERFJLxSURCTDyZnTHBu+Zw/Urg1RUTBkCPj7w3ffWV2diIiIpAcKSiKSYVWoYI4N/+IL8PaG336Dxo2hRQs4ftzq6kRERCQtU1ASkQzNZoMOHczpeAMGgIsLfP01+PnBiBHwzz9WVygiIiJpkYKSiGQKXl4wcSLs2wd168KtWxASAuXKwerVYBhWVygiIiJpiYKSiGQqfn7m2PBly6BgQXMLXvPm0KQJHDtmdXUiIiKSVigoiUimY7OZY8MPH4bBg8HV1Rzy4O9vDn34+2+rKxQRERGrKSiJSKaVPbs5NvzAAWjYEG7fNh+XLQsrVmg7noiISGamoCQimV6pUuYZpVWroEgROH0aWreGBg3Ms04iIiKS+SgoiYhgbsdr0QIOHYJhw8Dd3byWqUIFGDgQbtywukIRERFxJAUlEZF/8fAwx4YfPAjNmsGdOzBhApQpA4sXazueiIhIZqGgJCKShBIlzLHha9aYfz53Dtq3h2eeMa9pEhERkYxNQUlE5AGaNDGD0ahRkDUrhIVBpUoQHAzXrlldnYiIiNiLgpKIyENkyQLvvmsOdmjZEmJjYepUKF0aPvsM4uKsrlBERERSm4KSiEgyFSlijg1fv94MSX/+CZ06Qe3asHev1dWJiIhIanqkoHT69Gk2bdrE+vXr2b17N9HR0aldl4hImtWgAfz6K4wbB9myQXg4PPEE9O4NV65YXZ2IiIikhmQHpZMnTzJ48GCKFi1K0aJFCQwMpFGjRgQEBJAjRw6CgoJYvnw5cdqDIiKZgJubOTb8yBFo08bcfvfxx+Y9mWbP1nY8ERGR9C5ZQalfv36UL1+eY8eOMXLkSA4ePMi1a9e4ffs258+f59tvv+Wpp55i6NChVKhQgR07dti7bhGRNKFgQViyBH78Efz84OJF6N4dnnwS9FEoIiKSfrkkZ5Gbmxu///47jz32WKLv5cuXj7p161K3bl2GDx/Ot99+y8mTJ6latWqqFysiklY984x5ndK0aTB8uBmSqleHV16BMWMgb16rKxQREZGUSNYZpQkTJiQZkpLSuHFjWrdu/Z+KEhFJj1xd4Y03ICICOnY0b047a5a5HW/GDHNanoiIiKQP/3nq3e3bt7l582Zq1CIikiH4+JhjwzdtggoVzAEPvXpB1aqwZYvV1YmIiEhypCgozZs3j9dff52FCxcCMHjwYDw9PeOHOVy6dMkuRYqIpEdPPQW7dsFHH0GOHLBnD9SsCV26mKPFRUREJO1KdlB677336N27N4cPH6Zv37689tprzJ8/n5EjRzJ27FiOHDnCu+++a89aRUTSHRcX6NMHjh6Frl3NY/Pnm/dh+vBDuHPH0vJERETkPpI1zAFg/vz5zJkzh3bt2rFz506qV6/O0qVL469H8vf359VXX7VboSIi6Vm+fDBnDvToYd5vadcu6NfPHCU+bRo8/bTVFYqIiMi/JfuM0qlTp3jqqacACAgIwMXFhfLly8d/v0KFCkRGRqZ+hSIiGUj16rBtG8ycCblzw/79EBgIL70E585ZXZ2IiIjcleygFBMTg7u7e/xjNzc3XF1d4x+7uLgQq5FOIiIP5ewMPXua2/F69gSbDRYuNLfjTZwIMTFWVygiIiIpGuZw6NAhfv31V3799VcMw+DIkSPxjw8ePGivGkVEMqQ8ecwzS3fvuXTzJrz1FlSsCD/8YHV1IiIimVuyr1ECqFevHoZhxD9u2rQpADabDcMwsNlsqVudiEgm8MQTEB4OCxbAoEFw+DDUrw8vvAAffACFClldoYiISOaT7KB0/Phxe9YhIpKpOTmZY8NbtIDhw2H6dFi+HNauhXffhf794V+7n0VERMTOkh2UihQpYs86REQEyJXLHBverZs5VvyXX+Cdd2DePPP4s89aXaGIiEjmkOygdOrUqWStK1y48CMXIyIipooV4eefzSEPb70Fx45Bo0bmGafJk6FoUasrFBERydiSHZSKFSsW/+e71yn9+5qku9coafKdiEjqsNnMseHPPQcjRsDUqfDVV7BuHQwebAYolxRdaSoiIiLJlex/xdpsNgoWLEjnzp1p1qwZLvq3s4iIQ3h5mUMdunaF11+Hn34yr2OaPx8++MCGU4rml4qIiEhyJPtfr2fOnOG1115j6dKlNGnShM8//xw3NzcqVqyY4EtEROyjXDlzbPjSpVCgABw/Di1bujB6dHV++83q6kRERDKWZAclb29vBg0axOHDh/nyyy+5cuUK1atX58knn2TWrFnExcXZs04REcHcjvfii3DkCLz9Nri6Guzc6U2lSi68+y5ERVldoYiISMbwSBs2nnrqKebMmcOxY8fw8PDg1Vdf5erVq6lcmoiI3E/27PD++7B79x0qVbrA7ds23nsPypaFFSvgX7e8ExERkUfwSEEpPDycV155hVKlSnHz5k2mT59Ozpw5U7k0ERF5mNKlYfjwLSxbdofCheHUKWjdGho2hIgIq6sTERFJv5IdlCIjIxk3bhxlypTh+eefx8vLi/DwcLZv386rr76Kk64mFhGxhM0GLVoYHD4MQ4eaN6YNDYXy5WHQILh50+oKRURE0p8U3XDW19eXTp068dxzz+Hq6kpsbCy//vprgnUVKlRI9SJFROThPDxg5Ejo1An69YO1a2H8ePNeTBMnQps2ZqgSERGRh0t2ULpz5w6nTp1i1KhRjB49Gvjf/ZTu0n2URESsV6IErFljfvXrB3/8Ae3awSefwEcfgb+/1RWKiIikfckOSsePH7dnHSIiksqaNoX69WHCBBgzBjZuhEqVoG9f8z5MOXJYXaGIiEjalaKtdyIikr5kyWJet9SxI/TvD6tWweTJsGiRGaBeeknb8URERJKSrAkMp06dStGTnj179pGKERER+yhaFFauhHXroGRJ+PNPePllqF0b9u61ujoREZG0J1lBqWrVqnTv3p3t27ffd821a9eYNWsW/v7+rFy5MtUKFBGR1NOwIezfD2PHQrZssHkzPPEE9OkDV65YXZ2IiEjakaytd4cPH2bMmDE8++yzuLq6EhAQgK+vL1myZOHKlSscOnSIgwcPEhAQwIQJE2jUqJG96xYRkUfk7m6ODe/QAQYMgGXLYPp083/HjoXOnUF3fBARkcwuWf8qzJ07NxMnTuTcuXPMmDGDUqVKcfHiRY4dOwZAhw4d2LVrF5s3b1ZIEhFJJwoWhKVL4YcfwM8P/voLunWDGjVg506rqxMREbFWsoc5AGTJkoWWLVvSsmVLe9UjIiIOVreueZ3SRx9BSAhs3w7VqkH37ua0vDx5rK5QRETE8bS5QkREcHU1p+JFRJiT8AwDPv0USpWCmTNBt8gTEZHMJs0Epffffx+bzUZwcHD8McMwCAkJwdfXl6xZs1KnTh0OHjxoXZEiIhmcjw98/jn8/DNUqACXL8Nrr5lnmLZssbo6ERERx0kTQWnHjh18+umnVKhQIcHx8ePHM2nSJKZNm8aOHTvw9vYmKCiIGzduWFSpiEjmULs27NoFH35o3ph2926oWRO6doULF6yuTkRExP4sD0o3b96kQ4cOzJo1i1y5csUfNwyDKVOmMGTIEFq2bIm/vz8LFiwgKiqKRYsWWVixiEjm4OICr78OR49Cly7msXnzzO14H30Ed+5YW5+IiIg9pWiYgz307t2bJk2aUL9+fUaPHh1//Pjx45w/f54GDRrEH3N3dycwMJDw8HB69uyZ5PNFR0cTHR0d//j69esAxMTEEBMTY6ffInnuvr7VdWQm6rnjqeeO5Yh+58oFn3wCXbva6NvXmT17bPTtC7NmGUydGstTTxl2e+20SO9xx1PPHUv9djz13HFS0uNkBaXVq1cn+wmfe+65ZK9dsmQJu3fvZseOHYm+d/78eQDy58+f4Hj+/Pk5efLkfZ/z/fffZ8SIEYmOb9iwAQ8Pj2TXZk+hoaFWl5DpqOeOp547lqP6/e678P33RfjiCz/273ejbl0XAgNP06nTQXLnjn74E2Qgeo87nnruWOq346nn9hcVFZXstckKSi1atEjw2GazYRhGgsd3xSZzNNLp06fp168fGzZsIEuWLPdd9+/nBnNL3r3H/m3w4MH0798//vH169cpVKgQDRo0wMvLK1m12UtMTAyhoaEEBQXh6upqaS2ZhXrueOq5Y1nR72bNYNgwGDo0ljlznAgLK8Tu3QUZOjSO3r3jyOj/2PUedzz13LHUb8dTzx3n7m6z5EhWUIqLi4v/8/fff8+gQYMYM2YMNWrUwGazER4ezrvvvsuYMWOS/cK7du3iwoULPPHEE/HHYmNj+fnnn5k2bRoRERGAeWbJx8cnfs2FCxcSnWX6N3d3d9zd3RMdd3V1TTNvvLRUS2ahnjueeu5Yju63tzfMmgU9e0KfPrBtm42BA52ZP9+ZadPgmWccVopl9B53PPXcsdRvx1PP7S8l/U3xMIfg4GCmTp1Kw4YN8fLywtPTk4YNGzJp0iT69u2b7OepV68e+/fvZ+/evfFfAQEBdOjQgb1791K8eHG8vb0TnIK8ffs2YWFh1KxZM6Vli4iIHQQEQHg4zJkDefPCoUPmDWzbtIEzZ6yuTkRE5NGlOCj9/vvv5MiRI9HxHDlycOLEiWQ/j6enJ/7+/gm+smXLRp48efD394+/p9KYMWNYtWoVBw4coHPnznh4eNC+ffuUli0iInbi5GSODT961Dy75OQEy5ZB6dIwdixEZ65Ll0REJINIcVCqWrUqwcHBREZGxh87f/48AwYMoFq1aqla3MCBAwkODqZXr14EBARw9uxZNmzYgKenZ6q+joiI/He5cpljw3ftglq1ICoKBg82b1y7fr3V1YmIiKRMioPS3LlzuXDhAkWKFOHxxx/n8ccfp3DhwkRGRjJnzpz/VMzGjRuZMmVK/GObzUZISAiRkZHcunWLsLAw/P39/9NriIiIfVWqBJs2wWefQf785pmmZ5+Fli0hBRsPRERELJXi+yg9/vjj/Prrr4SGhnLkyBEMw8DPz4/69es/cBqdiIhkHjYbdOwIzz0HI0bAhx/CqlXw3Xfwzjvw1lvwgIGnIiIilnukG87abDYaNGjA008/jbu7uwKSiIgkKUcOmDQJunUzr1/auNEcLT5/PkydCk2bWl2hiIhI0lK89S4uLo5Ro0ZRoEABsmfPzvHjxwEYOnTof956JyIiGVO5cvDjj7B4Mfj6wh9/mPdjatYMfv/d6upEREQSS3FQGj16NPPnz2f8+PG4ubnFHy9fvjyzZ89O1eJERCTjsNmgbVuIiICBA8HVFdasMUPUsGHm8AcREZG0IsVB6bPPPuPTTz+lQ4cOODs7xx+vUKECR44cSdXiREQk48meHcaNg19/haAgc3z4qFHg52dex2QYVlcoIiLyCEHp7NmzPP7444mOx8XFERMTkypFiYhIxlemjDk2fMUKKFwYTp40J+M9+6x51klERMRKKQ5K5cqVY9OmTYmOL1++nMqVK6dKUSIikjnYbGY4OnwY3n0X3NxgwwYoXx7efhtu3rS6QhERyaxSPPVu+PDhdOzYkbNnzxIXF8fKlSuJiIjgs88+Y82aNfaoUUREMjgPD3P7XadO0K8ffPutuT3viy/ggw/gxRfNUCUiIuIoKT6j1KxZM5YuXcq3336LzWZj2LBhHD58mG+++YagoCB71CgiIpnE44/D2rWwejUUKwZnz5oDIOrVg4MHra5OREQykxQHJYCGDRsSFhbGzZs3iYqK4pdffqFBgwapXZuIiGRSzZqZwWjECPPGtD/9BJUqwYABcP261dWJiEhmkOKgdPr0ac6cORP/ePv27QQHB/Ppp5+mamEiIpK5Zc1qjg0/fBhatIA7d8yb15YubW7J03Q8ERGxpxQHpfbt2/PTTz8BcP78eerXr8/27dt55513GDlyZKoXKCIimVvRoubY8O++g5Il4fx56NgRnn4a9u2zujoREcmoUhyUDhw4QLVq1QBYtmwZ5cuXJzw8nEWLFjF//vzUrk9ERAQwx4bv3w9jxpjDH375BapUgddfh6tXra5OREQymhQHpZiYGNzd3QH4/vvvee655wAoU6YMkZGRqVudiIjIv7i7w+DBcOQIvPACxMXBtGlQqhTMnWs+FhERSQ2PdB+lmTNnsmnTJkJDQ3n22WcBOHfuHHny5En1AkVERO5VqBAsWwbffw9ly8Jff0G3blCrFuzaZXV1IiKSEaQ4KI0bN45PPvmEOnXq0K5dOypWrAjA6tWr47fkiYiIOEK9erB3L0ycCNmzw9atULUqvPoqXLpkdXUiIpKepTgo1alTh4sXL3Lx4kXmzp0bf7xHjx7MnDkzVYsTERF5GDc3c2x4RAS0b29Ow/vkE3M73iefQGys1RWKiEh69Ej3UXJ2diZXrlwJjhUtWpR8+fKlSlEiIiIp5esLCxdCWBiULw+XL5tnlqpXN880iYiIpESyg1KxYsUoXrx4oq/KlSvTtm1bdu7cac86RUREkuXpp2H3bpg6Fby8zGuWatQwr2H66y+rqxMRkfTCJbkLg4ODkzx+9epVduzYQY0aNdiwYQPPPPNMatUmIiLySFxcoG9faNMG3n4b5s83p+KtXAmjRplnmlyS/W9AERHJjJL9r4l+/fo98PujRo0iJCREQUlERNKM/Plh3jzo3h369IE9e8z7Ls2ebY4Vf+opqysUEZG06pGuUUpK69atOXjwYGo9nYiISKqpWRN27IAZMyBXLti3D2rXho4dQbcAFBGRpKRaUBIREUnLnJ3NLXdHj5pnmGw2+OILKF0aJk+GmBirKxQRkbQk1YLSl19+ib+/f2o9nYiIiF3kzQuffgrbtkG1anDjBvTvD5Urw08/WV2diIikFcm+RunDDz9M8vi1a9fYsWMH3333HevXr0+1wkREROypalXYssW8huntt+HgQahb1xwAMXEiFCxodYUiImKlZAelyZMnJ3ncy8uLMmXK8Msvv1C9evVUK0xERMTenJzMseHPPw/DhpnXMC1dCmvWwNCh8MYb5g1tRUQk80l2UDp+/Lg96xAREbFM7tzmFLxu3czpeOHh5lmmuXPho4+gQQNzXWwshIXZ+PnnAmTLZuOZZ8xrn0REJOPRMAcREZH/V7ky/PILLFhgjhY/ehQaNoRWreCTT6BoUQgKcmHSpACCglwoWtS8N5OIiGQ8CkoiIiL/YrPByy9DRAQEB5tnjFauNCfmnTmTcO3Zs9C6tcKSiEhGpKAkIiKShBw5zLHhO3fe/zolwzD/NzjY3JYnIiIZh4KSiIjIA1y9Crdv3//7hgGnT8OmTQ4rSUREHEBBSURE5AEiI1N3nYiIpA8pDkpFixZl5MiRnDp1yh71iIiIpCk+Pslb9/vv/9uKJyIi6V+Kg9KAAQP4+uuvKV68OEFBQSxZsoTo6Gh71CYiImK52rXNm8/abA9eN3QoNGkCv/3mmLpERMS+UhyUXn/9dXbt2sWuXbvw8/Ojb9+++Pj40KdPH3bv3m2PGkVERCzj7AxTp5p/vjcs2WzmV8uW4OoK330H5crBu+9CVJTjaxURkdTzyNcoVaxYkalTp3L27FmGDx/O7NmzqVq1KhUrVmTu3LkY2n8gIiIZRMuW8OWXUKBAwuMFC5rHV6yAAwfMey7dvg3vvQdly5rH9a9DEZH06ZGDUkxMDMuWLeO5555jwIABBAQEMHv2bF588UWGDBlChw4dUrNOERERS7VsCSdOQGjoHfr330lo6B2OHzePA5QqZZ5RWrkSCheGU6fMeyw1bGjek0lERNIXl5T+wO7du5k3bx6LFy/G2dmZjh07MnnyZMqUKRO/pkGDBjz99NOpWqiIiIjVnJ0hMNDg77/PEhhYEWfnhN+32eD5581w9P77MH48hIZC+fLQv7+5JS97dmtqFxGRlEnxGaWqVaty7NgxZsyYwZkzZ5g4cWKCkATg5+dH27ZtU61IERGR9MTDA0aNgoMHzQEPMTEwbpy5HW/ZMm3HExFJD1IUlGJjY5kzZw6LFi3ihRdewNXVNcl12bJlY968ealSoIiISHr1+OOwZg2sXg3FisGZM9CmDdSvD4cOWV2diIg8SIqCkrOzM6+++irXrl2zVz0iIiIZTrNm5tmlkBDIkgV+/BEqVoQ334QbN6yuTkREkpLirXfly5fnjz/+sEctIiIiGVbWrDB8uHkm6bnn4M4d+OADKF0aFi3SdjwRkbQmxUHpvffe480332TNmjVERkZy/fr1BF8iIiJyf8WKwddfw9q15ta8yEjo0AGeecYcMS4iImlDioPSs88+y759+3juuecoWLAguXLlIleuXOTMmZNcuXLZo0YREZEMp3Fj2L8fRo82zzaFhUGlShAcDNrhLiJivRSPB//pp5/sUYeIiEimkyULDBkCL71kjg9fuRKmToUlS8zR4h07miPHRUTE8VIclAIDA+1Rh4iISKZVpAisWAEbNsDrr8PRo9CpE3z6KUyfbg5+EBERx0rx1juAq1ev8sEHH/DKK6/QvXt3Jk+erEl4IiIi/1GDBuZ2vLFjIVs22LwZqlQxw9PVq1ZXJyKSuaQ4KO3cuZMSJUowefJkLl++zMWLF5k0aRIlSpRg9+7d9qhRREQk03Bzg0GD4MgRePFFiIuDadOgVCmYO9d8LCIi9pfioPTGG2/w3HPPceLECVauXMmqVas4fvw4TZs2JTg42A4lioiIZD4FC8LSpfD991C2LPz1F3TrBrVqgf5eUkTE/h7pjNKgQYNwcfnf5U0uLi4MHDiQnTt3pmpxIiIimV29erB3L0yYANmzw9atEBAAr70Gly9bXZ2ISMaV4qDk5eXFqVOnEh0/ffo0np6eqVKUiIiI/I+bG7z5JkREQPv25s1pZ840t+PNmqXteCIi9pDioNSmTRu6devG0qVLOX36NGfOnGHJkiW88sortGvXzh41ioiICODrCwsXwsaN4O8Ply5Bjx7w5JOwY4fV1YmIZCwpHg8+ceJEbDYbL7/8Mnfu3AHA1dWV1157jbFjx6Z6gSIiIpJQYKB5ndL06TB8uBmSqleHV16BMWMgb16rKxQRSf9SfEbJzc2NqVOncuXKFfbu3cuePXu4fPkykydPxt3d3R41ioiIyD1cXSE42NyO17GjuR1v1ixzO96MGRAba3WFIiLp2yPdRwnAw8OD8uXLU6FCBTw8PB7pOWbMmEGFChXw8vLCy8uLGjVq8N1338V/3zAMQkJC8PX1JWvWrNSpU4eDBw8+askiIiIZjrc3fPYZbNpk3pj2yhXo1QuqVYMtW6yuTkQk/UpxULp16xYTJkygcePGBAQEUKVKlQRfKVGwYEHGjh3Lzp072blzJ3Xr1qV58+bxYWj8+PFMmjSJadOmsWPHDry9vQkKCuLGjRspLVtERCRDe+op2LkTPvoIcuQwt+bVrAldu8KFC1ZXJyKS/qT4GqWuXbsSGhpK69atqVatGjab7ZFfvFmzZgkev/fee8yYMYOtW7fi5+fHlClTGDJkCC1btgRgwYIF5M+fn0WLFtGzZ89Hfl0REZGMyMUF+vQxb1T79tswb575tWoVjBoFr75qrhERkYdL8cfl2rVr+fbbb6lVq1aqFhIbG8vy5cv5+++/qVGjBsePH+f8+fM0aNAgfo27uzuBgYGEh4ffNyhFR0cTHR0d//j69esAxMTEEBMTk6o1p9Td17e6jsxEPXc89dyx1G/HSw89z5ULPvkEunSx0a+fM3v22Hj9dZg1y2Dq1Fhq1TKsLjFF0kPPMxL12/HUc8dJSY9thmGk6NPSz8+PJUuWUKFChRQXlpT9+/dTo0YNbt26Rfbs2Vm0aBGNGzcmPDycWrVqcfbsWXx9fePX9+jRg5MnT7J+/fokny8kJIQRI0YkOr5o0aJHvpZKREQkvYqNhdDQonzxRVlu3nQDoE6d03TqdJBcuaIf8tMiIhlLVFQU7du359q1a3h5eT1wbYqD0nfffceHH37IzJkzKVKkyH8qFOD27ducOnWKq1evsmLFCmbPnk1YWBhXr16lVq1anDt3Dh8fn/j13bt35/Tp06xbty7J50vqjFKhQoW4ePHiQ5thbzExMYSGhhIUFISrq6ultWQW6rnjqeeOpX47Xnrt+cWLMHSoM3Pn2jAMG15eBsOGxdGrV1ya346XXnueXqnfjqeeO87169fJmzdvsoJSij8aAwICuHXrFsWLF8fDwyPRP8zLly+n6Pnc3Nx4/PHH4597x44dTJ06lUGDBgFw/vz5BEHpwoUL5M+f/77P5+7unuSYcldX1zTzxktLtWQW6rnjqeeOpX47XnrruY8PzJ5t3qC2Tx/YscPGm286M3++M9OmmfdmSuvSW8/TO/Xb8dRz+0tJf1MclNq1a8fZs2cZM2YM+fPn/0/DHJJiGAbR0dEUK1YMb29vQkNDqVy5MmCefQoLC2PcuHGp+poiIiKZRbVqsHUrzJkDgwfDgQNQpw60awcTJ8K/druLiGRqKQ5K4eHhbNmyhYoVK/7nF3/nnXdo1KgRhQoV4saNGyxZsoSNGzeybt06bDYbwcHBjBkzhpIlS1KyZEnGjBmDh4cH7du3/8+vLSIiklk5OUH37tCqFbz7LsycCYsXwzffwPDh0K+feUNbEZHMLMX3USpTpgz//PNPqrz4n3/+SceOHSldujT16tVj27ZtrFu3jqCgIAAGDhxIcHAwvXr1IiAggLNnz7JhwwY8PT1T5fVFREQys9y54eOPzfsvPfkk3LwJb71l3rj2xx+trk5ExFopPqM0duxYBgwYwHvvvUf58uUT7fNLycCEOXPmPPD7NpuNkJAQQkJCUlqmiIiIJFOVKrB5MyxYAIMGweHDUK+eeT+mDz6AggWtrlBExPFSfEbp2WefZcuWLdSrV498+fKRK1cucuXKRc6cOcmVK5c9ahQRERE7c3KCLl0gIsIc9uDkBMuWQenSMHYs3L5tdYUiIo6V4jNKP/30kz3qEBERkTQgVy746CPo1s0MTJs3m0Mf5s0zj//rPvAiIhlaioNSYHqYHyoiIiL/SaVKsGkTfP45DBwIR49Cw4bQsiVMngyFC1tdoYiIfaV46x3Apk2beOmll6hZsyZnz54F4PPPP+eXX35J1eJERETEOjYbvPyyuR0vOBicnWHlSihTBt57D/51f3cRkQwnxUFpxYoVNGzYkKxZs7J7926i//9T8saNG4wZMybVCxQRERFr5chhnkXasweefhr++cccK+7vD99+a3V1IiL2keKgNHr0aGbOnMmsWbMSTLyrWbMmu3fvTtXiREREJO0oXx42boSFC8HHB377DZo0gebN4fhxq6sTEUldKQ5KERERPP3004mOe3l5cfXq1dSoSURERNIomw3at4cjR2DAAHBxgdWrwc8PRowwzzaJiGQEKQ5KPj4+/Pbbb4mO//LLLxQvXjxVihIREZG0zcsLJk6Effugbl24dQtCQqBcOfjmG6urExH571IclHr27Em/fv3Ytm0bNpuNc+fOsXDhQt5880169epljxpFREQkjfLzg++/h6VLoUABcwvec89B06bm1jwRkfQqxUFp4MCBtGjRgmeeeYabN2/y9NNP88orr9CzZ0/69OljjxpFREQkDbPZ4MUXze14gwaBqyusXWueXRo6FKKirK5QRCTlHmk8+HvvvcfFixfZvn07W7du5a+//mLUqFGpXZuIiIikI9mzw9ixsH8/BAXB7dswerR51mnVKjAMqysUEUm+RwpKAB4eHgQEBFCtWjWyZ8+emjWJiIhIOla6NKxfDytWmDemPXnSvFFto0bmjWtFRNIDl+Qu7Nq1a7LWzZ0795GLERERkYzBZjPD0bPPwpgxMGGCGZ78/c1pee++C9myWV2liMj9JfuM0vz58/npp5+4evUqV65cue+XiIiIyF0eHub2uwMHzDNKMTHm9rwyZWD5cm3HE5G0K9lnlF599VWWLFnCH3/8QdeuXXnppZfInTu3PWsTERGRDKJkSXPAw+rVEBwMJ06YAyDq14cPP4SyZa2uUEQkoWSfUfr444+JjIxk0KBBfPPNNxQqVIgXX3yR9evXY+ivg0REROQhbDZo3hwOHYLhw8Hd3RwtXqECDBwIN25YXaGIyP+kaJiDu7s77dq1IzQ0lEOHDlGuXDl69epFkSJFuHnzpr1qFBERkQwka1bz5rSHDkGzZnDnjnkNU5kysHixtuOJSNrwyFPvbDYbNpsNwzCIi4tLzZpEREQkEyhe3NyKt2aN+edz56B9e6hbFw4etLo6EcnsUhSUoqOjWbx4MUFBQZQuXZr9+/czbdo0Tp06pRHhIiIi8kiaNDGD0ciRkCULbNwIFStC//5w/brV1YlIZpXsoNSrVy98fHwYN24cTZs25cyZMyxfvpzGjRvj5PTIJ6ZEREREyJIFhg6Fw4fh+echNhYmTzbvybRwoU3b8UTE4ZI99W7mzJkULlyYYsWKERYWRlhYWJLrVq5cmWrFiYiISOZStCisXGnec+n11+HYMejSxQU/v1oUKgRPPGF1hSKSWSQ7KL388svYbDZ71iIiIiICQMOGsH8/TJoEo0cbHDqUl+rVDXr3hhEjIGdOqysUkYwu2UFp/vz5dixDREREJCF3dxg8GF588Q4vv3yB8PACfPghLFkC48bByy+Ddv+LiL3o40VERETStMKFYeDAnXz33R3KlIELF6BLF3jqKdizx+rqRCSjUlASERGRdKFePYN9+2D8eMiWDbZsgYAA6N0brlyxujoRyWgUlERERCTdcHODt96CiAho2xbi4uDjj6FUKZgzx3wsIpIaFJREREQk3SlQABYvhh9/BD8/uHgRXnkFatSAnTutrk5EMgIFJREREUm3nnkG9u41p+N5esL27VCtGvTsCZcuWV2diKRnCkoiIiKSrrm6whtvmNvxXnoJDAM+/dTcjvfJJ+bNa0VEUkpBSURERDIEHx/4/HP4+WcoXx4uX4ZXX4Xq1WHbNqurE5H0RkFJREREMpTatWH3bpg6Fby8YNcuePJJ6NYN/vrL6upEJL1QUBIREZEMx8UF+vaFo0ehc2fz2Ny55na86dO1HU9EHk5BSURERDKs/Plh3jzYvBkqVYKrV6FPH/P+S+HhVlcnImmZgpKIiIhkeDVrmmPDp0+HnDnNSXm1aplnm/780+LiRCRNUlASERGRTMHZGXr1MrfjdetmHluwwNyON3Uq3LljbX0ikrYoKImIiEim8thjMHs2bN0KTzwB169DcDBUqWJOzBMRAQUlERERyaTujg2fORNy54b9+yEw0LwXU2Sk1dWJiNUUlERERCTTcnaGnj3N7Xg9e4LNBgsXQunSMGkSxMRYXaGIWEVBSURERDK9PHnMM0vbt5tnmm7cgAEDzEl5P/1kdXUiYgUFJREREZH/d3ds+OzZkDcvHDoEdetC27Zw9qzV1YmIIykoiYiIiPyLk5M5FS8iAnr3Nh8vXWpuxxs/Hm7ftrpCEXEEBSURERGRJOTODdOmmfdfqlkT/v4bBg2CihXh+++trk5E7E1BSUREROQBKleGTZtg/nzIlw+OHIGgIGjdGk6dsro6EbEXBSURERGRh3Bygk6dzO14ffuaj1esgLJlYcwYiI62ukIRSW0KSiIiIiLJlDMnTJ0Ke/ZA7doQFQVDhkD58rBundXViUhqUlASERERSaEKFSAsDL74Ary94dgxaNQInn8eTpywujoRSQ0KSiIiIiKPwGaDDh3M7Xj9+5s3r/3qK3M73siRcOuW1RWKyH+hoCQiIiLyH3h5wQcfwL59UKeOGZCGD4dy5WDNGqurE5FHpaAkIiIikgrKlYMff4TFi8HXF/74A5o1M7/++MPq6kQkpRSURERERFKJzQZt25rb8QYOBBcX86ySn595lumff6yuUESSS0FJREREJJVlzw7jxsH+/VC/vjk+fORIMzB99RUYhtUVisjDKCiJiIiI2EmZMrBhAyxfDoUKmRPxnn8eGjc2J+WJSNqloCQiIiJiRzYbtG4Nhw/D4MHg6mrec8nf37wH099/W12hiCRFQUlERETEAbJlgzFj4MABePZZuH3bfFy2LKxYoe14ImmNpUHp/fffp2rVqnh6epIvXz5atGhBREREgjWGYRASEoKvry9Zs2alTp06HDx40KKKRURERP6bUqXg229h1SooUgROnzbPODVsaA6BEJG0wdKgFBYWRu/evdm6dSuhoaHcuXOHBg0a8Pe/zkGPHz+eSZMmMW3aNHbs2IG3tzdBQUHcuHHDwspFREREHp3NBi1awKFDMHQouLtDaCiULw9vvw03b1pdoYhYGpTWrVtH586dKVeuHBUrVmTevHmcOnWKXbt2AebZpClTpjBkyBBatmyJv78/CxYsICoqikWLFllZuoiIiMh/5uFhTsM7eBCaNIGYGHNaXpkysHSptuOJWMnF6gL+7dq1awDkzp0bgOPHj3P+/HkaNGgQv8bd3Z3AwEDCw8Pp2bNnoueIjo4mOjo6/vH169cBiImJISYmxp7lP9Td17e6jsxEPXc89dyx1G/HU88dLzP0vHBhcyve2rU2Bgxw5o8/bLRtC598EsfkybH4+TmulszQ77RGPXeclPTYZhhp4+8qDMOgefPmXLlyhU2bNgEQHh5OrVq1OHv2LL6+vvFre/TowcmTJ1m/fn2i5wkJCWHEiBGJji9atAgPDw/7/QIiIiIiqeD2bSdWrXqcFStKcfu2M87OcTRt+gdt20aQNesdq8sTSdeioqJo3749165dw8vL64Fr00xQ6t27N2vXruWXX36hYMGCwP+C0rlz5/Dx8Ylf2717d06fPs26desSPU9SZ5QKFSrExYsXH9oMe4uJiSE0NJSgoCBcXV0trSWzUM8dTz13LPXb8dRzx8usPT9+HN5805lvvjGvlPDxMRg7Npa2bQ1sNvu9bmbtt5XUc8e5fv06efPmTVZQShNb715//XVWr17Nzz//HB+SALy9vQE4f/58gqB04cIF8ufPn+Rzubu74+7unui4q6trmnnjpaVaMgv13PHUc8dSvx1PPXe8zNbzUqVg9Wr47jvo2xd++81Gp04uzJkD06aZgx/sKbP1Oy1Qz+0vJf21dJiDYRj06dOHlStX8uOPP1KsWLEE3y9WrBje3t6EhobGH7t9+zZhYWHUrFnT0eWKiIiIOFyjRua9l957D7JmhZ9/hsqVITgY/v/ybhGxA0uDUu/evfniiy9YtGgRnp6enD9/nvPnz/PPP/8AYLPZCA4OZsyYMaxatYoDBw7QuXNnPDw8aN++vZWli4iIiDiMuzu88w4cOQKtWkFsLEydCqVLw2efaTqeiD1YGpRmzJjBtWvXqFOnDj4+PvFfS5cujV8zcOBAgoOD6dWrFwEBAZw9e5YNGzbg6elpYeUiIiIijle4MHz5Jaxfb4akP/+ETp2gdm3Yu9fq6kQyFsu33iX11blz5/g1NpuNkJAQIiMjuXXrFmFhYfj7+1tXtIiIiIjFGjSAX3+FsWMhWzbYvBmeeAL69IErV6yuTiRjsDQoiYiIiMijcXODQYPM7Xht2kBcHEyfbp5pmjvXfCwij05BSURERCQdK1gQliyBH36AsmXhr7+gWzeoWRN27bK6OpH0S0FJREREJAOoWxf27YOJEyF7dti2DapWhddeg8uXra5OJP1RUBIRERHJIFxdYcAAiIiA9u3NaXgzZ5r3ZPr0U3Nanogkj4KSiIiISAbj6wsLF8LGjeDvD5cuQc+e8OSTsH271dWJpA8KSiIiIiIZVGAg7N4NU6aAlxfs3GmGpe7d4eJFq6sTSdsUlEREREQyMFdX6NfP3I738svmdrzZs83teDNmJNyOFxsLYWE2fv65AGFhNm3Vk0xNQUlEREQkE/D2hgUL4JdfoGJF835LvXqZAx+2bIGVK6FoUQgKcmHSpACCglwoWtQ8LpIZKSiJiIiIZCK1aplb8D76CHLkgD17zFHirVrBmTMJ1549C61bKyxJ5qSgJCIiIpLJuLhAnz5w9Ch07nz/dYZh/m9wsCbmSeajoCQiIiKSSeXLB506PXiNYcDp07Bpk2NqEkkrFJREREREMrHIyNRdJ5JRKCiJiIiIZGI+Pslb99hj9q1DJK1RUBIRERHJxGrXhoIFwWZ78Lq+feGnnxxTk0haoKAkIiIikok5O8PUqeaf7w1Ldx97esLhw1C3LrRpk3g6nkhGpKAkIiIiksm1bAlffgkFCiQ8XrAgrFgBJ09C797g5ATLlkHp0jB2LNy+bU29Io6goCQiIiIitGwJJ05AaOgd+vffSWjoHY4fN4/nygXTpsGuXeZ9mKKiYPBgKF8eNmywunIR+1BQEhERERHA3IYXGGjw9NNnCQw0cHZO+P1Klcwx4Z99Bvnzm/dhatjwfyFLJCNRUBIRERGRZLPZoGNHiIiAN94ww9WqVVC2LIwaBbduWV2hSOpQUBIRERGRFMuRAyZNgn37oE4dMyANGwblysGaNVZXJ/LfKSiJiIiIyCMrVw5+/BEWLwZfX/jjD2jWzPz6/XerqxN5dApKIiIiIvKf2GzQtq25HW/gQHB1Nc8qlStnnmWKirK6QpGUU1ASERERkVSRPTuMGwe//gpBQRAdbV63VLYsrFwJhmF1hSLJp6AkIiIiIqmqTBlYv968B1PhwnDqFLRqBc8+a551EkkPFJREREREJNXZbObY8MOH4d13wc3NvOdS+fLw9ttw86bVFYo8mIKSiIiIiNiNh4e5/e7gQWjSBGJizO15ZcrA0qXajidpl4KSiIiIiNjd44+bAx5Wr4ZixeDsWXMARL16ZogSSWsUlERERETEYZo1g0OHYORIyJIFfvoJKlaE/v3h+nWrqxP5HwUlEREREXGoLFlg6FDz+qXnn4fYWJg8GUqVgs8/13Y8SRsUlERERETEEkWLmmPD162DkiXhzz/h5Zfh6adh3z6rq5PMTkFJRERERCzVsCHs3w/vv28Of/jlF6hSBV5/Ha5csbo6yawUlERERETEcu7u5tjwI0fgxRchLg6mTYPSpWHuXPOxiCMpKImIiIhImlGokDk2/IcfwM8P/voLunWDGjVg506rq5PMREFJRERERNKcunVh71744APw9ITt26FaNejZEy5dsro6yQwUlEREREQkTXJ1NceGR0TASy+Z0/A+/dScjjdzpjktT8ReFJREREREJE3z8THHhv/8M1SoAJcvw2uvmWeYtmyxujrJqBSURERERCRdqF0bdu2CDz+EHDlg926oWRO6doULF6yuTjIaBSURERERSTdcXMyx4UePmgEJYN48czvehx/CnTvW1icZh4KSiIiIiKQ7+fLBnDnm1rsqVeDaNejXz/zzzz9bXZ1kBApKIiIiIpJuPfmkORFv5kzIndu8cW1goDn8ITLS6uokPVNQEhEREZF0zdnZHBt+9Kj5vzYbLFxobsf74AOIibG6QkmPFJREREREJEPIk8c8s7R9O1SvDjdvwptvQsWK5g1sRVJCQUlEREREMpSAAAgPh7lz4bHH4PBhqF8fXnwRTp+2ujpJLxSURERERCTDcXKCLl3Mm9W+/rr5ePlyKFMGxo6F6GirK5S0TkFJRERERDKsXLnMseG7d8NTT0FUFAweDOXLw7p1VlcnaZmCkoiIiIhkeBUrmmPDP/8cvL3h2DFo1Aiefx5OnLC6OkmLFJREREREJFOw2cyx4RER0L+/OS3vq6+gbFkYORL++cfqCiUtUVASERERkUzFy8scG75vHzzzDNy6BcOHQ7ly8M03VlcnaYWCkoiIiIhkSuXKmWPDly6FAgXg+HF47jlo2hR++83q6sRqCkoiIiIikmnZbObY8CNH4O23wdUV1q41Q9S775rDHyRzUlASERERkUwve3Z4/33Yvx8aNIDbt+G998zrl1asAMOwukJxNAUlEREREZH/V7q0OTZ85UooUgROnYLWraFhQ/Osk2QeCkoiIiIiIv9is5ljww8dgmHDwN0dQkOhQgUYNAhu3LC6QnEEBSURERERkSR4eMCIEXDwIDRrBjExMH48lCkDS5ZoO15GZ2lQ+vnnn2nWrBm+vr7YbDa++uqrBN83DIOQkBB8fX3JmjUrderU4eDBg9YUKyIiIiKZUokSsHo1rFkDxYvDuXPQrh3UrQsHDlhdndiLpUHp77//pmLFikybNi3J748fP55JkyYxbdo0duzYgbe3N0FBQdzQ+U4RERERcbAmTcyzS6NGQdassHEjVKoEb7wB165ZXZ2kNkuDUqNGjRg9ejQtW7ZM9D3DMJgyZQpDhgyhZcuW+Pv7s2DBAqKioli0aJEF1YqIiIhIZpclizk2/PBhaNkSYmNhyhRzCMRnn2k7XkbiYnUB93P8+HHOnz9PgwYN4o+5u7sTGBhIeHg4PXv2TPLnoqOjiY6Ojn98/fp1AGJiYoiJibFv0Q9x9/WtriMzUc8dTz13LPXb8dRzx1PPHUv9Th5fX/M6pdBQG2+84czRozY6dYJPPoljypRYKlVK/nOp546Tkh7bDCNt5F6bzcaqVato0aIFAOHh4dSqVYuzZ8/i6+sbv65Hjx6cPHmS9evXJ/k8ISEhjBgxItHxRYsW4eHhYZfaRURERCTziomx8c03JVi2rDS3brng5GTw7LPHad/+CNmzK/ykJVFRUbRv355r167h5eX1wLVp9ozSXTabLcFjwzASHfu3wYMH079///jH169fp1ChQjRo0OChzbC3mJgYQkNDCQoKwtXV1dJaMgv13PHUc8dSvx1PPXc89dyx1O9H07w5hIQYDBoUx/LlTnz7bXG2by/G6NGxdO5s4PSAC17Uc8e5u9ssOdJsUPL29gbg/Pnz+Pj4xB+/cOEC+fPnv+/Pubu74+7unui4q6trmnnjpaVaMgv13PHUc8dSvx1PPXc89dyx1O+UK1YMli2Dn36CPn3g0CEbr77qwty5MH06BAQ8+OfVc/tLSX/T7H2UihUrhre3N6GhofHHbt++TVhYGDVr1rSwMhERERGR+3vmGdi7FyZNAk9P2L4dqlWDHj3g4kWrq5PksjQo3bx5k71797J3717AHOCwd+9eTp06hc1mIzg4mDFjxrBq1SoOHDhA586d8fDwoH379laWLSIiIiLyQK6u5tjwo0ehY0dzGt6sWVCqFMyYYU7Lk7TN0qC0c+dOKleuTOXKlQHo378/lStXZtiwYQAMHDiQ4OBgevXqRUBAAGfPnmXDhg14enpaWbaIiIiISLJ4e5tjwzdtgooV4coV6NULqlaFLVusrk4exNKgVKdOHQzDSPQ1f/58wBzkEBISQmRkJLdu3SIsLAx/f38rSxYRERERSbGnnoKdO2HaNMiZE/bsgZo1oXNn+PNPq6uTpKTZa5RERERERDISFxfo3RsiIqBbN/PYggVQrpwL33xTnDt3rK1PElJQEhERERFxoHz5YPZs2LoVnngCrl+3MWdOeapVc+Hnn62uTu5SUBIRERERsUD16rBtG3z88R08PW9z4ICNwEDo0AHOnbO6OlFQEhERERGxiLMzvPKKwfTp39OjRyw2GyxaBKVLw8SJcPu21RVmXgpKIiIiIiIW8/KKYdq0OHbuhCefhJs34a23zEl5P/xgdXWZk4KSiIiIiEgaUaUKbN4M8+bBY4/BkSNQvz68+CKcPm11dZmLgpKIiIiISBri5GSODT96FPr2NR8vXw5lysCYMRAdbXWFmYOCkoiIiIhIGpQzJ0ydat5zqXZtiIqCIUPA3x+++87q6jI+BSURERERkTSsQgUIC4MvvgBvb/jtN2jcGFq0gOPHra4u41JQEhERERFJ42w2c2x4RAQMGGDevPbrr8HPD0aMgH/+sbrCjEdBSUREREQknfDyMseG79sHdevCrVsQEgLlysHq1WAYVleYcSgoiYiIiIikM35+8P33sGwZFCxobsFr3hyaNIFjx6yuLmNQUBIRERERSYdsNnjhBXOE+ODB4OpqDnnw9zeHPvz9t9UVpm8KSiIiIiIi6Vi2bObY8AMH4Nln4fZt83HZsvDll9qO96gUlEREREREMoBSpeDbb+Grr6BoUfMGtS+8AA0awOHDVleX/igoiYiIiIhkEDabea3SoUMwfDi4u5vXMlWoAAMHwo0bVleYfigoiYiIiIhkMFmzmtPwDh2C556DO3dgwgQoUwYWL9Z2vORQUBIRERERyaCKFzfvt7R2LZQoAefOQfv2UKcO7N9vdXVpm4KSiIiIiEgG17ixOexh9GjzbNPPP0PlyhAcDNeuWV1d2qSgJCIiIiKSCWTJYo4NP3IEWrWC2FiYOtUcArFgAcTFWV1h2qKgJCIiIiKSiRQubI4N37ABSpeGCxegc2eoXRv27LG6urRDQUlEREREJBMKCoJff4Xx4817MYWHQ0AA9OoFly9bXZ31FJRERERERDIpNzd46y2IiIB27cztdzNmmNvxZs3K3NvxFJRERERERDK5AgVg0SL46ScoVw4uXYIePeDJJ2HHDqurs4aCkoiIiIiIAObY8D17YPJk8PIyQ1L16tC9O1y8aHV1jqWgJCIiIiIi8VxdzbHhERHQqZN5c9rZs83teB9/bE7LywwUlEREREREJBFvb5g/H375BSpVgitXoHdvc+BDeLjV1dmfgpKIiIiIiNxXrVqwcydMnw45c8LeveaxTp3gzz+trs5+FJREREREROSBnJ3NseFHj8Irr4DNBp99Zm7HmzoV7tyxusLUp6AkIiIiIiLJ8thj5tjwrVvNLXjXr5vXM1WuDGFhVleXuhSUREREREQkRapVg23bzNCUJw8cOGBOzGvfHs6e/d+62FjYuBEWLzb/Nz0NglBQEhERERGRFHNyMrfhHT1qbstzcjIDUZkyMGECLFsGRYvCM8+YAeqZZ8zHK1daXXnyKCiJiIiIiMgjy53bHPSwcyfUqAE3b8LAgdCmDZw5k3Dt2bPQunX6CEsKSiIiIiIi8p9VrmyOEp871zy7lBTDMP83ODjtb8NTUBIRERERkVTh5ATFikFc3P3XGAacPg2bNjmurkehoCQiIiIiIqkmMjJ111lFQUlERERERFKNj0/qrrOKgpKIiIiIiKSa2rWhYEHzprRJsdmgUCFzXVqmoCQiIiIiIqnG2RmmTjX/fG9Yuvt4yhRzXVqmoCQiIiIiIqmqZUv48ksoUCDh8YIFzeMtW1pTV0q4WF2AiIiIiIhkPC1bQvPm5nS7yEjzmqTatdP+maS7FJRERERERMQunJ2hTh2rq3g02nonIiIiIiJyDwUlERERERGReygoiYiIiIiI3ENBSURERERE5B4KSiIiIiIiIvdQUBIREREREbmHgpKIiIiIiMg9FJRERERERETuoaAkIiIiIiJyDwUlERERERGReygoiYiIiIiI3ENBSURERERE5B4KSiIiIiIiIvdwsboAezMMA4Dr169bXAnExMQQFRXF9evXcXV1tbqcTEE9dzz13LHUb8dTzx1PPXcs9dvx1HPHuZsJ7maEB8nwQenGjRsAFCpUyOJKREREREQkLbhx4wY5cuR44BqbkZw4lY7FxcVx7tw5PD09sdlsltZy/fp1ChUqxOnTp/Hy8rK0lsxCPXc89dyx1G/HU88dTz13LPXb8dRzxzEMgxs3buDr64uT04OvQsrwZ5ScnJwoWLCg1WUk4OXlpf8TOJh67njquWOp346nnjueeu5Y6rfjqeeO8bAzSXdpmIOIiIiIiMg9FJRERERERETuoaDkQO7u7gwfPhx3d3erS8k01HPHU88dS/12PPXc8dRzx1K/HU89T5sy/DAHERERERGRlNIZJRERERERkXsoKImIiIiIiNxDQUlEREREROQeCkoiIiIiIiL3UFBKgY8//phixYqRJUsWnnjiCTZt2vTA9QsXLqRixYp4eHjg4+NDly5duHTpUoI1K1aswM/PD3d3d/z8/Fi1atV/ft2MJLV7PmvWLGrXrk2uXLnIlSsX9evXZ/v27QmeIyQkBJvNluDL29vbLr9fWpTaPZ8/f36iftpsNm7duvWfXjejSO1+16lTJ8l+N2nSJH6N3uMp6/n06dMpW7YsWbNmpXTp0nz22WeJ1uiz/MFSu+f6LH+w1O63PscfLrV7rs/yNMKQZFmyZInh6upqzJo1yzh06JDRr18/I1u2bMbJkyeTXL9p0ybDycnJmDp1qvHHH38YmzZtMsqVK2e0aNEifk14eLjh7OxsjBkzxjh8+LAxZswYw8XFxdi6desjv25GYo+et2/f3pg+fbqxZ88e4/Dhw0aXLl2MHDlyGGfOnIlfM3z4cKNcuXJGZGRk/NeFCxfs/vumBfbo+bx58wwvL68E/YyMjPxPr5tR2KPfly5dStDnAwcOGM7Ozsa8efPi1+g9nvyef/zxx4anp6exZMkS4/fffzcWL15sZM+e3Vi9enX8Gn2WP5g9eq7P8vuzR7/1Of5g9ui5PsvTBgWlZKpWrZrx6quvJjhWpkwZ4+23305y/YQJE4zixYsnOPbhhx8aBQsWjH/84osvGs8++2yCNQ0bNjTatm37yK+bkdij5/e6c+eO4enpaSxYsCD+2PDhw42KFSs+euHpmD16Pm/ePCNHjhyp+roZhSPe45MnTzY8PT2Nmzdvxh/Tezz5Pa9Ro4bx5ptvJjjWr18/o1atWvGP9Vn+YPbo+b30Wf4/9ui3PscfzBHvcX2WW0Nb75Lh9u3b7Nq1iwYNGiQ43qBBA8LDw5P8mZo1a3LmzBm+/fZbDMPgzz//5Msvv0xwynTLli2JnrNhw4bxz/kor5tR2Kvn94qKiiImJobcuXMnOH7s2DF8fX0pVqwYbdu25Y8//vjvv1QaZ8+e37x5kyJFilCwYEGaNm3Knj17/tPrZgSOeo/PmTOHtm3bki1btgTH9R7/nwf1PDo6mixZsiQ4ljVrVrZv305MTAygz/IHsVfP76XPcpM9+63P8aQ56j2uz3JrKCglw8WLF4mNjSV//vwJjufPn5/z588n+TM1a9Zk4cKFtGnTBjc3N7y9vcmZMycfffRR/Jrz588/8Dkf5XUzCnv1/F5vv/02BQoUoH79+vHHqlevzmeffcb69euZNWsW58+fp2bNmomuL8to7NXzMmXKMH/+fFavXs3ixYvJkiULtWrV4tixY4/8uhmBI97j27dv58CBA7zyyisJjus9nvyeN2zYkNmzZ7Nr1y4Mw2Dnzp3MnTuXmJgYLl68COiz/EHs1fN76bPcZK9+63P8/hzxHtdnuXUUlFLAZrMleGwYRqJjdx06dIi+ffsybNgwdu3axbp16zh+/Divvvpqip8zJa+b0dij53eNHz+exYsXs3LlygR/s9OoUSNatWpF+fLlqV+/PmvXrgVgwYIFqfRbpW2p3fMnn3ySl156iYoVK1K7dm2WLVtGqVKlEv3HfWZ9n9vzPT5nzhz8/f2pVq1aguN6jye/50OHDqVRo0Y8+eSTuLq60rx5czp37gyAs7Nzip4zs77HwT49v0uf5Ymldr/1Of5w9nyP67PcOgpKyZA3b16cnZ0T/c3AhQsXEv0Nwl3vv/8+tWrV4q233qJChQo0bNiQjz/+mLlz5xIZGQmAt7f3A5/zUV43o7BXz++aOHEiY8aMYcOGDVSoUOGBtWTLlo3y5cvH/81ZRmXvnt/l5ORE1apV4/uZWd/n9u53VFQUS5YsSfQ3kEnRe/z+Pc+aNStz584lKiqKEydOcOrUKYoWLYqnpyd58+YF9Fn+IPbq+V36LE/I3v2+S5/j/2Pvnuuz3FoKSsng5ubGE088QWhoaILjoaGh1KxZM8mfiYqKwskpYXvv/i2BYRgA1KhRI9FzbtiwIf45H+V1Mwp79RxgwoQJjBo1inXr1hEQEPDQWqKjozl8+DA+Pj4p/TXSFXv2/N8Mw2Dv3r3x/cys73N793vZsmVER0fz0ksvPbQWvccf/l5zdXWlYMGCODs7s2TJEpo2bRr/z0Kf5fdnr56DPsuTYs9+/5s+x//H3j3XZ7nFHDMzIv27O/pxzpw5xqFDh4zg4GAjW7ZsxokTJwzDMIy3337b6NixY/z6efPmGS4uLsbHH39s/P7778Yvv/xiBAQEGNWqVYtfs3nzZsPZ2dkYO3ascfjwYWPs2LH3HSl7v9fNyOzR83Hjxhlubm7Gl19+mWCc5o0bN+LXDBgwwNi4caPxxx9/GFu3bjWaNm1qeHp6qufGo/U8JCTEWLdunfH7778be/bsMbp06WK4uLgY27ZtS/brZlT26PddTz31lNGmTZskX1fv8eT3PCIiwvj888+No0ePGtu2bTPatGlj5M6d2zh+/Hj8Gn2WP5g9eq7P8vuzR7/1Of5g9uj5Xfost5aCUgpMnz7dKFKkiOHm5mZUqVLFCAsLi/9ep06djMDAwATrP/zwQ8PPz8/ImjWr4ePjY3To0CHBPR4MwzCWL19ulC5d2nB1dTXKlCljrFixIkWvm9Glds+LFCliAIm+hg8fHr+mTZs2ho+Pj+Hq6mr4+voaLVu2NA4ePGjvXzXNSO2eBwcHG4ULFzbc3NyMxx57zGjQoIERHh6eotfNyOzxuRIREWEAxoYNG5J8Tb3Hk9/zQ4cOGZUqVTKyZs1qeHl5Gc2bNzeOHDmS6Dn1Wf5gqd1zfZY/WGr3W5/jD2ePzxV9llvPZhj32R8jIiIiIiKSSekaJRERERERkXsoKImIiIiIiNxDQUlEREREROQeCkoiIiIiIiL3UFASERERERG5h4KSiIiIiIjIPRSURERERERE7qGgJCIiIiIicg8FJRERkSR07tyZFi1aWF2GiIhYREFJREQsdeHCBXr27EnhwoVxd3fH29ubhg0bsmXLFkvrmjp1KvPnz49/XKdOHYKDgy2rR0REHMvF6gJERCRza9WqFTExMSxYsIDixYvz559/8sMPP3D58mW7vWZMTAyurq4PXJMjRw67vb6IiKR9OqMkIiKWuXr1Kr/88gvjxo3jmWeeoUiRIlSrVo3BgwfTpEkTAGw2GzNmzKBRo0ZkzZqVYsWKsXz58gTPM2jQIEqVKoWHhwfFixdn6NChxMTExH8/JCSESpUqMXfuXIoXL467uzuGYfDll19Svnx5smbNSp48eahfvz5///03kHDrXefOnQkLC2Pq1KnYbDZsNhvHjx/n8ccfZ+LEiQlqOXDgAE5OTvz+++927JyIiNibgpKIiFgme/bsZM+ena+++oro6Oj7rhs6dCitWrVi3759vPTSS7Rr147Dhw/Hf9/T05P58+dz6NAhpk6dyqxZs5g8eXKC5/jtt99YtmwZK1asYO/evZw/f5527drRtWtXDh8+zMaNG2nZsiWGYSR6/alTp1KjRg26d+9OZGQkkZGRFC5cmK5duzJv3rwEa+fOnUvt2rUpUaLEf+yOiIhYSUFJREQs4+Liwvz581mwYAE5c+akVq1avPPOO/z6668J1r3wwgu88sorlCpVilGjRhEQEMBHH30U//13332XmjVrUrRoUZo1a8aAAQNYtmxZgue4ffs2n3/+OZUrV6ZChQpERkZy584dWrZsSdGiRSlfvjy9evUie/bsierMkSMHbm5ueHh44O3tjbe3N87OznTp0oWIiAi2b98OmFv6vvjiC7p27WqHbomIiCMpKImIiKVatWrFuXPnWL16NQ0bNmTjxo1UqVIlwSCFGjVqJPiZGjVqJDij9OWXX/LUU0/h7e1N9uzZGTp0KKdOnUrwM0WKFOGxxx6Lf1yxYkXq1atH+fLleeGFF5g1axZXrlxJUe0+Pj40adKEuXPnArBmzRpu3brFCy+8kKLnERGRtEdBSURELJclSxaCgoIYNmwY4eHhdO7cmeHDhz/wZ2w2GwBbt26lbdu2NGrUiDVr1rBnzx6GDBnC7du3E6zPli1bgsfOzs6Ehoby3Xff4efnx0cffUTp0qU5fvx4imp/5ZVXWLJkCf/88w/z5s2jTZs2eHh4pOg5REQk7VFQEhGRNMfPzy9+qAKYYejftm7dSpkyZQDYvHkzRYoUYciQIQQEBFCyZElOnjyZrNex2WzUqlWLESNGsGfPHtzc3Fi1alWSa93c3IiNjU10vHHjxmTLlo0ZM2bw3XffadudiEgGofHgIiJimUuXLvHCCy/QtWtXKlSogKenJzt37mT8+PE0b948ft3y5csJCAjgqaeeYuHChWzfvp05c+YA8Pjjj3Pq1CmWLFlC1apVWbt27X3Dzr9t27aNH374gQYNGpAvXz62bdvGX3/9RdmyZZNcX7RoUbZt28aJEyfInj07uXPnxsnJCWdnZzp37szgwYN5/PHHE20TFBGR9ElnlERExDLZs2enevXqTJ48maeffhp/f3+GDh1K9+7dmTZtWvy6ESNGsGTJEipUqMCCBQtYuHAhfn5+ADRv3pw33niDPn36UKlSJcLDwxk6dOhDX9vLy4uff/6Zxo0bU6pUKd59910++OADGjVqlOT6N998E2dnZ/z8/HjssccSXAPVrVs3bt++rbNJIiIZiM1Iag6qiIhIGmGz2Vi1alX8PY3Sos2bN1OnTh3OnDlD/vz5rS5HRERSgbbeiYiIPKLo6GhOnz7N0KFDefHFFxWSREQyEG29ExEReUSLFy+mdOnSXLt2jfHjx1tdjoiIpCJtvRMREREREbmHziiJiIiIiIjcQ0FJRERERETkHgpKIiIiIiIi91BQEhERERERuYeCkoiIiIiIyD0UlERERERERO6hoCQiIiIiInIPBSUREREREZF7/B9qypP26ob+SAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import psutil\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.sparse import random as sparse_random\n",
    "from scipy.sparse import csc_matrix\n",
    "import pandas as pd\n",
    "import gc\n",
    "import tracemalloc\n",
    "\n",
    "\n",
    "def generate_random_sparse_matrix(size, density):\n",
    "    \n",
    "    sparse_matrix = sparse_random(size, size, density=density, format='lil', dtype=np.float32)\n",
    "    return csc_matrix(sparse_matrix)\n",
    "\n",
    "def test_memory_vs_sparsity(matrix_sizes, densities):\n",
    "    process = psutil.Process()\n",
    "    results = []\n",
    "\n",
    "    for size in matrix_sizes:\n",
    "        for density in densities:\n",
    "            gc.collect()\n",
    "            tracemalloc.start()\n",
    "\n",
    "            start_time = time.time()\n",
    "            snapshot1 = tracemalloc.take_snapshot()\n",
    "\n",
    "            \n",
    "            A = generate_random_sparse_matrix(size, density)\n",
    "\n",
    "            snapshot2 = tracemalloc.take_snapshot()\n",
    "            end_time = time.time()\n",
    "\n",
    "            tracemalloc.stop()\n",
    "\n",
    "            stats = snapshot2.compare_to(snapshot1, 'lineno')\n",
    "            total_memory = sum([stat.size_diff for stat in stats]) / (1024 ** 2)  # Convert to MB\n",
    "            time_taken = end_time - start_time\n",
    "            sparsity = 1 - (A.count_nonzero() / (A.shape[0] * A.shape[1]))\n",
    "            results.append((size, density, total_memory, sparsity, time_taken))\n",
    "            print(f\"Matrix size: {size}, Density: {density:.2f}, Memory used: {total_memory:.2f} MB, Sparsity: {sparsity:.4f}, Time: {time_taken:.4f}s\")\n",
    "\n",
    "    \n",
    "    df = pd.DataFrame(results, columns=[\"Matrix Size\", \"Density\", \"Memory Used (MB)\", \"Sparsity\", \"Time Taken (s)\"])\n",
    "    return df\n",
    "\n",
    "matrix_sizes = [100, 500, 1000, 1500, 2000, 5000, 10000, 15000]  \n",
    "densities = [0.01, 0.05, 0.1,  0.2]  \n",
    "\n",
    "df = test_memory_vs_sparsity(matrix_sizes, densities)\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "df_grouped = df.groupby(\"Sparsity\").mean().reset_index()\n",
    "\n",
    "plt.plot(df_grouped['Sparsity'], df_grouped['Memory Used (MB)'], marker='o', linestyle='-', color='b')\n",
    "\n",
    "plt.xlabel('Sparsity')\n",
    "plt.ylabel('Memory Used (MB)')\n",
    "plt.title('Memory Usage vs Sparsity')\n",
    "\n",
    "\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Bubble plot\n",
    "plt.figure(figsize=(10, 6))\n",
    "bubble_sizes = (df['Sparsity'] ** 2) * 1000\n",
    "\n",
    "\n",
    "plt.scatter(df['Matrix Size'], df['Memory Used (MB)'], s=bubble_sizes, alpha=0.5, color='b')\n",
    "\n",
    "\n",
    "plt.xlabel('Matrix Size', fontsize=14)\n",
    "plt.ylabel('Memory Used (MB)', fontsize=14)\n",
    "plt.title('Memory Used vs Matrix Size (Bubble Size = Sparsity)', fontsize=16)\n",
    "\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matrix size: 10000x10000, Block size: 50, Memory used: 3.06 MB, Sparsity: 0.9997, Time: 0.6223s\n",
      "Matrix size: 10000x10000, Block size: 100, Memory used: 4.63 MB, Sparsity: 0.9995, Time: 0.9285s\n",
      "Matrix size: 10000x10000, Block size: 200, Memory used: 7.72 MB, Sparsity: 0.9990, Time: 1.2207s\n",
      "Matrix size: 10000x10000, Block size: 500, Memory used: 20.09 MB, Sparsity: 0.9975, Time: 2.9631s\n",
      "Matrix size: 10000x10000, Block size: 1000, Memory used: 48.52 MB, Sparsity: 0.9950, Time: 6.1969s\n",
      "Matrix size: 10000x10000, Block size: 2000, Memory used: 130.50 MB, Sparsity: 0.9900, Time: 12.0967s\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.sparse import lil_matrix, block_diag\n",
    "import pandas as pd\n",
    "import tracemalloc\n",
    "\n",
    "# Function to generate a blockwise random sparse matrix with a given block size and density\n",
    "def generate_blockwise_sparse_matrix(size, density, block_size):\n",
    "    \"\"\"Generates a random sparse matrix in blocks with given block size and density.\"\"\"\n",
    "    # Number of blocks\n",
    "    num_blocks = (size + block_size - 1) // block_size  # Calculate number of blocks\n",
    "\n",
    "    # List to store block matrices\n",
    "    block_matrices = []\n",
    "\n",
    "    # Generate each block as a sparse matrix\n",
    "    for _ in range(num_blocks):\n",
    "        block = lil_matrix((block_size, block_size), dtype=np.float32)\n",
    "        # Randomly fill the block with a given density\n",
    "        block[:] = np.random.choice([0, 1], size=(block_size, block_size), p=[1-density, density])\n",
    "        block_matrices.append(block)\n",
    "\n",
    "    # Combine the blocks into a block diagonal matrix\n",
    "    return block_diag(block_matrices, format='csc')\n",
    "\n",
    "# Function to test memory usage for different block sizes\n",
    "def test_memory_vs_block_size(matrix_size, density, block_sizes):\n",
    "    results = []\n",
    "\n",
    "    for block_size in block_sizes:\n",
    "        # Start tracing memory allocations\n",
    "        tracemalloc.start()\n",
    "        start_time = time.time()\n",
    "\n",
    "        # Generate a blockwise random sparse matrix with the given block size\n",
    "        A = generate_blockwise_sparse_matrix(matrix_size, density, block_size)\n",
    "\n",
    "        # Stop tracing memory allocations\n",
    "        end_time = time.time()\n",
    "        current, peak = tracemalloc.get_traced_memory()\n",
    "        tracemalloc.stop()\n",
    "\n",
    "        # Calculate memory used and time taken\n",
    "        memory_used = peak / (1024 ** 2)  # Convert bytes to MB\n",
    "        time_taken = end_time - start_time\n",
    "\n",
    "        # Calculate sparsity\n",
    "        sparsity = 1 - (A.count_nonzero() / (A.shape[0] * A.shape[1]))\n",
    "\n",
    "        # Append the result for this test case\n",
    "        results.append((A.shape[0], block_size, memory_used, sparsity, time_taken))\n",
    "        print(f\"Matrix size: {A.shape[0]}x{A.shape[1]}, Block size: {block_size}, Memory used: {memory_used:.2f} MB, Sparsity: {sparsity:.4f}, Time: {time_taken:.4f}s\")\n",
    "\n",
    "    # Convert the results into a pandas DataFrame for analysis and plotting\n",
    "    df = pd.DataFrame(results, columns=[\"Matrix Size N\", \"Block Size\", \"Memory Used (MB)\", \"Sparsity\", \"Time Taken (s)\"])\n",
    "    return df\n",
    "\n",
    "# Define matrix size, density, and block sizes to test\n",
    "matrix_size = 10000  # Fixed matrix size\n",
    "density = 0.05  # Fixed density (5% non-zero elements)\n",
    "block_sizes = [50, 100, 200, 500, 1000, 2000]  # Test different block sizes\n",
    "\n",
    "# Test memory usage for different block sizes\n",
    "df = test_memory_vs_block_size(matrix_size, density, block_sizes)\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Plot Memory Usage vs Batch Size\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(block_sizes, df['Memory Used (MB)'], marker='o', linestyle='-', color='b')\n",
    "\n",
    "# Add labels and title\n",
    "plt.xlabel('Batch Size')\n",
    "plt.ylabel('Memory Used (MB)')\n",
    "plt.title('Memory Usage vs Batch Size')\n",
    "\n",
    "# Show grid\n",
    "plt.grid(True)\n",
    "\n",
    "# Display the plot\n",
    "plt.show()\n",
    "\n",
    "\n"
   ]
  }
 ],
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   "language": "python",
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