Joshua E. Jodesty
GitHub
commit
bc2a1da70c
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@ -0,0 +1,526 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"from fn import op, _\n",
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"from itertools import repeat\n",
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"from functools import reduce\n",
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"# from objproxies import LazyProxy\n",
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"import json\n",
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"from copy import deepcopy, copy\n",
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"from pipetools import pipe\n",
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"from functools import partial"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"state_dict = {\n",
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" 's1': 2,\n",
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" 's2': 4,\n",
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" 's3': 300\n",
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"}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"# def pipeline(*steps):\n",
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"# return reduce(lambda x, y: y(x), list(steps))\n",
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"# def compose(*funcs):\n",
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"# return lambda x: reduce(lambda f, g: g(f), list(funcs), x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [],
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"source": [
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"# ToDo:\n",
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"# Handle case where Mechanisms have no input. Perhaps the sentinel value of 0"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [],
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"source": [
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"# UI Behavior Mechanisms per Mechanism\n",
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"def b1m1(s):\n",
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" return s['s1']\n",
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"def b2m1(s):\n",
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" return s['s1'] * s['s2']\n",
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"\n",
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"def b1m2(s):\n",
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" return s['s1']\n",
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"def b2m2(s):\n",
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" return s['s1'] / s['s2']\n",
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"\n",
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"# UI State Mechanisms per Mechanism\n",
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"def s1m1(s, _input):\n",
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" s['s1'] = s['s1']**2 + _input\n",
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"def s2m1(s, _input):\n",
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" s['s2'] = s['s2'] + 1 + _input \n",
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"def s3m1(s, _input):\n",
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" s['s3'] = s['s3']\n",
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"\n",
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"def s1m2(s, _input):\n",
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" s['s1'] = s['s1'] + _input\n",
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"def s2m2(s, _input):\n",
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" s['s2'] = s['s2']\n",
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"def s3m2(s, _input):\n",
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" s['s3'] = s['s3'] + 1\n",
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" \n",
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"j = {\n",
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" \"m1\": {\n",
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" \"behaviors\": {\n",
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" \"b1\": b1m1,\n",
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" \"b2\": b2m1\n",
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" },\n",
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" \"states\": {\n",
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" \"s1\": s1m1,\n",
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" \"s2\": s2m1,\n",
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" \"s3\": s3m1\n",
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" }\n",
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" },\n",
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" \"m2\": {\n",
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" \"behaviors\": {\n",
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" \"b1\": b1m2,\n",
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" \"b2\": b2m2\n",
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" },\n",
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" \"states\": {\n",
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" \"s1\": s1m2,\n",
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" \"s2\": s2m2,\n",
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" \"s3\": s3m2\n",
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" }\n",
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" }\n",
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"}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 57,
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"metadata": {},
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"outputs": [],
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"source": [
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"def generate_configs(j):\n",
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" return list(\n",
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" map(\n",
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" lambda x: (\n",
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" list(j[x][\"states\"].values()),\n",
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" list(j[x][\"behaviors\"].values())\n",
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" ), \n",
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" j.keys()\n",
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" )\n",
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" )\n",
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"\n",
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"def getColResults(s, funcs):\n",
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" return list(map(lambda f: f(s), funcs))\n",
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"\n",
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"def getBehaviorInput(s, funcs): \n",
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" return op.foldr(_ + _)(getColResults(s, funcs))\n",
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"\n",
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"def mech_step(sL, state_funcs, behavior_funcs):\n",
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" in_copy, out_copy, mutatable_copy = deepcopy(sL), deepcopy(sL), deepcopy(sL)\n",
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" last_in_obj, last_mut_obj = in_copy[-1], mutatable_copy[-1]\n",
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" \n",
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" _input = getBehaviorInput(last_in_obj, behavior_funcs)\n",
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"\n",
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" for f in state_funcs:\n",
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" f(last_mut_obj, _input)\n",
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" \n",
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" out_copy.append(last_mut_obj)\n",
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" return out_copy\n",
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"\n",
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"def pipeline(states_list, configs):\n",
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" for config in configs:\n",
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" s_conf, b_conf = config[0], config[1]\n",
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" states_list = mech_step(states_list, s_conf, b_conf)\n",
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" return states_list"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 59,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[{'s1': 2, 's2': 4, 's3': 300},\n",
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" {'s1': 14, 's2': 15, 's3': 300},\n",
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" {'s1': 28.933333333333334, 's2': 15, 's3': 301}]"
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]
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},
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"execution_count": 59,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"states_list = [state_dict]\n",
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"configs = generate_configs(j)\n",
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"pipeline(states_list, configs)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 60,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[{'s1': 2, 's2': 4, 's3': 300}]"
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]
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},
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"execution_count": 60,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"states_list"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 44,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[([<function __main__.s1m1(s, _input)>,\n",
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" <function __main__.s2m1(s, _input)>,\n",
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" <function __main__.s3m1(s, _input)>],\n",
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" [<function __main__.b1m1(s)>, <function __main__.b2m1(s)>]),\n",
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" ([<function __main__.s1m2(s, _input)>,\n",
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" <function __main__.s2m2(s, _input)>,\n",
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" <function __main__.s3m2(s, _input)>],\n",
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" [<function __main__.b1m2(s)>, <function __main__.b2m2(s)>])]"
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]
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},
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"execution_count": 44,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"sm1 = [s1m1, s2m1, s3m1]\n",
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"bm1 = [b1m1, b2m1]\n",
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"\n",
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"sm2 = [s1m2, s2m2, s3m2]\n",
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"bm2 = [b1m2, b2m2]\n",
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"\n",
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"configs = [(sm1, bm1), (sm2, bm2)]\n",
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"configs"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 139,
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"metadata": {},
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"outputs": [],
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"source": [
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"# UI State Mechanisms\n",
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"\n",
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"# s['s1']^2 + (s['s1'] + (s['s1'] * s['s2']))\n",
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"# 14 = 4 + (2 + (2 * 4))\n",
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"def m(sL, s_funcs, b_funcs):\n",
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" dSL = deepcopy(sL)\n",
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" in_copy = deepcopy(sL)\n",
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" out_copy = deepcopy(sL)\n",
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" s = dSL[-1]\n",
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" _input = getColInput(in_copy[-1], b_funcs)\n",
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" \n",
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"# s['s1'] = s['s1']**2 + _input\n",
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"# s['s2'] = s['s2'] + 1 + _input\n",
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" for f in s_funcs:\n",
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" f(s, _input)\n",
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" \n",
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" out_copy.append(s)\n",
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" return out_copy\n",
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"\n",
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"# s['s1'] + (s['s1'] + (s['s1'] / s['s2']))\n",
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"# 28.9 = 14 + (14 + (14/15))\n",
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"def m2(sL):\n",
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" dSL = deepcopy(sL)\n",
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" s = dSL[-1]\n",
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" _input = getColInput(deepcopy(sL)[-1], [b1m2, b2m2])\n",
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" \n",
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" s['s1'] = s['s1'] + _input\n",
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" s['s2'] = s['s2']\n",
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" \n",
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" sL.append(s)\n",
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" return sL\n",
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"\n",
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"# def s2m1(sL):\n",
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"# s = deepcopy(sL)[-1]\n",
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"# s['s2'] = s['s2'] + 1 + getColInput(s, [b1m2, b2m2])\n",
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"# sL.append(s)\n",
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"# return sL\n",
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"\n",
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"# def s2m2(sL):\n",
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"# s = deepcopy(sL)[-1]\n",
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"# s['s2'] = s['s2']\n",
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"# sL.append(s)\n",
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"# return sL"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 152,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[{'s1': 2, 's2': 4, 's3': 300},\n",
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" {'s1': 14, 's2': 15, 's3': 300},\n",
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" {'s1': 28.933333333333334, 's2': 15, 's3': 300}]"
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]
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},
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"execution_count": 152,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"pipeline3(states_list, configs)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 96,
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"metadata": {
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"collapsed": true
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},
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"outputs": [
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{
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"ename": "TypeError",
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"evalue": "s1m1() missing 1 required positional argument: '_input'",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m-----------\u001b[0m",
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"\u001b[0;31mTypeError\u001b[0mTraceback (most recent call last)",
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"\u001b[0;32m<ipython-input-96-5f9e087e72ee>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mdSL\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mpipeline2\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstates_list\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0ms1m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ms1m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
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"\u001b[0;32m<ipython-input-96-5f9e087e72ee>\u001b[0m in \u001b[0;36mpipeline2\u001b[0;34m(sL, funcs)\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0mdSL\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdeepcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msL\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfuncs\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mdSL\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdSL\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mdSL\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mTypeError\u001b[0m: s1m1() missing 1 required positional argument: '_input'"
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]
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}
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],
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"source": [
|
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"def pipeline2(sL, funcs):\n",
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" dSL = deepcopy(sL)\n",
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" for f in funcs:\n",
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" dSL = f(dSL)\n",
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" return dSL\n",
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"\n",
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"pipeline2(states_list, [s1m1, s1m2])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 101,
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"metadata": {},
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"outputs": [],
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"source": [
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"state_dict = {\n",
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" 's1': 2,\n",
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" 's2': 4,\n",
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" 's3': 300\n",
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"}\n",
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"# l = [state_dict]\n",
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"# l.append(state_dict)\n",
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"# l\n",
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"# print(s1m1([state_dict]))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 97,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[{'s1': 2, 's2': 4, 's3': 300}]"
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]
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},
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"execution_count": 97,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"state_dict\n",
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"states_list = [state_dict]\n",
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"states_list"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 140,
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"metadata": {
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"collapsed": true
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},
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"outputs": [
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{
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"ename": "TypeError",
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"evalue": "'function' object is not subscriptable",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m-----------\u001b[0m",
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"\u001b[0;31mTypeError\u001b[0mTraceback (most recent call last)",
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"\u001b[0;32m<ipython-input-140-e6d630186e0f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mpipeline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms1m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ms1m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
|
||||
"\u001b[0;32m<ipython-input-104-17d92fdcc430>\u001b[0m in \u001b[0;36mpipeline\u001b[0;34m(*steps)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mpipeline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0msteps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mreduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msteps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mcompose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mfuncs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mreduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mg\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfuncs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m<ipython-input-104-17d92fdcc430>\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(x, y)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mpipeline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0msteps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mreduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msteps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mcompose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mfuncs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mreduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mg\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfuncs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;32m<ipython-input-137-dac038f7b2cf>\u001b[0m in \u001b[0;36ms1m2\u001b[0;34m(sL)\u001b[0m\n\u001b[1;32m 17\u001b[0m \u001b[0;31m# dSL = deepcopy(sL)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 18\u001b[0m \u001b[0;31m# s = dSL[-1]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 19\u001b[0;31m \u001b[0ms\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msL\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 20\u001b[0m \u001b[0ms\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m's1'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0ms\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m's1'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mgetColInput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mb1m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mb2m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 21\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0msL\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
||||
"\u001b[0;31mTypeError\u001b[0m: 'function' object is not subscriptable"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"pipeline(s1m1, s1m2)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 99,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[{'s1': 2, 's2': 4, 's3': 300}]"
|
||||
]
|
||||
},
|
||||
"execution_count": 99,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"pipeline2(states_list, [s1m1, s1m2])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 40,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# def a(x):\n",
|
||||
"# return x + 1\n",
|
||||
"# func = F() >> s1m1 >> s1m1\n",
|
||||
"# func(state_dict)\n",
|
||||
"def s1_pipe(x): return pipe | s1m1 | s1m2 "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 44,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"s1m1 | s1m2"
|
||||
]
|
||||
},
|
||||
"execution_count": 44,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"s1_pipe(state_dict)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 45,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'s1': 2, 's2': 4, 's3': 300}"
|
||||
]
|
||||
},
|
||||
"execution_count": 45,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"state_dict"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 125,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"6\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from functools import partial\n",
|
||||
"\n",
|
||||
"def multiply(x,y):\n",
|
||||
" return x * y\n",
|
||||
"\n",
|
||||
"# create a new function that multiplies by 2\n",
|
||||
"dbl = partial(multiply,2)\n",
|
||||
"print(dbl(4))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.6.5"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
|
|
@ -0,0 +1,877 @@
|
|||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 491,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import pandas as pd\n",
|
||||
"from scipy.stats import poisson\n",
|
||||
"import numpy as np\n",
|
||||
"import math\n",
|
||||
"import seaborn as sns\n",
|
||||
"import matplotlib as mpl\n",
|
||||
"import matplotlib.pyplot as plt"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# UTILS"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 492,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def bound_norm_random(low, high):\n",
|
||||
" res = np.random.normal((high+low)/2,(high-low)/6)\n",
|
||||
" if (res<low or res>high):\n",
|
||||
" res = bound_norm_random(low, high)\n",
|
||||
" return res"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# TYPE/PHASE"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 493,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"EXPERIMENT_TYPES = ['1 off run', 'Monte Carlo', 'Monte Carlo Parameter Sweep', 'Monte Carlo Pairwise']\n",
|
||||
"\n",
|
||||
"experiment_type = EXPERIMENT_TYPES[1]\n",
|
||||
"monte_carlo_runs = 100\n",
|
||||
"\n",
|
||||
"#correct number of runs if inconsistent with experiment type\n",
|
||||
"if (experiment_type == EXPERIMENT_TYPES[0]):\n",
|
||||
" monte_carlo_runs = 1"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# TIMESCALE"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 494,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"SECOND = 1\n",
|
||||
"MINUTE = 60*SECOND\n",
|
||||
"HOUR = 60*MINUTE\n",
|
||||
"DAY = 24*HOUR\n",
|
||||
"DURATION_OF_A_STEP = 1*DAY\n",
|
||||
"\n",
|
||||
"experiment_steps = 1000\n",
|
||||
"experiment_duration = experiment_steps * DURATION_OF_A_STEP\n",
|
||||
"time_array = np.arange(0,experiment_steps*DURATION_OF_A_STEP,DURATION_OF_A_STEP)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# MECHANISMS (dimension)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 495,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"mechanisms_names = ['mech_one', 'mech_two', 'mech_three']"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# STATES (dimension)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 496,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"states_names = ['a', 'b', 'c']\n",
|
||||
"states_data = [[np.zeros(experiment_steps)]*len(states_names)]*monte_carlo_runs\n",
|
||||
"states_data = np.zeros((monte_carlo_runs, experiment_steps, len(states_names)), dtype=int)\n",
|
||||
"# states_data is a 3-dimensional array - montecarlo, time, states\n",
|
||||
"# montecarlo[time[states]]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Initial Conditions"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 497,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"states_0 = {\n",
|
||||
" 'a': 0,\n",
|
||||
" 'b': 0,\n",
|
||||
" 'c': 300\n",
|
||||
"}\n",
|
||||
"# an initial condition must be set for every state\n",
|
||||
"assert np.array([k in states_0 for k in states_names]).all(), 'Error: The initial condition of one or more states is unkonwn'\n",
|
||||
"\n",
|
||||
"# copy initial condition to the states dataset\n",
|
||||
"for i in range(len(states_names)):\n",
|
||||
" states_data[:,0,i] = states_0[states_names[i]]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 498,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"T_0 = 0\n",
|
||||
"time_array = T_0 + time_array"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Mechanisms Coef (params)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 499,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"mech_one_coef_A = 0.05"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# MECHANISMS EQUATIONS (func)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 500,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# state/mechanism matrix\n",
|
||||
"def mech_one(_states_data, _time_array, _run, _step, args):\n",
|
||||
"# print('mech 1')\n",
|
||||
" _states_data[_run, _step, states_names.index('a')] += (1-mech_one_coef_A)*args[0]\n",
|
||||
" _states_data[_run, _step, states_names.index('b')] += mech_one_coef_A*args[0]\n",
|
||||
" return _states_data\n",
|
||||
"\n",
|
||||
"def mech_two(_states_data, _time_array, _run, _step, args):\n",
|
||||
"# print('mech 2')\n",
|
||||
" _states_data[_run, _step, states_names.index('a')] -= args[0]\n",
|
||||
" return _states_data\n",
|
||||
"\n",
|
||||
"def mech_three(_states_data, _time_array, _run, _step, args):\n",
|
||||
"# print('mech 3')\n",
|
||||
" _states_data[_run, _step, states_names.index('b')] -= args[0]\n",
|
||||
" return _states_data\n",
|
||||
"\n",
|
||||
"def mech_four(_states_data, _time_array, _run, _step):\n",
|
||||
"# print('mech 4')\n",
|
||||
" _states_data[_run, _step, states_names.index('a')] = _states_data[_run, _step-1, states_names.index('a')]\n",
|
||||
" _states_data[_run, _step, states_names.index('b')] = _states_data[_run, _step-1, states_names.index('b')] \n",
|
||||
" return _states_data\n",
|
||||
"\n",
|
||||
"mechanisms = [eval(m) for m in mechanisms_names]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Behavioral Model Coef (params) "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 501,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"behavior_one_coef_A = 0.01\n",
|
||||
"behavior_one_coef_B = -0.01\n",
|
||||
"\n",
|
||||
"behavior_two_coef_A = 1"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# BEHAVIORAL MODEL (func)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 502,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"behaviors_names = ['behavior_one', 'behavior_two']\n",
|
||||
"def behavior_one(_states_data, _time_array, _run, _step): \n",
|
||||
" c_var = ( _states_data[_run, _step, states_names.index('c')]\n",
|
||||
" - _states_data[_run, _step-1, states_names.index('c')] )\n",
|
||||
" c_var_perc = c_var / _states_data[_run, _step-1, states_names.index('c')]\n",
|
||||
" \n",
|
||||
" if (c_var_perc > behavior_one_coef_A):\n",
|
||||
" return mech_one(_states_data, _time_array, _run, _step, [c_var])\n",
|
||||
" elif (c_var_perc < behavior_one_coef_B):\n",
|
||||
" return mech_two(_states_data, _time_array, _run, _step, [-c_var])\n",
|
||||
" return _states_data\n",
|
||||
"\n",
|
||||
"def behavior_two(_states_data, _time_array, _run, _step):\n",
|
||||
" b_balance = _states_data[_run, _step-1, states_names.index('b')]\n",
|
||||
" if (b_balance > behavior_two_coef_A):\n",
|
||||
" return mech_three(_states_data, _time_array, _run, _step, [b_balance])\n",
|
||||
" return _states_data\n",
|
||||
"\n",
|
||||
"behaviors = [eval(b) for b in behaviors_names] "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# ENVIRONMENTAL PROCESS (dimension)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 503,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"env_proc_names = ['proc_one']"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Stochastic Process Coef (params)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 504,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"proc_one_coef_A = 0.7\n",
|
||||
"proc_one_coef_B = 1.3"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# ENVIRONMENTAL PROCESS (func)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 505,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def proc_one(_states_data, _time_array, _run, _step):\n",
|
||||
" _states_data[_run, _step, states_names.index('a')] = _states_data[_run, _step-1, states_names.index('a')]\n",
|
||||
" _states_data[_run, _step, states_names.index('b')] = _states_data[_run, _step-1, states_names.index('b')] \n",
|
||||
" _states_data[_run, _step, states_names.index('c')] = ( _states_data[_run, _step-1, states_names.index('c')]\n",
|
||||
" * bound_norm_random(proc_one_coef_A, proc_one_coef_B) )\n",
|
||||
" return _states_data\n",
|
||||
"\n",
|
||||
"env_proc = [eval(p) for p in env_proc_names]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# ENGINE"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 506,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"/Users/markusbkoch/.local/share/virtualenvs/DiffyQ-SimCAD-4_qpgnP9/lib/python3.6/site-packages/ipykernel_launcher.py:5: RuntimeWarning: invalid value encountered in long_scalars\n",
|
||||
" \"\"\"\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"for i in range(monte_carlo_runs):\n",
|
||||
" for t in range(1,experiment_steps):\n",
|
||||
" for p in env_proc:\n",
|
||||
" states_data = p(_states_data=states_data,\n",
|
||||
" _time_array=time_array, \n",
|
||||
" _run=i, \n",
|
||||
" _step=t)\n",
|
||||
" for b in behaviors:\n",
|
||||
" states_data = b(_states_data=states_data,\n",
|
||||
" _time_array=time_array, \n",
|
||||
" _run=i, \n",
|
||||
" _step=t) #behaviors have access to exogenous data @ step-1, not @ step"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# DATA COLLECTION"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 507,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th></th>\n",
|
||||
" <th>a</th>\n",
|
||||
" <th>b</th>\n",
|
||||
" <th>c</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th rowspan=\"30\" valign=\"top\">0</th>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>300</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>86400</th>\n",
|
||||
" <td>-7</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>293</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>172800</th>\n",
|
||||
" <td>-20</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>280</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>259200</th>\n",
|
||||
" <td>-86</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>214</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>345600</th>\n",
|
||||
" <td>-67</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>234</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>432000</th>\n",
|
||||
" <td>-67</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>233</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>518400</th>\n",
|
||||
" <td>-91</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>209</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>604800</th>\n",
|
||||
" <td>-99</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>201</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>691200</th>\n",
|
||||
" <td>-93</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>207</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>777600</th>\n",
|
||||
" <td>-104</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>196</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>864000</th>\n",
|
||||
" <td>-101</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>199</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>950400</th>\n",
|
||||
" <td>-86</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>214</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1036800</th>\n",
|
||||
" <td>-92</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>208</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1123200</th>\n",
|
||||
" <td>-92</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>210</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1209600</th>\n",
|
||||
" <td>-99</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>203</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1296000</th>\n",
|
||||
" <td>-122</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>180</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1382400</th>\n",
|
||||
" <td>-135</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>167</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1468800</th>\n",
|
||||
" <td>-161</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>141</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1555200</th>\n",
|
||||
" <td>-161</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>141</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1641600</th>\n",
|
||||
" <td>-187</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>115</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1728000</th>\n",
|
||||
" <td>-195</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>107</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1814400</th>\n",
|
||||
" <td>-201</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>101</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1900800</th>\n",
|
||||
" <td>-189</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>113</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1987200</th>\n",
|
||||
" <td>-189</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>112</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2073600</th>\n",
|
||||
" <td>-189</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>111</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2160000</th>\n",
|
||||
" <td>-191</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>109</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2246400</th>\n",
|
||||
" <td>-200</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>100</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2332800</th>\n",
|
||||
" <td>-206</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>94</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2419200</th>\n",
|
||||
" <td>-206</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>94</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2505600</th>\n",
|
||||
" <td>-218</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>82</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>...</th>\n",
|
||||
" <th>...</th>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" <td>...</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th rowspan=\"30\" valign=\"top\">99</th>\n",
|
||||
" <th>83808000</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>83894400</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>83980800</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>84067200</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>84153600</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>84240000</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>84326400</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>84412800</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>84499200</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>84585600</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>84672000</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>84758400</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>84844800</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>84931200</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>85017600</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>85104000</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>85190400</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>85276800</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>85363200</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>85449600</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>85536000</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>85622400</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>85708800</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>85795200</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>85881600</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>85968000</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>86054400</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>86140800</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>86227200</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>86313600</th>\n",
|
||||
" <td>-386</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" <td>0</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"<p>100000 rows × 3 columns</p>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" a b c\n",
|
||||
"0 0 0 0 300\n",
|
||||
" 86400 -7 0 293\n",
|
||||
" 172800 -20 0 280\n",
|
||||
" 259200 -86 0 214\n",
|
||||
" 345600 -67 1 234\n",
|
||||
" 432000 -67 1 233\n",
|
||||
" 518400 -91 1 209\n",
|
||||
" 604800 -99 1 201\n",
|
||||
" 691200 -93 1 207\n",
|
||||
" 777600 -104 1 196\n",
|
||||
" 864000 -101 1 199\n",
|
||||
" 950400 -86 1 214\n",
|
||||
" 1036800 -92 1 208\n",
|
||||
" 1123200 -92 1 210\n",
|
||||
" 1209600 -99 1 203\n",
|
||||
" 1296000 -122 1 180\n",
|
||||
" 1382400 -135 1 167\n",
|
||||
" 1468800 -161 1 141\n",
|
||||
" 1555200 -161 1 141\n",
|
||||
" 1641600 -187 1 115\n",
|
||||
" 1728000 -195 1 107\n",
|
||||
" 1814400 -201 1 101\n",
|
||||
" 1900800 -189 1 113\n",
|
||||
" 1987200 -189 1 112\n",
|
||||
" 2073600 -189 1 111\n",
|
||||
" 2160000 -191 1 109\n",
|
||||
" 2246400 -200 1 100\n",
|
||||
" 2332800 -206 1 94\n",
|
||||
" 2419200 -206 1 94\n",
|
||||
" 2505600 -218 1 82\n",
|
||||
"... ... .. ...\n",
|
||||
"99 83808000 -386 0 0\n",
|
||||
" 83894400 -386 0 0\n",
|
||||
" 83980800 -386 0 0\n",
|
||||
" 84067200 -386 0 0\n",
|
||||
" 84153600 -386 0 0\n",
|
||||
" 84240000 -386 0 0\n",
|
||||
" 84326400 -386 0 0\n",
|
||||
" 84412800 -386 0 0\n",
|
||||
" 84499200 -386 0 0\n",
|
||||
" 84585600 -386 0 0\n",
|
||||
" 84672000 -386 0 0\n",
|
||||
" 84758400 -386 0 0\n",
|
||||
" 84844800 -386 0 0\n",
|
||||
" 84931200 -386 0 0\n",
|
||||
" 85017600 -386 0 0\n",
|
||||
" 85104000 -386 0 0\n",
|
||||
" 85190400 -386 0 0\n",
|
||||
" 85276800 -386 0 0\n",
|
||||
" 85363200 -386 0 0\n",
|
||||
" 85449600 -386 0 0\n",
|
||||
" 85536000 -386 0 0\n",
|
||||
" 85622400 -386 0 0\n",
|
||||
" 85708800 -386 0 0\n",
|
||||
" 85795200 -386 0 0\n",
|
||||
" 85881600 -386 0 0\n",
|
||||
" 85968000 -386 0 0\n",
|
||||
" 86054400 -386 0 0\n",
|
||||
" 86140800 -386 0 0\n",
|
||||
" 86227200 -386 0 0\n",
|
||||
" 86313600 -386 0 0\n",
|
||||
"\n",
|
||||
"[100000 rows x 3 columns]"
|
||||
]
|
||||
},
|
||||
"execution_count": 507,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"data = pd.DataFrame(states_data[0], \n",
|
||||
" index=[[0]*experiment_steps, time_array], \n",
|
||||
" columns=states_names)\n",
|
||||
"for i in range(1,monte_carlo_runs):\n",
|
||||
" b = pd.DataFrame(states_data[i],\n",
|
||||
" index=[[i]*experiment_steps, time_array], \n",
|
||||
" columns=states_names)\n",
|
||||
" data = data.append(b)\n",
|
||||
"data"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "DiffyQ-SimCAD Env",
|
||||
"language": "python",
|
||||
"name": "diffyq-simcad"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.6.5"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
Loading…
Reference in New Issue