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SeanMcOwenSeanMcOwen
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Finish testing
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‎simulation/__init__.py

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Original file line numberDiff line numberDiff line change
@@ -1,4 +1,11 @@
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from .config import state_base, params_base, experiments_map
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from .config import (
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state_base,
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params_base,
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experiments_map,
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state_test1,
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params_test1,
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params_test2,
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)
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from .preprocessing import compute_starting_total_length, check_d_probability
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from .postprocessing import (
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post_processing_function,

‎simulation/config/params.py

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@@ -9,6 +9,13 @@
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params_test1 = deepcopy(params_base)
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params_test1["DUMMY D Probability"] = 1
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params_test1["FP DUMMY Length-1 DEF Control Action"] = (
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"DUMMY Length-1 DEF D Probability Option"
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)
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params_test2 = deepcopy(params_base)
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params_test2["DUMMY D Probability"] = 0
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params_test2["FP DUMMY Length-1 DEF Control Action"] = (
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"DUMMY Length-1 DEF D Probability Option"
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)

‎tests/DUMMY Economic Test.ipynb

Lines changed: 99 additions & 17 deletions
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@@ -4,30 +4,112 @@
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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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{
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"ename": "AssertionError",
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"evalue": "Bring in a test state and test parameter set",
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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;31mAssertionError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mBring in a test state and test parameter set\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
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"\u001b[0;31mAssertionError\u001b[0m: Bring in a test state and test parameter set"
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]
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}
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],
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"outputs": [],
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"source": [
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"import sys\n",
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"import os\n",
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"\n",
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"sys.path.append(os.path.abspath('..'))\n",
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"\n",
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"\n",
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"from simulation import (params_test2, params_test1, state_test1, params_base, state_base, compute_starting_total_length, check_d_probability, post_processing_function,\n",
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" percent_ending_in_d_metric, average_d_count_metric, plot_length_single_simulation)\n",
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"\n",
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"#from math_spec_mapping import load_from_json\n",
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"\n",
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"# For development purposes\n",
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"sys.path.append(os.path.abspath('../..'))\n",
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"from MSML.src.math_spec_mapping import (load_from_json)\n",
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"\n",
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"from copy import deepcopy\n",
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"from src import math_spec_json\n",
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"\n",
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"ms = load_from_json(deepcopy(math_spec_json))\n",
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"\n",
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"blocks = [\"DUMMY Control Wiring\"] * 100\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"assert False, \"Bring in a test state and test parameter set that has 100% D and 0% D\"\n",
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"assert False, \"Also start time at T=100 and make sure time is appropriately updated\""
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"Time will be 200 instead of 100 for the first two experiments because of the test state setting as starting at time = 100"
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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": null,
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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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"source": [
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"experiment = {\"Name\": \"Test 1\",\n",
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" \"Param Modifications\": None,\n",
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" \"State Modifications\": None,\n",
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" \"Blocks\": blocks}\n",
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"\n",
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"state, params, msi, df, metrics= ms.run_experiment(experiment,\n",
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" params_test1,\n",
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" state_test1,\n",
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" post_processing_function,\n",
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" state_preperation_functions=[compute_starting_total_length],\n",
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" parameter_preperation_functions=[check_d_probability],\n",
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" metrics_functions=[percent_ending_in_d_metric,\n",
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" average_d_count_metric])\n",
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"\n",
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"assert metrics.to_dict() == {'Percent Ending in D': 1.0, 'Average D Count': 50.5}\n",
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"assert state[\"Time\"] == 200"
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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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"experiment = {\"Name\": \"Test 2\",\n",
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" \"Param Modifications\": None,\n",
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" \"State Modifications\": None,\n",
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" \"Blocks\": blocks}\n",
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"\n",
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"state, params, msi, df, metrics= ms.run_experiment(experiment,\n",
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" params_test2,\n",
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" state_test1,\n",
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" post_processing_function,\n",
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" state_preperation_functions=[compute_starting_total_length],\n",
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" parameter_preperation_functions=[check_d_probability],\n",
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" metrics_functions=[percent_ending_in_d_metric,\n",
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" average_d_count_metric])\n",
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"\n",
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"\n",
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"assert metrics.to_dict() == {'Percent Ending in D': 0, 'Average D Count': 0}\n",
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"assert state[\"Time\"] == 200"
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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": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"experiment = {\"Name\": \"Baseline\",\n",
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" \"Param Modifications\": None,\n",
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" \"State Modifications\": None,\n",
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" \"Blocks\": blocks}\n",
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"\n",
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"state, params, msi, df, metrics= ms.run_experiment(experiment,\n",
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" params_base,\n",
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" state_base,\n",
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" post_processing_function,\n",
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" state_preperation_functions=[compute_starting_total_length],\n",
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" parameter_preperation_functions=[check_d_probability],\n",
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" metrics_functions=[percent_ending_in_d_metric,\n",
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" average_d_count_metric])\n",
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"\n",
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"\n",
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"assert metrics.to_dict()['Average D Count'] >= 0 and metrics.to_dict()['Average D Count'] <= 50.5\n",
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"assert state[\"Time\"] == 100"
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]
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},
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{
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"cell_type": "code",

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