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resolved ModuleNotFoundError

This commit is contained in:
Joshua E. Jodesty 2019-01-10 21:38:38 -05:00
parent 141680e3a1
commit 19503e3d32
6 changed files with 1911 additions and 190 deletions
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17
.gitignore vendored
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@ -1,15 +1,14 @@
demos
SimCAD
simularions
setup.py
build
.idea
.ipynb_checkpoints
.DS_Store
.idea
SimCAD.egg-info
__pycache__
Pipfile
Pipfile.lock
results
.mypy_cache
.mypy_cache
*.csv
*.txt
simulations/.ipynb_checkpoints
build
SimCAD.egg-info

37
demos/sim_test.py
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@ -1,37 +0,0 @@
import pandas as pd
from tabulate import tabulate
# The following imports NEED to be in the exact order
from SimCAD.engine import ExecutionMode, ExecutionContext, Executor
from simulations.validation import config1, config2
from SimCAD import configs
exec_mode = ExecutionMode()
print("Simulation Execution 1")
print()
first_config = [configs[0]] # from config1
single_proc_ctx = ExecutionContext(context=exec_mode.single_proc)
run1 = Executor(exec_context=single_proc_ctx, configs=first_config)
run1_raw_result, tensor_field = run1.main()
result = pd.DataFrame(run1_raw_result)
print()
print("Tensor Field:")
print(tabulate(tensor_field, headers='keys', tablefmt='psql'))
print("Output:")
print(tabulate(result, headers='keys', tablefmt='psql'))
print()
print("Simulation Execution 2: Pairwise Execution")
print()
multi_proc_ctx = ExecutionContext(context=exec_mode.multi_proc)
run2 = Executor(exec_context=multi_proc_ctx, configs=configs)
for raw_result, tensor_field in run2.main():
result = pd.DataFrame(raw_result)
print()
print("Tensor Field:")
print(tabulate(tensor_field, headers='keys', tablefmt='psql'))
print("Output:")
print(tabulate(result, headers='keys', tablefmt='psql'))
print()

137
demos/test.ipynb
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@ -1,137 +0,0 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import pandas as pd\n",
"\n",
"# The following imports NEED to be in the exact order\n",
"from SimCAD.engine import ExecutionMode, ExecutionContext, Executor\n",
"from simulations.validation import config1, config2\n",
"from SimCAD import configs\n",
"\n",
"exec_mode = ExecutionMode()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(\"Simulation Execution 1\")\n",
"print()\n",
"first_config = [configs[0]] # from config1\n",
"single_proc_ctx = ExecutionContext(context=exec_mode.single_proc)\n",
"run1 = Executor(exec_context=single_proc_ctx, configs=first_config)\n",
"run1_raw_result, raw_tensor_field = run1.main()\n",
"result = pd.DataFrame(run1_raw_result)\n",
"tensor_field = pd.DataFrame(raw_tensor_field)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(\"Tensor Field:\")\n",
"tensor_field"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(\"Output:\")\n",
"result"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(\"Simulation Execution 2: Pairwise Execution\")\n",
"print()\n",
"multi_proc_ctx = ExecutionContext(context=exec_mode.multi_proc)\n",
"run2 = Executor(exec_context=multi_proc_ctx, configs=configs)\n",
"results = []\n",
"tensor_fields = []\n",
"for raw_result, raw_tensor_field in run2.main():\n",
" results.append(pd.DataFrame(raw_result))\n",
" tensor_fields.append(pd.DataFrame(raw_tensor_field))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"\n",
"print(\"Tensor Field A:\")\n",
"tensor_fields[0]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(\"Output A:\")\n",
"results[0]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(\"Tensor Field B:\")\n",
"tensor_fields[1]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(\"Output B:\")\n",
"results[1]"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 0
}

4
setup.py
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@ -1,4 +1,4 @@
from setuptools import setup
from setuptools import setup, find_packages
long_description = "SimCAD is a differential games based simulation software package for research, validation, and \
Computer Aided Design of economic systems. An economic system is treated as a state based model and defined through \
@ -19,5 +19,5 @@ setup(name='SimCAD',
author='Joshua E. Jodesty',
author_email='joshua@block.science',
license='licenses',
packages=['SimCAD']
packages=find_packages() #['SimCAD']
)

7
simulations/sim_test.py
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@ -1,13 +1,11 @@
import pandas as pd
from tabulate import tabulate
# The following imports NEED to be in the exact same order
# The following imports NEED to be in the exact order
from SimCAD.engine import ExecutionMode, ExecutionContext, Executor
from simulations.validation import config_1, config_2
from simulations.validation import config1, config2
from SimCAD import configs
# ToDo: pass ExecutionContext with execution method as ExecutionContext input
exec_mode = ExecutionMode()
@ -18,7 +16,6 @@ single_proc_ctx = ExecutionContext(context=exec_mode.single_proc)
run1 = Executor(exec_context=single_proc_ctx, configs=first_config)
run1_raw_result, tensor_field = run1.main()
result = pd.DataFrame(run1_raw_result)
# result.to_csv('~/Projects/DiffyQ-SimCAD/results/config4.csv', sep=',')
print()
print("Tensor Field:")
print(tabulate(tensor_field, headers='keys', tablefmt='psql'))

1899
simulations/test.ipynb Normal file
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