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Joshua E. Jodesty 2019-02-21 15:09:19 -05:00
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# SimCad
# cadCAD
**Warning**:
**Do not** publish this package / software to **any** software repository **except** one permitted by BlockScience.
**Description:**
SimCAD is a differential games based simulation software package for research, validation, and Computer \
cadCAD 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 a \
set of endogenous and exogenous state variables which are updated through mechanisms and environmental \
processes, respectively. Behavioral models, which may be deterministic or stochastic, provide the evolution of \
@ -41,48 +41,89 @@ Intructions:
Examples:
`/simulations/validation/*`
**3. Import SimCAD & Run Simulation:**
**3. Import cadCAD & Run Simulations:**
Examples: `/simulations/example_run.py` or `/simulations/example_run.ipynb`
Examples: `/simulations/*.py` or `/simulations/*.ipynb`
`/simulations/example_run.py`:
Single Simulation Run: `/simulations/single_config_run.py`
```python
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 validation import config1, config2
from SimCAD import configs
from cadCAD.engine import ExecutionMode, ExecutionContext, Executor
from simulations.validation import config1
from cadCAD import configs
exec_mode = ExecutionMode()
print("Simulation Execution 1")
print("Simulation Execution: Single Configuration")
print()
first_config = [configs[0]] # from config1
first_config = configs # only contains 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("Tensor Field: config1")
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()
Parameter Sweep Simulation Run (Concurrent): `/simulations/param_sweep_run.py`
```python
import pandas as pd
from tabulate import tabulate
# The following imports NEED to be in the exact order
from cadCAD.engine import ExecutionMode, ExecutionContext, Executor
from simulations.validation import sweep_config
from cadCAD import configs
exec_mode = ExecutionMode()
print("Simulation Execution: Concurrent Execution")
multi_proc_ctx = ExecutionContext(context=exec_mode.multi_proc)
run2 = Executor(exec_context=multi_proc_ctx, configs=configs)
i = 0
config_names = ['sweep_config_A', 'sweep_config_B']
for raw_result, tensor_field in run2.main():
result = pd.DataFrame(raw_result)
print()
print("Tensor Field:")
print("Tensor Field: " + config_names[i])
print(tabulate(tensor_field, headers='keys', tablefmt='psql'))
print("Output:")
print(tabulate(result, headers='keys', tablefmt='psql'))
print()
i += 1
```
Multiple Simulation Runs (Concurrent): `/simulations/multi_config run.py`
```python
import pandas as pd
from tabulate import tabulate
# The following imports NEED to be in the exact order
from cadCAD.engine import ExecutionMode, ExecutionContext, Executor
from simulations.validation import config1, config2
from cadCAD import configs
exec_mode = ExecutionMode()
print("Simulation Execution: Concurrent Execution")
multi_proc_ctx = ExecutionContext(context=exec_mode.multi_proc)
run2 = Executor(exec_context=multi_proc_ctx, configs=configs)
i = 0
config_names = ['config1', 'config2']
for raw_result, tensor_field in run2.main():
result = pd.DataFrame(raw_result)
print()
print("Tensor Field: " + config_names[i])
print(tabulate(tensor_field, headers='keys', tablefmt='psql'))
print("Output:")
print(tabulate(result, headers='keys', tablefmt='psql'))
print()
i =+ 1
```
The above can be run in Jupyter.