91 lines
3.1 KiB
Markdown
91 lines
3.1 KiB
Markdown
# SimCad
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**Warning**:
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**Do not** publish this package / software to **any** software repository **except** one permitted by BlockScience.
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**Description:**
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SimCAD is a differential games based simulation software package for research, validation, and Computer \
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Aided Design of economic systems. An economic system is treated as a state based model and defined through a \
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set of endogenous and exogenous state variables which are updated through mechanisms and environmental \
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processes, respectively. Behavioral models, which may be deterministic or stochastic, provide the evolution of \
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the system within the action space of the mechanisms. Mathematical formulations of these economic games \
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treat agent utility as derived from state rather than direct from action, creating a rich dynamic modeling framework.
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Simulations may be run with a range of initial conditions and parameters for states, behaviors, mechanisms, \
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and environmental processes to understand and visualize network behavior under various conditions. Support for \
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A/B testing policies, monte carlo analysis and other common numerical methods is provided.
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**1. Install Dependencies:**
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**Option A:** Package Repository Access
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*Note:* Tokens are issued to trial users and BlockScience employees. Please replace <TOKEN> with and issued token in the script below.
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```bash
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pip3 install pandas pathos fn tabulate
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pip3 install cadCAD --extra-index-url https://<TOKEN>@repo.fury.io/blockscience/
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```
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**Option B:** Build From Source
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```bash
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pip3 install -r requirements.txt
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python3 setup.py sdist bdist_wheel
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pip3 install dist/*.whl
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```
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**2. Configure Simulation:**
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Intructions:
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`/Simulation.md`
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Examples:
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`/simulations/validation/*`
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**3. Import SimCAD & Run Simulation:**
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Examples: `/simulations/example_run.py` or `/simulations/example_run.ipynb`
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`/simulations/example_run.py`:
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```python
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import pandas as pd
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from tabulate import tabulate
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# The following imports NEED to be in the exact order
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from SimCAD.engine import ExecutionMode, ExecutionContext, Executor
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from validation import config1, config2
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from SimCAD import configs
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exec_mode = ExecutionMode()
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print("Simulation Execution 1")
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print()
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first_config = [configs[0]] # from config1
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single_proc_ctx = ExecutionContext(context=exec_mode.single_proc)
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run1 = Executor(exec_context=single_proc_ctx, configs=first_config)
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run1_raw_result, tensor_field = run1.main()
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result = pd.DataFrame(run1_raw_result)
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print()
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print("Tensor Field:")
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print(tabulate(tensor_field, headers='keys', tablefmt='psql'))
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print("Output:")
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print(tabulate(result, headers='keys', tablefmt='psql'))
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print()
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print("Simulation Execution 2: Pairwise Execution")
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print()
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multi_proc_ctx = ExecutionContext(context=exec_mode.multi_proc)
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run2 = Executor(exec_context=multi_proc_ctx, configs=configs)
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for raw_result, tensor_field in run2.main():
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result = pd.DataFrame(raw_result)
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print()
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print("Tensor Field:")
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print(tabulate(tensor_field, headers='keys', tablefmt='psql'))
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print("Output:")
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print(tabulate(result, headers='keys', tablefmt='psql'))
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print()
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```
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The above can be run in Jupyter.
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```bash
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jupyter notebook
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```git s |