Merge pull request #1 from BlockScience/master

merge

.gitignore

@@ -3,6 +3,7 @@ jupyter notebook
 .ipynb_checkpoints
 .DS_Store
 .idea
+.pytest_cache/
 notebooks
 *.egg-info
 __pycache__

AUTHORS.txt

@@ -16,14 +16,14 @@ Contributors:
 - Matthew V. Barlin
 - Michael Zargham
 - Zixuan Zhang
+- Charles Rice
 
 
 We’d also like to thank:
 - Andrew Clark
 - Nikhil Jamdade
 - Nick Hirannet
+- Jonathan Gabler
+- Chris Frazier
 - Harry Goodnight
 - Charlie Hoppes
-- Jonathan Gabler
-- Charles Rice
-

CONTRIBUTING.md

@@ -0,0 +1,21 @@
+# Contributing to cadCAD (Draft)
+
+:+1::tada: First off, thanks for taking the time to contribute! :tada::+1:
+
+The following is a set of guidelines for contributing to cadCAD. These are mostly guidelines, not rules. 
+Use your best judgment, and feel free to propose changes to this document in a pull request.
+
+### Pull Requests:
+
+Pull Request (PR) presented as "->".
+
+General Template:
+fork/branch -> BlockScience/staging
+
+Contributing a new feature:
+fork/feature -> BlockScience/staging
+
+Contributing to an existing feature:
+fork/feature -> BlockScience/feature
+
+Thanks! :heart:

README.md

@@ -32,7 +32,7 @@ under various conditions. Support for A/B testing policies, Monte Carlo analysis
 provided.
 
 
-In essence, cadCAD tool allows us to represent a company’s or community’s current business model along with a desired 
+For example, cadCAD tool allows us to represent a company’s or community’s current business model along with a desired 
 future state and helps make informed, rigorously tested decisions on how to get from today’s stage to the future state. 
 It allows us to use code to solidify our conceptualized ideas and see if the outcome meets our expectations. We can 
 iteratively refine our work until we have constructed a model that closely reflects reality at the start of the model, 
@@ -49,14 +49,19 @@ and see how it evolves. We can then use these results to inform business decisio
 
 **Python 3.6.5** :: Anaconda, Inc.
 
-**Option A:** Build From Source
+**Option A:** [PyPi](https://pypi.org/project/cadCAD/): pip install
+```bash
+pip install cadCAD
+```
+
+**Option B:** Build From Source
 ```bash
 pip3 install -r requirements.txt
 python3 setup.py sdist bdist_wheel
 pip3 install dist/*.whl
 ```
 
-**Option B:** Proprietary Build Access
+**Option C:** Proprietary Build Access
 
 ***IMPORTANT NOTE:*** Tokens are issued to those with access to proprietary builds of cadCAD and BlockScience employees **ONLY**. 
 Replace \<TOKEN\> with an issued token in the script below.

ascii_art.txt

@@ -0,0 +1,15 @@
+Complex Adaptive Dynamics
+o       i        e
+m       d        s
+p       e        i
+u       d        g
+t                n
+e
+r
+
+                    __________   ____
+  ________ __ _____/ ____/   |  / __ \
+ / ___/ __` / __  / /   / /| | / / / /
+/ /__/ /_/ / /_/ / /___/ ___ |/ /_/ /
+\___/\__,_/\__,_/\____/_/  |_/_____/
+by BlockScience

cadCAD/configuration/__init__.py

@@ -47,6 +47,8 @@ def append_configs(sim_configs={}, initial_state={}, seeds={}, raw_exogenous_sta
             partial_state_update_blocks=partial_state_update_blocks,
             policy_ops=policy_ops
         )
+        print(sim_configs)
+        #for each sim config create new config
         configs.append(config)
 
 

cadCAD/engine/simulation.py

@@ -222,10 +222,13 @@ class Executor:
 
             return first_timestep_per_run
 
+        tp = TPool(runs)
         pipe_run: List[List[Dict[str, Any]]] = flatten(
-            TPool().map(
+            tp.map(
                 lambda run: execute_run(sweep_dict, states_list, configs, env_processes, time_seq, run),
                 list(range(runs))
             )
         )
+
+        tp.clear()
         return pipe_run

setup.py

@@ -1,14 +1,22 @@
 from setuptools import setup, find_packages
 
-long_description = "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 the system \
-    within the action space of the mechanisms. Mathematical formulations of these economic games treat agent utility as \
-    derived from state rather than direct from action, creating a rich dynamic modeling framework. Simulations may be \
-    run with a range of initial conditions and parameters for states, behaviors, mechanisms, and environmental \
-    processes to understand and visualize network behavior under various conditions. Support for A/B testing policies, \
-    monte carlo analysis and other common numerical methods is provided."
+long_description = """
+cadCAD (complex adaptive systems computer-aided design) is a python based, unified modeling framework for stochastic 
+dynamical systems and differential games for research, validation, and Computer Aided Design of economic systems created 
+by BlockScience. It is capable of modeling systems at all levels of abstraction from Agent Based Modeling (ABM) to 
+System Dynamics (SD), and enabling smooth integration of computational social science simulations with empirical data 
+science workflows.
+
+
+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 the system within the action space of the mechanisms. 
+Mathematical formulations of these economic games treat agent utility as derived from the state rather than direct from 
+an action, creating a rich, dynamic modeling framework. Simulations may be run with a range of initial conditions and 
+parameters for states, behaviors, mechanisms, and environmental processes to understand and visualize network behavior 
+under various conditions. Support for A/B testing policies, Monte Carlo analysis, and other common numerical methods is 
+provided.
+"""
 
 setup(name='cadCAD',
       version='0.3.0',

tutorials/README.md

@@ -6,5 +6,6 @@ In this series, we introduce basic concepts of cadCAD and system modelling in ge
 [Part 3](robot-marbles-part-3/robot-marbles-part-3.ipynb) - From Synchronous to Asynchronous Time  
 [Part 4](robot-marbles-part-4/robot-marbles-part-4.ipynb) - Uncertainty and Stochastic Processes  
 [Part 5](robot-marbles-part-5/robot-marbles-part-5.ipynb) - Using class objects as state variables  
+[Part 6](robot-marbles-part-6/robot-marbles-part-6.ipynb) - A/B testing  
 
 Check out the [videos](videos) folder for detailed walkthroughs of each one of the tutorials.