PySD Development Pathway¶
High priority features, bugs, and other elements of active effort are listed on the github issue tracker. To get involved see Development Guidelines.
High Priority¶
Improve running speed using numpy.arrays instead of xarray.DataArrays
Adding unit and full tests for Xmile translation
Medium Priority¶
Improve model execution speed using cython, theano, numba, or another package
Low Priority¶
Import model component documentation in a way that enables doctest, to enable writing unit tests within the modeling environment
Handle simulating over timeseries
Implement run memoization to improve speed of larger analyses
Implement an interface for running the model over a range of conditions, build in intelligent parallelization.
Not Planned¶
Model Construction
Outputting models to XMILE or other formats
Ideas for Other Projects¶
SD-lint checker (units, modeling conventions, bounds/limits, etc)
Contribution to external Data Science tools to make them more appropriate for dynamic assistant
Current Features¶
Basic XMILE and Vensim parser
Established library structure and data formats
Simulation using existing Python integration tools
Integration with basic Python Data Science functionality
Run-at-a-time parameter modification
Time-variant exogenous inputs
Extended backends for storing parameters and output values
Demonstration of integration with Machine Learning/Monte Carlo/Statistical Methods
Python methods for programmatically manipulating SD model structure
Turn off and on ‘traces’ or records of the values of variables