PySD Development Pathway ======================== High priority features, bugs, and other elements of active effort are listed on the `github issue tracker. `_ To get involved see :doc:`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