Compartmental PK/PD Fit/Train page

[blakeaw]

Complete implementation of the compartmental PK/PD modeling "Fit/Train" page: pages/compartmental/fit.py

This page will allow users to upload concentration-time profiles, train PK/PD models to fit the data (model calibration), and estimate relevant PK parameters (e.g., distribution and elimination rate constants).

[blakeaw]

I think the first step is to develop a new PySB add-on that facilitates model fitting: https://github.com/Borealis-BioModeling/pysb-fit

I should be able to integrate some of the functionality from utilities like

• swarm_it: https://github.com/LoLab-MSM/swarm_it
• pydream_it: https://github.com/LoLab-MSM/pydream_it
• galibrate_it: https://github.com/blakeaw/GAlibrate/blob/master/galibrate/pysb/galibrate_it.py
• nestedsample_it: https://github.com/LoLab-MSM/Gleipnir/blob/master/gleipnir/pysb_utilities/nestedsample_it.py
  into a more unified implementation that supports different calibration methods. This would function similarly to the pysb simulators, possibly with an interface similar to scikit-learn models .fit function: e.g., something along the lines of calibrated = pysb.fit.stochastic_optimization.PSO.fit(model, observables, data) for particle swarm optimization.