A sampling algorithm for convex and non-convex metabolic models
Project description
GapSplit is a sampling algorithm designed to generate uniform, high-coverage sample points on any metabolic model
regardless of convexity (i.e. logical/integer constraints).
Functions
- sample(fname, n_points, lower_bounds=None, upper_bounds=None, n_update=100, n_secondary=0)
Generate samples from a given input model.
- INPUT:
- fname - str
String representing path to model file (see gurobipy.read() for acceptable file types).
- n_points - int
Number of desired sample points.
- lower_bounds - list/ndarray, optional
FVA minimums for model. Generated if not provided.
- upper_bounds - list/ndarray, optional
FVA maximums for model. Generated if not provided.
- n_update - int, optional
Refresh rate (in points) for console output of current model coverage and sample count.
- n_secondary - int, optional
Number of additional gaps targeted for splitting.
- OUTPUT:
- samples - ndarray
n_points by n_reactions array of sample points.
Dependencies
gurobipy: 7.0 and up (requires download and license from gurobi.com - license provided free for academic users)
numpy: 1.14.5
Project details
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