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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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