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Efficient random sampling for COBRA models
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README.md

gapsplit

Efficient random sampling for constraint-based (COBRA) models. gapsplit samples both convex (LP) and non-convex (MILP) models by targeting unexplored regions of the solution space.

gapsplit is available for Matlab and Python.

Matlab

Installation

Download the gapsplit repository and add the matlab directory to Matlab's path. gapsplit requires the COBRA Toolbox with a QP solver (or MIQP solver to sample MILP models).

Test your gapsplit installation with the test_gapsplit script. (Be sure to initialize the COBRA Toolbox first.)

>> initCobraToolbox
>> test_gapsplit
Calculating feasible ranges for variables. (0.45 seconds)
Targeting 1 primary and 1 secondary variables.
Sampling LP model with 10/10 unblocked variables (100.00%).

Samples   Coverage   MinGap   Median   MaxGap     Elapsed     Remaining   Infeasible
 10/100     77.47%   0.1879   0.2499   0.2502        0.04          0.37            0
 20/100     88.10%   0.0943   0.1250   0.1258        0.07          0.28            0
 30/100     89.45%   0.0624   0.1234   0.1241        0.10          0.24            0
 40/100     94.04%   0.0476   0.0626   0.0629        0.13          0.20            0
 50/100     94.38%   0.0463   0.0623   0.0627        0.16          0.16            0
 60/100     94.70%   0.0331   0.0607   0.0623        0.19          0.13            0
 70/100     95.77%   0.0312   0.0407   0.0612        0.23          0.10            0
 80/100     96.61%   0.0278   0.0319   0.0461        0.26          0.06            0
 90/100     96.72%   0.0238   0.0314   0.0455        0.29          0.03            0
100/100     97.03%   0.0236   0.0312   0.0313        0.32          0.00            0

Using gapsplit

gapsplit is a single function called gapsplit. For more information, see help gapsplit.

Python

Citation

Keaty TC, Jensen PA. gapsplit: Efficient random sampling for non-convex constraint-based models. bioRxiv.

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