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fix: fractionOfOptimum of getPfbaEnzymes for a negative optimum #25

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Merged
edkerk merged 1 commit into from
Nov 2, 2026
Merged

fix: fractionOfOptimum of getPfbaEnzymes for a negative optimum #25

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15 changes: 8 additions & 7 deletions src/flux_analysis/getPfbaEnzymes.m
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,10 @@
% (default: use model.c as given).
% fractionOfOptimum : double
% fraction of the optimal objective value to fix before minimising
% enzyme usage (default 1.0).
% enzyme usage (default 1.0). A value below 1.0 lets the objective fall
% by (1 - fractionOfOptimum) times the magnitude of its optimum, so it
% also applies to a negative optimum (for example the exchange flux of
% a nutrient that is maximised).
%
% Returns
% -------
Expand Down Expand Up @@ -89,12 +92,10 @@

% Fix the objective as a constraint, same "fake metabolite" technique
% solveLP's own minFlux=1 option uses (see solveLP.m).
target = fractionOfOptimum * solOrig.f;
if target > 0
target = target * 0.999999;
else
target = target * 1.000001;
end
% The objective may fall by (1 - fractionOfOptimum*0.999999) of the magnitude
% of its optimum, for a positive and a negative optimum alike (the band that
% setParam(model, 'var', ...) sets around a value).
target = solOrig.f - (1 - fractionOfOptimum*0.999999) * abs(solOrig.f);
fixModel = model;
fixModel.S(end+1, :) = model.c';
fixModel.mets{end+1, 1} = 'getPfbaEnzymes_objective';
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28 changes: 28 additions & 0 deletions test/unit_tests/geckoCoreFunctionTests.m
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Expand Up @@ -1264,6 +1264,34 @@ function testPfbaEnzymesMinimisesEnzymeUsage_tc0025(testCase)
end


function testPfbaEnzymesFractionOfNegativeOptimum_tc0285(testCase)
% Verifies that 'fractionOfOptimum' below 1 lets a negative optimum fall
% by that fraction of its magnitude. The objective is -R5 with R5 >= 10,
% so its optimum is -10; at 0.9 the objective may fall to -11, and the
% solution stays feasible with R5 at its lower bound.
geckoPath = findGECKOroot;
adapter = ModelAdapterManager.getAdapter(fullfile(geckoPath,'test','unit_tests','ecTestGEM', 'TestGEMAdapter.m'));
model = getGeckoTestModel();
ecModel = makeEcModel(model, false, adapter);
ecModel = getECfromGEM(ecModel);
ecModel.ec.kcat(:) = 10;
ecModel.ec.source(:) = {'manual'};
ecModel = applyKcatConstraints(ecModel);
ecModel = setProtPoolSize(ecModel, 0.5, 0.5, 0.5, adapter);
ecModel = setParam(ecModel, 'lb', 'R5', 10);
ecModel = setParam(ecModel, 'obj', 'R5', -1);

solution = getPfbaEnzymes(ecModel);
verifyEqual(testCase, solution.stat, 1)
verifyEqual(testCase, solution.objectiveValue, -10, 'RelTol', 1e-5)

solution = getPfbaEnzymes(ecModel, 'fractionOfOptimum', 0.9);
verifyEqual(testCase, solution.stat, 1)
verifyEqual(testCase, solution.objectiveValue, -10, 'RelTol', 1e-5)
verifyGreaterThanOrEqual(testCase, solution.objectiveValue, -11)
end


function ecModel = fixtureForRelaxProteomicsGreedy()
% Builds the shared fixture used by the relaxProteomicsGreedy tests below:
% ecTestGEM with uniform kcat=10 and protein pool sized via
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