ccpn.AnalysisScreen.lib package

Module Documentation here

Submodules

ccpn.AnalysisScreen.lib.MixturesGeneration module

ccpn.AnalysisScreen.lib.SimulatedAnnealing module

ccpn.AnalysisScreen.lib.SimulatedAnnealing.annealling(mixtures, coolingMethod='Linear', startTemp=1000, finalTemp=0.01, maxSteps=1000, tempK=200, minDistance=0.01)[source]
ccpn.AnalysisScreen.lib.SimulatedAnnealing.calculateOverlapCount(compoundA, mixture, minimalOverlap)[source]

called from score single sampleComponent and sample

ccpn.AnalysisScreen.lib.SimulatedAnnealing.calculateTotalScore(mixturesDict, peaksDistance=0.01)[source]
ccpn.AnalysisScreen.lib.SimulatedAnnealing.findBestMixtures(mixturesSteps)[source]
ccpn.AnalysisScreen.lib.SimulatedAnnealing.getExponentialSteps(startTemp=1000.0, finalTemp=0.1, maxSteps=100)[source]
ccpn.AnalysisScreen.lib.SimulatedAnnealing.getLinearSteps(startTemp=1000.0, finalTemp=0.1, maxSteps=1000)[source]
ccpn.AnalysisScreen.lib.SimulatedAnnealing.getOverlappedCount(mixtureCompounds, minDist=0.01)[source]

called from score single sample

ccpn.AnalysisScreen.lib.SimulatedAnnealing.getProbability(scoreDiff, currentTemp, tempK)[source]
ccpn.AnalysisScreen.lib.SimulatedAnnealing.greedyMixtures(compounds, maxSize, minDistance, maxPeaksOverlapped=None)[source]
ccpn.AnalysisScreen.lib.SimulatedAnnealing.iterateAnnealing(mixtures, startTemp=1000, finalTemp=0.01, maxSteps=1000, tempK=200, coolingMethod='linear', nIterations=1, minDistance=0.01, minTotalScore=None)[source]
ccpn.AnalysisScreen.lib.SimulatedAnnealing.mixTwoMixturesDict(mixtures)[source]
ccpn.AnalysisScreen.lib.SimulatedAnnealing.randomDictMixtures(name, compounds, nMixtures)[source]
ccpn.AnalysisScreen.lib.SimulatedAnnealing.runCooling(type, startTemp=1000.0, finalTemp=0.1, maxSteps=1000)[source]
ccpn.AnalysisScreen.lib.SimulatedAnnealing.scoreCompound(compoundA, compoundB, minDist, scalingFactor=1)[source]
ccpn.AnalysisScreen.lib.SimulatedAnnealing.scoreCompound_OLD(compoundA, compoundB, minDist, scalingFactor=1)[source]

OLD slow keep for backup

ccpn.AnalysisScreen.lib.SimulatedAnnealing.scoreMixture(mixture, minDist)[source]
ccpn.AnalysisScreen.lib.SimulatedAnnealing.scoreMixture_(mixture, minDist)[source]

for refactoring