constrains = [] # varyingParamStrings = ["Disc",r'$\mathrm{Square} \rightarrow \mathrm{Disc}$',"Rhombus",r'$\mathrm{Square} \rightarrow \mathrm{Disc}$',r'$\mathrm{Square} \rightarrow \mathrm{Disc} \rightarrow \mathrm{Rhombus}$'] # listOfModels = ["disc", "squareDisc","los", "squareDisc", "squareDiscLos"] # # listOfLearningCycles = ["1000", "1000", "1000", "1750", "2500"] # listOfLearningCycles = [ "2000", "3500","2000", "3500", "5000"] varyingParamStrings = ["Disc",r'$\mathrm{Square} \rightarrow \mathrm{Disc}$',"Rhombus",r'$\mathrm{Square} \rightarrow \mathrm{Disc}$',r'$\mathrm{Square} \rightarrow \mathrm{Disc} \rightarrow \mathrm{Rhombus}$'] listOfModels = ["disc", "squareDisc","los", "squareDisc", "squareDiscLos"] # listOfLearningCycles = ["1000", "1000", "1000", "1750", "2500"] listOfLearningCycles = [ "2000", "3500","2000", "3500", "5000"] for mod,cycl in zip(listOfModels,listOfLearningCycles): PARAMETERS.model = mod PARAMETERS.learningCycles = cycl constrains.append(PARAMETERS.getConstainsLabelsAreYStrings(xLabelStrings, XYDevMinMax)) PLOTTING.LEGEND_IN=False _PLOT.barWithDeviationConstrained(xLabelStrings, varyingParamStrings, PARAMETERS.colors, PARAMETERS.intervalColors, PARAMETERS.markers, figName, ylabel, False, logYScale, constrains, 1, 1, PARAMETERS.figSize) # _PLOT.plotWitMinMaxWithFillBetweenConstrained(labelStrings, PARAMETERS.colors, PARAMETERS.intervalColors, PARAMETERS.markers, # figName, xlabel, ylabel, False, logYScale, # constrains, 1, 1, PARAMETERS.figSize) # _PLOT.plotWithDeviationWithFillBetweenConstrained(labelStrings, PARAMETERS.colors, PARAMETERS.intervalColors, PARAMETERS.markers, # figName, xlabel, ylabel, True, logYScale, # constrains, 1, 1, PARAMETERS.figSize) # _PLOT.plotWitMinMaxWithFillBetweenConstrained(labelStrings, PARAMETERS.colors, PARAMETERS.intervalColors, PARAMETERS.markers, # figName, xlabel, ylabel, True, logYScale,
print(figName) varyingParamValues = ["0", "1000", "10000", "20000", "100000"] # varyingParamValues = ["0","500","1000","2000","4000","6000","10000","20000","50000","100000"] varyingParamStrings = [] for val in varyingParamValues: varyingParamStrings.append(r'$\mathcal{E}^N_{lifelong} = $' + val) PARAMETERS.isActiveLearning = "false" PARAMETERS.isSelfLearning = "true" PARAMETERS.isLearnFromNeighbors = "true" constrains = [] PARAMETERS.activeExploitationCycles = "0" constrains.append( PARAMETERS.getConstainsLabelsAreYStrings(xLabelStrings, XYDevMinMax)) PARAMETERS.isActiveExploitation = "true" for val in varyingParamValues[1:]: PARAMETERS.activeExploitationCycles = val constrains.append( PARAMETERS.getConstainsLabelsAreYStrings(xLabelStrings, XYDevMinMax)) PLOTTING.ROTATION = 0 _PLOT.barWithDeviationConstrained(xLabelStrings, varyingParamStrings, PARAMETERS.colors, PARAMETERS.intervalColors, PARAMETERS.markers, figName, ylabel, False, logYScale, constrains, 1, 100, PARAMETERS.figSize)
logYScale = False yStringLong = "" for label in labelStrings: yStringLong += label + "_" XYDevMinMax = [] for y, yDev, min, max in zip(yStringsAvg, yStringsDev, yStringsMin, yStringsMax): XYDevMinMax.append([xString, y, yDev, min, max]) figName = PARAMETERS.figPrefix + yStringLong + "_DepOn_" + xString + "-" + PARAMETERS.getFigName( ) + figEndName print(figName) constrains = PARAMETERS.getConstainsLabelsAreYStrings(labelStrings, XYDevMinMax) print(constrains) _PLOT.plotWithDeviationWithFillBetweenConstrained( labelStrings, PARAMETERS.colors, PARAMETERS.intervalColors, PARAMETERS.markers, figName, xlabel, ylabel, False, logYScale, constrains, 1, 100, PARAMETERS.figSize) _PLOT.plotWitMinMaxWithFillBetweenConstrained(labelStrings, PARAMETERS.colors, PARAMETERS.intervalColors, PARAMETERS.markers, figName, xlabel, ylabel, False, logYScale, constrains, 1, 100, PARAMETERS.figSize) _PLOT.plotWithDeviationWithFillBetweenConstrained( labelStrings, PARAMETERS.colors, PARAMETERS.intervalColors, PARAMETERS.markers, figName, xlabel, ylabel, True, logYScale, constrains,