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,