def plotRug(self, noUpdate=False):
for rug in self.rugKeys:
rug.detach()
self.rugKeys = []
if self.master.showRug:
targetClass = self.master.targetClass
if self.contingency:
freqhigh = [
(val, freq[targetClass]) for val, freq in self.contingency.items() if freq[targetClass] > 1e-6
]
freqlow = [(val, freq.abs - freq[targetClass]) for val, freq in self.contingency.items()]
freqlow = [f for f in freqlow if f[1] > 1e-6]
elif self.probDist:
freqhigh = []
freqlow = self.probDist.items()
else:
return
if freqhigh:
maxf = max([f[1] for f in freqhigh])
if freqlow:
maxf = max(maxf, max([f[1] for f in freqlow]))
elif freqlow:
maxf = max([f[1] for f in freqlow])
else:
return
freqfac = maxf > 1e-6 and 0.1 / maxf or 1
xData = sum(([val, val] for val, freq in freqhigh), []) + sum(([val, val] for val, freq in freqlow), [])
yData = sum(([1.0, 1.0 - max(0.02, freqfac * freq)] for val, freq in freqhigh), []) + sum(
([0.04, 0.04 + max(0.02, freqfac * freq)] for val, freq in freqlow), []
)
c = UnconnectedLinesCurve("rug", xData=xData, yData=yData)
c.set_auto_scale(True)
c.set_y_axis(yRight)
self.add_custom_curve(c)
self.rugKeys.append(c)
if not noUpdate:
self.replot()
def plotRug(self, noUpdate = False):
for rug in self.rugKeys:
rug.detach()
self.rugKeys = []
if self.master.showRug:
targetClass = self.master.targetClass
if self.contingency:
freqhigh = [(val, freq[targetClass]) for val, freq in self.contingency.items() if freq[targetClass] > 1e-6]
freqlow = [(val, freq.abs - freq[targetClass]) for val, freq in self.contingency.items()]
freqlow = [f for f in freqlow if f[1] > 1e-6]
elif self.probDist:
freqhigh = []
freqlow = self.probDist.items()
else:
return
if freqhigh:
maxf = max([f[1] for f in freqhigh])
if freqlow:
maxf = max(maxf, max([f[1] for f in freqlow]))
elif freqlow:
maxf = max([f[1] for f in freqlow])
else:
return
freqfac = maxf > 1e-6 and .1 / maxf or 1
xData = sum(([val, val] for val, freq in freqhigh), []) + sum(([val, val] for val, freq in freqlow), [])
yData = sum(([1.0, 1.0 - max(0.02, freqfac * freq)] for val, freq in freqhigh), []) + sum(([0.04, 0.04 + max(.02, freqfac * freq)] for val, freq in freqlow), [])
c = UnconnectedLinesCurve('rug', xData = xData, yData = yData)
c.set_auto_scale(True)
c.set_y_axis(yRight)
self.add_custom_curve(c)
self.rugKeys.append(c)
if not noUpdate:
self.replot()
def updateData(self, labels = None, setAnchors = 0, **args):
for c in self._extra_curves:
c.detach()
self._extra_curves = []
self.tooltipMarkers = []
for c in self.value_line_curves:
c.detach()
self.value_line_curves = []
self.legend().clear()
self.clear_markers()
self.__dict__.update(args)
if labels == None: labels = [anchor[2] for anchor in self.anchorData]
self.shownAttributes = labels
self.dataMap = {} # dictionary with keys of form "x_i-y_i" with values (x_i, y_i, color, data)
self.valueLineCurves = [{}, {}] # dicts for x and y set of coordinates for unconnected lines
if not self.haveData or len(labels) < 3:
self.anchorData = []
self.updateLayout()
return
if setAnchors or (args.has_key("XAnchors") and args.has_key("YAnchors")):
self.potentialsBmp = None
self.setAnchors(args.get("XAnchors"), args.get("YAnchors"), labels)
#self.anchorData = self.createAnchors(len(labels), labels) # used for showing tooltips
indices = [self.attributeNameIndex[anchor[2]] for anchor in self.anchorData] # store indices to shown attributes
# do we want to show anchors and their labels
if self.showAnchors:
if self.hideRadius > 0:
circle = CircleCurve(QColor(200,200,200), QColor(200,200,200), radius = self.hideRadius)
circle.ignore_alpha = True
self.add_custom_curve(circle)
self._extra_curves.append(circle)
# draw dots at anchors
shownAnchorData = filter(lambda p, r=self.hideRadius**2/100: p[0]**2+p[1]**2>r, self.anchorData)
self.remove_all_axes(user_only = False)
if not self.normalizeExamples:
r=self.hideRadius**2/100
for i,(x,y,a) in enumerate(shownAnchorData):
if x > 0:
line = QLineF(0, 0, x, y)
arrows = AxisEnd
label_pos = AxisEnd
else:
line = QLineF(x, y, 0, 0)
arrows = AxisStart
label_pos = AxisStart
self.add_axis(UserAxis + i, title=a, title_location=label_pos, line=line, arrows=arrows, zoomable=True)
self.setAxisLabels(UserAxis + i, [])
else:
XAnchors = [a[0] for a in shownAnchorData]
YAnchors = [a[1] for a in shownAnchorData]
c = self.addCurve("dots", QColor(160,160,160), QColor(160,160,160), 10, style = Qt.NoPen, symbol = OWPoint.Ellipse, xData = XAnchors, yData = YAnchors, showFilledSymbols = 1)
c.ignore_alpha = True
self._extra_curves.append(c)
# draw text at anchors
if self.showAttributeNames:
for x, y, a in shownAnchorData:
self.addMarker(a, x*1.07, y*1.04, Qt.AlignCenter, bold = 1)
if self.showAnchors and self.normalizeExamples:
# draw "circle"
circle = CircleCurve()
circle.ignore_alpha = True
self.add_custom_curve(circle)
self._extra_curves.append(circle)
self.potentialsClassifier = None # remove the classifier so that repaint won't recompute it
self.updateLayout()
if self.dataHasDiscreteClass:
self.discPalette.setNumberOfColors(len(self.dataDomain.classVar.values))
useDifferentSymbols = self.useDifferentSymbols and self.dataHasDiscreteClass and len(self.dataDomain.classVar.values) < len(self.curveSymbols)
dataSize = len(self.rawData)
validData = self.getValidList(indices)
transProjData = self.createProjectionAsNumericArray(indices, validData = validData, scaleFactor = self.scaleFactor, normalize = self.normalizeExamples, jitterSize = -1, useAnchorData = 1, removeMissingData = 0)
if transProjData == None:
return
projData = transProjData.T
x_positions = projData[0]
y_positions = projData[1]
xPointsToAdd = {}
yPointsToAdd = {}
if self.potentialsCurve:
self.potentialsCurve.detach()
self.potentialsCurve = None
if self.showProbabilities and self.haveData and self.dataHasClass:
# construct potentialsClassifier from unscaled positions
domain = orange.Domain([self.dataDomain[i].name for i in indices]+[self.dataDomain.classVar.name], self.dataDomain)
offsets = [self.attrValues[self.attributeNames[i]][0] for i in indices]
normalizers = [self.getMinMaxVal(i) for i in indices]
selectedData = numpy.take(self.originalData, indices, axis = 0)
averages = numpy.average(numpy.compress(validData, selectedData, axis=1), 1)
classData = numpy.compress(validData, self.originalData[self.dataClassIndex])
if classData.any():
self.potentialsClassifier = orange.P2NN(domain, numpy.transpose(numpy.array([numpy.compress(validData, self.unscaled_x_positions), numpy.compress(validData, self.unscaled_y_positions), classData])), self.anchorData, offsets, normalizers, averages, self.normalizeExamples, law=1)
self.potentialsCurve = ProbabilitiesItem(self.potentialsClassifier, self.squareGranularity, self.trueScaleFactor/2, self.spaceBetweenCells, QRectF(-1, -1, 2, 2))
self.potentialsCurve.attach(self)
else:
self.potentialsClassifier = None
self.potentialsImage = None
if self.useDifferentColors:
if self.dataHasDiscreteClass:
color_data = [QColor(*self.discPalette.getRGB(i)) for i in self.originalData[self.dataClassIndex]]
elif self.dataHasContinuousClass:
color_data = [QColor(*self.contPalette.getRGB(i)) for i in self.originalData[self.dataClassIndex]]
else:
color_data = [Qt.black]
else:
color_data = [Qt.black]
if self.useDifferentSymbols and self.dataHasDiscreteClass:
symbol_data = [self.curveSymbols[int(i)] for i in self.originalData[self.dataClassIndex]]
else:
symbol_data = [OWPoint.Ellipse]
size_data = [self.point_width]
label_data = []
if self.haveSubsetData:
subset_ids = [example.id for example in self.rawSubsetData]
marked_data = [example.id in subset_ids for example in self.rawData]
showFilled = 0
else:
marked_data = []
self.set_main_curve_data(x_positions, y_positions, color_data, label_data, size_data, symbol_data, marked_data, validData)
# ##############################################################
# show model quality
# ##############################################################
if self.insideColors != None or self.showKNN and self.haveData:
# if we want to show knn classifications of the examples then turn the projection into example table and run knn
if self.insideColors:
insideData, stringData = self.insideColors
else:
shortData = self.createProjectionAsExampleTable([self.attributeNameIndex[attr] for attr in labels], useAnchorData = 1)
predictions, probabilities = self.widget.vizrank.kNNClassifyData(shortData)
if self.showKNN == 2: insideData, stringData = [1.0 - val for val in predictions], "Probability of wrong classification = %.2f%%"
else: insideData, stringData = predictions, "Probability of correct classification = %.2f%%"
if self.dataHasDiscreteClass: classColors = self.discPalette
elif self.dataHasContinuousClass: classColors = self.contPalette
if len(insideData) != len(self.rawData):
j = 0
for i in range(len(self.rawData)):
if not validData[i]: continue
if self.dataHasClass:
fillColor = classColors.getRGB(self.originalData[self.dataClassIndex][i], 255*insideData[j])
edgeColor = classColors.getRGB(self.originalData[self.dataClassIndex][i])
else:
fillColor = edgeColor = (0,0,0)
if self.showValueLines:
self.addValueLineCurve(x_positions[i], y_positions[i], edgeColor, i, indices)
self.addTooltipKey(x_positions[i], y_positions[i], QColor(*edgeColor), i, stringData % (100*insideData[j]))
j+= 1
else:
for i in range(len(self.rawData)):
if not validData[i]: continue
if self.dataHasClass:
fillColor = classColors.getRGB(self.originalData[self.dataClassIndex][i], 255*insideData[i])
edgeColor = classColors.getRGB(self.originalData[self.dataClassIndex][i])
else:
fillColor = edgeColor = (0,0,0)
if self.showValueLines:
self.addValueLineCurve(x_positions[i], y_positions[i], edgeColor, i, indices)
self.addTooltipKey(x_positions[i], y_positions[i], QColor(*edgeColor), i, stringData % (100*insideData[i]))
# ##############################################################
# do we have a subset data to show?
# ##############################################################
elif self.haveSubsetData:
shownSubsetCount = 0
subsetIdsToDraw = dict([(example.id,1) for example in self.rawSubsetData])
# draw the rawData data set. examples that exist also in the subset data draw full, other empty
for i in range(dataSize):
if not validData[i]: continue
if subsetIdsToDraw.has_key(self.rawData[i].id):
continue
if self.dataHasDiscreteClass and self.useDifferentColors:
newColor = self.discPalette.getRGB(self.originalData[self.dataClassIndex][i])
elif self.dataHasContinuousClass and self.useDifferentColors:
newColor = self.contPalette.getRGB(self.noJitteringScaledData[self.dataClassIndex][i])
else:
newColor = (0,0,0)
if self.useDifferentSymbols and self.dataHasDiscreteClass:
curveSymbol = self.curveSymbols[int(self.originalData[self.dataClassIndex][i])]
else:
curveSymbol = self.curveSymbols[0]
if self.showValueLines:
self.addValueLineCurve(x_positions[i], y_positions[i], newColor, i, indices)
self.addTooltipKey(x_positions[i], y_positions[i], QColor(*newColor), i)
elif not self.dataHasClass:
xs = []; ys = []
for i in range(dataSize):
if not validData[i]: continue
xs.append(x_positions[i])
ys.append(y_positions[i])
self.addTooltipKey(x_positions[i], y_positions[i], QColor(Qt.black), i)
if self.showValueLines:
self.addValueLineCurve(x_positions[i], y_positions[i], (0,0,0), i, indices)
# ##############################################################
# CONTINUOUS class
# ##############################################################
elif self.dataHasContinuousClass:
for i in range(dataSize):
if not validData[i]: continue
newColor = self.contPalette.getRGB(self.noJitteringScaledData[self.dataClassIndex][i])
if self.showValueLines:
self.addValueLineCurve(x_positions[i], y_positions[i], newColor, i, indices)
self.addTooltipKey(x_positions[i], y_positions[i], QColor(*newColor), i)
# ##############################################################
# DISCRETE class
# ##############################################################
elif self.dataHasDiscreteClass:
for i in range(dataSize):
if not validData[i]: continue
if self.useDifferentColors: newColor = self.discPalette.getRGB(self.originalData[self.dataClassIndex][i])
else: newColor = (0,0,0)
if self.showValueLines:
self.addValueLineCurve(x_positions[i], y_positions[i], newColor, i, indices)
self.addTooltipKey(x_positions[i], y_positions[i], QColor(*newColor), i)
# first draw value lines
if self.showValueLines:
for i, color in enumerate(self.valueLineCurves[0].keys()):
curve = UnconnectedLinesCurve("", QPen(QColor(*color + (self.alphaValue,))), self.valueLineCurves[0][color], self.valueLineCurves[1][color])
curve.attach(self)
self.value_line_curves.append(curve)
# ##############################################################
# draw the legend
# ##############################################################
# show legend for discrete class
if self.dataHasDiscreteClass:
classVariableValues = getVariableValuesSorted(self.dataDomain.classVar)
for index in range(len(classVariableValues)):
if self.useDifferentColors: color = QColor(self.discPalette[index])
else: color = QColor(Qt.black)
if not self.useDifferentSymbols: curveSymbol = self.curveSymbols[0]
else: curveSymbol = self.curveSymbols[index]
self.legend().add_item(self.dataDomain.classVar.name, classVariableValues[index], OWPoint(curveSymbol, color, self.pointWidth))
# show legend for continuous class
elif self.dataHasContinuousClass:
self.legend().add_color_gradient(self.dataDomain.classVar.name, [("%%.%df" % self.dataDomain.classVar.numberOfDecimals % v) for v in self.attrValues[self.dataDomain.classVar.name]])
self.replot()
def updateData(self, labels=None, setAnchors=0, **args):
for c in self._extra_curves:
c.detach()
self._extra_curves = []
self.tooltipMarkers = []
for c in self.value_line_curves:
c.detach()
self.value_line_curves = []
self.legend().clear()
self.clear_markers()
self.__dict__.update(args)
if labels == None: labels = [anchor[2] for anchor in self.anchorData]
self.shownAttributes = labels
self.dataMap = {
} # dictionary with keys of form "x_i-y_i" with values (x_i, y_i, color, data)
self.valueLineCurves = [
{}, {}
] # dicts for x and y set of coordinates for unconnected lines
if not self.haveData or len(labels) < 3:
self.anchorData = []
self.updateLayout()
return
if setAnchors or (args.has_key("XAnchors")
and args.has_key("YAnchors")):
self.potentialsBmp = None
self.setAnchors(args.get("XAnchors"), args.get("YAnchors"), labels)
#self.anchorData = self.createAnchors(len(labels), labels) # used for showing tooltips
indices = [
self.attributeNameIndex[anchor[2]] for anchor in self.anchorData
] # store indices to shown attributes
# do we want to show anchors and their labels
if self.showAnchors:
if self.hideRadius > 0:
circle = CircleCurve(QColor(200, 200, 200),
QColor(200, 200, 200),
radius=self.hideRadius)
circle.ignore_alpha = True
self.add_custom_curve(circle)
self._extra_curves.append(circle)
# draw dots at anchors
shownAnchorData = filter(
lambda p, r=self.hideRadius**2 / 100: p[0]**2 + p[1]**2 > r,
self.anchorData)
self.remove_all_axes(user_only=False)
if not self.normalizeExamples:
r = self.hideRadius**2 / 100
for i, (x, y, a) in enumerate(shownAnchorData):
if x > 0:
line = QLineF(0, 0, x, y)
arrows = AxisEnd
label_pos = AxisEnd
else:
line = QLineF(x, y, 0, 0)
arrows = AxisStart
label_pos = AxisStart
self.add_axis(UserAxis + i,
title=a,
title_location=label_pos,
line=line,
arrows=arrows,
zoomable=True)
self.setAxisLabels(UserAxis + i, [])
else:
XAnchors = [a[0] for a in shownAnchorData]
YAnchors = [a[1] for a in shownAnchorData]
c = self.addCurve("dots",
QColor(160, 160, 160),
QColor(160, 160, 160),
10,
style=Qt.NoPen,
symbol=OWPoint.Ellipse,
xData=XAnchors,
yData=YAnchors,
showFilledSymbols=1)
c.ignore_alpha = True
self._extra_curves.append(c)
# draw text at anchors
if self.showAttributeNames:
for x, y, a in shownAnchorData:
self.addMarker(a,
x * 1.07,
y * 1.04,
Qt.AlignCenter,
bold=1)
if self.showAnchors and self.normalizeExamples:
# draw "circle"
circle = CircleCurve()
circle.ignore_alpha = True
self.add_custom_curve(circle)
self._extra_curves.append(circle)
self.potentialsClassifier = None # remove the classifier so that repaint won't recompute it
self.updateLayout()
if self.dataHasDiscreteClass:
self.discPalette.setNumberOfColors(
len(self.dataDomain.classVar.values))
useDifferentSymbols = self.useDifferentSymbols and self.dataHasDiscreteClass and len(
self.dataDomain.classVar.values) < len(self.curveSymbols)
dataSize = len(self.rawData)
validData = self.getValidList(indices)
transProjData = self.createProjectionAsNumericArray(
indices,
validData=validData,
scaleFactor=self.scaleFactor,
normalize=self.normalizeExamples,
jitterSize=-1,
useAnchorData=1,
removeMissingData=0)
if transProjData == None:
return
projData = transProjData.T
x_positions = projData[0]
y_positions = projData[1]
xPointsToAdd = {}
yPointsToAdd = {}
if self.potentialsCurve:
self.potentialsCurve.detach()
self.potentialsCurve = None
if self.showProbabilities and self.haveData and self.dataHasClass:
# construct potentialsClassifier from unscaled positions
domain = orange.Domain([self.dataDomain[i].name for i in indices] +
[self.dataDomain.classVar.name],
self.dataDomain)
offsets = [
self.attrValues[self.attributeNames[i]][0] for i in indices
]
normalizers = [self.getMinMaxVal(i) for i in indices]
selectedData = numpy.take(self.originalData, indices, axis=0)
averages = numpy.average(
numpy.compress(validData, selectedData, axis=1), 1)
classData = numpy.compress(validData,
self.originalData[self.dataClassIndex])
if classData.any():
self.potentialsClassifier = orange.P2NN(
domain,
numpy.transpose(
numpy.array([
numpy.compress(validData,
self.unscaled_x_positions),
numpy.compress(validData,
self.unscaled_y_positions),
classData
])),
self.anchorData,
offsets,
normalizers,
averages,
self.normalizeExamples,
law=1)
self.potentialsCurve = ProbabilitiesItem(
self.potentialsClassifier, self.squareGranularity,
self.trueScaleFactor / 2, self.spaceBetweenCells,
QRectF(-1, -1, 2, 2))
self.potentialsCurve.attach(self)
else:
self.potentialsClassifier = None
self.potentialsImage = None
if self.useDifferentColors:
if self.dataHasDiscreteClass:
color_data = [
QColor(*self.discPalette.getRGB(i))
for i in self.originalData[self.dataClassIndex]
]
elif self.dataHasContinuousClass:
color_data = [
QColor(*self.contPalette.getRGB(i))
for i in self.originalData[self.dataClassIndex]
]
else:
color_data = [Qt.black]
else:
color_data = [Qt.black]
if self.useDifferentSymbols and self.dataHasDiscreteClass:
symbol_data = [
self.curveSymbols[int(i)]
for i in self.originalData[self.dataClassIndex]
]
else:
symbol_data = [OWPoint.Ellipse]
size_data = [self.point_width]
label_data = []
if self.haveSubsetData:
subset_ids = [example.id for example in self.rawSubsetData]
marked_data = [
example.id in subset_ids for example in self.rawData
]
showFilled = 0
else:
marked_data = []
self.set_main_curve_data(x_positions, y_positions, color_data,
label_data, size_data, symbol_data,
marked_data, validData)
# ##############################################################
# show model quality
# ##############################################################
if self.insideColors != None or self.showKNN and self.haveData:
# if we want to show knn classifications of the examples then turn the projection into example table and run knn
if self.insideColors:
insideData, stringData = self.insideColors
else:
shortData = self.createProjectionAsExampleTable(
[self.attributeNameIndex[attr] for attr in labels],
useAnchorData=1)
predictions, probabilities = self.widget.vizrank.kNNClassifyData(
shortData)
if self.showKNN == 2:
insideData, stringData = [
1.0 - val for val in predictions
], "Probability of wrong classification = %.2f%%"
else:
insideData, stringData = predictions, "Probability of correct classification = %.2f%%"
if self.dataHasDiscreteClass: classColors = self.discPalette
elif self.dataHasContinuousClass: classColors = self.contPalette
if len(insideData) != len(self.rawData):
j = 0
for i in range(len(self.rawData)):
if not validData[i]: continue
if self.dataHasClass:
fillColor = classColors.getRGB(
self.originalData[self.dataClassIndex][i],
255 * insideData[j])
edgeColor = classColors.getRGB(
self.originalData[self.dataClassIndex][i])
else:
fillColor = edgeColor = (0, 0, 0)
if self.showValueLines:
self.addValueLineCurve(x_positions[i], y_positions[i],
edgeColor, i, indices)
self.addTooltipKey(x_positions[i], y_positions[i],
QColor(*edgeColor), i,
stringData % (100 * insideData[j]))
j += 1
else:
for i in range(len(self.rawData)):
if not validData[i]: continue
if self.dataHasClass:
fillColor = classColors.getRGB(
self.originalData[self.dataClassIndex][i],
255 * insideData[i])
edgeColor = classColors.getRGB(
self.originalData[self.dataClassIndex][i])
else:
fillColor = edgeColor = (0, 0, 0)
if self.showValueLines:
self.addValueLineCurve(x_positions[i], y_positions[i],
edgeColor, i, indices)
self.addTooltipKey(x_positions[i], y_positions[i],
QColor(*edgeColor), i,
stringData % (100 * insideData[i]))
# ##############################################################
# do we have a subset data to show?
# ##############################################################
elif self.haveSubsetData:
shownSubsetCount = 0
subsetIdsToDraw = dict([(example.id, 1)
for example in self.rawSubsetData])
# draw the rawData data set. examples that exist also in the subset data draw full, other empty
for i in range(dataSize):
if not validData[i]: continue
if subsetIdsToDraw.has_key(self.rawData[i].id):
continue
if self.dataHasDiscreteClass and self.useDifferentColors:
newColor = self.discPalette.getRGB(
self.originalData[self.dataClassIndex][i])
elif self.dataHasContinuousClass and self.useDifferentColors:
newColor = self.contPalette.getRGB(
self.noJitteringScaledData[self.dataClassIndex][i])
else:
newColor = (0, 0, 0)
if self.useDifferentSymbols and self.dataHasDiscreteClass:
curveSymbol = self.curveSymbols[int(
self.originalData[self.dataClassIndex][i])]
else:
curveSymbol = self.curveSymbols[0]
if self.showValueLines:
self.addValueLineCurve(x_positions[i], y_positions[i],
newColor, i, indices)
self.addTooltipKey(x_positions[i], y_positions[i],
QColor(*newColor), i)
elif not self.dataHasClass:
xs = []
ys = []
for i in range(dataSize):
if not validData[i]: continue
xs.append(x_positions[i])
ys.append(y_positions[i])
self.addTooltipKey(x_positions[i], y_positions[i],
QColor(Qt.black), i)
if self.showValueLines:
self.addValueLineCurve(x_positions[i], y_positions[i],
(0, 0, 0), i, indices)
# ##############################################################
# CONTINUOUS class
# ##############################################################
elif self.dataHasContinuousClass:
for i in range(dataSize):
if not validData[i]: continue
newColor = self.contPalette.getRGB(
self.noJitteringScaledData[self.dataClassIndex][i])
if self.showValueLines:
self.addValueLineCurve(x_positions[i], y_positions[i],
newColor, i, indices)
self.addTooltipKey(x_positions[i], y_positions[i],
QColor(*newColor), i)
# ##############################################################
# DISCRETE class
# ##############################################################
elif self.dataHasDiscreteClass:
for i in range(dataSize):
if not validData[i]: continue
if self.useDifferentColors:
newColor = self.discPalette.getRGB(
self.originalData[self.dataClassIndex][i])
else:
newColor = (0, 0, 0)
if self.showValueLines:
self.addValueLineCurve(x_positions[i], y_positions[i],
newColor, i, indices)
self.addTooltipKey(x_positions[i], y_positions[i],
QColor(*newColor), i)
# first draw value lines
if self.showValueLines:
for i, color in enumerate(self.valueLineCurves[0].keys()):
curve = UnconnectedLinesCurve(
"", QPen(QColor(*color + (self.alphaValue, ))),
self.valueLineCurves[0][color],
self.valueLineCurves[1][color])
curve.attach(self)
self.value_line_curves.append(curve)
# ##############################################################
# draw the legend
# ##############################################################
# show legend for discrete class
if self.dataHasDiscreteClass:
classVariableValues = getVariableValuesSorted(
self.dataDomain.classVar)
for index in range(len(classVariableValues)):
if self.useDifferentColors:
color = QColor(self.discPalette[index])
else:
color = QColor(Qt.black)
if not self.useDifferentSymbols:
curveSymbol = self.curveSymbols[0]
else:
curveSymbol = self.curveSymbols[index]
self.legend().add_item(
self.dataDomain.classVar.name, classVariableValues[index],
OWPoint(curveSymbol, color, self.pointWidth))
# show legend for continuous class
elif self.dataHasContinuousClass:
self.legend().add_color_gradient(
self.dataDomain.classVar.name,
[("%%.%df" % self.dataDomain.classVar.numberOfDecimals % v)
for v in self.attrValues[self.dataDomain.classVar.name]])
self.replot()
def showAnchorLines(self):
for i, color in enumerate(self.xLinesToAdd.keys()):
curve = UnconnectedLinesCurve("", QPen(QColor(*color)), self.xLinesToAdd[color], self.yLinesToAdd[color])
curve.attach(self)
