def __init__(self, parent=None, signalManager=None, name="Model Map"):
OWNxExplorer.__init__(self, parent, signalManager, name,
NetworkCanvas=OWModelMapCanvas)
self.inputs = [("Distances", orange.SymMatrix, self.setMatrix, Default),
("Model Subset", orange.ExampleTable, self.setSubsetModels)]
self.outputs = [("Model", orange.Example),
("Classifier", orange.Classifier),
("Selected Models", orange.ExampleTable)]
self.vertexSize = 32
self.autoSendSelection = False
self.minVertexSize = 16
self.maxVertexSize = 16
self.lastColorAttribute = ""
self.lastSizeAttribute = ""
self.vizAccurancy = False
self.vizAttributes = False
self.radius = 100
self.attrIntersection = []
self.attrIntersectionList = []
self.attrDifference = []
self.attrDifferenceList = []
self.loadSettings()
self.matrixTab = OWGUI.widgetBox(self.tabs, addToLayout = 0, margin = 4)
self.modelTab = OWGUI.widgetBox(self.tabs, addToLayout = 0, margin = 4)
self.tabs.insertTab(0, self.matrixTab, "Matrix")
self.tabs.insertTab(1, self.modelTab, "Model Info")
self.tabs.setCurrentIndex(self.tabIndex)
self.networkCanvas.appendToSelection = 0
self.networkCanvas.minVertexSize = self.minVertexSize
self.networkCanvas.maxVertexSize = self.maxVertexSize
self.networkCanvas.invertEdgeSize = 1
# MARTIX CONTROLS
self.addHistogramControls(self.matrixTab)
self.kNN = 1
boxHistogram = OWGUI.widgetBox(self.matrixTab, box = "Distance histogram")
self.histogram = OWHist(self, boxHistogram)
boxHistogram.layout().addWidget(self.histogram)
# VISUALIZATION CONTROLS
vizPredAcc = OWGUI.widgetBox(self.modelTab, "Prediction Accuracy", orientation = "vertical")
OWGUI.checkBox(vizPredAcc, self, "vizAccurancy", "Visualize prediction accurancy", callback=self.visualizeInfo)
OWGUI.spin(vizPredAcc, self, "radius", 10, 300, 1, label="Radius: ", callback = self.visualizeInfo)
self.predGraph = OWDistributionGraph(self, vizPredAcc)
self.predGraph.setMaximumSize(QSize(300, 300))
self.predGraph.setYRlabels(None)
self.predGraph.setAxisScale(QwtPlot.xBottom, 0.0, 1.0, 0.1)
self.predGraph.numberOfBars = 2
self.predGraph.barSize = 200 / (self.predGraph.numberOfBars + 1)
vizPredAcc.layout().addWidget(self.predGraph)
vizPredAcc = OWGUI.widgetBox(self.modelTab, "Attribute lists", orientation = "vertical")
OWGUI.checkBox(vizPredAcc, self, "vizAttributes", "Display attribute lists", callback = self.visualizeInfo)
self.attrIntersectionBox = OWGUI.listBox(vizPredAcc, self, "attrIntersection", "attrIntersectionList", "Attribute intersection", selectionMode=QListWidget.NoSelection)
self.attrDifferenceBox = OWGUI.listBox(vizPredAcc, self, "attrDifference", "attrDifferenceList", "Attribute difference", selectionMode=QListWidget.NoSelection)
self.attBox.hide()
self.visualizeInfo()
QObject.connect(self.networkCanvas, SIGNAL('selection_changed()'), self.node_selection_changed)
self.matrixTab.layout().addStretch(1)
self.modelTab.layout().addStretch(1)
def __init__(self, parent=None, signalManager=None, name="Model Map"):
OWNxExplorer.__init__(self,
parent,
signalManager,
name,
NetworkCanvas=OWModelMapCanvas)
self.inputs = [
("Distances", orange.SymMatrix, self.setMatrix, Default),
("Model Subset", orange.ExampleTable, self.setSubsetModels)
]
self.outputs = [("Model", orange.Example),
("Classifier", orange.Classifier),
("Selected Models", orange.ExampleTable)]
self.vertexSize = 32
self.autoSendSelection = False
self.minVertexSize = 16
self.maxVertexSize = 16
self.lastColorAttribute = ""
self.lastSizeAttribute = ""
self.vizAccurancy = False
self.vizAttributes = False
self.radius = 100
self.attrIntersection = []
self.attrIntersectionList = []
self.attrDifference = []
self.attrDifferenceList = []
self.loadSettings()
self.matrixTab = OWGUI.widgetBox(self.tabs, addToLayout=0, margin=4)
self.modelTab = OWGUI.widgetBox(self.tabs, addToLayout=0, margin=4)
self.tabs.insertTab(0, self.matrixTab, "Matrix")
self.tabs.insertTab(1, self.modelTab, "Model Info")
self.tabs.setCurrentIndex(self.tabIndex)
self.networkCanvas.appendToSelection = 0
self.networkCanvas.minVertexSize = self.minVertexSize
self.networkCanvas.maxVertexSize = self.maxVertexSize
self.networkCanvas.invertEdgeSize = 1
# MARTIX CONTROLS
self.addHistogramControls(self.matrixTab)
self.kNN = 1
boxHistogram = OWGUI.widgetBox(self.matrixTab,
box="Distance histogram")
self.histogram = OWHist(self, boxHistogram)
boxHistogram.layout().addWidget(self.histogram)
# VISUALIZATION CONTROLS
vizPredAcc = OWGUI.widgetBox(self.modelTab,
"Prediction Accuracy",
orientation="vertical")
OWGUI.checkBox(vizPredAcc,
self,
"vizAccurancy",
"Visualize prediction accurancy",
callback=self.visualizeInfo)
OWGUI.spin(vizPredAcc,
self,
"radius",
10,
300,
1,
label="Radius: ",
callback=self.visualizeInfo)
self.predGraph = OWDistributionGraph(self, vizPredAcc)
self.predGraph.setMaximumSize(QSize(300, 300))
self.predGraph.setYRlabels(None)
self.predGraph.setAxisScale(QwtPlot.xBottom, 0.0, 1.0, 0.1)
self.predGraph.numberOfBars = 2
self.predGraph.barSize = 200 / (self.predGraph.numberOfBars + 1)
vizPredAcc.layout().addWidget(self.predGraph)
vizPredAcc = OWGUI.widgetBox(self.modelTab,
"Attribute lists",
orientation="vertical")
OWGUI.checkBox(vizPredAcc,
self,
"vizAttributes",
"Display attribute lists",
callback=self.visualizeInfo)
self.attrIntersectionBox = OWGUI.listBox(
vizPredAcc,
self,
"attrIntersection",
"attrIntersectionList",
"Attribute intersection",
selectionMode=QListWidget.NoSelection)
self.attrDifferenceBox = OWGUI.listBox(
vizPredAcc,
self,
"attrDifference",
"attrDifferenceList",
"Attribute difference",
selectionMode=QListWidget.NoSelection)
self.attBox.hide()
self.visualizeInfo()
QObject.connect(self.networkCanvas, SIGNAL('selection_changed()'),
self.node_selection_changed)
self.matrixTab.layout().addStretch(1)
self.modelTab.layout().addStretch(1)
class OWModelMapQt(OWNxExplorer, OWNxHist):
# settingsList = ["vertexSize", "lastSizeAttribute", "lastColorAttribute",
# "maxVertexSize", "minVertexSize", "tabIndex",
# "colorSettings", "selectedSchemaIndex", "iterations",
# "radius", "vizAccurancy", "vizAttributes",
# "autoSendSelection", "spinExplicit", "spinPercentage",
# "maxLinkSize", "renderAntialiased", "labelsOnMarkedOnly",
# "invertSize", "optMethod", "lastVertexSizeColumn",
# "lastColorColumn", "lastNameComponentAttribute",
# "lastLabelColumns", "lastTooltipColumns", "showWeights",
# "showIndexes", "showEdgeLabels", "edgeColorSettings",
# "selectedEdgeSchemaIndex", "showMissingValues", "fontSize",
# "mdsTorgerson", "mdsAvgLinkage", "mdsSteps", "mdsRefresh",
# "mdsStressDelta", "organism","showTextMiningInfo",
# "toolbarSelection", "minComponentEdgeWidth",
# "maxComponentEdgeWidth", "mdsFromCurrentPos"]
#
settingsList = ["autoSendSelection", "spinExplicit", "spinPercentage",
"maxLinkSize", "minVertexSize", "maxVertexSize", "networkCanvas.animate_plot",
"networkCanvas.animate_points", "networkCanvas.antialias_plot",
"networkCanvas.antialias_points", "networkCanvas.antialias_lines",
"networkCanvas.auto_adjust_performance", "invertSize", "optMethod",
"lastVertexSizeColumn", "lastColorColumn", "networkCanvas.show_indices", "networkCanvas.show_weights",
"lastNameComponentAttribute", "lastLabelColumns", "lastTooltipColumns",
"showWeights", "showEdgeLabels", "colorSettings",
"selectedSchemaIndex", "edgeColorSettings", "selectedEdgeSchemaIndex",
"showMissingValues", "fontSize", "mdsTorgerson", "mdsAvgLinkage",
"mdsSteps", "mdsRefresh", "mdsStressDelta", "organism","showTextMiningInfo",
"toolbarSelection", "minComponentEdgeWidth", "maxComponentEdgeWidth",
"mdsFromCurrentPos", "labelsOnMarkedOnly", "tabIndex",
"networkCanvas.trim_label_words", "opt_from_curr", "networkCanvas.explore_distances",
"networkCanvas.show_component_distances", "fontWeight", "networkCanvas.state",
"networkCanvas.selection_behavior"]
def __init__(self, parent=None, signalManager=None, name="Model Map"):
OWNxExplorer.__init__(self, parent, signalManager, name,
NetworkCanvas=OWModelMapCanvas)
self.inputs = [("Distances", orange.SymMatrix, self.setMatrix, Default),
("Model Subset", orange.ExampleTable, self.setSubsetModels)]
self.outputs = [("Model", orange.Example),
("Classifier", orange.Classifier),
("Selected Models", orange.ExampleTable)]
self.vertexSize = 32
self.autoSendSelection = False
self.minVertexSize = 16
self.maxVertexSize = 16
self.lastColorAttribute = ""
self.lastSizeAttribute = ""
self.vizAccurancy = False
self.vizAttributes = False
self.radius = 100
self.attrIntersection = []
self.attrIntersectionList = []
self.attrDifference = []
self.attrDifferenceList = []
self.loadSettings()
self.matrixTab = OWGUI.widgetBox(self.tabs, addToLayout = 0, margin = 4)
self.modelTab = OWGUI.widgetBox(self.tabs, addToLayout = 0, margin = 4)
self.tabs.insertTab(0, self.matrixTab, "Matrix")
self.tabs.insertTab(1, self.modelTab, "Model Info")
self.tabs.setCurrentIndex(self.tabIndex)
self.networkCanvas.appendToSelection = 0
self.networkCanvas.minVertexSize = self.minVertexSize
self.networkCanvas.maxVertexSize = self.maxVertexSize
self.networkCanvas.invertEdgeSize = 1
# MARTIX CONTROLS
self.addHistogramControls(self.matrixTab)
self.kNN = 1
boxHistogram = OWGUI.widgetBox(self.matrixTab, box = "Distance histogram")
self.histogram = OWHist(self, boxHistogram)
boxHistogram.layout().addWidget(self.histogram)
# VISUALIZATION CONTROLS
vizPredAcc = OWGUI.widgetBox(self.modelTab, "Prediction Accuracy", orientation = "vertical")
OWGUI.checkBox(vizPredAcc, self, "vizAccurancy", "Visualize prediction accurancy", callback=self.visualizeInfo)
OWGUI.spin(vizPredAcc, self, "radius", 10, 300, 1, label="Radius: ", callback = self.visualizeInfo)
self.predGraph = OWDistributionGraph(self, vizPredAcc)
self.predGraph.setMaximumSize(QSize(300, 300))
self.predGraph.setYRlabels(None)
self.predGraph.setAxisScale(QwtPlot.xBottom, 0.0, 1.0, 0.1)
self.predGraph.numberOfBars = 2
self.predGraph.barSize = 200 / (self.predGraph.numberOfBars + 1)
vizPredAcc.layout().addWidget(self.predGraph)
vizPredAcc = OWGUI.widgetBox(self.modelTab, "Attribute lists", orientation = "vertical")
OWGUI.checkBox(vizPredAcc, self, "vizAttributes", "Display attribute lists", callback = self.visualizeInfo)
self.attrIntersectionBox = OWGUI.listBox(vizPredAcc, self, "attrIntersection", "attrIntersectionList", "Attribute intersection", selectionMode=QListWidget.NoSelection)
self.attrDifferenceBox = OWGUI.listBox(vizPredAcc, self, "attrDifference", "attrDifferenceList", "Attribute difference", selectionMode=QListWidget.NoSelection)
self.attBox.hide()
self.visualizeInfo()
QObject.connect(self.networkCanvas, SIGNAL('selection_changed()'), self.node_selection_changed)
self.matrixTab.layout().addStretch(1)
self.modelTab.layout().addStretch(1)
def plotAccuracy(self, vertices=None):
self.predGraph.tips.removeAll()
self.predGraph.clear()
#self.predGraph.setAxisScale(QwtPlot.yRight, 0.0, 1.0, 0.2)
self.predGraph.setAxisScale(QwtPlot.xBottom, 0.0, 1.0, 0.2)
if not vertices:
self.predGraph.replot()
return
self.predGraph.setAxisScale(QwtPlot.yLeft, -0.5, len(self.matrix.originalData.domain.classVar.values) - 0.5, 1)
scores = [[float(ca) for ca in ex["CA by class"].value.split(", ")] for ex in self.graph.items().getitems(vertices)]
scores = [sum(score) / len(score) for score in zip(*scores)]
currentBarsHeight = [0] * len(scores)
for cn, score in enumerate(scores):
subBarHeight = score
ckey = PolygonCurve(pen = QPen(self.predGraph.discPalette[cn]), brush = QBrush(self.predGraph.discPalette[cn]))
ckey.attach(self.predGraph)
ckey.setRenderHint(QwtPlotItem.RenderAntialiased, self.predGraph.useAntialiasing)
tmpx = cn - (self.predGraph.barSize/2.0)/100.0
tmpx2 = cn + (self.predGraph.barSize/2.0)/100.0
ckey.setData([currentBarsHeight[cn], currentBarsHeight[cn] + subBarHeight, currentBarsHeight[cn] + subBarHeight, currentBarsHeight[cn]], [tmpx, tmpx, tmpx2, tmpx2])
currentBarsHeight[cn] += subBarHeight
self.predGraph.replot()
def displayAttributeInfo(self, vertices=None):
self.attrIntersectionList = []
self.attrDifferenceList = []
if vertices is None or len(vertices) == 0:
return
attrList = [self.graph.items()[v]["attributes"].value.split(", ") for v in vertices]
attrIntersection = set(attrList[0])
attrUnion = set()
for attrs in attrList:
attrIntersection = attrIntersection.intersection(attrs)
attrUnion = attrUnion.union(attrs)
self.attrIntersectionList = attrIntersection
self.attrDifferenceList = attrUnion.difference(attrIntersection)
def visualizeInfo(self):
self.networkCanvas.radius = self.radius
if self.vizAccurancy:
self.networkCanvas.plotAccuracy = self.plotAccuracy
else:
self.networkCanvas.plotAccuracy = None
self.plotAccuracy(None)
if self.vizAttributes:
self.networkCanvas.vizAttributes = self.displayAttributeInfo
else:
self.networkCanvas.vizAttributes = None
self.displayAttributeInfo(None)
def setSubsetModels(self, subsetData):
self.info()
if "uuid" not in subsetData.domain:
self.info("Invalid subset data. Data domain must contain 'uuid' attribute.")
return
uuids = set([ex["uuid"].value for ex in subsetData])
for v in self.vertices:
v.highlight = 1 if v.uuid in uuids else 0
def setMatrix(self, matrix):
self.warning()
if matrix is None:
self.warning("Data matrix is None.")
return
if not hasattr(matrix, "items") or not hasattr(matrix, "results") or not hasattr(matrix, "originalData"):
self.warning("Data matrix does not have required data for items, results and originalData.")
return
requiredAttrs = set(["CA", "AUC", "attributes", "uuid"])
attrs = [attr.name for attr in matrix.items.domain]
if len(requiredAttrs.intersection(attrs)) != len(requiredAttrs):
self.warning("Items ExampleTable does not contain required attributes: %s." % ", ".join(requiredAttrs))
return
for ex in matrix.items:
ex["attributes"] = ", ".join(sorted(ex["attributes"].value.split(", ")))
OWNxHist.setMatrix(self, matrix)
def set_node_sizes(self):
OWNxExplorer.set_node_sizes(self)
self.networkCanvas.loadIcons()
self.networkCanvas.replot()
def set_node_styles(self):
#for v in self.networkCanvas.networkCurve.nodes().itervalues():
# #auc = self.graph.items()[v.index()]
# v.style = 1 #auc
pass
def node_selection_changed(self):
self.warning()
if self.graph is None or self.graph.items() is None or self.graph_matrix is None:
self.send("Model", None)
self.send("Selected Models", None)
return
if self.graph.number_of_nodes() != self.graph_matrix.dim:
self.warning('Network items and matrix results not of equal length.')
self.send("Model", None)
self.send("Selected Models", None)
return
selection = self.networkCanvas.selected_nodes()
if len(selection) == 1:
modelInstance = self.graph.items()[selection[0]]
# modelInfo - Python Dict; keys: method, classifier, probabilities,
# results, XAnchors, YAnchors, attributes
modelInfo = self.graph_matrix.results[modelInstance['uuid'].value]
#uuid = modelInstance["uuid"].value
#method, vizr_result, projection_points, classifier, attrs = self.matrix.results[uuid]
if 'YAnchors' in modelInfo and 'XAnchors' in modelInfo:
if not modelInstance.domain.hasmeta('anchors'):
modelInstance.domain.addmeta(orange.newmetaid(), orange.PythonVariable('anchors'))
modelInstance['anchors'] = (modelInfo['XAnchors'], modelInfo['YAnchors'])
if 'classifier' in modelInfo and modelInfo['classifier'] is not None:
if not modelInstance.domain.hasmeta('classifier'):
modelInstance.domain.addmeta(orange.newmetaid(), orange.PythonVariable('classifier'))
modelInstance['classifier'] = modelInfo['classifier']
self.send('Classifier', modelInfo['classifier'])
self.send('Model', modelInstance)
self.send('Selected Models', self.graph.items().getitems(selection))
elif len(selection) > 1:
self.send('Model', None)
self.send('Selected Models', self.graph.items().getitems(selection))
else:
self.send('Model', None)
self.send('Selected Models', None)
def setColors(self):
dlg = self.createColorDialog(self.colorSettings, self.selectedSchemaIndex)
if dlg.exec_():
self.colorSettings = dlg.getColorSchemas()
self.selectedSchemaIndex = dlg.selectedSchemaIndex
self.networkCanvas.contPalette = dlg.getContinuousPalette("contPalette")
self.networkCanvas.discPalette = dlg.getDiscretePalette("discPalette")
self.set_node_colors()
def set_node_colors(self):
if self.graph is None:
return
self.networkCanvas.set_node_colors(self.colorCombo.currentText())
self.lastColorAttribute = self.colorCombo.currentText()
#self.networkCanvas.updateData()
#self.networkCanvas.replot()
def sendSignals(self):
if self.graph is None or self.graph_matrix is None:
return
self.set_graph(self.graph, ModelCurve)
self.set_items_distance_matrix(self.graph_matrix)
# TODO clickedAttLstBox -> setLabelText(["attributes"]
nodes = self.networkCanvas.networkCurve.nodes()
for i, ex in enumerate(self.graph.items()):
nodes[i].uuid = ex["uuid"].value
self.set_node_sizes()
self.set_node_styles()
self.set_node_colors()
labels = self.matrix.originalData.domain.classVar.values.native()
self.predGraph.numberOfBars = len(labels)
self.predGraph.barSize = 200 / (self.predGraph.numberOfBars + 1)
self.predGraph.setYLlabels(labels)
#self.predGraph.setShowMainTitle(self.showMainTitle)
#self.predGraph.setYLaxisTitle(self.matrix.originalData.domain.classVar.name)
#self.predGraph.setShowYLaxisTitle(True)
self.predGraph.setAxisScale(QwtPlot.xBottom, 0.0, 1.0, 0.2)
self.predGraph.setAxisScale(QwtPlot.yLeft, -0.5, len(self.matrix.originalData.domain.classVar.values) - 0.5, 1)
self.predGraph.enableYRaxis(0)
self.predGraph.setYRaxisTitle("")
self.predGraph.setXaxisTitle("CA")
self.predGraph.setShowXaxisTitle(True)
self.predGraph.replot()
self.visualizeInfo()
class OWModelMapQt(OWNxExplorer, OWNxHist):
# settingsList = ["vertexSize", "lastSizeAttribute", "lastColorAttribute",
# "maxVertexSize", "minVertexSize", "tabIndex",
# "colorSettings", "selectedSchemaIndex", "iterations",
# "radius", "vizAccurancy", "vizAttributes",
# "autoSendSelection", "spinExplicit", "spinPercentage",
# "maxLinkSize", "renderAntialiased", "labelsOnMarkedOnly",
# "invertSize", "optMethod", "lastVertexSizeColumn",
# "lastColorColumn", "lastNameComponentAttribute",
# "lastLabelColumns", "lastTooltipColumns", "showWeights",
# "showIndexes", "showEdgeLabels", "edgeColorSettings",
# "selectedEdgeSchemaIndex", "showMissingValues", "fontSize",
# "mdsTorgerson", "mdsAvgLinkage", "mdsSteps", "mdsRefresh",
# "mdsStressDelta", "organism","showTextMiningInfo",
# "toolbarSelection", "minComponentEdgeWidth",
# "maxComponentEdgeWidth", "mdsFromCurrentPos"]
#
settingsList = [
"autoSendSelection", "spinExplicit", "spinPercentage", "maxLinkSize",
"minVertexSize", "maxVertexSize", "networkCanvas.animate_plot",
"networkCanvas.animate_points", "networkCanvas.antialias_plot",
"networkCanvas.antialias_points", "networkCanvas.antialias_lines",
"networkCanvas.auto_adjust_performance", "invertSize", "optMethod",
"lastVertexSizeColumn", "lastColorColumn",
"networkCanvas.show_indices", "networkCanvas.show_weights",
"lastNameComponentAttribute", "lastLabelColumns", "lastTooltipColumns",
"showWeights", "showEdgeLabels", "colorSettings",
"selectedSchemaIndex", "edgeColorSettings", "selectedEdgeSchemaIndex",
"showMissingValues", "fontSize", "mdsTorgerson", "mdsAvgLinkage",
"mdsSteps", "mdsRefresh", "mdsStressDelta", "organism",
"showTextMiningInfo", "toolbarSelection", "minComponentEdgeWidth",
"maxComponentEdgeWidth", "mdsFromCurrentPos", "labelsOnMarkedOnly",
"tabIndex", "networkCanvas.trim_label_words", "opt_from_curr",
"networkCanvas.explore_distances",
"networkCanvas.show_component_distances", "fontWeight",
"networkCanvas.state", "networkCanvas.selection_behavior"
]
def __init__(self, parent=None, signalManager=None, name="Model Map"):
OWNxExplorer.__init__(self,
parent,
signalManager,
name,
NetworkCanvas=OWModelMapCanvas)
self.inputs = [
("Distances", orange.SymMatrix, self.setMatrix, Default),
("Model Subset", orange.ExampleTable, self.setSubsetModels)
]
self.outputs = [("Model", orange.Example),
("Classifier", orange.Classifier),
("Selected Models", orange.ExampleTable)]
self.vertexSize = 32
self.autoSendSelection = False
self.minVertexSize = 16
self.maxVertexSize = 16
self.lastColorAttribute = ""
self.lastSizeAttribute = ""
self.vizAccurancy = False
self.vizAttributes = False
self.radius = 100
self.attrIntersection = []
self.attrIntersectionList = []
self.attrDifference = []
self.attrDifferenceList = []
self.loadSettings()
self.matrixTab = OWGUI.widgetBox(self.tabs, addToLayout=0, margin=4)
self.modelTab = OWGUI.widgetBox(self.tabs, addToLayout=0, margin=4)
self.tabs.insertTab(0, self.matrixTab, "Matrix")
self.tabs.insertTab(1, self.modelTab, "Model Info")
self.tabs.setCurrentIndex(self.tabIndex)
self.networkCanvas.appendToSelection = 0
self.networkCanvas.minVertexSize = self.minVertexSize
self.networkCanvas.maxVertexSize = self.maxVertexSize
self.networkCanvas.invertEdgeSize = 1
# MARTIX CONTROLS
self.addHistogramControls(self.matrixTab)
self.kNN = 1
boxHistogram = OWGUI.widgetBox(self.matrixTab,
box="Distance histogram")
self.histogram = OWHist(self, boxHistogram)
boxHistogram.layout().addWidget(self.histogram)
# VISUALIZATION CONTROLS
vizPredAcc = OWGUI.widgetBox(self.modelTab,
"Prediction Accuracy",
orientation="vertical")
OWGUI.checkBox(vizPredAcc,
self,
"vizAccurancy",
"Visualize prediction accurancy",
callback=self.visualizeInfo)
OWGUI.spin(vizPredAcc,
self,
"radius",
10,
300,
1,
label="Radius: ",
callback=self.visualizeInfo)
self.predGraph = OWDistributionGraph(self, vizPredAcc)
self.predGraph.setMaximumSize(QSize(300, 300))
self.predGraph.setYRlabels(None)
self.predGraph.setAxisScale(QwtPlot.xBottom, 0.0, 1.0, 0.1)
self.predGraph.numberOfBars = 2
self.predGraph.barSize = 200 / (self.predGraph.numberOfBars + 1)
vizPredAcc.layout().addWidget(self.predGraph)
vizPredAcc = OWGUI.widgetBox(self.modelTab,
"Attribute lists",
orientation="vertical")
OWGUI.checkBox(vizPredAcc,
self,
"vizAttributes",
"Display attribute lists",
callback=self.visualizeInfo)
self.attrIntersectionBox = OWGUI.listBox(
vizPredAcc,
self,
"attrIntersection",
"attrIntersectionList",
"Attribute intersection",
selectionMode=QListWidget.NoSelection)
self.attrDifferenceBox = OWGUI.listBox(
vizPredAcc,
self,
"attrDifference",
"attrDifferenceList",
"Attribute difference",
selectionMode=QListWidget.NoSelection)
self.attBox.hide()
self.visualizeInfo()
QObject.connect(self.networkCanvas, SIGNAL('selection_changed()'),
self.node_selection_changed)
self.matrixTab.layout().addStretch(1)
self.modelTab.layout().addStretch(1)
def plotAccuracy(self, vertices=None):
self.predGraph.tips.removeAll()
self.predGraph.clear()
#self.predGraph.setAxisScale(QwtPlot.yRight, 0.0, 1.0, 0.2)
self.predGraph.setAxisScale(QwtPlot.xBottom, 0.0, 1.0, 0.2)
if not vertices:
self.predGraph.replot()
return
self.predGraph.setAxisScale(
QwtPlot.yLeft, -0.5,
len(self.matrix.originalData.domain.classVar.values) - 0.5, 1)
scores = [[float(ca) for ca in ex["CA by class"].value.split(", ")]
for ex in self.graph.items().getitems(vertices)]
scores = [sum(score) / len(score) for score in zip(*scores)]
currentBarsHeight = [0] * len(scores)
for cn, score in enumerate(scores):
subBarHeight = score
ckey = PolygonCurve(pen=QPen(self.predGraph.discPalette[cn]),
brush=QBrush(self.predGraph.discPalette[cn]))
ckey.attach(self.predGraph)
ckey.setRenderHint(QwtPlotItem.RenderAntialiased,
self.predGraph.useAntialiasing)
tmpx = cn - (self.predGraph.barSize / 2.0) / 100.0
tmpx2 = cn + (self.predGraph.barSize / 2.0) / 100.0
ckey.setData([
currentBarsHeight[cn], currentBarsHeight[cn] + subBarHeight,
currentBarsHeight[cn] + subBarHeight, currentBarsHeight[cn]
], [tmpx, tmpx, tmpx2, tmpx2])
currentBarsHeight[cn] += subBarHeight
self.predGraph.replot()
def displayAttributeInfo(self, vertices=None):
self.attrIntersectionList = []
self.attrDifferenceList = []
if vertices is None or len(vertices) == 0:
return
attrList = [
self.graph.items()[v]["attributes"].value.split(", ")
for v in vertices
]
attrIntersection = set(attrList[0])
attrUnion = set()
for attrs in attrList:
attrIntersection = attrIntersection.intersection(attrs)
attrUnion = attrUnion.union(attrs)
self.attrIntersectionList = attrIntersection
self.attrDifferenceList = attrUnion.difference(attrIntersection)
def visualizeInfo(self):
self.networkCanvas.radius = self.radius
if self.vizAccurancy:
self.networkCanvas.plotAccuracy = self.plotAccuracy
else:
self.networkCanvas.plotAccuracy = None
self.plotAccuracy(None)
if self.vizAttributes:
self.networkCanvas.vizAttributes = self.displayAttributeInfo
else:
self.networkCanvas.vizAttributes = None
self.displayAttributeInfo(None)
def setSubsetModels(self, subsetData):
self.info()
if "uuid" not in subsetData.domain:
self.info(
"Invalid subset data. Data domain must contain 'uuid' attribute."
)
return
uuids = set([ex["uuid"].value for ex in subsetData])
for v in self.vertices:
v.highlight = 1 if v.uuid in uuids else 0
def setMatrix(self, matrix):
self.warning()
if matrix is None:
self.warning("Data matrix is None.")
return
if not hasattr(matrix, "items") or not hasattr(
matrix, "results") or not hasattr(matrix, "originalData"):
self.warning(
"Data matrix does not have required data for items, results and originalData."
)
return
requiredAttrs = set(["CA", "AUC", "attributes", "uuid"])
attrs = [attr.name for attr in matrix.items.domain]
if len(requiredAttrs.intersection(attrs)) != len(requiredAttrs):
self.warning(
"Items ExampleTable does not contain required attributes: %s."
% ", ".join(requiredAttrs))
return
for ex in matrix.items:
ex["attributes"] = ", ".join(
sorted(ex["attributes"].value.split(", ")))
OWNxHist.setMatrix(self, matrix)
def set_node_sizes(self):
OWNxExplorer.set_node_sizes(self)
self.networkCanvas.loadIcons()
self.networkCanvas.replot()
def set_node_styles(self):
#for v in self.networkCanvas.networkCurve.nodes().itervalues():
# #auc = self.graph.items()[v.index()]
# v.style = 1 #auc
pass
def node_selection_changed(self):
self.warning()
if self.graph is None or self.graph.items(
) is None or self.graph_matrix is None:
self.send("Model", None)
self.send("Selected Models", None)
return
if self.graph.number_of_nodes() != self.graph_matrix.dim:
self.warning(
'Network items and matrix results not of equal length.')
self.send("Model", None)
self.send("Selected Models", None)
return
selection = self.networkCanvas.selected_nodes()
if len(selection) == 1:
modelInstance = self.graph.items()[selection[0]]
# modelInfo - Python Dict; keys: method, classifier, probabilities,
# results, XAnchors, YAnchors, attributes
modelInfo = self.graph_matrix.results[modelInstance['uuid'].value]
#uuid = modelInstance["uuid"].value
#method, vizr_result, projection_points, classifier, attrs = self.matrix.results[uuid]
if 'YAnchors' in modelInfo and 'XAnchors' in modelInfo:
if not modelInstance.domain.hasmeta('anchors'):
modelInstance.domain.addmeta(
orange.newmetaid(), orange.PythonVariable('anchors'))
modelInstance['anchors'] = (modelInfo['XAnchors'],
modelInfo['YAnchors'])
if 'classifier' in modelInfo and modelInfo[
'classifier'] is not None:
if not modelInstance.domain.hasmeta('classifier'):
modelInstance.domain.addmeta(
orange.newmetaid(),
orange.PythonVariable('classifier'))
modelInstance['classifier'] = modelInfo['classifier']
self.send('Classifier', modelInfo['classifier'])
self.send('Model', modelInstance)
self.send('Selected Models',
self.graph.items().getitems(selection))
elif len(selection) > 1:
self.send('Model', None)
self.send('Selected Models',
self.graph.items().getitems(selection))
else:
self.send('Model', None)
self.send('Selected Models', None)
def setColors(self):
dlg = self.createColorDialog(self.colorSettings,
self.selectedSchemaIndex)
if dlg.exec_():
self.colorSettings = dlg.getColorSchemas()
self.selectedSchemaIndex = dlg.selectedSchemaIndex
self.networkCanvas.contPalette = dlg.getContinuousPalette(
"contPalette")
self.networkCanvas.discPalette = dlg.getDiscretePalette(
"discPalette")
self.set_node_colors()
def set_node_colors(self):
if self.graph is None:
return
self.networkCanvas.set_node_colors(self.colorCombo.currentText())
self.lastColorAttribute = self.colorCombo.currentText()
#self.networkCanvas.updateData()
#self.networkCanvas.replot()
def sendSignals(self):
if self.graph is None or self.graph_matrix is None:
return
self.set_graph(self.graph, ModelCurve)
self.set_items_distance_matrix(self.graph_matrix)
# TODO clickedAttLstBox -> setLabelText(["attributes"]
nodes = self.networkCanvas.networkCurve.nodes()
for i, ex in enumerate(self.graph.items()):
nodes[i].uuid = ex["uuid"].value
self.set_node_sizes()
self.set_node_styles()
self.set_node_colors()
labels = self.matrix.originalData.domain.classVar.values.native()
self.predGraph.numberOfBars = len(labels)
self.predGraph.barSize = 200 / (self.predGraph.numberOfBars + 1)
self.predGraph.setYLlabels(labels)
#self.predGraph.setShowMainTitle(self.showMainTitle)
#self.predGraph.setYLaxisTitle(self.matrix.originalData.domain.classVar.name)
#self.predGraph.setShowYLaxisTitle(True)
self.predGraph.setAxisScale(QwtPlot.xBottom, 0.0, 1.0, 0.2)
self.predGraph.setAxisScale(
QwtPlot.yLeft, -0.5,
len(self.matrix.originalData.domain.classVar.values) - 0.5, 1)
self.predGraph.enableYRaxis(0)
self.predGraph.setYRaxisTitle("")
self.predGraph.setXaxisTitle("CA")
self.predGraph.setShowXaxisTitle(True)
self.predGraph.replot()
self.visualizeInfo()