def calculate(self):
if self.configurationWidget is None:
self.configurationWidget = PCAParametersDialog(None, regions=True)
self._status = qt.QLabel(self.configurationWidget)
self._status.setAlignment(qt.Qt.AlignHCenter)
font = qt.QFont(self._status.font())
font.setBold(True)
self._status.setFont(font)
self._status.setText("Ready")
self.configurationWidget.layout().addWidget(self._status)
activeCurve = self.getActiveCurve()
if activeCurve is None:
#I could get some defaults from the stack itslef
raise ValueError("Please select an active curve")
return
x, spectrum, legend, info = activeCurve
spectrumLength = max(spectrum.shape)
oldValue = self.configurationWidget.nPC.value()
self.configurationWidget.nPC.setMaximum(spectrumLength)
self.configurationWidget.nPC.setValue(min(oldValue, spectrumLength))
binningOptions = [1]
for number in [2, 3, 4, 5, 7, 9, 10, 11, 13, 15, 17, 19]:
if (spectrumLength % number) == 0:
binningOptions.append(number)
# TODO: Should inform the configuration widget about the possibility
# to encounter non-finite data?
ddict = {'options': binningOptions,
'binning': 1,
'method': 0}
self.configurationWidget.setParameters(ddict)
y = spectrum
self.configurationWidget.setSpectrum(x, y)
ret = self.configurationWidget.exec_()
if ret:
self._executeFunctionAndParameters()
def calculate(self):
if self.configurationWidget is None:
stack = self.getStackDataObject()
index = stack.info.get("McaIndex", -1)
if index == len(stack.data.shape):
index = -1
stack = None
self.configurationWidget = PCAParametersDialog(None,
regions=True,
index=index)
self._status = qt.QLabel(self.configurationWidget)
self._status.setAlignment(qt.Qt.AlignHCenter)
font = qt.QFont(self._status.font())
font.setBold(True)
self._status.setFont(font)
self._status.setText("Ready")
self.configurationWidget.layout().addWidget(self._status)
self.configurationWidget.setEnabled(True)
activeCurve = self.getActiveCurve()
if activeCurve is None:
#I could get some defaults from the stack itslef
raise ValueError("Please select an active curve")
return
x, spectrum, legend, info = activeCurve
spectrumLength = max(spectrum.shape)
oldValue = self.configurationWidget.nPC.value()
self.configurationWidget.nPC.setMaximum(spectrumLength)
self.configurationWidget.nPC.setValue(min(oldValue, spectrumLength))
binningOptions = [1]
for number in [2, 3, 4, 5, 7, 9, 10, 11, 13, 15, 17, 19]:
if (spectrumLength % number) == 0:
binningOptions.append(number)
# TODO: Should inform the configuration widget about the possibility
# to encounter non-finite data?
ddict = {'options': binningOptions,
'binning': 1,
'method': 0}
self.configurationWidget.setParameters(ddict)
y = spectrum
self.configurationWidget.setSpectrum(x, y, legend=legend, info=info)
self.configurationWidget.show()
ret = self.configurationWidget.exec()
if ret:
self._kMeansWidget = None
self._executeFunctionAndParameters()
class PCAStackPlugin(StackPluginBase.StackPluginBase):
def __init__(self, stackWindow, **kw):
if _logger.getEffectiveLevel() == logging.DEBUG:
StackPluginBase.pluginBaseLogger.setLevel(logging.DEBUG)
StackPluginBase.StackPluginBase.__init__(self, stackWindow, **kw)
self.methodDict = {
'Calculate': [self.calculate, "Perform PCA", None],
'Show':
[self._showWidget, "Show last results", PyMca_Icons.brushselect]
}
self.__methodKeys = ['Calculate', 'Show']
self.configurationWidget = None
self.widget = None
self.thread = None
def stackUpdated(self):
_logger.debug("PCAStackPlugin.stackUpdated() called")
self.configurationWidget = None
self.widget = None
def selectionMaskUpdated(self):
if self.widget is None:
return
if self.widget.isHidden():
return
mask = self.getStackSelectionMask()
self.widget.setSelectionMask(mask)
def mySlot(self, ddict):
_logger.debug("mySlot %s %s", ddict['event'], ddict.keys())
if ddict['event'] == "selectionMaskChanged":
self.setStackSelectionMask(ddict['current'])
elif ddict['event'] == "addImageClicked":
self.addImage(ddict['image'], ddict['title'])
elif ddict['event'] == "addAllClicked":
for i in range(len(ddict["images"])):
self.addImage(ddict['images'][i], ddict['titles'][i])
elif ddict['event'] == "removeImageClicked":
self.removeImage(ddict['title'])
elif ddict['event'] == "replaceImageClicked":
self.replaceImage(ddict['image'], ddict['title'])
elif ddict['event'] == "resetSelection":
self.setStackSelectionMask(None)
#Methods implemented by the plugin
def getMethods(self):
if self.widget is None:
return [self.__methodKeys[0]]
else:
return self.__methodKeys
def getMethodToolTip(self, name):
return self.methodDict[name][1]
def getMethodPixmap(self, name):
return self.methodDict[name][2]
def applyMethod(self, name):
return self.methodDict[name][0]()
#The specific part
def calculate(self):
if self.configurationWidget is None:
stack = self.getStackDataObject()
index = stack.info.get("McaIndex", -1)
if index == len(stack.data.shape):
index = -1
stack = None
self.configurationWidget = PCAParametersDialog(None,
regions=True,
index=index)
self._status = qt.QLabel(self.configurationWidget)
self._status.setAlignment(qt.Qt.AlignHCenter)
font = qt.QFont(self._status.font())
font.setBold(True)
self._status.setFont(font)
self._status.setText("Ready")
self.configurationWidget.layout().addWidget(self._status)
self.configurationWidget.setEnabled(True)
activeCurve = self.getActiveCurve()
if activeCurve is None:
#I could get some defaults from the stack itslef
raise ValueError("Please select an active curve")
return
x, spectrum, legend, info = activeCurve
spectrumLength = max(spectrum.shape)
oldValue = self.configurationWidget.nPC.value()
self.configurationWidget.nPC.setMaximum(spectrumLength)
self.configurationWidget.nPC.setValue(min(oldValue, spectrumLength))
binningOptions = [1]
for number in [2, 3, 4, 5, 7, 9, 10, 11, 13, 15, 17, 19]:
if (spectrumLength % number) == 0:
binningOptions.append(number)
# TODO: Should inform the configuration widget about the possibility
# to encounter non-finite data?
ddict = {'options': binningOptions, 'binning': 1, 'method': 0}
self.configurationWidget.setParameters(ddict)
y = spectrum
self.configurationWidget.setSpectrum(x, y, legend=legend, info=info)
self.configurationWidget.show()
ret = self.configurationWidget.exec_()
if ret:
self._executeFunctionAndParameters()
def _executeFunctionAndParameters(self):
self.widget = None
self.configurationWidget.show()
if _logger.getEffectiveLevel() == logging.DEBUG:
self.thread = CalculationThread.CalculationThread(\
calculation_method=self.actualCalculation)
self.thread.result = self.actualCalculation()
self.threadFinished()
else:
self.thread = CalculationThread.CalculationThread(\
calculation_method=self.actualCalculation)
self.thread.finished.connect(self.threadFinished)
self.thread.start()
message = "Please wait. PCA Calculation going on."
CalculationThread.waitingMessageDialog(
self.thread, message=message, parent=self.configurationWidget)
def actualCalculation(self):
pcaParameters = self.configurationWidget.getParameters()
self._status.setText("Calculation going on")
self.configurationWidget.setEnabled(False)
#self.configurationWidget.close()
self.__methodlabel = pcaParameters.get('methodlabel', "")
function = pcaParameters['function']
pcaParameters['ncomponents'] = pcaParameters['npc']
# At some point I should make sure I get directly the
# function and the parameters from the configuration widget
del pcaParameters['npc']
del pcaParameters['method']
del pcaParameters['function']
del pcaParameters['methodlabel']
# binning = pcaParameters['binning']
# mask = pcaParameters['mask']
regions = pcaParameters['regions']
spectral_mask = pcaParameters['spectral_mask']
#print("regions = ", regions)
#del pcaParameters['regions']
#del pcaParameters['spectral_mask']
#print("Regions and spectral mask not handled yet")
if not self.isStackFinite():
# one has to check for NaNs in the used region(s)
# for the time being only in the global image
# spatial_mask = numpy.isfinite(image_data)
spatial_mask = numpy.isfinite(self.getStackOriginalImage())
pcaParameters['mask'] = spatial_mask
pcaParameters["legacy"] = False
_logger.info("PCA function %s" % function.__name__)
_logger.info("PCA parameters %s" % pcaParameters)
if "Multiple" in self.__methodlabel:
stackList = self.getStackDataObjectList()
oldShapes = []
for stack in stackList:
oldShapes.append(stack.data.shape)
result = function(stackList, **pcaParameters)
for i in range(len(stackList)):
stackList[i].data.shape = oldShapes[i]
return result
else:
stack = self.getStackDataObject()
if isinstance(stack, numpy.ndarray):
if stack.data.dtype not in [numpy.float, numpy.float32]:
_logger.warning("WARNING: Non floating point data")
text = "Calculation going on."
text += " WARNING: Non floating point data."
self._status.setText(text)
oldShape = stack.data.shape
result = function(stack, **pcaParameters)
if stack.data.shape != oldShape:
stack.data.shape = oldShape
return result
def threadFinished(self):
result = self.thread.getResult()
self.thread = None
if type(result) == type((1, )):
#if we receive a tuple there was an error
if len(result):
if result[0] == "Exception":
self._status.setText("Ready after calculation error")
self.configurationWidget.setEnabled(True)
raise Exception(result[1], result[2])
return
self._status.setText("Ready")
curve = self.configurationWidget.getSpectrum(binned=True)
if curve not in [None, []]:
xValues = curve[0]
else:
xValues = None
self.configurationWidget.setEnabled(True)
self.configurationWidget.close()
if hasattr(result, "keys"):
# new way
images = result["scores"]
eigenValues = result["eigenvalues"]
eigenVectors = result["eigenvectors"]
variance = result.get("variance", None)
if variance is not None:
explainedVariance = []
for value in eigenValues:
explainedVariance.append(100 * (value / variance))
else:
variance = None
images, eigenValues, eigenVectors = result
methodlabel = self.__methodlabel
imageNames = None
vectorNames = None
nimages = images.shape[0]
imageNames = []
vectorNames = []
itmp = nimages
if " ICA " in methodlabel:
itmp = int(nimages / 2)
for i in range(itmp):
imageNames.append("ICAimage %02d" % i)
vectorNames.append("ICAvector %02d" % i)
if "Multiple" in methodlabel:
xValues = None
for i in range(itmp):
imageNames.append("Eigenimage %02d" % i)
vectorNames.append("Eigenvector %02d" % i)
if variance is not None:
vectorNames[-1] = "EV%02d Explained variance %.4f %%" % \
(i, explainedVariance[i])
self.widget = StackPluginResultsWindow.StackPluginResultsWindow(\
usetab=True)
self.widget.buildAndConnectImageButtonBox(replace=True, multiple=True)
qt = StackPluginResultsWindow.qt
self.widget.sigMaskImageWidgetSignal.connect(self.mySlot)
if xValues is not None:
xValues = [xValues] * nimages
self.widget.setStackPluginResults(images,
spectra=eigenVectors,
image_names=imageNames,
xvalues=xValues,
spectra_names=vectorNames)
self._showWidget()
def _showWidget(self):
if self.widget is None:
return
#Show
self.widget.show()
self.widget.raise_()
#update
self.selectionMaskUpdated()
class PCAStackPlugin(StackPluginBase.StackPluginBase):
def __init__(self, stackWindow, **kw):
StackPluginBase.DEBUG = DEBUG
StackPluginBase.StackPluginBase.__init__(self, stackWindow, **kw)
self.methodDict = {'Calculate': [self.calculate, "Perform PCA", None],
'Show': [self._showWidget,
"Show last results",
PyMca_Icons.brushselect]}
self.__methodKeys = ['Calculate', 'Show']
self.configurationWidget = None
self.widget = None
self.thread = None
def stackUpdated(self):
if DEBUG:
print("PCAStackPlugin.stackUpdated() called")
self.configurationWidget = None
self.widget = None
def selectionMaskUpdated(self):
if self.widget is None:
return
if self.widget.isHidden():
return
mask = self.getStackSelectionMask()
self.widget.setSelectionMask(mask)
def mySlot(self, ddict):
if DEBUG:
print("mySlot ", ddict['event'], ddict.keys())
if ddict['event'] == "selectionMaskChanged":
self.setStackSelectionMask(ddict['current'])
elif ddict['event'] == "addImageClicked":
self.addImage(ddict['image'], ddict['title'])
elif ddict['event'] == "removeImageClicked":
self.removeImage(ddict['title'])
elif ddict['event'] == "replaceImageClicked":
self.replaceImage(ddict['image'], ddict['title'])
elif ddict['event'] == "resetSelection":
self.setStackSelectionMask(None)
#Methods implemented by the plugin
def getMethods(self):
if self.widget is None:
return [self.__methodKeys[0]]
else:
return self.__methodKeys
def getMethodToolTip(self, name):
return self.methodDict[name][1]
def getMethodPixmap(self, name):
return self.methodDict[name][2]
def applyMethod(self, name):
return self.methodDict[name][0]()
#The specific part
def calculate(self):
if self.configurationWidget is None:
self.configurationWidget = PCAParametersDialog(None, regions=True)
self._status = qt.QLabel(self.configurationWidget)
self._status.setAlignment(qt.Qt.AlignHCenter)
font = qt.QFont(self._status.font())
font.setBold(True)
self._status.setFont(font)
self._status.setText("Ready")
self.configurationWidget.layout().addWidget(self._status)
activeCurve = self.getActiveCurve()
if activeCurve is None:
#I could get some defaults from the stack itslef
raise ValueError("Please select an active curve")
return
x, spectrum, legend, info = activeCurve
spectrumLength = max(spectrum.shape)
oldValue = self.configurationWidget.nPC.value()
self.configurationWidget.nPC.setMaximum(spectrumLength)
self.configurationWidget.nPC.setValue(min(oldValue, spectrumLength))
binningOptions = [1]
for number in [2, 3, 4, 5, 7, 9, 10, 11, 13, 15, 17, 19]:
if (spectrumLength % number) == 0:
binningOptions.append(number)
# TODO: Should inform the configuration widget about the possibility
# to encounter non-finite data?
ddict = {'options': binningOptions,
'binning': 1,
'method': 0}
self.configurationWidget.setParameters(ddict)
y = spectrum
self.configurationWidget.setSpectrum(x, y)
ret = self.configurationWidget.exec_()
if ret:
self._executeFunctionAndParameters()
def _executeFunctionAndParameters(self):
self.widget = None
self.configurationWidget.show()
if DEBUG:
self.thread = CalculationThread.CalculationThread(\
calculation_method=self.actualCalculation)
self.thread.result = self.actualCalculation()
self.threadFinished()
else:
self.thread = CalculationThread.CalculationThread(\
calculation_method=self.actualCalculation)
qt.QObject.connect(self.thread,
qt.SIGNAL('finished()'),
self.threadFinished)
self.thread.start()
message = "Please wait. PCA Calculation going on."
CalculationThread.waitingMessageDialog(self.thread,
message=message,
parent=self.configurationWidget)
def actualCalculation(self):
pcaParameters = self.configurationWidget.getParameters()
self._status.setText("Calculation going on")
self.configurationWidget.setEnabled(False)
#self.configurationWidget.close()
self.__methodlabel = pcaParameters.get('methodlabel', "")
function = pcaParameters['function']
pcaParameters['ncomponents'] = pcaParameters['npc']
# At some point I should make sure I get directly the
# function and the parameters from the configuration widget
del pcaParameters['npc']
del pcaParameters['method']
del pcaParameters['function']
del pcaParameters['methodlabel']
# binning = pcaParameters['binning']
# mask = pcaParameters['mask']
if not self.isStackFinite():
# one has to check for NaNs in the used region(s)
# for the time being only in the global image
# spatial_mask = numpy.isfinite(image_data)
spatial_mask = numpy.isfinite(self.getStackOriginalImage())
pcaParameters['mask'] = spatial_mask
stack = self.getStackDataObject()
if isinstance(stack, numpy.ndarray):
if stack.data.dtype not in [numpy.float, numpy.float32]:
print("WARNING: Non floating point data")
text = "Calculation going on."
text += " WARNING: Non floating point data."
self._status.setText(text)
oldShape = stack.data.shape
result = function(stack, **pcaParameters)
if stack.data.shape != oldShape:
stack.data.shape = oldShape
return result
def threadFinished(self):
result = self.thread.result
self.thread = None
if type(result) == type((1,)):
#if we receive a tuple there was an error
if len(result):
if result[0] == "Exception":
self._status.setText("Ready after calculation error")
self.configurationWidget.setEnabled(True)
raise Exception(result[1], result[2])
return
self._status.setText("Ready")
self.configurationWidget.setEnabled(True)
self.configurationWidget.close()
images, eigenValues, eigenVectors = result
methodlabel = self.__methodlabel
imageNames = None
vectorNames = None
nimages = images.shape[0]
imageNames = []
vectorNames = []
itmp = nimages
if " ICA " in methodlabel:
itmp = nimages / 2
for i in range(itmp):
imageNames.append("ICAimage %02d" % i)
vectorNames.append("ICAvector %02d" % i)
for i in range(itmp):
imageNames.append("Eigenimage %02d" % i)
vectorNames.append("Eigenvector %02d" % i)
self.widget = StackPluginResultsWindow.StackPluginResultsWindow(\
usetab=True)
self.widget.buildAndConnectImageButtonBox()
qt = StackPluginResultsWindow.qt
self.widget.sigMaskImageWidgetSignal.connect(self.mySlot)
self.widget.setStackPluginResults(images,
spectra=eigenVectors,
image_names=imageNames,
spectra_names=vectorNames)
self._showWidget()
def _showWidget(self):
if self.widget is None:
return
#Show
self.widget.show()
self.widget.raise_()
#update
self.selectionMaskUpdated()
class PCAStackPlugin(StackPluginBase.StackPluginBase):
def __init__(self, stackWindow, **kw):
if _logger.getEffectiveLevel() == logging.DEBUG:
StackPluginBase.pluginBaseLogger.setLevel(logging.DEBUG)
StackPluginBase.StackPluginBase.__init__(self, stackWindow, **kw)
self.methodDict = {'Calculate': [self.calculate, "Perform PCA", None],
'Show': [self._showWidget,
"Show last results",
PyMca_Icons.brushselect]}
self.__methodKeys = ['Calculate', 'Show']
self.configurationWidget = None
self.widget = None
self.thread = None
def stackUpdated(self):
_logger.debug("PCAStackPlugin.stackUpdated() called")
self.configurationWidget = None
self.widget = None
def selectionMaskUpdated(self):
if self.widget is None:
return
if self.widget.isHidden():
return
mask = self.getStackSelectionMask()
self.widget.setSelectionMask(mask)
def mySlot(self, ddict):
_logger.debug("mySlot %s %s", ddict['event'], ddict.keys())
if ddict['event'] == "selectionMaskChanged":
self.setStackSelectionMask(ddict['current'])
elif ddict['event'] == "addImageClicked":
self.addImage(ddict['image'], ddict['title'])
elif ddict['event'] == "addAllClicked":
for i in range(len(ddict["images"])):
self.addImage(ddict['images'][i], ddict['titles'][i])
elif ddict['event'] == "removeImageClicked":
self.removeImage(ddict['title'])
elif ddict['event'] == "replaceImageClicked":
self.replaceImage(ddict['image'], ddict['title'])
elif ddict['event'] == "resetSelection":
self.setStackSelectionMask(None)
#Methods implemented by the plugin
def getMethods(self):
if self.widget is None:
return [self.__methodKeys[0]]
else:
return self.__methodKeys
def getMethodToolTip(self, name):
return self.methodDict[name][1]
def getMethodPixmap(self, name):
return self.methodDict[name][2]
def applyMethod(self, name):
return self.methodDict[name][0]()
#The specific part
def calculate(self):
if self.configurationWidget is None:
stack = self.getStackDataObject()
index = stack.info.get("McaIndex", -1)
stack = None
self.configurationWidget = PCAParametersDialog(None,
regions=True,
index=index)
self._status = qt.QLabel(self.configurationWidget)
self._status.setAlignment(qt.Qt.AlignHCenter)
font = qt.QFont(self._status.font())
font.setBold(True)
self._status.setFont(font)
self._status.setText("Ready")
self.configurationWidget.layout().addWidget(self._status)
self.configurationWidget.setEnabled(True)
activeCurve = self.getActiveCurve()
if activeCurve is None:
#I could get some defaults from the stack itslef
raise ValueError("Please select an active curve")
return
x, spectrum, legend, info = activeCurve
spectrumLength = max(spectrum.shape)
oldValue = self.configurationWidget.nPC.value()
self.configurationWidget.nPC.setMaximum(spectrumLength)
self.configurationWidget.nPC.setValue(min(oldValue, spectrumLength))
binningOptions = [1]
for number in [2, 3, 4, 5, 7, 9, 10, 11, 13, 15, 17, 19]:
if (spectrumLength % number) == 0:
binningOptions.append(number)
# TODO: Should inform the configuration widget about the possibility
# to encounter non-finite data?
ddict = {'options': binningOptions,
'binning': 1,
'method': 0}
self.configurationWidget.setParameters(ddict)
y = spectrum
self.configurationWidget.setSpectrum(x, y, legend=legend, info=info)
ret = self.configurationWidget.exec_()
if ret:
self._executeFunctionAndParameters()
def _executeFunctionAndParameters(self):
self.widget = None
self.configurationWidget.show()
if _logger.getEffectiveLevel() == logging.DEBUG:
self.thread = CalculationThread.CalculationThread(\
calculation_method=self.actualCalculation)
self.thread.result = self.actualCalculation()
self.threadFinished()
else:
self.thread = CalculationThread.CalculationThread(\
calculation_method=self.actualCalculation)
self.thread.finished.connect(self.threadFinished)
self.thread.start()
message = "Please wait. PCA Calculation going on."
CalculationThread.waitingMessageDialog(self.thread,
message=message,
parent=self.configurationWidget)
def actualCalculation(self):
pcaParameters = self.configurationWidget.getParameters()
self._status.setText("Calculation going on")
self.configurationWidget.setEnabled(False)
#self.configurationWidget.close()
self.__methodlabel = pcaParameters.get('methodlabel', "")
function = pcaParameters['function']
pcaParameters['ncomponents'] = pcaParameters['npc']
# At some point I should make sure I get directly the
# function and the parameters from the configuration widget
del pcaParameters['npc']
del pcaParameters['method']
del pcaParameters['function']
del pcaParameters['methodlabel']
# binning = pcaParameters['binning']
# mask = pcaParameters['mask']
regions = pcaParameters['regions']
spectral_mask = pcaParameters['spectral_mask']
#print("regions = ", regions)
#del pcaParameters['regions']
#del pcaParameters['spectral_mask']
#print("Regions and spectral mask not handled yet")
if not self.isStackFinite():
# one has to check for NaNs in the used region(s)
# for the time being only in the global image
# spatial_mask = numpy.isfinite(image_data)
spatial_mask = numpy.isfinite(self.getStackOriginalImage())
pcaParameters['mask'] = spatial_mask
pcaParameters["legacy"] = False
if "Multiple" in self.__methodlabel:
stackList = self.getStackDataObjectList()
oldShapes = []
for stack in stackList:
oldShapes.append(stack.data.shape)
result = function(stackList, **pcaParameters)
for i in range(len(stackList)):
stackList[i].data.shape = oldShapes[i]
return result
else:
stack = self.getStackDataObject()
if isinstance(stack, numpy.ndarray):
if stack.data.dtype not in [numpy.float, numpy.float32]:
_logger.warning("WARNING: Non floating point data")
text = "Calculation going on."
text += " WARNING: Non floating point data."
self._status.setText(text)
oldShape = stack.data.shape
result = function(stack, **pcaParameters)
if stack.data.shape != oldShape:
stack.data.shape = oldShape
return result
def threadFinished(self):
result = self.thread.getResult()
self.thread = None
if type(result) == type((1,)):
#if we receive a tuple there was an error
if len(result):
if result[0] == "Exception":
self._status.setText("Ready after calculation error")
self.configurationWidget.setEnabled(True)
raise Exception(result[1], result[2])
return
self._status.setText("Ready")
curve = self.configurationWidget.getSpectrum(binned=True)
if curve not in [None, []]:
xValues = curve[0]
else:
xValues = None
self.configurationWidget.setEnabled(True)
self.configurationWidget.close()
if hasattr(result, "keys"):
# new way
images = result["scores"]
eigenValues = result["eigenvalues"]
eigenVectors = result["eigenvectors"]
variance = result.get("variance", None)
if variance is not None:
explainedVariance = []
for value in eigenValues:
explainedVariance.append(100 * (value/variance))
else:
variance = None
images, eigenValues, eigenVectors = result
methodlabel = self.__methodlabel
imageNames = None
vectorNames = None
nimages = images.shape[0]
imageNames = []
vectorNames = []
itmp = nimages
if " ICA " in methodlabel:
itmp = int(nimages / 2)
for i in range(itmp):
imageNames.append("ICAimage %02d" % i)
vectorNames.append("ICAvector %02d" % i)
if "Multiple" in methodlabel:
xValues = None
for i in range(itmp):
imageNames.append("Eigenimage %02d" % i)
vectorNames.append("Eigenvector %02d" % i)
if variance is not None:
vectorNames[-1] = "EV%02d Explained variance %.4f %%" % \
(i, explainedVariance[i])
self.widget = StackPluginResultsWindow.StackPluginResultsWindow(\
usetab=True)
self.widget.buildAndConnectImageButtonBox(replace=True,
multiple=True)
qt = StackPluginResultsWindow.qt
self.widget.sigMaskImageWidgetSignal.connect(self.mySlot)
if xValues is not None:
xValues = [xValues] * nimages
self.widget.setStackPluginResults(images,
spectra=eigenVectors,
image_names=imageNames,
xvalues=xValues,
spectra_names=vectorNames)
self._showWidget()
def _showWidget(self):
if self.widget is None:
return
#Show
self.widget.show()
self.widget.raise_()
#update
self.selectionMaskUpdated()