def calculate(self):
stack = self.getStackDataObject()
mcaIndex = stack.info.get('McaIndex')
shape = stack.data.shape
stack = None
if mcaIndex not in [-1, len(shape) - 1]:
raise IndexError("NNMA does not support stacks of images yet")
return
if self.configurationWidget is None:
self.configurationWidget = NNMAParametersDialog(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 = int(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()
self.configurationWidget.raise_()
ret = self.configurationWidget.exec_()
if ret:
self._executeFunctionAndParameters()
def calculate(self):
stack = self.getStackDataObject()
mcaIndex = stack.info.get('McaIndex')
shape = stack.data.shape
stack = None
if mcaIndex not in [-1, len(shape) - 1]:
raise IndexError("NNMA does not support stacks of images yet")
return
if self.configurationWidget is None:
self.configurationWidget = NNMAParametersDialog(None)
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 = int(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)
ddict = {'options': binningOptions,
'binning': 1,
'method': 0}
self.configurationWidget.setParameters(ddict)
y = spectrum
self.configurationWidget.setSpectrum(x, y)
self.configurationWidget.show()
self.configurationWidget.raise_()
ret = self.configurationWidget.exec_()
if ret:
self._executeFunctionAndParameters()
class NNMAStackPlugin(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 NNMA",
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("NNMAStackPlugin.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):
stack = self.getStackDataObject()
mcaIndex = stack.info.get('McaIndex')
shape = stack.data.shape
stack = None
if mcaIndex not in [-1, len(shape) - 1]:
raise IndexError("NNMA does not support stacks of images yet")
return
if self.configurationWidget is None:
self.configurationWidget = NNMAParametersDialog(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 = int(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()
self.configurationWidget.raise_()
ret = self.configurationWidget.exec_()
if ret:
self._executeFunctionAndParameters()
def _executeFunctionAndParameters(self):
_logger.debug("NNMAStackPlugin _executeFunctionAndParameters")
self.widget = None
self.thread = CalculationThread.CalculationThread(\
calculation_method=self.actualCalculation)
self.thread.finished.connect(self.threadFinished)
self.configurationWidget.show()
message = "Please wait. NNMA Calculation going on."
_logger.debug("NNMAStackPlugin starting thread")
self.thread.start()
_logger.debug("NNMAStackPlugin waitingMessageDialog")
CalculationThread.waitingMessageDialog(self.thread,
message=message,
parent=self.configurationWidget)
_logger.debug("NNMAStackPlugin waitingMessageDialog passed")
def actualCalculation(self):
_logger.debug("NNMAStackPlugin actualCalculation")
nnmaParameters = self.configurationWidget.getParameters()
self._status.setText("Calculation going on")
self.configurationWidget.setEnabled(False)
#self.configurationWidget.close()
#At some point I should make sure I get directly the
#function and the parameters from the configuration widget
function = nnmaParameters['function']
ddict = {}
ddict.update(nnmaParameters['kw'])
ddict['ncomponents'] = nnmaParameters['npc']
ddict['binning'] = nnmaParameters['binning']
ddict['spectral_mask'] = nnmaParameters['spectral_mask']
#ddict['kmeans'] = False
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())
ddictParameters['mask'] = spatial_mask
del nnmaParameters
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, **ddict)
if stack.data.shape != oldShape:
stack.data.shape = oldShape
return result
def threadFinished(self):
_logger.debug("NNMAStackPlugin threadFinished")
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 type(result[0]) == type("Exception"):
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()
images, eigenValues, eigenVectors = result
imageNames = None
vectorNames = None
nimages = images.shape[0]
imageNames = []
vectorNames = []
vectorTitles = []
for i in range(nimages):
imageNames.append("NNMA Image %02d" % i)
vectorNames.append("NNMA Component %02d" % i)
vectorTitles.append("%g %% explained intensity" %\
eigenValues[i])
_logger.debug("NNMAStackPlugin threadFinished. Create widget")
self.widget = StackPluginResultsWindow.StackPluginResultsWindow(\
usetab=True)
_logger.debug("NNMAStackPlugin threadFinished. Widget created")
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,
spectra_titles=vectorTitles)
self._showWidget()
def _showWidget(self):
if self.widget is None:
return
#Show
self.widget.show()
self.widget.raise_()
#update
self.selectionMaskUpdated()
class NNMAStackPlugin(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 NNMA",
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("NNMAStackPlugin.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):
stack = self.getStackDataObject()
mcaIndex = stack.info.get('McaIndex')
shape = stack.data.shape
stack = None
if mcaIndex not in [-1, len(shape) - 1]:
raise IndexError("NNMA does not support stacks of images yet")
return
if self.configurationWidget is None:
self.configurationWidget = NNMAParametersDialog(None)
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 = int(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)
ddict = {'options': binningOptions,
'binning': 1,
'method': 0}
self.configurationWidget.setParameters(ddict)
y = spectrum
self.configurationWidget.setSpectrum(x, y)
self.configurationWidget.show()
self.configurationWidget.raise_()
ret = self.configurationWidget.exec_()
if ret:
self._executeFunctionAndParameters()
def _executeFunctionAndParameters(self):
_logger.debug("NNMAStackPlugin _executeFunctionAndParameters")
self.widget = None
self.thread = CalculationThread.CalculationThread(\
calculation_method=self.actualCalculation)
self.thread.finished.connect(self.threadFinished)
self.configurationWidget.show()
message = "Please wait. NNMA Calculation going on."
_logger.debug("NNMAStackPlugin starting thread")
self.thread.start()
_logger.debug("NNMAStackPlugin waitingMessageDialog")
CalculationThread.waitingMessageDialog(self.thread,
message=message,
parent=self.configurationWidget)
_logger.debug("NNMAStackPlugin waitingMessageDialog passed")
def actualCalculation(self):
_logger.debug("NNMAStackPlugin actualCalculation")
nnmaParameters = self.configurationWidget.getParameters()
self._status.setText("Calculation going on")
self.configurationWidget.setEnabled(False)
#self.configurationWidget.close()
#At some point I should make sure I get directly the
#function and the parameters from the configuration widget
function = nnmaParameters['function']
ddict = {}
ddict.update(nnmaParameters['kw'])
ddict['ncomponents'] = nnmaParameters['npc']
ddict['binning'] = nnmaParameters['binning']
#ddict['kmeans'] = False
del nnmaParameters
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, **ddict)
if stack.data.shape != oldShape:
stack.data.shape = oldShape
return result
def threadFinished(self):
_logger.debug("NNMAStackPlugin threadFinished")
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 type(result[0]) == type("Exception"):
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()
images, eigenValues, eigenVectors = result
imageNames = None
vectorNames = None
nimages = images.shape[0]
imageNames = []
vectorNames = []
vectorTitles = []
for i in range(nimages):
imageNames.append("NNMA Image %02d" % i)
vectorNames.append("NNMA Component %02d" % i)
vectorTitles.append("%g %% explained intensity" %\
eigenValues[i])
_logger.debug("NNMAStackPlugin threadFinished. Create widget")
self.widget = StackPluginResultsWindow.StackPluginResultsWindow(\
usetab=True)
_logger.debug("NNMAStackPlugin threadFinished. Widget created")
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,
spectra_titles=vectorTitles)
self._showWidget()
def _showWidget(self):
if self.widget is None:
return
#Show
self.widget.show()
self.widget.raise_()
#update
self.selectionMaskUpdated()