[components] Save W matrix with all images shape

darfix/core/dataset.py

@@ -359,9 +359,6 @@ class Dataset(qt.QObject):
         """
         if not self._dimensions_values:
             data = self.metadata
-            # Use only metadata of high intensity data
-            if self._filter_data:
-                data = numpy.array(self.metadata)[self.threshold]
             for dimension in self.__dims:
                 values = numpy.empty((len(data)))
                 for row, metadata_frame in enumerate(data):

darfix/gui/blindSourceSeparationWidget.py

@@ -148,6 +148,13 @@ class BSSWidget(qt.QMainWindow):
         self._displayComponentsWidget.show()
         self.computeButton.setEnabled(True)
         self.nComponentsLE.setEnabled(True)
+        if numpy.any(self.dataset.li_data):
+            # If filter data is activated, the matrix W has reduced dimensionality, so reshaping is not possible
+            # Create empty array with shape the total number of frames
+            W = numpy.zeros((self.dataset.nframes, n_comp))
+            # Set actual values of W where threshold of filter is True
+            W[self.dataset.threshold] = self.W
+            self.W = W
         self._displayComponentsWidget.setComponents(self.comp, self.W, self.dataset.get_dimensions_values())
 
     def _detectComp(self):

darfix/gui/displayComponentsWidget.py

@@ -218,20 +218,6 @@ class DisplayComponentsWidget(qt.QMainWindow):
             self._plot_rocking_curves.getBrowser().setRange(0, len(self.dimensions[text]) - 1)
             self._plot_rocking_curves.getBrowser().setValue(0)
             for i in range(len(self.W.T)):
-                """
-                if numpy.any(self.dataset.li_data):
-                    # If filter data is activated, the matrix W has reduced dimensionality, so reshaping is not possible
-                    # Create empty array with shape the total number of frames
-                    W = numpy.empty(self.dataset.threshold.shape)
-                    # Set actual values of W where threshold of filter is True
-                    W[self.dataset.threshold] = self.W.T[i]
-                    # Take only the thresholds for the dimension
-                    threshold = numpy.take(self.dataset.threshold.reshape(self.dataset.dims.shape), 0, axis=self.dimension)
-                    # Reshape W into the dimensions and take the first element of the chosen dimension
-                    W = numpy.take(W.reshape(self.dataset.dims.shape), 0, self.dimension)
-                    # Take only the values of W that correspond to high intensity data
-                    W = W[threshold]
-                else:"""
                 dimensions_shape = numpy.array(self.dimensions.values()).shape
                 W = numpy.take(self.W.T[i].reshape(dimensions_shape), self.index, self.dimension)
                 self._plot_rocking_curves.addCurve(numpy.arange(len(W)), W, legend=str(i))
@@ -246,19 +232,6 @@ class DisplayComponentsWidget(qt.QMainWindow):
         self.index = index
         self._plot_rocking_curves.clear()
         for i in range(len(self.W.T)):
-            """if numpy.any(self.dataset.li_data):
-                # If filter data is activated, the matrix W has reduced dimensionality, so reshaping is not possible
-                # Create empty array with shape the total number of frames
-                W = numpy.empty(self.dataset.threshold.shape)
-                # Set actual values of W where threshold of filter is True
-                W[self.dataset.threshold] = self.W.T[i]
-                # Take only the thresholds for the dimension
-                threshold = numpy.take(self.dataset.threshold.reshape(self.dataset.dims.shape), self.index, axis=self.dimension)
-                # Reshape W into the dimensions and take the chosen element and dimension
-                W = numpy.take(W.reshape(self.dataset.dims.shape), self.index, self.dimension)
-                # Take only the values of W that correspond to high intensity data
-                W = W[threshold]
-            else:"""
             dimensions_shape = numpy.array(self.dimensions.values()).shape
             W = numpy.take(self.W.T[i].reshape(dimensions_shape), self.index, self.dimension)
             self._plot_rocking_curves.addCurve(numpy.arange(len(W)), W, legend=str(i))