[core][dataset] Modify dimension values to be adictionary with key the dimensions names

darfix/core/dataset.py

@@ -89,7 +89,7 @@ class Dataset(qt.QObject):
         self.dark_filename = dark_filename
         self.filenames = filenames
         self.__dims = AcquisitionDims()
-        self._dimensions_values = None
+        self._dimensions_values = {}
 
         # Initialize data
         self._file_series = fabio.open_series(first_filename=raw_filename,
@@ -325,7 +325,7 @@ class Dataset(qt.QObject):
         unique values.
         """
         self.__dims.clear()
-        self._dimensions_values = None
+        self._dimensions_values = {}
 
         keys = numpy.array(list(self.metadata[0].get_keys(kind)))
         values = numpy.array([[data.get_value(kind=kind, name=key)[0] for data
@@ -357,18 +357,17 @@ class Dataset(qt.QObject):
 
         :returns: array_like
         """
-        if self._dimensions_values is None:
+        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]
-            values = numpy.empty((self.__dims.ndim, len(data)))
-            for row, metadata_frame in enumerate(data):
-                for dimension in self.__dims:
-                    val = metadata_frame.get_value(kind=dimension[1].kind, name=dimension[1].name)
-                    values[dimension[0]][row] = val[0]
-
-            self._dimensions_values = values
+            for dimension in self.__dims:
+                values = numpy.empty((len(data)))
+                for row, metadata_frame in enumerate(data):
+                    values[row] = (metadata_frame.get_value(kind=dimension[1].kind,
+                                   name=dimension[1].name)[0])
+                self._dimensions_values[dimension[1].name] = values
         return self._dimensions_values
 
     def __deepcopy__(self, memo):