Merge pull request #129 from pycroscopy/nsid_reader_fn

Nsid reader fn

SciFiReaders/readers/SID/Nsid_reader.py

@@ -90,6 +90,21 @@ def read(self, h5_object=None):
             return read_h5py_dataset(h5_object)
         else:
             return self.read_all(parent=h5_object)
+
+        #TODO: We need to add the ability to read functions in any sidpy datasets.
+        # We will assume that fitting functions are contained within a dictionary of the same name. 
+        #They will have been saved with dill and encoded. To decode them, use:
+
+        '''
+        fit_fn_packed = fit_data.metadata['fitting_functions']
+        loaded_dict = {}
+        fit_fns = []
+        for key in fit_fn_packed.keys():
+            encoded_value = fit_fn_packed['my_function']
+            serialized_value = base64.b64decode(encoded_value)
+            loaded_dict[key] = dill.loads(serialized_value)
+            fit_fns.append(loaded_dict[key]) #retrieve the function
+        '''
 
     def __validate_obj_in_same_file(self, h5_object):
         """

SciFiReaders/readers/microscopy/spm/afm/bruker_nano.py

@@ -152,7 +152,7 @@ def _read_image_stack(self):
         #Here are teh dimension details
         num_samps_line = layer_info['Samps/line']
         num_lines = layer_info['Number of lines']
-
+        
         #Read through and write to sidpy dataset objects
         datasets = []
         for class_name in self.meta_data.keys():
@@ -162,10 +162,21 @@ def _read_image_stack(self):
                 quantity = layer_info.pop('Image Data_2')
                 title = quantity.split("\"")[1]
                 data = self._read_image_layer(layer_info)
-                num_cols, num_rows = data.shape
-                data_set = sid.Dataset.from_array(data, name=title)
-                data_set.data_type = 'Image'
+                traces = None
+                if len(data.shape)==2:
+                  num_cols, num_rows = data.shape
+
+                elif len(data.shape)==3:
+                  num_cols, num_rows, traces = data.shape
+                else:
+                  raise ValueError("data is shape {}, too few/many for image stack".format(data.shape))
 
+                data_set = sid.Dataset.from_array(data, name=title)
+                if traces is None:
+                  data_set.data_type = 'Image'
+                else:
+                  data_set.data_type='Image_Stack'
+
                 #Add quantity and units
                 data_set.units = 'nm' #check this one
                 data_set.quantity = quantity
@@ -179,10 +190,11 @@ def _read_image_stack(self):
                                                         name = 'y',
                                                         units='nm', quantity='y',
                                                         dimension_type='spatial'))
-
+                if traces is not None:
+                  data_set.set_dimension(2, sid.Dimension(np.arange(traces), name = 'trace #', units ='#', quantity = 'none', dimension_type = 'frame'))
+
                 # append metadata
                 data_set.original_metadata = self.meta_data[class_name]
-                data_set.data_type = 'image'
 
                 datasets.append(data_set)
 
@@ -335,7 +347,11 @@ def _read_image_layer(self, layer_info):
             2D array representing the requested channel of information
         """
         data_vec = self._read_data_vector(layer_info)
-        data_mat = data_vec.reshape(layer_info['Number of lines'], layer_info['Samps/line'])
+        if np.size(data_vec)==layer_info['Number of lines']*layer_info['Samps/line']:
+          data_mat = data_vec.reshape(layer_info['Number of lines'], layer_info['Samps/line'])
+        elif np.size(data_vec)==layer_info['Number of lines']*layer_info['Samps/line']*2:
+          print('detected trace and retrace, attempting to reshape')
+          data_mat = data_vec.reshape(layer_info['Number of lines'], layer_info['Samps/line'],2)
         return data_mat
 
     def can_read(self):
@@ -348,3 +364,4 @@ def can_read(self):
         """
         return super(BrukerAFMReader, self).can_read(extension='')
 
+