Refactor, fix issue with some sample workspaces

Some workspaces have differing numbers of array elements for X, Y and E
values, just choose the samllest and trim the longer arrays

Refs #7860

Code/Mantid/Framework/PythonInterface/plugins/algorithms/Symmetrise.py

@@ -36,68 +36,80 @@ def PyExec(self):
 
         StartTime('Symmetrise')
         self._setup()
-        num_spectra, sample_aray_len = CheckHistZero(self._sample)
+        num_spectra, _ = CheckHistZero(self._sample)
         sample_x = mtd[self._sample].readX(0)
 
         if math.fabs(self._x_cut) < 1e-5:
             raise ValueError('XCut point is Zero')
 
-        # Find range of values to flip
+        # Find the smallest data array in the first spectra
+        len_x = len(mtd[self._sample].readX(0))
+        len_y = len(mtd[self._sample].readY(0))
+        len_e = len(mtd[self._sample].readE(0))
+        sample_array_len = min(len_x, len_y, len_e) - 1
+
         delta_x = sample_x[1] - sample_x[0]
 
+        # Find array index of negative XCut
         negative_diff = np.absolute(sample_x + self._x_cut)
         negative_index = np.where(negative_diff < delta_x)[0][-1]
-        self._check_bounds(negative_index, sample_aray_len, label='Negative')
+        self._check_bounds(negative_index, sample_array_len, label='Negative')
 
+        # FInd array index of positive XCut
         positive_diff = np.absolute(sample_x + sample_x[negative_index])
         positive_index = np.where(positive_diff < delta_x)[0][-1]
-        self._check_bounds(positive_index, sample_aray_len, label='Positive')
+        self._check_bounds(positive_index, sample_array_len, label='Positive')
 
-        new_array_len = 2 * sample_aray_len - (positive_index + negative_index) + 1
+        # Calculate number of elements neede dfor new array (per spectra)
+        new_array_len = 2 * sample_array_len - (positive_index + negative_index) + 1
 
         if self._verbose:
-            logger.notice('No. points = %d' % sample_aray_len)
-            logger.notice('Negative : at i =%d; x = %f'
+            logger.notice('No. points = %d' % sample_array_len)
+            logger.notice('Negative at i=%d, x=%f'
                           % (negative_index, sample_x[negative_index]))
-            logger.notice('Positive : at i =%d; x = %f'
+            logger.notice('Positive at i=%d, x=%f'
                           % (positive_index, sample_x[positive_index]))
             logger.notice('New array size = %d' % new_array_len)
 
+        # Create an empty workspace with enough storage for the new data
         zeros = np.zeros(new_array_len * num_spectra)
         CreateWorkspace(OutputWorkspace=self._output_workspace,
                         DataX=zeros, DataY=zeros, DataE=zeros,
                         NSpec=num_spectra)
 
+        # Copy logs and properties from sample workspace
         CopyLogs(InputWorkspace=self._sample, OutputWorkspace=self._output_workspace)
         CopyInstrumentParameters(InputWorkspace=self._sample, OutputWorkspace=self._output_workspace)
         # CopySample(InputWorkspace=self._sample, OutputWorkspace=self._output_workspace)
 
         # For each spectrum copy positive values to the negative
         for index in xrange(num_spectra):
-            x_in = mtd[self._sample].readX(index)
-            y_in = mtd[self._sample].readY(index)
-            e_in = mtd[self._sample].readE(index)
+            # Strip any additional array cells
+            x_in = mtd[self._sample].readX(index)[:sample_array_len + 1]
+            y_in = mtd[self._sample].readY(index)[:sample_array_len + 1]
+            e_in = mtd[self._sample].readE(index)[:sample_array_len + 1]
 
+            # Get some zeroed data to overwrite with copies from sample
             x_out = np.zeros(new_array_len)
             y_out = np.zeros(new_array_len)
             e_out = np.zeros(new_array_len)
 
             # Left hand side of cut
-            x_out[:sample_aray_len - positive_index] = -x_in[sample_aray_len:positive_index:-1]
-            y_out[:sample_aray_len - positive_index] = y_in[sample_aray_len:positive_index:-1]
-            e_out[:sample_aray_len - positive_index] = e_in[sample_aray_len:positive_index:-1]
+            x_out[:sample_array_len - positive_index] = -x_in[sample_array_len:positive_index:-1]
+            y_out[:sample_array_len - positive_index] = y_in[sample_array_len:positive_index:-1]
+            e_out[:sample_array_len - positive_index] = e_in[sample_array_len:positive_index:-1]
 
             # Right hand side of cut
-            x_out[sample_aray_len - positive_index:] = x_in[negative_index:]
-            y_out[sample_aray_len - positive_index:] = y_in[negative_index:]
-            e_out[sample_aray_len - positive_index:] = e_in[negative_index:]
+            x_out[sample_array_len - positive_index:] = x_in[negative_index:]
+            y_out[sample_array_len - positive_index:] = y_in[negative_index:]
+            e_out[sample_array_len - positive_index:] = e_in[negative_index:]
 
             mtd[self._output_workspace].setX(index, x_out)
             mtd[self._output_workspace].setY(index, y_out)
             mtd[self._output_workspace].setE(index, e_out)
 
             logger.information('Spectra %d out of %d done'
-                               % (index, num_spectra))
+                               % (index + 1, num_spectra))
 
         if self._save:
             self._save_output()
@@ -154,7 +166,7 @@ def _plot_output(self):
         """
         from IndirectImport import import_mantidplot
         mtd_plot = import_mantidplot()
-        mtd_plot.plotSpectrum([self._output_workspace, self._sample], 0)
+        mtd_plot.plotSpectrum([self._sample, self._output_workspace], 0)
 
 # Register algorithm with Mantid
 AlgorithmFactory.subscribe(Symmetrise)