Minor fix in usage and csv output (#2199)

* test_aggregate_slicewise: Added unit test perlevel

* sct_extract_metric,sct_process_segmentation: Clarified usage

Explicitly says that perlevel requires flag -vert

* aggregate_slicewise: Now always display VertLevel column

Fixes #2141

* test_aggregate_slicewise: Updated to account for VertLevel column

scripts/sct_extract_metric.py

@@ -131,7 +131,7 @@ def get_parser():
     parser.add_option(name='-perlevel',
                       type_value='int',
                       description='Set to 1 to output one metric per vertebral level instead of a single '
-                                  'output metric.',
+                                  'output metric. This flag needs to be used with flag -vert.',
                       mandatory=False,
                       default_value=0)
     parser.add_option(name="-v",

scripts/sct_process_segmentation.py

@@ -106,7 +106,7 @@ def get_parser():
     parser.add_option(name='-perlevel',
                       type_value='int',
                       description='Set to 1 to output one metric per vertebral level instead of a single '
-                                  'output metric.',
+                                  'output metric. This flag needs to be used with flag -vert.',
                       mandatory=False,
                       default_value=Param().perlevel)
     parser.add_option(name='-r',

spinalcordtoolbox/aggregate_slicewise.py

@@ -107,7 +107,9 @@ def aggregate_per_slice_or_level(metric, mask=None, slices=[], levels=[], persli
     # loop across slice group
     for slicegroup in slicegroups:
         # add level info
-        if levels:
+        if vertgroups is None:
+            agg_metric[slicegroup]['VertLevel'] = None
+        else:
             agg_metric[slicegroup]['VertLevel'] = vertgroups[slicegroups.index(slicegroup)]
         # Loop across functions (e.g.: MEAN, STD)
         for (name, func) in group_funcs:
@@ -402,7 +404,7 @@ def save_as_csv(agg_metric, fname_out, fname_in=None, append=False):
     # list_item = ['VertLevel', 'Label', 'MEAN', 'WA', 'BIN', 'ML', 'MAP', 'STD', 'MAX']
     # TODO: The thing below is ugly and needs to be fixed, but this is the only solution I found to order the columns
     #  without refactoring the code with OrderedDict.
-    list_item = ['VertLevel', 'Label', 'Size [vox]', 'MEAN(area)', 'STD(area)', 'MEAN(AP_diameter)', 'STD(AP_diameter)',
+    list_item = ['Label', 'Size [vox]', 'MEAN(area)', 'STD(area)', 'MEAN(AP_diameter)', 'STD(AP_diameter)',
                  'MEAN(RL_diameter)', 'STD(RL_diameter)', 'MEAN(ratio_minor_major)', 'STD(ratio_minor_major)',
                  'MEAN(eccentricity)', 'STD(eccentricity)', 'MEAN(orientation)', 'STD(orientation)',
                  'MEAN(equivalent_diameter)', 'STD(equivalent_diameter)', 'MEAN(solidity)', 'STD(solidity)',
@@ -412,7 +414,7 @@ def save_as_csv(agg_metric, fname_out, fname_in=None, append=False):
     if not append or not os.path.isfile(fname_out):
         with open(fname_out, 'w') as csvfile:
             # spamwriter = csv.writer(csvfile, delimiter=',')
-            header = ['Timestamp', 'SCT Version', 'Filename', 'Slice (I->S)']
+            header = ['Timestamp', 'SCT Version', 'Filename', 'Slice (I->S)', 'VertLevel']
             agg_metric_key = agg_metric[agg_metric.keys()[0]].keys()
             for item in list_item:
                 for key in agg_metric_key:
@@ -431,15 +433,11 @@ def save_as_csv(agg_metric, fname_out, fname_in=None, append=False):
             line.append(sct.__version__)  # SCT Version
             line.append(fname_in)  # file name associated with the results
             line.append(parse_num_list_inv(slicegroup))  # list all slices in slicegroup
+            line.append(parse_num_list_inv(agg_metric[slicegroup]['VertLevel']))  # list vertebral levels
             agg_metric_key = agg_metric[agg_metric.keys()[0]].keys()
             for item in list_item:
                 for key in agg_metric_key:
                     if item in key:
-                        # Special case for VertLevel
-                        if key == 'VertLevel':
-                            line.append(
-                                parse_num_list_inv(agg_metric[slicegroup]['VertLevel']))  # list vertebral levels
-                        else:
-                            line.append(str(agg_metric[slicegroup][key]))
+                        line.append(str(agg_metric[slicegroup][key]))
                         break
             spamwriter.writerow(line)

unit_testing/test_aggregate_slicewise.py

@@ -199,15 +199,15 @@ def test_save_as_csv(dummy_metrics):
     with open('tmp_file_out.csv', 'r') as csvfile:
         spamreader = csv.reader(csvfile, delimiter=',')
         spamreader.next()  # skip header
-        assert spamreader.next()[1:] == [sct.__version__, 'FakeFile.txt', '3:4', '45.5', '4.5']
+        assert spamreader.next()[1:] == [sct.__version__, 'FakeFile.txt', '3:4', '', '45.5', '4.5']
     # with appending
     aggregate_slicewise.save_as_csv(agg_metric, 'tmp_file_out.csv')
     aggregate_slicewise.save_as_csv(agg_metric, 'tmp_file_out.csv', append=True)
     with open('tmp_file_out.csv', 'r') as csvfile:
         spamreader = csv.reader(csvfile, delimiter=',')
         spamreader.next()  # skip header
-        assert spamreader.next()[1:] == [sct.__version__, '', '3:4', '45.5', '4.5']
-        assert spamreader.next()[1:] == [sct.__version__, '', '3:4', '45.5', '4.5']
+        assert spamreader.next()[1:] == [sct.__version__, '', '3:4', '', '45.5', '4.5']
+        assert spamreader.next()[1:] == [sct.__version__, '', '3:4', '', '45.5', '4.5']
 
 
 # noinspection 801,PyShadowingNames
@@ -225,6 +225,43 @@ def test_save_as_csv_slices(dummy_metrics, dummy_vert_level):
         assert row['VertLevel'] == '3:4'
 
 
+# noinspection 801,PyShadowingNames
+def test_save_as_csv_per_level(dummy_metrics, dummy_vert_level):
+    """Make sure slices are listed in reduced form"""
+    agg_metric = aggregate_slicewise.aggregate_per_slice_or_level(dummy_metrics['with float'], levels=[3, 4],
+                                                                  perlevel=True,
+                                                                  vert_level=dummy_vert_level,
+                                                                  group_funcs=(('WA', aggregate_slicewise.func_wa),))
+    aggregate_slicewise.save_as_csv(agg_metric, 'tmp_file_out.csv')
+    with open('tmp_file_out.csv', 'r') as csvfile:
+        reader = csv.DictReader(csvfile, delimiter=',')
+        row = reader.next()
+        assert row['Slice (I->S)'] == '2:3'
+        assert row['VertLevel'] == '3'
+
+
+# noinspection 801,PyShadowingNames
+def test_save_as_csv_per_slice_then_per_level(dummy_metrics, dummy_vert_level):
+    """Test with and without specifying perlevel. See: https://github.com/neuropoly/spinalcordtoolbox/issues/2141"""
+    agg_metric = aggregate_slicewise.aggregate_per_slice_or_level(dummy_metrics['with float'], levels=[3, 4],
+                                                                  perlevel=True,
+                                                                  vert_level=dummy_vert_level,
+                                                                  group_funcs=(('WA', aggregate_slicewise.func_wa),))
+    aggregate_slicewise.save_as_csv(agg_metric, 'tmp_file_out.csv')
+    agg_metric = aggregate_slicewise.aggregate_per_slice_or_level(dummy_metrics['with float'], slices=[0],
+                                                                  group_funcs=(('WA', aggregate_slicewise.func_wa),),)
+    aggregate_slicewise.save_as_csv(agg_metric, 'tmp_file_out.csv', append=True)
+    with open('tmp_file_out.csv', 'r') as csvfile:
+        reader = csv.DictReader(csvfile, delimiter=',')
+        row = reader.next()
+        assert row['Slice (I->S)'] == '2:3'
+        assert row['VertLevel'] == '3'
+        reader.next()
+        row = reader.next()
+        assert row['Slice (I->S)'] == '0'
+        assert row['VertLevel'] == ''
+
+
 # noinspection 801,PyShadowingNames
 def test_save_as_csv_sorting(dummy_metrics):
     """Make sure slices are sorted in output csv file"""
@@ -248,4 +285,4 @@ def test_save_as_csv_extract_metric(dummy_data_and_labels):
     with open('tmp_file_out.csv', 'r') as csvfile:
         spamreader = csv.reader(csvfile, delimiter=',')
         spamreader.next()  # skip header
-        assert spamreader.next()[1:-1] == [sct.__version__, '', '0:4', 'label_0', '2.5', '38.0']
+        assert spamreader.next()[1:-1] == [sct.__version__, '', '0:4', '', 'label_0', '2.5', '38.0']