Merge f7cce70 into 95cb121

calour/analysis.py

@@ -130,7 +130,6 @@ def correlation(exp: Experiment, field, method='spearman', nonzero=False, transf
     keep, odif, pvals = dsfdr.dsfdr(data, labels, method=method, transform_type=transform, alpha=alpha, numperm=numperm, fdr_method=fdr_method)
     logger.info('Positive correlated features : %d. Negative correlated features : %d. total %d'
                 % (np.sum(odif[keep] > 0), np.sum(odif[keep] < 0), np.sum(keep)))
-
     newexp = _new_experiment_from_pvals(cexp, exp, keep, odif, pvals)
     newexp.feature_metadata[_CALOUR_DIRECTION] = [field if x > 0 else 'Anti-%s' % field for x in newexp.feature_metadata[_CALOUR_STAT]]
     return newexp

calour/dsfdr.py

@@ -272,15 +272,18 @@ def dsfdr(data, labels, transform_type='rankdata', method='meandiff',
             index = np.nonzero(data[i, :])
             label_nonzero = labels[index]
             sample_nonzero = data[i, :][index]
+            if len(sample_nonzero) == 0:
+                continue
             if method == 'nonzerospearman':
                 sample_nonzero = sp.stats.rankdata(sample_nonzero)
                 label_nonzero = sp.stats.rankdata(label_nonzero)
             sample_nonzero = sample_nonzero - np.mean(sample_nonzero)
             label_nonzero = label_nonzero - np.mean(label_nonzero)
             tstat[i] = np.dot(sample_nonzero, label_nonzero)
             t[i] = np.abs(tstat[i])
+            if np.std(sample_nonzero) == 0:
+                continue
             tstat[i] = tstat[i] / (np.std(sample_nonzero) * np.std(label_nonzero) * len(sample_nonzero))
-
             permlabels = np.zeros([len(label_nonzero), numperm])
             for cperm in range(numperm):
                 rlabels = np.random.permutation(label_nonzero)

calour/export_html.py

@@ -34,22 +34,22 @@
 logger = getLogger(__name__)
 
 
-def _list_to_string(l):
+def _list_to_string(cl):
     '''Convert a list to a string representation of the list
 
     For use in the html javascript
 
     Parameters
     ----------
-    l : list
+    cl : list
 
     Returns
     -------
     str
         ready for embedding into html javascript
     '''
     cstr = '['
-    for cval in l:
+    for cval in cl:
         cstr += '"'
         cstr += str(cval)
         cstr += '",'

calour/heatmap/plotgui.py

@@ -139,7 +139,7 @@ def _set_figure(self, figure=None, tree_size=0):
             self.ax_legend = self.figure.add_subplot(gs[7])
             self.gridspec = gs
 
-    def resize_figure (self, *args, **kwargs):
+    def resize_figure(self, *args, **kwargs):
         '''Resize the figure.
 
         It is a convenient function that wraps on

calour/tests/test_analysis.py

@@ -116,7 +116,7 @@ def test_correlation_complex_spearman(self):
         np.random.seed(2017)
         # test on real complex dataset (timeseries) with spearman correlation
         dd = self.complex.correlation('MF_SAMPLE_NUMBER', method='spearman')
-        print(len(dd.feature_metadata))
+        # print(len(dd.feature_metadata))
         self.assertTrue(np.abs(51 - len(dd.feature_metadata)) < 5)
 
     def test_diff_abundance_kw(self):

calour/tests/test_database.py

@@ -36,11 +36,15 @@ def test_mock_db(self):
     def test_gui_interface(self):
         mdb = self.mock_db
         res = mdb.get_seq_annotation_strings(self.s1)
-        print(res)
+        self.assertEqual(len(res), 2)
+        self.assertEqual(res[1][1], 'nice')
+        self.assertFalse('_db_interface' in res[0][0])
         gui = _create_plot_gui(self.test1, gui='qt5', databases=[])
         gui.databases.append(mdb)
         res = gui.get_database_annotations(self.s1)
-        print(res)
+        self.assertEqual(len(res), 2)
+        self.assertTrue('_db_interface' in res[0][0])
+        self.assertEqual(res[1][1], 'nice')
 
     def test_get_database_class(self):
         d = mkdtemp()

calour/util.py

@@ -70,28 +70,28 @@ def compute_prevalence(abundance):
     return cutoffs, prevalences
 
 
-def _transition_index(l):
+def _transition_index(obj):
     '''Return the transition index and current value of the list.
 
     Examples
     -------
-    >>> l = ['a', 'a', 'b']
-    >>> list(_transition_index(l))
+    >>> obj = ['a', 'a', 'b']
+    >>> list(_transition_index(obj))
     [(2, 'a'), (3, 'b')]
-    >>> l = ['a', 'a', 'b', 1, 2, None, None]
-    >>> list(_transition_index(l))
+    >>> obj = ['a', 'a', 'b', 1, 2, None, None]
+    >>> list(_transition_index(obj))
     [(2, 'a'), (3, 'b'), (4, 1), (5, 2), (7, None)]
 
     Parameters
     ----------
-    l : Iterable of arbitrary objects
+    obj : Iterable of arbitrary objects
 
     Yields
     ------
     tuple of (int, arbitrary)
         the transition index, the item value
     '''
-    it = enumerate(l)
+    it = enumerate(obj)
     i, item = next(it)
     item = str(type(item)), item
     for i, current in it: