flake + bump version number 2.4.2

Author: mayofaulkner

phylib/__init__.py

@@ -24,7 +24,7 @@
 
 __author__ = 'Cyrille Rossant'
 __email__ = 'cyrille.rossant at gmail.com'
-__version__ = '2.4.1'
+__version__ = '2.4.2'
 __version_git__ = __version__ + _git_version()
 
 

phylib/io/alf.py

@@ -239,7 +239,8 @@ def make_template_and_spikes_objects(self):
         # and not seconds
         self._save_npy('spikes.times.npy', self.model.spike_times)
         self._save_npy('spikes.samples.npy', self.model.spike_samples)
-        spike_amps, templates_v, template_amps = self.model.get_amplitudes_true(self.ampfactor, use='templates')
+        spike_amps, templates_v, template_amps = self.model.get_amplitudes_true(self.ampfactor,
+                                                                                use='templates')
         self._save_npy('spikes.amps.npy', spike_amps)
         self._save_npy('templates.amps.npy', template_amps)
 
@@ -264,7 +265,8 @@ def make_template_and_spikes_objects(self):
             np.save(self.out_path.joinpath('templates.waveforms'), templates)
             np.save(self.out_path.joinpath('templates.waveformsChannels'), templates_inds)
 
-            _, clusters_v, cluster_amps = self.model.get_amplitudes_true(self.ampfactor, use='clusters')
+            _, clusters_v, cluster_amps = self.model.get_amplitudes_true(self.ampfactor,
+                                                                         use='clusters')
             n_clusters, n_wavsamps, nchall = clusters_v.shape
             # for some datasets, 32 may be too much
             ncw = min(self.model.n_closest_channels, nchall)
@@ -284,11 +286,8 @@ def make_template_and_spikes_objects(self):
                 templates[t, ...] = clusters_v[t, :][:, templates_inds[t, :]]
             np.save(self.out_path.joinpath('clusters.waveforms'), templates)
             np.save(self.out_path.joinpath('clusters.waveformsChannels'), templates_inds)
-
-            # TODO check if we should save this here, will be inconsistent with what we have at the moment
             np.save(self.out_path.joinpath('clusters.amps'), cluster_amps)
 
-
     def rename_with_label(self):
         """add the label as an ALF part name before the extension if any label provided"""
         if not self.label:

phylib/io/model.py

@@ -413,7 +413,8 @@ def _load_data(self):
             self.n_channels_loc = 0
 
         # Clusters waveforms
-        if not np.all(self.spike_clusters == self.spike_templates) and self.sparse_templates.cols is None:
+        if not np.all(self.spike_clusters == self.spike_templates) and \
+                self.sparse_templates.cols is None:
             self.merge_map, self.nan_idx = self.get_merge_map()
             self.sparse_clusters = self.cluster_waveforms()
             self.n_clusters = self.spike_clusters.max() + 1
@@ -872,7 +873,8 @@ def _template_n_channels(self, template_id, n_channels):
             channel_ids += [-1] * (n_channels - len(channel_ids))
         return channel_ids
 
-    def _get_template_dense(self, template_id, channel_ids=None, amplitude_threshold=None, unwhiten=True):
+    def _get_template_dense(self, template_id, channel_ids=None, amplitude_threshold=None,
+                            unwhiten=True):
         """Return data for one template."""
         if not self.sparse_templates:
             return
@@ -955,7 +957,8 @@ def get_template(self, template_id, channel_ids=None, amplitude_threshold=None,
             return self._get_template_sparse(template_id, unwhiten=unwhiten)
         else:
             return self._get_template_dense(
-                template_id, channel_ids=channel_ids, amplitude_threshold=amplitude_threshold, unwhiten=unwhiten)
+                template_id, channel_ids=channel_ids, amplitude_threshold=amplitude_threshold,
+                unwhiten=unwhiten)
 
     def get_waveforms(self, spike_ids, channel_ids=None):
         """Return spike waveforms on specified channels."""
@@ -1212,7 +1215,8 @@ def get_cluster_mean_waveforms(self, cluster_id, unwhiten=True):
         template = self.get_template(best_template, unwhiten=unwhiten)
         channel_ids = template.channel_ids
         # Get all templates from which this cluster stems from.
-        templates = [self.get_template(template_id, unwhiten=unwhiten) for template_id in template_ids]
+        templates = [self.get_template(template_id, unwhiten=unwhiten)
+                     for template_id in template_ids]
         # Construct the waveforms array.
         ns = self.n_samples_waveforms
         data = np.zeros((len(template_ids), ns, self.n_channels))
@@ -1313,7 +1317,8 @@ def cluster_waveforms(self):
         for clust, val in self.merge_map.items():
             if len(val) > 1:
                 mean_waveform = self.get_cluster_mean_waveforms(clust, unwhiten=False)
-                data[clust, :, mean_waveform.channel_ids] = np.swapaxes(mean_waveform.mean_waveforms, 0, 1)
+                data[clust, :, mean_waveform.channel_ids] = \
+                    np.swapaxes(mean_waveform.mean_waveforms, 0, 1)
             elif len(val) == 1:
                 data[clust, :, :] = self.sparse_templates.data[val[0], :, :]
 

phylib/io/tests/test_alf.py

@@ -20,7 +20,6 @@
 from ..model import TemplateModel
 
 
-
 #------------------------------------------------------------------------------
 # Fixture
 #------------------------------------------------------------------------------
@@ -236,7 +235,8 @@ def test_merger(dataset):
 
     # merge the first two clusters
     merge_clu = clu[0:2]
-    spike_clusters[np.bitwise_or(spike_clusters == clu[0], spike_clusters == clu[1])] = np.max(clu) + 1
+    spike_clusters[np.bitwise_or(spike_clusters == clu[0],
+                                 spike_clusters == clu[1])] = np.max(clu) + 1
     # split the cluster with the most spikes
     split_clu = clu[-1]
     idx = np.where(spike_clusters == split_clu)[0]