def get_waveforms(self, spikes=None, clusters=None):
if self.waveforms_selected is None:
return None
# Special case: return the already-selected values from the cache.
if spikes is None and clusters is None:
values = self.process_waveforms(self.waveforms_selected)
return pandaize(values, self.spikes_waveforms)
# Normal case.
if self.spikes_selected_table is None:
return None
if spikes is not None:
return select(self.waveforms, spikes)
else:
if clusters is None:
clusters = self.clusters_selected
if clusters is not None:
spikes = get_some_spikes_in_clusters(clusters, self.clusters,
counter=self.counter,
nspikes_max_expected=self.userpref['waveforms_nspikes_max_expected'],
nspikes_per_cluster_min=self.userpref['waveforms_nspikes_per_cluster_min'])
else:
spikes = self.spikes_selected
return select(self.waveforms, spikes)
def get_waveforms(self, spikes=None, clusters=None):
if spikes is not None:
return select(self.waveforms, spikes)
else:
if clusters is None:
clusters = self.clusters_selected
if clusters is not None:
spikes = get_some_spikes_in_clusters(clusters, self.clusters,
counter=self.counter,
nspikes_max_expected=self.userpref['waveforms_nspikes_max_expected'],
nspikes_per_cluster_min=self.userpref['waveforms_nspikes_per_cluster_min'])
else:
spikes = self.spikes_selected
return select(self.waveforms, spikes)
def get_waveforms(self, spikes=None, clusters=None):
if spikes is not None:
return select(self.waveforms, spikes)
else:
if clusters is None:
clusters = self.clusters_selected
if clusters is not None:
spikes = get_some_spikes_in_clusters(clusters, self.clusters,
counter=self.counter,
nspikes_max_expected=self.userpref['waveforms_nspikes_max_expected'],
nspikes_per_cluster_min=self.userpref['waveforms_nspikes_per_cluster_min'])
else:
spikes = self.spikes_selected
return select(self.waveforms, spikes)
def get_some_features(self, clusters=None):
"""Return the features for a subset of all spikes: a large number
of spikes from any cluster, and a controlled subset of the selected
clusters."""
if clusters is None:
clusters = self.clusters_selected
if clusters is not None:
spikes_background = get_some_spikes(self.clusters,
nspikes_max=self.userpref['features_nspikes_background_max'],)
spikes_clusters = get_some_spikes_in_clusters(
clusters,
self.clusters,
counter=self.counter,
nspikes_max_expected=self.userpref[
'features_nspikes_selection_max'],
nspikes_per_cluster_min=self.userpref[
'features_nspikes_per_cluster_min'])
spikes = np.union1d(spikes_background, spikes_clusters)
else:
spikes = self.spikes_selected
return select(self.features, spikes)
def get_some_features(self, clusters=None):
"""Return the features for a subset of all spikes: a large number
of spikes from any cluster, and a controlled subset of the selected
clusters."""
if clusters is None:
clusters = self.clusters_selected
if clusters is not None:
spikes_background = get_some_spikes(self.clusters,
nspikes_max=self.userpref['features_nspikes_background_max'],)
spikes_clusters = get_some_spikes_in_clusters(
clusters,
self.clusters,
counter=self.counter,
nspikes_max_expected=self.userpref[
'features_nspikes_selection_max'],
nspikes_per_cluster_min=self.userpref[
'features_nspikes_per_cluster_min'])
spikes = np.union1d(spikes_background, spikes_clusters)
else:
spikes = self.spikes_selected
return select(self.features, spikes)
def select(self, spikes=None, clusters=None):
if clusters is not None:
if not hasattr(clusters, '__len__'):
clusters = [clusters]
spikes = get_spikes_in_clusters(clusters, self.clusters)
# HDD access here: get the portion of the table with the requested
# clusters (cache). It is very quick to access the different columns
# from this in-memory table later.
if spikes is not None:
self.spikes_selected_table = self.spike_table[spikes]
# Select waveforms too.
self.spikes_waveforms = get_some_spikes_in_clusters(clusters, self.clusters,
counter=self.counter,
nspikes_max_expected=self.userpref['waveforms_nspikes_max_expected'],
nspikes_per_cluster_min=self.userpref['waveforms_nspikes_per_cluster_min'])
self.waveforms_selected = self.waveforms[0][self.spikes_waveforms]['waveform_filtered']
else:
self.spikes_selected_table = None
self.waveforms_selected = None
self.spikes_selected = spikes
self.clusters_selected = clusters
