def split_clusters(self, clusters, clusters_old, cluster_groups,
cluster_colors, clusters_new):
if not hasattr(clusters, '__len__'):
clusters = [clusters]
spikes = get_indices(clusters_old)
# Find groups and colors of old clusters.
cluster_indices_old = np.unique(clusters_old)
cluster_indices_new = np.unique(clusters_new)
# Get group and color of the new clusters, from the old clusters.
groups = self.loader.get_cluster_groups(cluster_indices_old)
# colors = self.loader.get_cluster_colors(cluster_indices_old)
# Add clusters.
for cluster_new, group in zip(cluster_indices_new,
groups):
self.loader.add_cluster(cluster_new, group, random_color())
# Set the new clusters to the corresponding spikes.
self.loader.set_cluster(spikes, clusters_new)
# Remove empty clusters.
clusters_empty = self.loader.remove_empty_clusters()
self.loader.unselect()
clusters_to_select = sorted(set(cluster_indices_old).union(
set(cluster_indices_new)) - set(clusters_empty))
return dict(clusters_to_split=clusters,
clusters_split=get_array(cluster_indices_new),
clusters_empty=clusters_empty)
def split_clusters(self, clusters, clusters_old, cluster_groups,
cluster_colors, clusters_new):
if not hasattr(clusters, '__len__'):
clusters = [clusters]
spikes = get_indices(clusters_old)
# Find groups and colors of old clusters.
cluster_indices_old = np.unique(clusters_old)
cluster_indices_new = np.unique(clusters_new)
# Get group and color of the new clusters, from the old clusters.
groups = self.loader.get_cluster_groups(cluster_indices_old)
# colors = self.loader.get_cluster_colors(cluster_indices_old)
# Add clusters.
self.loader.add_clusters(cluster_indices_new,
# HACK: take the group of the first cluster for all new clusters
get_array(groups)[0]*np.ones(len(cluster_indices_new)),
random_color(len(cluster_indices_new)))
# Set the new clusters to the corresponding spikes.
self.loader.set_cluster(spikes, clusters_new)
# Remove empty clusters.
clusters_empty = self.loader.remove_empty_clusters()
self.loader.unselect()
clusters_to_select = sorted(set(cluster_indices_old).union(
set(cluster_indices_new)) - set(clusters_empty))
return dict(clusters_to_split=clusters,
clusters_split=get_array(cluster_indices_new),
clusters_empty=clusters_empty)
def _wizard_change_candidate_color(self):
candidate = self.wizard.current_candidate()
target = self.wizard.current_target()
# color = self.loader.get_cluster_color(candidate)
return ('_cluster_color_changed', (
candidate,
random_color(),
))
def add_group(self, name, channels=[]):
color = random_color()
group = self.model.add_group(name, color)
groupidx = group.groupidx()
# Signal.
log.debug("Adding group {0:s}.".format(name))
self.groupAdded.emit(groupidx, name, color)
# Move the selected channels to the new group.
if channels:
self.move_channels(channels, groupidx)
self.expandAll()
return groupidx
def add_group(self, name, channels=[]):
color = random_color()
group = self.model.add_group(name, color)
groupidx = group.groupidx()
# Signal.
log.debug("Adding group {0:s}.".format(name))
self.groupAdded.emit(groupidx, name, color)
# Move the selected channels to the new group.
if channels:
self.move_channels(channels, groupidx)
self.expandAll()
return groupidx
def merge_clusters(self, clusters_old, cluster_groups, cluster_colors,
cluster_merged):
# Get spikes in clusters to merge.
# spikes = self.loader.get_spikes(clusters=clusters_to_merge)
spikes = get_indices(clusters_old)
clusters_to_merge = get_indices(cluster_groups)
group = np.max(get_array(cluster_groups))
# color_old = get_array(cluster_colors)[0]
color_new = random_color()
self.loader.add_cluster(cluster_merged, group, color_new)
# Set the new cluster to the corresponding spikes.
self.loader.set_cluster(spikes, cluster_merged)
# Remove old clusters.
for cluster in clusters_to_merge:
self.loader.remove_cluster(cluster)
self.loader.unselect()
return dict(clusters_to_merge=clusters_to_merge,
cluster_merged=cluster_merged,
cluster_merged_colors=(color_new, color_new),)
def merge_clusters(self, clusters_old, cluster_groups, cluster_colors,
cluster_merged):
# Get spikes in clusters to merge.
# spikes = self.loader.get_spikes(clusters=clusters_to_merge)
spikes = get_indices(clusters_old)
clusters_to_merge = get_indices(cluster_groups)
group = np.max(get_array(cluster_groups))
# color_old = get_array(cluster_colors)[0]
color_new = random_color()
self.loader.add_cluster(cluster_merged, group, color_new)
# Set the new cluster to the corresponding spikes.
self.loader.set_cluster(spikes, cluster_merged)
# Remove old clusters.
for cluster in clusters_to_merge:
self.loader.remove_cluster(cluster)
self.loader.unselect()
return dict(clusters_to_merge=clusters_to_merge,
cluster_merged=cluster_merged,
cluster_merged_colors=(color_new, color_new),)
def _wizard_change_candidate_color(self):
candidate = self.wizard.current_candidate()
target = self.wizard.current_target()
# color = self.loader.get_cluster_color(candidate)
return ('_cluster_color_changed', (candidate, random_color(),))
