def _update_cluster_ids(self, to_remove=None, to_add=None):
# Update the list of non-empty cluster ids.
self._cluster_ids = _unique(self._spike_clusters)
# Clusters to remove.
if to_remove is not None:
for clu in to_remove:
self._spikes_per_cluster.pop(clu, None)
# Clusters to add.
if to_add:
for clu, spk in to_add.items():
self._spikes_per_cluster[clu] = spk
# If spikes_per_cluster is invalid, recompute the entire
# spikes_per_cluster array.
coherent = np.all(
np.in1d(self._cluster_ids, sorted(self._spikes_per_cluster)))
if not coherent:
logger.debug(
"Recompute spikes_per_cluster manually: this might take a while."
)
sc = self._spike_clusters
self._spikes_per_cluster = _spikes_per_cluster(sc)
def _do_assign(self, spike_ids, new_spike_clusters):
"""Make spike-cluster assignments after the spike selection has
been extended to full clusters."""
# Ensure spike_clusters has the right shape.
spike_ids = _as_array(spike_ids)
if len(new_spike_clusters) == 1 and len(spike_ids) > 1:
new_spike_clusters = np.ones(
len(spike_ids), dtype=np.int64) * new_spike_clusters[0]
old_spike_clusters = self._spike_clusters[spike_ids]
assert len(spike_ids) == len(old_spike_clusters)
assert len(new_spike_clusters) == len(spike_ids)
# Update the spikes per cluster structure.
old_clusters = _unique(old_spike_clusters)
# NOTE: shortcut to a merge if this assignment is effectively a merge
# i.e. if all spikes are assigned to a single cluster.
# The fact that spike selection has been previously extended to
# whole clusters is critical here.
new_clusters = _unique(new_spike_clusters)
if len(new_clusters) == 1:
return self._do_merge(spike_ids, old_clusters, new_clusters[0])
# We return the UpdateInfo structure.
up = _assign_update_info(spike_ids, old_spike_clusters,
new_spike_clusters)
# We update the new cluster id (strictly increasing during a session).
self._new_cluster_id = max(self._new_cluster_id, max(up.added) + 1)
# We make the assignments.
self._spike_clusters[spike_ids] = new_spike_clusters
# OPTIM: we update spikes_per_cluster manually.
new_spc = _spikes_per_cluster(new_spike_clusters, spike_ids)
self._update_cluster_ids(to_remove=old_clusters, to_add=new_spc)
up.all_cluster_ids = list(self.cluster_ids)
return up
def __init__(self, model):
self.model = model
self.dir_path = Path(model.dir_path)
self.spc = _spikes_per_cluster(model.spike_clusters)
self.cluster_ids = _unique(self.model.spike_clusters)
def test_feature_view(qtbot, gui, n_channels):
nc = n_channels
ns = 10000
features = artificial_features(ns, nc, 4)
spike_clusters = artificial_spike_clusters(ns, 4)
spike_times = np.linspace(0., 1., ns)
spc = _spikes_per_cluster(spike_clusters)
def get_spike_ids(cluster_id):
return (spc[cluster_id] if cluster_id is not None else np.arange(ns))
def get_features(cluster_id=None,
channel_ids=None,
spike_ids=None,
load_all=None):
if load_all:
spike_ids = spc[cluster_id]
else:
spike_ids = get_spike_ids(cluster_id)
return Bunch(
data=features[spike_ids],
spike_ids=spike_ids,
masks=np.random.rand(ns, nc),
channel_ids=(channel_ids
if channel_ids is not None else np.arange(nc)[::-1]),
)
def get_time(cluster_id=None, load_all=None):
return Bunch(data=spike_times[get_spike_ids(cluster_id)], lim=(0., 1.))
v = FeatureView(features=get_features, attributes={'time': get_time})
v.show()
qtbot.waitForWindowShown(v.canvas)
v.attach(gui)
v.set_grid_dim(_get_default_grid())
v.on_select(cluster_ids=[])
v.on_select(cluster_ids=[0])
v.on_select(cluster_ids=[0, 2, 3])
v.on_select(cluster_ids=[0, 2])
assert v.status
v.increase()
v.decrease()
v.increase_marker_size()
v.decrease_marker_size()
v.on_select_channel(channel_id=3, button='Left', key=None)
v.on_select_channel(channel_id=3, button='Right', key=None)
v.on_select_channel(channel_id=3, button='Right', key=2)
v.clear_channels()
v.toggle_automatic_channel_selection(True)
# Test feature selection with Alt+click.
_l = []
@connect(sender=v)
def on_select_feature(sender, dim=None, channel_id=None, pc=None):
_l.append((dim, channel_id, pc))
for i, j, dim_x, dim_y in v._iter_subplots():
for k, button in enumerate(('Left', 'Right')):
# Click on the center of every subplot.
w, h = v.canvas.get_size()
w, h = w / 4, h / 4
x, y = w / 2, h / 2
mouse_click(qtbot,
v.canvas, (x + j * w, y + i * h),
button=button,
modifiers=('Alt', ))
assert _l[-1][0] == v.grid_dim[i][j].split(',')[k]
# Split without selection.
spike_ids = v.on_request_split()
assert len(spike_ids) == 0
a, b = 10, 100
mouse_click(qtbot, v.canvas, (a, a), modifiers=('Control', ))
mouse_click(qtbot, v.canvas, (a, b), modifiers=('Control', ))
mouse_click(qtbot, v.canvas, (b, b), modifiers=('Control', ))
mouse_click(qtbot, v.canvas, (b, a), modifiers=('Control', ))
# Split lassoed points.
spike_ids = v.on_request_split()
# HACK: this seems to fail because qtbot.mouseClick is not working??
# assert len(spike_ids) > 0
v.set_state(v.state)
_stop_and_close(qtbot, v)