def extract_spikes(traces,
interval,
sample_rate=None,
spike_times=None,
spike_clusters=None,
cluster_groups=None,
all_masks=None,
n_samples_waveforms=None):
cluster_groups = cluster_groups or {}
sr = sample_rate
ns = n_samples_waveforms
if not isinstance(ns, tuple):
ns = (ns // 2, ns // 2)
offset_samples = ns[0]
wave_len = ns[0] + ns[1]
# Find spikes.
a, b = spike_times.searchsorted(interval)
st = spike_times[a:b]
sc = spike_clusters[a:b]
m = all_masks[a:b]
n = len(st)
assert len(sc) == n
assert m.shape[0] == n
# Extract waveforms.
spikes = []
for i in range(n):
b = Bunch()
# Find the start of the waveform in the extracted traces.
sample_start = int(round((st[i] - interval[0]) * sr))
sample_start -= offset_samples
o = _extract_wave(traces, sample_start, m[i], wave_len)
if o is None: # pragma: no cover
logger.debug("Unable to extract spike %d.", i)
continue
b.waveforms, b.channels = o
# Masks on unmasked channels.
b.masks = m[i, b.channels]
b.spike_time = st[i]
b.spike_cluster = sc[i]
b.cluster_group = cluster_groups.get(b.spike_cluster, None)
b.offset_samples = offset_samples
spikes.append(b)
return spikes
