def add_cluster(self, id=None, color=None, **kwargs):
channel_group_id = self._node._v_parent._v_parent._v_name
clustering = self._node._v_name
add_cluster(self._files, channel_group_id=channel_group_id,
color=color,
id=str(id), clustering=clustering, **kwargs)
self._update()
def add_cluster(self, id=None, color=None, **kwargs):
channel_group_id = self._node._v_parent._v_parent._v_name
clustering = self._node._v_name
add_cluster(self._files, channel_group_id=channel_group_id,
color=color,
id=str(id), clustering=clustering, **kwargs)
self._update()
def _setup(_name, has_masks=True):
# Create files.
prm = {'nfeatures': 3, 'waveforms_nsamples': 10, 'nchannels': 3,
'sample_rate': 20000.,
'nfeatures_per_channel': 1,
'has_masks': has_masks
}
prb = {0:
{
'channels': [4, 6, 8],
'graph': [[4, 6], [8, 4]],
'geometry': {4: [0.4, 0.6], 6: [0.6, 0.8], 8: [0.8, 0.0]},
}
}
create_files(_name, dir=DIRPATH, prm=prm, prb=prb)
# Open the files.
files = open_files(_name, dir=DIRPATH, mode='a')
# Add data.
add_recording(files,
sample_rate=20000.,
start_time=10.,
start_sample=200000.,
bit_depth=16,
band_high=100.,
band_low=500.,
nchannels=3,)
add_event_type(files, 'myevents')
add_cluster_group(files, channel_group_id='0', id='0', name='Noise')
add_cluster(files, channel_group_id='0', cluster_group=0)
# Close the files
close_files(files)
def _setup(_name, has_masks=True):
# Create files.
prm = {'nfeatures': 3, 'waveforms_nsamples': 10, 'nchannels': 3,
'sample_rate': 20000.,
'nfeatures_per_channel': 1,
'has_masks': has_masks
}
prb = {0:
{
'channels': [4, 6, 8],
'graph': [[4, 6], [8, 4]],
'geometry': {4: [0.4, 0.6], 6: [0.6, 0.8], 8: [0.8, 0.0]},
}
}
create_files(_name, dir=DIRPATH, prm=prm, prb=prb)
# Open the files.
files = open_files(_name, dir=DIRPATH, mode='a')
# Add data.
add_recording(files,
sample_rate=20000.,
start_time=10.,
start_sample=200000.,
bit_depth=16,
band_high=100.,
band_low=500.,
nchannels=3,)
add_event_type(files, 'myevents')
add_cluster_group(files, channel_group_id='0', id='0', name='Noise')
add_cluster(files, channel_group_id='0', cluster_group=0)
# Close the files
close_files(files)
def _setup(_name, has_masks=True):
# Create files.
prm = {
'nfeatures': 3 * 3,
'waveforms_nsamples': 10,
'nchannels': 3,
'sample_rate': 20000.,
'nfeatures_per_channel': 3,
'has_masks': has_masks
}
prb = {
0: {
'channels': [0, 1, 2],
'graph': [[0, 1], [0, 2]],
'geometry': {
0: [0.4, 0.6],
1: [0.6, 0.8],
2: [0.8, 0.0]
},
}
}
create_files(_name, dir=DIRPATH, prm=prm, prb=prb)
# Open the files.
files = open_files(_name, dir=DIRPATH, mode='a')
# Add data.
add_recording(
files,
sample_rate=20000.,
bit_depth=16,
band_high=100.,
band_low=500.,
nchannels=3,
)
add_event_type(files, 'myevents')
add_cluster_group(files, channel_group_id='0', id='0', name='Noise')
add_cluster_group(files, channel_group_id='0', id='1', name='MUA')
add_cluster_group(files, channel_group_id='0', id='2', name='Good')
add_cluster_group(files, channel_group_id='0', id='3', name='Unsorted')
add_cluster(files, channel_group_id='0', cluster_group=0)
add_spikes(
files,
channel_group_id='0',
cluster=np.random.randint(5, 10, 1000),
time_samples=np.cumsum(np.random.randint(0, 1000,
1000)).astype(np.int64),
features=np.random.randint(-30000, 30000, (1000, 9)).astype(np.int16),
masks=np.random.randint(0, 2, (1000, 9)).astype(np.int16),
)
# Close the files
close_files(files)
def _consistency_check(self):
exp = self.experiment
chgrp = self.shank
cg = exp.channel_groups[chgrp]
clusters = cg.clusters.main.keys()
clusters_unique = np.unique(cg.spikes.clusters.main[:])
# Find missing clusters in the kwik file.
missing = sorted(set(clusters_unique)-set(clusters))
# Add all missing clusters with a default color and "Unsorted" cluster group (group #3).
for idx in missing:
warn("Consistency check: adding cluster %d in the kwik file" % idx)
add_cluster(exp._files, channel_group_id='%d' % chgrp,
id=idx,
clustering='main',
cluster_group=3)
def add_missing_clusters(exp):
shanks = sorted(exp.channel_groups.keys())
for shank in shanks:
cg = exp.channel_groups[shank]
clusters = cg.clusters.main.keys()
clusters_unique = np.unique(cg.spikes.clusters.main[:])
# Find missing clusters in the kwik file.
missing = sorted(set(clusters_unique)-set(clusters))
# Add all missing clusters with a default color and "Unsorted" cluster group (group #3).
for idx in missing:
info("Adding missing cluster %d in shank %d." % (idx, shank))
add_cluster(exp._files, channel_group_id='%d' % shank,
id=str(idx),
clustering='main',
cluster_group=3)
def _consistency_check(self):
exp = self.experiment
chgrp = self.shank
cg = exp.channel_groups[chgrp]
clusters = cg.clusters.main.keys()
clusters_unique = np.unique(cg.spikes.clusters.main[:])
# Find missing clusters in the kwik file.
missing = sorted(set(clusters_unique) - set(clusters))
# Add all missing clusters with a default color and "Unsorted" cluster group (group #3).
for idx in missing:
warn("Consistency check: adding cluster %d in the kwik file" % idx)
add_cluster(exp._files,
channel_group_id='%d' % chgrp,
id=idx,
clustering='main',
cluster_group=3)
def add_missing_clusters(exp):
shanks = sorted(exp.channel_groups.keys())
for shank in shanks:
cg = exp.channel_groups[shank]
clusters = cg.clusters.main.keys()
clusters_unique = np.unique(cg.spikes.clusters.main[:])
# Find missing clusters in the kwik file.
missing = sorted(set(clusters_unique) - set(clusters))
# Add all missing clusters with a default color and "Unsorted" cluster group (group #3).
for idx in missing:
info("Adding missing cluster %d in shank %d." % (idx, shank))
add_cluster(exp._files,
channel_group_id='%d' % shank,
id=str(idx),
clustering='main',
cluster_group=3)
def _setup(_name, has_masks=True):
# Create files.
prm = {
"nfeatures": 3 * 3,
"waveforms_nsamples": 10,
"nchannels": 3,
"sample_rate": 20000.0,
"nfeatures_per_channel": 3,
"has_masks": has_masks,
}
prb = {
0: {"channels": [0, 1, 2], "graph": [[0, 1], [0, 2]], "geometry": {0: [0.4, 0.6], 1: [0.6, 0.8], 2: [0.8, 0.0]}}
}
create_files(_name, dir=DIRPATH, prm=prm, prb=prb)
# Open the files.
files = open_files(_name, dir=DIRPATH, mode="a")
# Add data.
add_recording(files, sample_rate=20000.0, bit_depth=16, band_high=100.0, band_low=500.0, nchannels=3)
add_event_type(files, "myevents")
add_cluster_group(files, channel_group_id="0", id="0", name="Noise")
add_cluster_group(files, channel_group_id="0", id="1", name="MUA")
add_cluster_group(files, channel_group_id="0", id="2", name="Good")
add_cluster_group(files, channel_group_id="0", id="3", name="Unsorted")
add_cluster(files, channel_group_id="0", cluster_group=0)
add_spikes(
files,
channel_group_id="0",
cluster=np.random.randint(5, 10, 1000),
time_samples=np.cumsum(np.random.randint(0, 1000, 1000)).astype(np.int64),
features=np.random.randint(-30000, 30000, (1000, 9)).astype(np.int16),
masks=np.random.randint(0, 2, (1000, 9)).astype(np.int16),
)
# Close the files
close_files(files)