def test_resolve_hdf5_path():
path = "{kwx}/channel_groups/0"
files = open_files('myexperiment', dir=DIRPATH)
assert _resolve_hdf5_path(files, path)
close_files(files)
def test_resolve_hdf5_path():
path = "{kwx}/channel_groups/0"
files = open_files('myexperiment', dir=DIRPATH)
assert _resolve_hdf5_path(files, path)
close_files(files)
def __init__(self, name=None, dir=None, files=None, mode='r', prm={}):
"""`name` must correspond to the basename of the files."""
self.name = name
self._dir = dir
self.dir = dir
self._mode = mode
self._files = files
self._prm = prm
if self._files is None:
self._files = open_files(self.name, dir=self._dir, mode=self._mode)
def _get_filename(file):
if file is None:
return None
else:
return os.path.realpath(file.filename)
self._filenames = {type: _get_filename(file)
for type, file in iteritems(self._files)}
super(Experiment, self).__init__(self._files)
self._root = self._node
# Ensure the version of the kwik format is exactly 2.
assert self._root._f_getAttr('kwik_version') == 2
self.application_data = NodeWrapper(self._root.application_data)
self.user_data = NodeWrapper(self._root.user_data)
self.channel_groups = self._gen_children('channel_groups', ChannelGroup)
self.recordings = self._gen_children('recordings', Recording)
self.event_types = self._gen_children('event_types', EventType)
# Initialize the spike cache of all channel groups.
for grp in self.channel_groups.itervalues():
grp.spikes.init_cache()
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 __init__(self, name=None, dir=None, files=None, mode='r', prm={}):
"""`name` must correspond to the basename of the files."""
self.name = name
self._dir = dir
self.dir = dir
self._mode = mode
self._files = files
self._prm = prm
if self._files is None:
self._files = open_files(self.name, dir=self._dir, mode=self._mode)
def _get_filename(file):
if file is None:
return None
else:
return os.path.realpath(file.filename)
self._filenames = {type: _get_filename(file)
for type, file in iteritems(self._files)}
super(Experiment, self).__init__(self._files)
self._root = self._node
# Ensure the version of the kwik format is exactly 2.
assert self._root._f_getAttr('kwik_version') == 2
self.application_data = NodeWrapper(self._root.application_data)
# self.user_data = NodeWrapper(self._root.user_data)
self.channel_groups = self._gen_children('channel_groups', ChannelGroup)
self.recordings = self._gen_children('recordings', Recording)
# self.event_types = self._gen_children('event_types', EventType)
# Initialize the spike cache of all channel groups.
for grp in self.channel_groups.itervalues():
grp.spikes.init_cache()
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 _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)