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._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
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)
def _print_instance(obj, depth=0, name=''):
# Handle the first element of the list/dict.
if isinstance(obj, (list, dict)):
if not obj:
r = []
return r
if isinstance(obj, list):
sobj = obj[0]
key = '0'
elif isinstance(obj, dict):
key, sobj = next(iteritems(obj))
if isinstance(sobj, (list, dict, int, long, string_types, np.ndarray,
float)):
r = []
else:
r = [(depth+1, str(key))] + _print_instance(sobj, depth+1)
# Arrays do not have children.
elif isinstance(obj, (np.ndarray, tb.EArray)):
r = []
# Handle class instances.
elif hasattr(obj, '__dict__'):
fields = {k: v
for k, v in iteritems(vars(obj))
if not k.startswith('_')}
r = list(chain(*[_print_instance(fields[n], depth=depth+1, name=str(n))
for n in sorted(iterkeys(fields))]))
else:
r = []
# Add the current object's display string.
if name:
if isinstance(obj, tb.EArray):
s = name + ' [{dtype} {shape}]'.format(dtype=obj.dtype,
shape=obj.shape)
else:
s = name
r = [(depth, s)] + r
return r
def open_files(name, dir=None, mode=None):
filenames = get_filenames(name, dir=dir)
return {
type: open_file(filename, mode=mode)
for type, filename in iteritems(filenames)
}
def create_kwik(path, experiment_name=None, prm=None, prb=None):
"""Create a KWIK file.
Arguments:
* path: path to the .kwik file.
* experiment_name
* prm: a dictionary representing the contents of the PRM file (used for
SpikeDetekt)
* prb: a dictionary with the contents of the PRB file
"""
if experiment_name is None:
experiment_name = ''
if prm is None:
prm = {}
if prb is None:
prb = {}
file = tb.openFile(path, mode='w')
file.root._f_setAttr('kwik_version', 2)
file.root._f_setAttr('name', experiment_name)
file.createGroup('/', 'application_data')
# Set the SpikeDetekt parameters
file.createGroup('/application_data', 'spikedetekt')
for prm_name, prm_value in iteritems(prm):
file.root.application_data.spikedetekt._f_setAttr(prm_name, prm_value)
file.createGroup('/', 'user_data')
# Create channel groups.
file.createGroup('/', 'channel_groups')
for igroup, group_info in enumerate(prb.get('channel_groups', [])):
group = file.createGroup('/channel_groups', str(igroup))
# group_info: channel, graph, geometry
group._f_setAttr('name', 'channel_group_{0:d}'.format(igroup))
group._f_setAttr('adjacency_graph',
group_info.get('graph', np.zeros((0, 2))))
file.createGroup(group, 'application_data')
file.createGroup(group, 'user_data')
# Create channels.
file.createGroup(group, 'channels')
channels = group_info.get('channels', [])
for channel_idx in channels:
# channel is the absolute channel index.
channel = file.createGroup(group.channels, str(channel_idx))
channel._f_setAttr('name', 'channel_{0:d}'.format(channel_idx))
############### TODO
channel._f_setAttr('kwd_index', 0)
channel._f_setAttr('ignored', False)
channel._f_setAttr('position', group_info.get('geometry', {}). \
get(channel_idx, None))
channel._f_setAttr('voltage_gain', 0.)
channel._f_setAttr('display_threshold', 0.)
file.createGroup(channel, 'application_data')
file.createGroup(channel.application_data, 'spikedetekt')
file.createGroup(channel.application_data, 'klustaviewa')
file.createGroup(channel, 'user_data')
# Create spikes.
spikes = file.createGroup(group, 'spikes')
file.createEArray(spikes,
'time_samples',
tb.UInt64Atom(), (0, ),
expectedrows=1000000)
file.createEArray(spikes,
'time_fractional',
tb.UInt8Atom(), (0, ),
expectedrows=1000000)
file.createEArray(spikes,
'recording',
tb.UInt16Atom(), (0, ),
expectedrows=1000000)
clusters = file.createGroup(spikes, 'clusters')
file.createEArray(clusters,
'main',
tb.UInt32Atom(), (0, ),
expectedrows=1000000)
file.createEArray(clusters,
'original',
tb.UInt32Atom(), (0, ),
expectedrows=1000000)
fm = file.createGroup(spikes, 'features_masks')
fm._f_setAttr('hdf5_path', '{{kwx}}/channel_groups/{0:d}/features_masks'. \
format(igroup))
wr = file.createGroup(spikes, 'waveforms_raw')
wr._f_setAttr('hdf5_path', '{{kwx}}/channel_groups/{0:d}/waveforms_raw'. \
format(igroup))
wf = file.createGroup(spikes, 'waveforms_filtered')
wf._f_setAttr('hdf5_path', '{{kwx}}/channel_groups/{0:d}/waveforms_filtered'. \
format(igroup))
# TODO: add clusters 0, 1, 2, 3 by default
# Create clusters.
clusters = file.createGroup(group, 'clusters')
file.createGroup(clusters, 'main')
file.createGroup(clusters, 'original')
# Create cluster groups.
cluster_groups = file.createGroup(group, 'cluster_groups')
file.createGroup(cluster_groups, 'main')
file.createGroup(cluster_groups, 'original')
# Create recordings.
file.createGroup('/', 'recordings')
# Create event types.
file.createGroup('/', 'event_types')
file.close()
def create_kwik(path, experiment_name=None, prm=None, prb=None):
"""Create a KWIK file.
Arguments:
* path: path to the .kwik file.
* experiment_name
* prm: a dictionary representing the contents of the PRM file (used for
SpikeDetekt)
* prb: a dictionary with the contents of the PRB file
"""
if experiment_name is None:
experiment_name = ''
if prm is None:
prm = {}
if prb is None:
prb = {}
file = tb.openFile(path, mode='w')
file.root._f_setAttr('kwik_version', 2)
file.root._f_setAttr('name', experiment_name)
file.createGroup('/', 'application_data')
# Set the SpikeDetekt parameters
file.createGroup('/application_data', 'spikedetekt')
for prm_name, prm_value in iteritems(prm):
file.root.application_data.spikedetekt._f_setAttr(prm_name, prm_value)
file.createGroup('/', 'user_data')
# Create channel groups.
file.createGroup('/', 'channel_groups')
for igroup, group_info in enumerate(prb.get('channel_groups', [])):
group = file.createGroup('/channel_groups', str(igroup))
# group_info: channel, graph, geometry
group._f_setAttr('name', 'channel_group_{0:d}'.format(igroup))
group._f_setAttr('adjacency_graph', group_info.get('graph', np.zeros((0, 2))))
file.createGroup(group, 'application_data')
file.createGroup(group, 'user_data')
# Create channels.
file.createGroup(group, 'channels')
channels = group_info.get('channels', [])
for channel_idx in channels:
# channel is the absolute channel index.
channel = file.createGroup(group.channels, str(channel_idx))
channel._f_setAttr('name', 'channel_{0:d}'.format(channel_idx))
############### TODO
channel._f_setAttr('kwd_index', 0)
channel._f_setAttr('ignored', False)
channel._f_setAttr('position', group_info.get('geometry', {}). \
get(channel_idx, None))
channel._f_setAttr('voltage_gain', 0.)
channel._f_setAttr('display_threshold', 0.)
file.createGroup(channel, 'application_data')
file.createGroup(channel.application_data, 'spikedetekt')
file.createGroup(channel.application_data, 'klustaviewa')
file.createGroup(channel, 'user_data')
# Create spikes.
spikes = file.createGroup(group, 'spikes')
file.createEArray(spikes, 'time_samples', tb.UInt64Atom(), (0,),
expectedrows=1000000)
file.createEArray(spikes, 'time_fractional', tb.UInt8Atom(), (0,),
expectedrows=1000000)
file.createEArray(spikes, 'recording', tb.UInt16Atom(), (0,),
expectedrows=1000000)
clusters = file.createGroup(spikes, 'clusters')
file.createEArray(clusters, 'main', tb.UInt32Atom(), (0,),
expectedrows=1000000)
file.createEArray(clusters, 'original', tb.UInt32Atom(), (0,),
expectedrows=1000000)
fm = file.createGroup(spikes, 'features_masks')
fm._f_setAttr('hdf5_path', '{{kwx}}/channel_groups/{0:d}/features_masks'. \
format(igroup))
wr = file.createGroup(spikes, 'waveforms_raw')
wr._f_setAttr('hdf5_path', '{{kwx}}/channel_groups/{0:d}/waveforms_raw'. \
format(igroup))
wf = file.createGroup(spikes, 'waveforms_filtered')
wf._f_setAttr('hdf5_path', '{{kwx}}/channel_groups/{0:d}/waveforms_filtered'. \
format(igroup))
# TODO: add clusters 0, 1, 2, 3 by default
# Create clusters.
clusters = file.createGroup(group, 'clusters')
file.createGroup(clusters, 'main')
file.createGroup(clusters, 'original')
# Create cluster groups.
cluster_groups = file.createGroup(group, 'cluster_groups')
file.createGroup(cluster_groups, 'main')
file.createGroup(cluster_groups, 'original')
# Create recordings.
file.createGroup('/', 'recordings')
# Create event types.
file.createGroup('/', 'event_types')
file.close()
def open_files(name, dir=None, mode=None):
filenames = get_filenames(name, dir=dir)
return {type: open_file(filename, mode=mode)
for type, filename in iteritems(filenames)}