def nwb_copy_file(old_file, new_file, cp_objs={}):
"""
Copy fields defined in 'obj', from existing NWB file to new NWB file.
Parameters
----------
old_file : str, path
String such as '/path/to/old_file.nwb'.
new_file : str, path
String such as '/path/to/new_file.nwb'.
cp_objs : dict
Name:Value pairs (Group:Children) listing the groups and respective
children from the current NWB file to be copied. Children can be:
- Boolean, indicating an attribute (e.g. for institution, lab)
- List of strings, containing several children names
Example:
{'institution':True,
'lab':True,
'acquisition':['microphone'],
'ecephys':['LFP','DecompositionSeries']}
"""
manager = get_manager()
# Open original signal file
with NWBHDF5IO(old_file, 'r', manager=manager,
load_namespaces=True) as io1:
nwb_old = io1.read()
# Creates new file
nwb_new = NWBFile(session_description=str(nwb_old.session_description),
identifier='',
session_start_time=datetime.now(tzlocal()))
with NWBHDF5IO(new_file, mode='w', manager=manager,
load_namespaces=False) as io2:
# Institution name ------------------------------------------------
if 'institution' in cp_objs:
nwb_new.institution = str(nwb_old.institution)
# Lab name --------------------------------------------------------
if 'lab' in cp_objs:
nwb_new.lab = str(nwb_old.lab)
# Session id ------------------------------------------------------
if 'session' in cp_objs:
nwb_new.session_id = nwb_old.session_id
# Devices ---------------------------------------------------------
if 'devices' in cp_objs:
for aux in list(nwb_old.devices.keys()):
dev = Device(nwb_old.devices[aux].name)
nwb_new.add_device(dev)
# Electrode groups ------------------------------------------------
if 'electrode_groups' in cp_objs:
for aux in list(nwb_old.electrode_groups.keys()):
nwb_new.create_electrode_group(
name=str(nwb_old.electrode_groups[aux].name),
description=str(nwb_old.electrode_groups[
aux].description),
location=str(nwb_old.electrode_groups[aux].location),
device=nwb_new.get_device(
nwb_old.electrode_groups[aux].device.name)
)
# Electrodes ------------------------------------------------------
if 'electrodes' in cp_objs:
nElec = len(nwb_old.electrodes['x'].data[:])
for aux in np.arange(nElec):
nwb_new.add_electrode(
x=nwb_old.electrodes['x'][aux],
y=nwb_old.electrodes['y'][aux],
z=nwb_old.electrodes['z'][aux],
imp=nwb_old.electrodes['imp'][aux],
location=str(nwb_old.electrodes['location'][aux]),
filtering=str(nwb_old.electrodes['filtering'][aux]),
group=nwb_new.get_electrode_group(
nwb_old.electrodes['group'][aux].name),
group_name=str(nwb_old.electrodes['group_name'][aux])
)
# if there are custom variables
new_vars = list(nwb_old.electrodes.colnames)
default_vars = ['x', 'y', 'z', 'imp', 'location', 'filtering',
'group', 'group_name']
[new_vars.remove(var) for var in default_vars]
for var in new_vars:
if var == 'label':
var_data = [str(elem) for elem in nwb_old.electrodes[
var].data[:]]
else:
var_data = np.array(nwb_old.electrodes[var].data[:])
nwb_new.add_electrode_column(name=str(var),
description=
str(nwb_old.electrodes[
var].description),
data=var_data)
# Epochs ----------------------------------------------------------
if 'epochs' in cp_objs:
nEpochs = len(nwb_old.epochs['start_time'].data[:])
for i in np.arange(nEpochs):
nwb_new.add_epoch(
start_time=nwb_old.epochs['start_time'].data[i],
stop_time=nwb_old.epochs['stop_time'].data[i])
# if there are custom variables
new_vars = list(nwb_old.epochs.colnames)
default_vars = ['start_time', 'stop_time', 'tags',
'timeseries']
[new_vars.remove(var) for var in default_vars if
var in new_vars]
for var in new_vars:
nwb_new.add_epoch_column(name=var,
description=nwb_old.epochs[
var].description,
data=nwb_old.epochs[var].data[:])
# Invalid times ---------------------------------------------------
if 'invalid_times' in cp_objs:
nInvalid = len(nwb_old.invalid_times['start_time'][:])
for aux in np.arange(nInvalid):
nwb_new.add_invalid_time_interval(
start_time=nwb_old.invalid_times['start_time'][aux],
stop_time=nwb_old.invalid_times['stop_time'][aux])
# Trials ----------------------------------------------------------
if 'trials' in cp_objs:
nTrials = len(nwb_old.trials['start_time'])
for aux in np.arange(nTrials):
nwb_new.add_trial(
start_time=nwb_old.trials['start_time'][aux],
stop_time=nwb_old.trials['stop_time'][aux])
# if there are custom variables
new_vars = list(nwb_old.trials.colnames)
default_vars = ['start_time', 'stop_time']
[new_vars.remove(var) for var in default_vars]
for var in new_vars:
nwb_new.add_trial_column(name=var,
description=nwb_old.trials[
var].description,
data=nwb_old.trials[var].data[:])
# Intervals -------------------------------------------------------
if 'intervals' in cp_objs:
all_objs_names = list(nwb_old.intervals.keys())
for obj_name in all_objs_names:
obj_old = nwb_old.intervals[obj_name]
# create and add TimeIntervals
obj = TimeIntervals(name=obj_old.name,
description=obj_old.description)
nInt = len(obj_old['start_time'])
for ind in np.arange(nInt):
obj.add_interval(start_time=obj_old['start_time'][ind],
stop_time=obj_old['stop_time'][ind])
# Add to file
nwb_new.add_time_intervals(obj)
# Stimulus --------------------------------------------------------
if 'stimulus' in cp_objs:
all_objs_names = list(nwb_old.stimulus.keys())
for obj_name in all_objs_names:
obj_old = nwb_old.stimulus[obj_name]
obj = TimeSeries(name=obj_old.name,
description=obj_old.description,
data=obj_old.data[:],
rate=obj_old.rate,
resolution=obj_old.resolution,
conversion=obj_old.conversion,
starting_time=obj_old.starting_time,
unit=obj_old.unit)
nwb_new.add_stimulus(obj)
# Processing modules ----------------------------------------------
if 'ecephys' in cp_objs:
if cp_objs['ecephys'] is True:
interfaces = nwb_old.processing[
'ecephys'].data_interfaces.keys()
else: # list of items
interfaces = [
nwb_old.processing['ecephys'].data_interfaces[key]
for key in cp_objs['ecephys']
]
# Add ecephys module to NWB file
ecephys_module = ProcessingModule(
name='ecephys',
description='Extracellular electrophysiology data.'
)
nwb_new.add_processing_module(ecephys_module)
for interface_old in interfaces:
obj = copy_obj(interface_old, nwb_old, nwb_new)
if obj is not None:
ecephys_module.add_data_interface(obj)
# Acquisition -----------------------------------------------------
if 'acquisition' in cp_objs:
if cp_objs['acquisition'] is True:
all_acq_names = list(nwb_old.acquisition.keys())
else: # list of items
all_acq_names = cp_objs['acquisition']
for acq_name in all_acq_names:
obj_old = nwb_old.acquisition[acq_name]
obj = copy_obj(obj_old, nwb_old, nwb_new)
if obj is not None:
nwb_new.add_acquisition(obj)
# Subject ---------------------------------------------------------
if 'subject' in cp_objs:
try:
cortical_surfaces = CorticalSurfaces()
surfaces = nwb_old.subject.cortical_surfaces.surfaces
for sfc in list(surfaces.keys()):
cortical_surfaces.create_surface(
name=surfaces[sfc].name,
faces=surfaces[sfc].faces,
vertices=surfaces[sfc].vertices)
nwb_new.subject = ECoGSubject(
cortical_surfaces=cortical_surfaces,
subject_id=nwb_old.subject.subject_id,
age=nwb_old.subject.age,
description=nwb_old.subject.description,
genotype=nwb_old.subject.genotype,
sex=nwb_old.subject.sex,
species=nwb_old.subject.species,
weight=nwb_old.subject.weight,
date_of_birth=nwb_old.subject.date_of_birth)
except:
nwb_new.subject = Subject(age=nwb_old.subject.age,
description=nwb_old.subject.description,
genotype=nwb_old.subject.genotype,
sex=nwb_old.subject.sex,
species=nwb_old.subject.species,
subject_id=nwb_old.subject.subject_id,
weight=nwb_old.subject.weight,
date_of_birth=nwb_old.subject.date_of_birth)
# Write new file with copied fields
io2.write(nwb_new, link_data=False)
class NWBFileTest(TestCase):
def setUp(self):
self.start = datetime(2017, 5, 1, 12, 0, 0, tzinfo=tzlocal())
self.ref_time = datetime(1979, 1, 1, 0, tzinfo=tzutc())
self.create = [
datetime(2017, 5, 1, 12, tzinfo=tzlocal()),
datetime(2017, 5, 2, 13, 0, 0, 1, tzinfo=tzutc()),
datetime(2017, 5, 2, 14, tzinfo=tzutc())
]
self.path = 'nwbfile_test.h5'
self.nwbfile = NWBFile(
'a test session description for a test NWBFile',
'FILE123',
self.start,
file_create_date=self.create,
timestamps_reference_time=self.ref_time,
experimenter='A test experimenter',
lab='a test lab',
institution='a test institution',
experiment_description='a test experiment description',
session_id='test1',
notes='my notes',
pharmacology='drugs',
protocol='protocol',
related_publications='my pubs',
slices='my slices',
surgery='surgery',
virus='a virus',
source_script='noscript',
source_script_file_name='nofilename',
stimulus_notes='test stimulus notes',
data_collection='test data collection notes',
keywords=('these', 'are', 'keywords'))
def test_constructor(self):
self.assertEqual(self.nwbfile.session_description,
'a test session description for a test NWBFile')
self.assertEqual(self.nwbfile.identifier, 'FILE123')
self.assertEqual(self.nwbfile.session_start_time, self.start)
self.assertEqual(self.nwbfile.file_create_date, self.create)
self.assertEqual(self.nwbfile.lab, 'a test lab')
self.assertEqual(self.nwbfile.experimenter, ('A test experimenter', ))
self.assertEqual(self.nwbfile.institution, 'a test institution')
self.assertEqual(self.nwbfile.experiment_description,
'a test experiment description')
self.assertEqual(self.nwbfile.session_id, 'test1')
self.assertEqual(self.nwbfile.stimulus_notes, 'test stimulus notes')
self.assertEqual(self.nwbfile.data_collection,
'test data collection notes')
self.assertEqual(self.nwbfile.related_publications, ('my pubs', ))
self.assertEqual(self.nwbfile.source_script, 'noscript')
self.assertEqual(self.nwbfile.source_script_file_name, 'nofilename')
self.assertEqual(self.nwbfile.keywords, ('these', 'are', 'keywords'))
self.assertEqual(self.nwbfile.timestamps_reference_time, self.ref_time)
def test_create_electrode_group(self):
name = 'example_electrode_group'
desc = 'An example electrode'
loc = 'an example location'
d = self.nwbfile.create_device('a fake device')
elecgrp = self.nwbfile.create_electrode_group(name, desc, loc, d)
self.assertEqual(elecgrp.description, desc)
self.assertEqual(elecgrp.location, loc)
self.assertIs(elecgrp.device, d)
def test_create_custom_intervals(self):
df_words = pd.DataFrame({
'start_time': [.1, 2.],
'stop_time': [.8, 2.3],
'label': ['hello', 'there']
})
words = TimeIntervals.from_dataframe(df_words, name='words')
self.nwbfile.add_time_intervals(words)
self.assertEqual(self.nwbfile.intervals['words'], words)
def test_create_electrode_group_invalid_index(self):
"""
Test the case where the user creates an electrode table region with
indexes that are out of range of the amount of electrodes added.
"""
nwbfile = NWBFile('a', 'b', datetime.now(tzlocal()))
device = nwbfile.create_device('a')
elecgrp = nwbfile.create_electrode_group('a',
'b',
device=device,
location='a')
for i in range(4):
nwbfile.add_electrode(np.nan,
np.nan,
np.nan,
np.nan,
'a',
'a',
elecgrp,
id=i)
with self.assertRaises(IndexError):
nwbfile.create_electrode_table_region(list(range(6)), 'test')
def test_access_group_after_io(self):
"""
Motivated by #739
"""
nwbfile = NWBFile('a', 'b', datetime.now(tzlocal()))
device = nwbfile.create_device('a')
elecgrp = nwbfile.create_electrode_group('a',
'b',
device=device,
location='a')
nwbfile.add_electrode(np.nan,
np.nan,
np.nan,
np.nan,
'a',
'a',
elecgrp,
id=0)
with NWBHDF5IO('electrodes_mwe.nwb', 'w') as io:
io.write(nwbfile)
with NWBHDF5IO('electrodes_mwe.nwb', 'a') as io:
nwbfile_i = io.read()
for aa, bb in zip(nwbfile_i.electrodes['group'][:],
nwbfile.electrodes['group'][:]):
self.assertEqual(aa.name, bb.name)
for i in range(4):
nwbfile.add_electrode(np.nan,
np.nan,
np.nan,
np.nan,
'a',
'a',
elecgrp,
id=i + 1)
with NWBHDF5IO('electrodes_mwe.nwb', 'w') as io:
io.write(nwbfile)
with NWBHDF5IO('electrodes_mwe.nwb', 'a') as io:
nwbfile_i = io.read()
for aa, bb in zip(nwbfile_i.electrodes['group'][:],
nwbfile.electrodes['group'][:]):
self.assertEqual(aa.name, bb.name)
remove_test_file("electrodes_mwe.nwb")
def test_access_processing(self):
self.nwbfile.create_processing_module('test_mod', 'test_description')
# test deprecate .modules
with self.assertWarnsWith(DeprecationWarning,
'replaced by NWBFile.processing'):
modules = self.nwbfile.modules['test_mod']
self.assertIs(self.nwbfile.processing['test_mod'], modules)
def test_epoch_tags(self):
tags1 = ['t1', 't2']
tags2 = ['t3', 't4']
tstamps = np.arange(1.0, 100.0, 0.1, dtype=np.float)
ts = TimeSeries("test_ts",
list(range(len(tstamps))),
'unit',
timestamps=tstamps)
expected_tags = tags1 + tags2
self.nwbfile.add_epoch(0.0, 1.0, tags1, ts)
self.nwbfile.add_epoch(0.0, 1.0, tags2, ts)
tags = self.nwbfile.epoch_tags
self.assertEqual(set(expected_tags), set(tags))
def test_add_acquisition(self):
self.nwbfile.add_acquisition(
TimeSeries('test_ts', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
self.assertEqual(len(self.nwbfile.acquisition), 1)
def test_add_stimulus(self):
self.nwbfile.add_stimulus(
TimeSeries('test_ts', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
self.assertEqual(len(self.nwbfile.stimulus), 1)
def test_add_stimulus_template(self):
self.nwbfile.add_stimulus_template(
TimeSeries('test_ts', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
self.assertEqual(len(self.nwbfile.stimulus_template), 1)
def test_add_analysis(self):
self.nwbfile.add_analysis(
TimeSeries('test_ts', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
self.assertEqual(len(self.nwbfile.analysis), 1)
def test_add_acquisition_check_dups(self):
self.nwbfile.add_acquisition(
TimeSeries('test_ts', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
with self.assertRaises(ValueError):
self.nwbfile.add_acquisition(
TimeSeries('test_ts', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
def test_get_acquisition_empty(self):
with self.assertRaisesWith(ValueError,
"acquisition of NWBFile 'root' is empty"):
self.nwbfile.get_acquisition()
def test_get_acquisition_multiple_elements(self):
self.nwbfile.add_acquisition(
TimeSeries('test_ts1', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
self.nwbfile.add_acquisition(
TimeSeries('test_ts2', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
msg = "more than one element in acquisition of NWBFile 'root' -- must specify a name"
with self.assertRaisesWith(ValueError, msg):
self.nwbfile.get_acquisition()
def test_add_acquisition_invalid_name(self):
self.nwbfile.add_acquisition(
TimeSeries('test_ts', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
msg = "\"'TEST_TS' not found in acquisition of NWBFile 'root'\""
with self.assertRaisesWith(KeyError, msg):
self.nwbfile.get_acquisition("TEST_TS")
def test_set_electrode_table(self):
table = ElectrodeTable()
dev1 = self.nwbfile.create_device('dev1')
group = self.nwbfile.create_electrode_group('tetrode1',
'tetrode description',
'tetrode location', dev1)
table.add_row(x=1.0,
y=2.0,
z=3.0,
imp=-1.0,
location='CA1',
filtering='none',
group=group,
group_name='tetrode1')
table.add_row(x=1.0,
y=2.0,
z=3.0,
imp=-2.0,
location='CA1',
filtering='none',
group=group,
group_name='tetrode1')
table.add_row(x=1.0,
y=2.0,
z=3.0,
imp=-3.0,
location='CA1',
filtering='none',
group=group,
group_name='tetrode1')
table.add_row(x=1.0,
y=2.0,
z=3.0,
imp=-4.0,
location='CA1',
filtering='none',
group=group,
group_name='tetrode1')
self.nwbfile.set_electrode_table(table)
self.assertIs(self.nwbfile.electrodes, table)
self.assertIs(table.parent, self.nwbfile)
def test_add_unit_column(self):
self.nwbfile.add_unit_column('unit_type', 'the type of unit')
self.assertEqual(self.nwbfile.units.colnames, ('unit_type', ))
def test_add_unit(self):
self.nwbfile.add_unit(id=1)
self.assertEqual(len(self.nwbfile.units), 1)
self.nwbfile.add_unit(id=2)
self.nwbfile.add_unit(id=3)
self.assertEqual(len(self.nwbfile.units), 3)
def test_add_trial_column(self):
self.nwbfile.add_trial_column('trial_type', 'the type of trial')
self.assertEqual(self.nwbfile.trials.colnames,
('start_time', 'stop_time', 'trial_type'))
def test_add_trial(self):
self.nwbfile.add_trial(start_time=10.0, stop_time=20.0)
self.assertEqual(len(self.nwbfile.trials), 1)
self.nwbfile.add_trial(start_time=30.0, stop_time=40.0)
self.nwbfile.add_trial(start_time=50.0, stop_time=70.0)
self.assertEqual(len(self.nwbfile.trials), 3)
def test_add_invalid_times_column(self):
self.nwbfile.add_invalid_times_column(
'comments', 'description of reason for omitting time')
self.assertEqual(self.nwbfile.invalid_times.colnames,
('start_time', 'stop_time', 'comments'))
def test_add_invalid_time_interval(self):
self.nwbfile.add_invalid_time_interval(start_time=0.0, stop_time=12.0)
self.assertEqual(len(self.nwbfile.invalid_times), 1)
self.nwbfile.add_invalid_time_interval(start_time=15.0, stop_time=16.0)
self.nwbfile.add_invalid_time_interval(start_time=17.0, stop_time=20.5)
self.assertEqual(len(self.nwbfile.invalid_times), 3)
def test_add_invalid_time_w_ts(self):
ts = TimeSeries(name='name', data=[1.2], rate=1.0, unit='na')
self.nwbfile.add_invalid_time_interval(start_time=18.0,
stop_time=20.6,
timeseries=ts,
tags=('hi', 'there'))
def test_add_electrode(self):
dev1 = self.nwbfile.create_device('dev1')
group = self.nwbfile.create_electrode_group('tetrode1',
'tetrode description',
'tetrode location', dev1)
self.nwbfile.add_electrode(1.0,
2.0,
3.0,
-1.0,
'CA1',
'none',
group=group,
id=1)
elec = self.nwbfile.electrodes[0]
self.assertEqual(elec.index[0], 1)
self.assertEqual(elec.iloc[0]['x'], 1.0)
self.assertEqual(elec.iloc[0]['y'], 2.0)
self.assertEqual(elec.iloc[0]['z'], 3.0)
self.assertEqual(elec.iloc[0]['location'], 'CA1')
self.assertEqual(elec.iloc[0]['filtering'], 'none')
self.assertEqual(elec.iloc[0]['group'], group)
def test_all_children(self):
ts1 = TimeSeries('test_ts1', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5])
ts2 = TimeSeries('test_ts2', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5])
self.nwbfile.add_acquisition(ts1)
self.nwbfile.add_acquisition(ts2)
name = 'example_electrode_group'
desc = 'An example electrode'
loc = 'an example location'
device = self.nwbfile.create_device('a fake device')
elecgrp = self.nwbfile.create_electrode_group(name, desc, loc, device)
children = self.nwbfile.all_children()
self.assertIn(ts1, children)
self.assertIn(ts2, children)
self.assertIn(device, children)
self.assertIn(elecgrp, children)
def test_fail_if_source_script_file_name_without_source_script(self):
with self.assertRaises(ValueError):
# <-- source_script_file_name without source_script is not allowed
NWBFile('a test session description for a test NWBFile',
'FILE123',
self.start,
source_script=None,
source_script_file_name='nofilename')
def test_get_neurodata_type(self):
ts1 = TimeSeries('test_ts1', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5])
ts2 = TimeSeries('test_ts2', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5])
self.nwbfile.add_acquisition(ts1)
self.nwbfile.add_acquisition(ts2)
p1 = ts1.get_ancestor(neurodata_type='NWBFile')
self.assertIs(p1, self.nwbfile)
p2 = ts2.get_ancestor(neurodata_type='NWBFile')
self.assertIs(p2, self.nwbfile)
def test_print_units(self):
self.nwbfile.add_unit(spike_times=[1., 2., 3.])
expected = """units pynwb.misc.Units at 0x%d
Fields:
colnames: ['spike_times']
columns: (
spike_times_index <class 'hdmf.common.table.VectorIndex'>,
spike_times <class 'hdmf.common.table.VectorData'>
)
description: Autogenerated by NWBFile
id: id <class 'hdmf.common.table.ElementIdentifiers'>
"""
expected = expected % id(self.nwbfile.units)
self.assertEqual(str(self.nwbfile.units), expected)
def test_copy(self):
self.nwbfile.add_unit(spike_times=[1., 2., 3.])
device = self.nwbfile.create_device('a')
elecgrp = self.nwbfile.create_electrode_group('a',
'b',
device=device,
location='a')
self.nwbfile.add_electrode(np.nan,
np.nan,
np.nan,
np.nan,
'a',
'a',
elecgrp,
id=0)
self.nwbfile.add_electrode(np.nan, np.nan, np.nan, np.nan, 'b', 'b',
elecgrp)
elec_region = self.nwbfile.create_electrode_table_region([1], 'name')
ts1 = TimeSeries('test_ts1', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5])
ts2 = ElectricalSeries('test_ts2', [0, 1, 2, 3, 4, 5],
electrodes=elec_region,
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5])
self.nwbfile.add_acquisition(ts1)
self.nwbfile.add_acquisition(ts2)
self.nwbfile.add_trial(start_time=50.0, stop_time=70.0)
self.nwbfile.add_invalid_times_column(
'comments', 'description of reason for omitting time')
self.nwbfile.create_processing_module('test_mod', 'test_description')
self.nwbfile.create_time_intervals('custom_interval',
'a custom time interval')
self.nwbfile.intervals['custom_interval'].add_interval(start_time=10.,
stop_time=20.)
newfile = self.nwbfile.copy()
# test dictionaries
self.assertIs(self.nwbfile.devices['a'], newfile.devices['a'])
self.assertIs(self.nwbfile.acquisition['test_ts1'],
newfile.acquisition['test_ts1'])
self.assertIs(self.nwbfile.acquisition['test_ts2'],
newfile.acquisition['test_ts2'])
self.assertIs(self.nwbfile.processing['test_mod'],
newfile.processing['test_mod'])
# test dynamic tables
self.assertIsNot(self.nwbfile.electrodes, newfile.electrodes)
self.assertIs(self.nwbfile.electrodes['x'], newfile.electrodes['x'])
self.assertIsNot(self.nwbfile.units, newfile.units)
self.assertIs(self.nwbfile.units['spike_times'],
newfile.units['spike_times'])
self.assertIsNot(self.nwbfile.trials, newfile.trials)
self.assertIsNot(self.nwbfile.trials.parent, newfile.trials.parent)
self.assertIs(self.nwbfile.trials.id, newfile.trials.id)
self.assertIs(self.nwbfile.trials['start_time'],
newfile.trials['start_time'])
self.assertIs(self.nwbfile.trials['stop_time'],
newfile.trials['stop_time'])
self.assertIsNot(self.nwbfile.invalid_times, newfile.invalid_times)
self.assertTupleEqual(self.nwbfile.invalid_times.colnames,
newfile.invalid_times.colnames)
self.assertIsNot(self.nwbfile.intervals['custom_interval'],
newfile.intervals['custom_interval'])
self.assertTupleEqual(
self.nwbfile.intervals['custom_interval'].colnames,
newfile.intervals['custom_interval'].colnames)
self.assertIs(self.nwbfile.intervals['custom_interval']['start_time'],
newfile.intervals['custom_interval']['start_time'])
self.assertIs(self.nwbfile.intervals['custom_interval']['stop_time'],
newfile.intervals['custom_interval']['stop_time'])
def test_multi_experimenters(self):
self.nwbfile = NWBFile('a test session description for a test NWBFile',
'FILE123',
self.start,
experimenter=('experimenter1', 'experimenter2'))
self.assertTupleEqual(self.nwbfile.experimenter,
('experimenter1', 'experimenter2'))
def test_multi_publications(self):
self.nwbfile = NWBFile('a test session description for a test NWBFile',
'FILE123',
self.start,
related_publications=('pub1', 'pub2'))
self.assertTupleEqual(self.nwbfile.related_publications,
('pub1', 'pub2'))
def chang2nwb(blockpath, out_file_path=None, save_to_file=False, htk_config=None):
"""
Parameters
----------
blockpath: str
out_file_path: None | str
if None, output = [blockpath]/[blockname].nwb
save_to_file : bool
If True, saves to file. If False, just returns nwbfile object
htk_config : dict
Dictionary cotaining HTK conversion paths and options. Example:
{
ecephys_path: 'path_to/ecephys_htk_files',
ecephys_type: 'raw', 'preprocessed' or 'high_gamma',
analog_path: 'path_to/analog_htk_files',
anin1: {present: True, name: 'microphone', type: 'acquisition'},
anin2: {present: True, name: 'speaker1', type: 'stimulus'},
anin3: {present: False, name: 'speaker2', type: 'stimulus'},
anin4: {present: False, name: 'custom', type: 'acquisition'},
metadata: metadata,
electrodes_file: electrodes_file,
bipolar_file: bipolar_file
}
Returns
-------
"""
metadata = {}
if htk_config is None:
blockpath = Path(blockpath)
else:
blockpath = Path(htk_config['ecephys_path'])
metadata = htk_config['metadata']
blockname = blockpath.parent.name
subject_id = blockpath.parent.parent.name[2:]
if out_file_path is None:
out_file_path = blockpath.resolve().parent / ''.join(['EC', subject_id, '_', blockname, '.nwb'])
# file paths
ecog_path = blockpath
anin_path = htk_config['analog_path']
bad_time_file = path.join(blockpath, 'Artifacts', 'badTimeSegments.mat')
# Create the NWB file object
nwbfile_dict = {
'session_description': blockname,
'identifier': blockname,
'session_start_time': datetime.now().astimezone(),
'institution': 'University of California, San Francisco',
'lab': 'Chang Lab'
}
if 'NWBFile' in metadata:
nwbfile_dict.update(metadata['NWBFile'])
nwbfile = NWBFile(**nwbfile_dict)
# Read electrophysiology data from HTK files
print('reading htk acquisition...', flush=True)
ecog_rate, data = readhtks(ecog_path)
data = data.squeeze()
print('done', flush=True)
# Get electrodes info from mat file
if htk_config['electrodes_file'] is not None:
nwbfile = elecs_to_electrode_table(
nwbfile=nwbfile,
elecspath=htk_config['electrodes_file'],
)
n_electrodes = nwbfile.electrodes[:].shape[0]
all_elecs = list(range(n_electrodes))
elecs_region = nwbfile.create_electrode_table_region(
region=all_elecs,
description='ECoG electrodes on brain'
)
else:
ecephys_dict = {
'Device': [{'name': 'auto_device'}],
'ElectricalSeries': [{'name': 'ECoG', 'description': 'description'}],
'ElectrodeGroup': [{'name': 'auto_group', 'description': 'auto_group',
'location': 'location', 'device': 'auto_device'}]
}
if 'Ecephys' in metadata:
ecephys_dict.update(metadata['Ecephys'])
# Create devices
for dev in ecephys_dict['Device']:
device = nwbfile.create_device(dev['name'])
# Electrode groups
for el_grp in ecephys_dict['ElectrodeGroup']:
device = nwbfile.devices[el_grp['device']]
electrode_group = nwbfile.create_electrode_group(
name=el_grp['name'],
description=el_grp['description'],
location=el_grp['location'],
device=device
)
# Electrodes table
n_electrodes = data.shape[1]
nwbfile.add_electrode_column('label', 'label of electrode')
nwbfile.add_electrode_column('bad', 'electrode identified as too noisy')
nwbfile.add_electrode_column('x_warped', 'x warped onto cvs_avg35_inMNI152')
nwbfile.add_electrode_column('y_warped', 'y warped onto cvs_avg35_inMNI152')
nwbfile.add_electrode_column('z_warped', 'z warped onto cvs_avg35_inMNI152')
nwbfile.add_electrode_column('null', 'if not connected to real electrode')
bad_elecs_inds = get_bad_elecs(blockpath)
for elec_counter in range(n_electrodes):
bad = elec_counter in bad_elecs_inds
nwbfile.add_electrode(
id=elec_counter,
x=np.nan,
y=np.nan,
z=np.nan,
imp=np.nan,
x_warped=np.nan,
y_warped=np.nan,
z_warped=np.nan,
location='',
filtering='none',
group=electrode_group,
label='',
bad=bad,
null=False,
)
all_elecs = list(range(n_electrodes))
elecs_region = nwbfile.create_electrode_table_region(
region=all_elecs,
description='ECoG electrodes on brain'
)
# Get Bipolar table from file
if htk_config['bipolar_file'] is not None:
df = pd.read_csv(htk_config['bipolar_file'], index_col='id', sep='\t')
# Create bipolar scheme table
bipolar_scheme_table = BipolarSchemeTable(
name='bipolar_scheme_table',
description='desc'
)
# Columns for bipolar scheme - all anodes and cathodes within the same
# bipolar row are considered to have the same group and location
bipolar_scheme_table.add_column(
name='group_name',
description='electrode group name'
)
bipolar_scheme_table.add_column(
name='location',
description='electrode location'
)
# Iterate over anode / cathode rows
for i, r in df.iterrows():
if isinstance(r['anodes'], str):
anodes = [int(a) for a in r['anodes'].split(',')]
else:
anodes = [int(r['anodes'])]
if isinstance(r['cathodes'], str):
cathodes = [int(a) for a in r['cathodes'].split(',')]
else:
cathodes = [int(r['cathodes'])]
bipolar_scheme_table.add_row(
anodes=anodes,
cathodes=cathodes,
group_name=nwbfile.electrodes['group_name'][anodes[0]],
location=nwbfile.electrodes['location'][anodes[0]]
)
bipolar_scheme_table.anodes.table = nwbfile.electrodes
bipolar_scheme_table.cathodes.table = nwbfile.electrodes
# Creates bipolar table region
elecs_region = DynamicTableRegion(
name='electrodes',
data=np.arange(0, df.shape[0]),
description='desc',
table=bipolar_scheme_table
)
ecephys_ext = EcephysExt(name='ecephys_ext')
ecephys_ext.bipolar_scheme_table = bipolar_scheme_table
nwbfile.add_lab_meta_data(ecephys_ext)
# Stores HTK electrophysiology data as raw, preprocessed or high gamma
if htk_config['ecephys_type'] == 'raw':
ecog_es = ElectricalSeries(name='ECoG',
data=H5DataIO(data[:, 0:n_electrodes], compression='gzip'),
electrodes=elecs_region,
rate=ecog_rate,
description='all Wav data')
nwbfile.add_acquisition(ecog_es)
elif htk_config['ecephys_type'] == 'preprocessed':
lfp = LFP()
ecog_es = ElectricalSeries(name='preprocessed',
data=H5DataIO(data[:, 0:n_electrodes], compression='gzip'),
electrodes=elecs_region,
rate=ecog_rate,
description='all Wav data')
lfp.add_electrical_series(ecog_es)
# Creates the ecephys processing module
ecephys_module = nwbfile.create_processing_module(
name='ecephys',
description='preprocessed electrophysiology data'
)
ecephys_module.add_data_interface(lfp)
elif htk_config['ecephys_type'] == 'high_gamma':
ecog_es = ElectricalSeries(name='high_gamma',
data=H5DataIO(data[:, 0:n_electrodes], compression='gzip'),
electrodes=elecs_region,
rate=ecog_rate,
description='all Wav data')
# Creates the ecephys processing module
ecephys_module = nwbfile.create_processing_module(
name='ecephys',
description='preprocessed electrophysiology data'
)
ecephys_module.add_data_interface(ecog_es)
# Add ANIN 1
if htk_config['anin1']['present']:
fs, data = get_analog(anin_path, 1)
ts = TimeSeries(
name=htk_config['anin1']['name'],
data=data,
unit='NA',
rate=fs,
)
if htk_config['anin1']['type'] == 'acquisition':
nwbfile.add_acquisition(ts)
else:
nwbfile.add_stimulus(ts)
print('ANIN1 saved with name "', htk_config['anin1']['name'], '" in ',
htk_config['anin1']['type'])
# Add ANIN 2
if htk_config['anin2']['present']:
fs, data = get_analog(anin_path, 2)
ts = TimeSeries(
name=htk_config['anin2']['name'],
data=data,
unit='NA',
rate=fs,
)
if htk_config['anin2']['type'] == 'acquisition':
nwbfile.add_acquisition(ts)
else:
nwbfile.add_stimulus(ts)
print('ANIN2 saved with name "', htk_config['anin2']['name'], '" in ',
htk_config['anin2']['type'])
# Add ANIN 3
if htk_config['anin3']['present']:
fs, data = get_analog(anin_path, 3)
ts = TimeSeries(
name=htk_config['anin3']['name'],
data=data,
unit='NA',
rate=fs,
)
if htk_config['anin3']['type'] == 'acquisition':
nwbfile.add_acquisition(ts)
else:
nwbfile.add_stimulus(ts)
print('ANIN3 saved with name "', htk_config['anin3']['name'], '" in ',
htk_config['anin3']['type'])
# Add ANIN 4
if htk_config['anin4']['present']:
fs, data = get_analog(anin_path, 4)
ts = TimeSeries(
name=htk_config['anin4']['name'],
data=data,
unit='NA',
rate=fs,
)
if htk_config['anin4']['type'] == 'acquisition':
nwbfile.add_acquisition(ts)
else:
nwbfile.add_stimulus(ts)
print('ANIN4 saved with name "', htk_config['anin4']['name'], '" in ',
htk_config['anin4']['type'])
# Add bad time segments
if os.path.exists(bad_time_file) and os.stat(bad_time_file).st_size:
bad_time = sio.loadmat(bad_time_file)['badTimeSegments']
for row in bad_time:
nwbfile.add_invalid_time_interval(start_time=row[0],
stop_time=row[1],
tags=('ECoG artifact',),
timeseries=ecog_es)
# Subject
subject_dict = {'subject_id': subject_id}
if 'Subject' in metadata:
subject_dict.update(metadata['Subject'])
subject = ECoGSubject(**subject_dict)
nwbfile.subject = subject
if save_to_file:
print('Saving HTK content to NWB file...')
# Export the NWB file
with NWBHDF5IO(str(out_file_path), manager=manager, mode='w') as io:
io.write(nwbfile)
# read check
with NWBHDF5IO(str(out_file_path), manager=manager, mode='r') as io:
io.read()
print('NWB file saved: ', str(out_file_path))
return nwbfile, out_file_path, subject_id, blockname
class NWBFileTest(unittest.TestCase):
def setUp(self):
self.start = datetime(2017, 5, 1, 12, 0, 0, tzinfo=tzlocal())
self.ref_time = datetime(1979, 1, 1, 0, tzinfo=tzutc())
self.create = [
datetime(2017, 5, 1, 12, tzinfo=tzlocal()),
datetime(2017, 5, 2, 13, 0, 0, 1, tzinfo=tzutc()),
datetime(2017, 5, 2, 14, tzinfo=tzutc())
]
self.path = 'nwbfile_test.h5'
self.nwbfile = NWBFile(
'a test session description for a test NWBFile',
'FILE123',
self.start,
file_create_date=self.create,
timestamps_reference_time=self.ref_time,
experimenter='A test experimenter',
lab='a test lab',
institution='a test institution',
experiment_description='a test experiment description',
session_id='test1',
notes='my notes',
pharmacology='drugs',
protocol='protocol',
related_publications='my pubs',
slices='my slices',
surgery='surgery',
virus='a virus',
source_script='noscript',
source_script_file_name='nofilename',
stimulus_notes='test stimulus notes',
data_collection='test data collection notes',
keywords=('these', 'are', 'keywords'))
def test_constructor(self):
self.assertEqual(self.nwbfile.session_description,
'a test session description for a test NWBFile')
self.assertEqual(self.nwbfile.identifier, 'FILE123')
self.assertEqual(self.nwbfile.session_start_time, self.start)
self.assertEqual(self.nwbfile.file_create_date, self.create)
self.assertEqual(self.nwbfile.lab, 'a test lab')
self.assertEqual(self.nwbfile.experimenter, 'A test experimenter')
self.assertEqual(self.nwbfile.institution, 'a test institution')
self.assertEqual(self.nwbfile.experiment_description,
'a test experiment description')
self.assertEqual(self.nwbfile.session_id, 'test1')
self.assertEqual(self.nwbfile.stimulus_notes, 'test stimulus notes')
self.assertEqual(self.nwbfile.data_collection,
'test data collection notes')
self.assertEqual(self.nwbfile.source_script, 'noscript')
self.assertEqual(self.nwbfile.source_script_file_name, 'nofilename')
self.assertEqual(self.nwbfile.keywords, ('these', 'are', 'keywords'))
self.assertEqual(self.nwbfile.timestamps_reference_time, self.ref_time)
def test_create_electrode_group(self):
name = 'example_electrode_group'
desc = 'An example electrode'
loc = 'an example location'
d = self.nwbfile.create_device('a fake device')
elecgrp = self.nwbfile.create_electrode_group(name, desc, loc, d)
self.assertEqual(elecgrp.description, desc)
self.assertEqual(elecgrp.location, loc)
self.assertIs(elecgrp.device, d)
def test_create_electrode_group_invalid_index(self):
"""
Test the case where the user creates an electrode table region with
indexes that are out of range of the amount of electrodes added.
"""
nwbfile = NWBFile('a', 'b', datetime.now(tzlocal()))
device = nwbfile.create_device('a')
elecgrp = nwbfile.create_electrode_group('a',
'b',
device=device,
location='a')
for i in range(4):
nwbfile.add_electrode(np.nan,
np.nan,
np.nan,
np.nan,
'a',
'a',
elecgrp,
id=i)
with self.assertRaises(IndexError):
nwbfile.create_electrode_table_region(list(range(6)), 'test')
def test_access_group_after_io(self):
"""
Motivated by #739
"""
nwbfile = NWBFile('a', 'b', datetime.now(tzlocal()))
device = nwbfile.create_device('a')
elecgrp = nwbfile.create_electrode_group('a',
'b',
device=device,
location='a')
nwbfile.add_electrode(np.nan,
np.nan,
np.nan,
np.nan,
'a',
'a',
elecgrp,
id=0)
with NWBHDF5IO('electrodes_mwe.nwb', 'w') as io:
io.write(nwbfile)
with NWBHDF5IO('electrodes_mwe.nwb', 'a') as io:
nwbfile_i = io.read()
for aa, bb in zip(nwbfile_i.electrodes['group'][:],
nwbfile.electrodes['group'][:]):
self.assertEqual(aa.name, bb.name)
for i in range(4):
nwbfile.add_electrode(np.nan,
np.nan,
np.nan,
np.nan,
'a',
'a',
elecgrp,
id=i + 1)
with NWBHDF5IO('electrodes_mwe.nwb', 'w') as io:
io.write(nwbfile)
with NWBHDF5IO('electrodes_mwe.nwb', 'a') as io:
nwbfile_i = io.read()
for aa, bb in zip(nwbfile_i.electrodes['group'][:],
nwbfile.electrodes['group'][:]):
self.assertEqual(aa.name, bb.name)
os.remove("electrodes_mwe.nwb")
def test_epoch_tags(self):
tags1 = ['t1', 't2']
tags2 = ['t3', 't4']
tstamps = np.arange(1.0, 100.0, 0.1, dtype=np.float)
ts = TimeSeries("test_ts",
list(range(len(tstamps))),
'unit',
timestamps=tstamps)
expected_tags = tags1 + tags2
self.nwbfile.add_epoch(0.0, 1.0, tags1, ts)
self.nwbfile.add_epoch(0.0, 1.0, tags2, ts)
tags = self.nwbfile.epoch_tags
six.assertCountEqual(self, expected_tags, tags)
def test_add_acquisition(self):
self.nwbfile.add_acquisition(
TimeSeries('test_ts', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
self.assertEqual(len(self.nwbfile.acquisition), 1)
def test_add_stimulus(self):
self.nwbfile.add_stimulus(
TimeSeries('test_ts', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
self.assertEqual(len(self.nwbfile.stimulus), 1)
def test_add_stimulus_template(self):
self.nwbfile.add_stimulus_template(
TimeSeries('test_ts', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
self.assertEqual(len(self.nwbfile.stimulus_template), 1)
def test_add_acquisition_check_dups(self):
self.nwbfile.add_acquisition(
TimeSeries('test_ts', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
with self.assertRaises(ValueError):
self.nwbfile.add_acquisition(
TimeSeries('test_ts', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
def test_get_acquisition_empty(self):
with self.assertRaisesRegex(ValueError,
"acquisition of NWBFile 'root' is empty"):
self.nwbfile.get_acquisition()
def test_get_acquisition_multiple_elements(self):
self.nwbfile.add_acquisition(
TimeSeries('test_ts1', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
self.nwbfile.add_acquisition(
TimeSeries('test_ts2', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
msg = "more than one element in acquisition of NWBFile 'root' -- must specify a name"
with self.assertRaisesRegex(ValueError, msg):
self.nwbfile.get_acquisition()
def test_add_acquisition_invalid_name(self):
self.nwbfile.add_acquisition(
TimeSeries('test_ts', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5]))
msg = "'TEST_TS' not found in acquisition of NWBFile 'root'"
with self.assertRaisesRegex(KeyError, msg):
self.nwbfile.get_acquisition("TEST_TS")
def test_set_electrode_table(self):
table = ElectrodeTable() # noqa: F405
dev1 = self.nwbfile.create_device('dev1') # noqa: F405
group = self.nwbfile.create_electrode_group('tetrode1',
'tetrode description',
'tetrode location', dev1)
table.add_row(x=1.0,
y=2.0,
z=3.0,
imp=-1.0,
location='CA1',
filtering='none',
group=group,
group_name='tetrode1')
table.add_row(x=1.0,
y=2.0,
z=3.0,
imp=-2.0,
location='CA1',
filtering='none',
group=group,
group_name='tetrode1')
table.add_row(x=1.0,
y=2.0,
z=3.0,
imp=-3.0,
location='CA1',
filtering='none',
group=group,
group_name='tetrode1')
table.add_row(x=1.0,
y=2.0,
z=3.0,
imp=-4.0,
location='CA1',
filtering='none',
group=group,
group_name='tetrode1')
self.nwbfile.set_electrode_table(table)
self.assertIs(self.nwbfile.electrodes, table)
self.assertIs(table.parent, self.nwbfile)
def test_add_unit_column(self):
self.nwbfile.add_unit_column('unit_type', 'the type of unit')
self.assertEqual(self.nwbfile.units.colnames, ('unit_type', ))
def test_add_unit(self):
self.nwbfile.add_unit(id=1)
self.assertEqual(len(self.nwbfile.units), 1)
self.nwbfile.add_unit(id=2)
self.nwbfile.add_unit(id=3)
self.assertEqual(len(self.nwbfile.units), 3)
def test_add_trial_column(self):
self.nwbfile.add_trial_column('trial_type', 'the type of trial')
self.assertEqual(self.nwbfile.trials.colnames,
('start_time', 'stop_time', 'trial_type'))
def test_add_trial(self):
self.nwbfile.add_trial(start_time=10.0, stop_time=20.0)
self.assertEqual(len(self.nwbfile.trials), 1)
self.nwbfile.add_trial(start_time=30.0, stop_time=40.0)
self.nwbfile.add_trial(start_time=50.0, stop_time=70.0)
self.assertEqual(len(self.nwbfile.trials), 3)
def test_add_invalid_times_column(self):
self.nwbfile.add_invalid_times_column(
'comments', 'description of reason for omitting time')
self.assertEqual(self.nwbfile.invalid_times.colnames,
('start_time', 'stop_time', 'comments'))
def test_add_invalid_time_interval(self):
self.nwbfile.add_invalid_time_interval(start_time=0.0, stop_time=12.0)
self.assertEqual(len(self.nwbfile.invalid_times), 1)
self.nwbfile.add_invalid_time_interval(start_time=15.0, stop_time=16.0)
self.nwbfile.add_invalid_time_interval(start_time=17.0, stop_time=20.5)
self.assertEqual(len(self.nwbfile.invalid_times), 3)
def test_add_invalid_time_w_ts(self):
ts = TimeSeries(name='name', data=[1.2], rate=1.0, unit='na')
self.nwbfile.add_invalid_time_interval(start_time=18.0,
stop_time=20.6,
timeseries=ts,
tags=('hi', 'there'))
def test_add_electrode(self):
dev1 = self.nwbfile.create_device('dev1') # noqa: F405
group = self.nwbfile.create_electrode_group('tetrode1',
'tetrode description',
'tetrode location', dev1)
self.nwbfile.add_electrode(1.0,
2.0,
3.0,
-1.0,
'CA1',
'none',
group=group,
id=1)
self.assertEqual(self.nwbfile.ec_electrodes[0][0], 1)
self.assertEqual(self.nwbfile.ec_electrodes[0][1], 1.0)
self.assertEqual(self.nwbfile.ec_electrodes[0][2], 2.0)
self.assertEqual(self.nwbfile.ec_electrodes[0][3], 3.0)
self.assertEqual(self.nwbfile.ec_electrodes[0][4], -1.0)
self.assertEqual(self.nwbfile.ec_electrodes[0][5], 'CA1')
self.assertEqual(self.nwbfile.ec_electrodes[0][6], 'none')
self.assertEqual(self.nwbfile.ec_electrodes[0][7], group)
def test_all_children(self):
ts1 = TimeSeries('test_ts1', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5])
ts2 = TimeSeries('test_ts2', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5])
self.nwbfile.add_acquisition(ts1)
self.nwbfile.add_acquisition(ts2)
name = 'example_electrode_group'
desc = 'An example electrode'
loc = 'an example location'
device = self.nwbfile.create_device('a fake device')
elecgrp = self.nwbfile.create_electrode_group(name, desc, loc, device)
children = self.nwbfile.all_children()
self.assertIn(ts1, children)
self.assertIn(ts2, children)
self.assertIn(device, children)
self.assertIn(elecgrp, children)
def test_fail_if_source_script_file_name_without_source_script(self):
with self.assertRaises(ValueError):
# <-- source_script_file_name without source_script is not allowed
NWBFile('a test session description for a test NWBFile',
'FILE123',
self.start,
source_script=None,
source_script_file_name='nofilename')
def test_get_neurodata_type(self):
ts1 = TimeSeries('test_ts1', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5])
ts2 = TimeSeries('test_ts2', [0, 1, 2, 3, 4, 5],
'grams',
timestamps=[0.0, 0.1, 0.2, 0.3, 0.4, 0.5])
self.nwbfile.add_acquisition(ts1)
self.nwbfile.add_acquisition(ts2)
p1 = ts1.get_ancestor(neurodata_type='NWBFile')
self.assertIs(p1, self.nwbfile)
p2 = ts2.get_ancestor(neurodata_type='NWBFile')
self.assertIs(p2, self.nwbfile)
def chang2nwb(blockpath,
outpath=None,
session_start_time=None,
session_description=None,
identifier=None,
anin4=False,
ecog_format='auto',
external_subject=True,
include_pitch=False,
include_intensity=False,
speakers=True,
mic=False,
mini=False,
hilb=False,
verbose=False,
imaging_path=None,
parse_transcript=False,
include_cortical_surfaces=True,
include_electrodes=True,
include_ekg=True,
subject_image_list=None,
rest_period=None,
load_warped=False,
**kwargs):
"""
Parameters
----------
blockpath: str
outpath: None | str
if None, output = [blockpath]/[blockname].nwb
session_start_time: datetime.datetime
default: datetime(1900, 1, 1)
session_description: str
default: blockname
identifier: str
default: blockname
anin4: False | str
Whether or not to convert ANIN4. ANIN4 is used as an extra channel for
things like button presses, and is usually unused. If a string is
supplied, that is used as the name of the timeseries.
ecog_format: str
({'htk'}, 'mat', 'raw')
external_subject: bool (optional)
True: (default) cortical mesh is saved in an external file and a link is
provided to that file. This is useful if you have multiple sessions for a single subject.
False: cortical mesh is saved normally
include_pitch: bool (optional)
add pitch data. Default: False
include_intensity: bool (optional)
add intensity data. Default: False
speakers: bool (optional)
Default: False
mic: bool (optional)
default: False
mini: only save data stub. Used for testing
hilb: bool
include Hilbert Transform data. Default: False
verbose: bool (optional)
imaging_path: str (optional)
None: use IMAGING_DIR
'local': use subject_dir/Imaging/
else: use supplied string
parse_transcript: str (optional)
include_cortical_surfaces: bool (optional)
include_electrodes: bool (optional)
include_ekg: bool (optional)
subject_image_list: list (optional)
List of paths of images to include
rest_period: None | array-like
kwargs: dict
passed to pynwb.NWBFile
Returns
-------
"""
behav_module = None
basepath, blockname = os.path.split(blockpath)
subject_id = get_subject_id(blockname)
if identifier is None:
identifier = blockname
if session_description is None:
session_description = blockname
if outpath is None:
outpath = blockpath + '.nwb'
out_base_path = os.path.split(outpath)[0]
if session_start_time is None:
session_start_time = datetime(1900, 1, 1).astimezone(timezone('UTC'))
if imaging_path is None:
subj_imaging_path = path.join(IMAGING_PATH, subject_id)
elif imaging_path == 'local':
subj_imaging_path = path.join(basepath, 'imaging')
else:
subj_imaging_path = os.path.join(imaging_path, subject_id)
# file paths
bad_time_file = path.join(blockpath, 'Artifacts', 'badTimeSegments.mat')
ecog_path = path.join(blockpath, 'RawHTK')
ecog400_path = path.join(blockpath, 'ecog400', 'ecog.mat')
elec_metadata_file = path.join(subj_imaging_path, 'elecs',
'TDT_elecs_all.mat')
mesh_path = path.join(subj_imaging_path, 'Meshes')
pial_files = glob.glob(path.join(mesh_path, '*pial.mat'))
# Create the NWB file object
nwbfile = NWBFile(session_description,
identifier,
session_start_time,
datetime.now().astimezone(),
session_id=identifier,
institution='University of California, San Francisco',
lab='Chang Lab',
**kwargs)
nwbfile.add_electrode_column('bad', 'electrode identified as too noisy')
bad_elecs_inds = get_bad_elecs(blockpath)
if include_electrodes:
add_electrodes(nwbfile,
elec_metadata_file,
bad_elecs_inds,
load_warped=load_warped)
else:
device = nwbfile.create_device('256Grid')
electrode_group = nwbfile.create_electrode_group(
name='256Grid electrodes',
description='auto_group',
location='location',
device=device)
for elec_counter in range(256):
bad = elec_counter in bad_elecs_inds
nwbfile.add_electrode(id=elec_counter + 1,
x=np.nan,
y=np.nan,
z=np.nan,
imp=np.nan,
location=' ',
filtering='none',
group=electrode_group,
bad=bad)
ecog_elecs = list(range(len(nwbfile.electrodes)))
ecog_elecs_region = nwbfile.create_electrode_table_region(
ecog_elecs, 'ECoG electrodes on brain')
# Read electrophysiology data from HTK files and add them to NWB file
if ecog_format == 'auto':
ecog_rate, data, ecog_path = auto_ecog(blockpath,
ecog_elecs,
verbose=False)
elif ecog_format == 'htk':
if verbose:
print('reading htk acquisition...', flush=True)
ecog_rate, data = readhtks(ecog_path, ecog_elecs)
data = data.squeeze()
if verbose:
print('done', flush=True)
elif ecog_format == 'mat':
with File(ecog400_path, 'r') as f:
data = f['ecogDS']['data'][:, ecog_elecs]
ecog_rate = f['ecogDS']['sampFreq'][:].ravel()[0]
ecog_path = ecog400_path
elif ecog_format == 'raw':
ecog_path = os.path.join(tdt_data_path, subject_id, blockname,
'raw.mat')
ecog_rate, data = load_wavs(ecog_path)
else:
raise ValueError('unrecognized argument: ecog_format')
ts_desc = "all Wav data"
if mini:
data = data[:2000]
ecog_ts = ElectricalSeries(name='ElectricalSeries',
data=H5DataIO(data, compression='gzip'),
electrodes=ecog_elecs_region,
rate=ecog_rate,
description=ts_desc,
conversion=0.001)
nwbfile.add_acquisition(ecog_ts)
if include_ekg:
ekg_elecs = find_ekg_elecs(elec_metadata_file)
if len(ekg_elecs):
add_ekg(nwbfile, ecog_path, ekg_elecs)
if mic:
# Add microphone recording from room
fs, data = get_analog(blockpath, 1)
nwbfile.add_acquisition(
TimeSeries('microphone',
data,
'audio unit',
rate=fs,
description="audio recording from microphone in room"))
if speakers:
fs, data = get_analog(blockpath, 2)
# Add audio stimulus 1
nwbfile.add_stimulus(
TimeSeries('speaker 1',
data,
'NA',
rate=fs,
description="audio stimulus 1"))
# Add audio stimulus 2
fs, data = get_analog(blockpath, 3)
if fs is not None:
nwbfile.add_stimulus(
TimeSeries('speaker 2',
data,
'NA',
rate=fs,
description='the second stimulus source'))
if anin4:
fs, data = get_analog(blockpath, 4)
nwbfile.add_acquisition(
TimeSeries(anin4,
data,
'aux unit',
rate=fs,
description="aux analog recording"))
# Add bad time segments
if os.path.exists(bad_time_file) and os.stat(bad_time_file).st_size:
bad_time = sio.loadmat(bad_time_file)['badTimeSegments']
for row in bad_time:
nwbfile.add_invalid_time_interval(start_time=row[0],
stop_time=row[1],
tags=('ECoG artifact', ),
timeseries=ecog_ts)
if rest_period is not None:
nwbfile.add_epoch_column(name='label', description='label')
nwbfile.add_epoch(start_time=rest_period[0],
stop_time=rest_period[1],
label='rest_period')
if hilb:
block_hilb_path = os.path.join(hilb_dir, subject_id, blockname,
blockname + '_AA.h5')
file = File(block_hilb_path, 'r')
data = transpose_iter(
file['X']) # transposes data during iterative write
filter_center = file['filter_center'][:]
filter_sigma = file['filter_sigma'][:]
data = H5DataIO(DataChunkIterator(tqdm(data,
desc='writing hilbert data'),
buffer_size=400 * 20),
compression='gzip')
decomp_series = DecompositionSeries(
name='LFPDecompositionSeries',
description='Gaussian band Hilbert transform',
data=data,
rate=400.,
source_timeseries=ecog_ts,
metric='amplitude')
for band_mean, band_stdev in zip(filter_center, filter_sigma):
decomp_series.add_band(band_mean=band_mean, band_stdev=band_stdev)
hilb_mod = nwbfile.create_processing_module(
name='ecephys', description='holds hilbert analysis results')
hilb_mod.add_container(decomp_series)
if include_cortical_surfaces:
subject = ECoGSubject(subject_id=subject_id)
subject.cortical_surfaces = create_cortical_surfaces(
pial_files, subject_id)
else:
subject = Subject(subject_id=subject_id, species='H**o sapiens')
if subject_image_list is not None:
subject = add_images_to_subject(subject, subject_image_list)
if external_subject:
subj_fpath = path.join(out_base_path, subject_id + '.nwb')
if not os.path.isfile(subj_fpath):
subj_nwbfile = NWBFile(session_description=subject_id,
identifier=subject_id,
subject=subject,
session_start_time=datetime(
1900, 1, 1).astimezone(timezone('UTC')))
with NWBHDF5IO(subj_fpath, manager=manager, mode='w') as subj_io:
subj_io.write(subj_nwbfile)
subj_read_io = NWBHDF5IO(subj_fpath, manager=manager, mode='r')
subj_nwbfile = subj_read_io.read()
subject = subj_nwbfile.subject
nwbfile.subject = subject
if parse_transcript:
if parse_transcript == 'CV':
parseout = parse(blockpath, blockname)
df = make_df(parseout, 0, subject_id, align_pos=1)
nwbfile.add_trial_column('cv_transition_time',
'time of CV transition in seconds')
nwbfile.add_trial_column(
'speak',
'if True, subject is speaking. If False, subject is listening')
nwbfile.add_trial_column('condition', 'syllable spoken')
for _, row in df.iterrows():
nwbfile.add_trial(start_time=row['start'],
stop_time=row['stop'],
cv_transition_time=row['align'],
speak=row['mode'] == 'speak',
condition=row['label'])
elif parse_transcript == 'singing':
parseout = parse(blockpath, blockname)
df = make_df(parseout, 0, subject_id, align_pos=0)
if not len(df):
df = pd.DataFrame(parseout)
df['mode'] = 'speak'
df = df.loc[df['label'].astype('bool'), :] # handle empty labels
nwbfile.add_trial_column(
'speak',
'if True, subject is speaking. If False, subject is listening')
nwbfile.add_trial_column('condition', 'syllable spoken')
for _, row in df.iterrows():
nwbfile.add_trial(start_time=row['start'],
stop_time=row['stop'],
speak=row['mode'] == 'speak',
condition=row['label'])
elif parse_transcript == 'emphasis':
parseout = parse(blockpath, blockname)
try:
df = make_df(parseout, 0, subject_id, align_pos=0)
except:
df = pd.DataFrame(parseout)
if not len(df):
df = pd.DataFrame(parseout)
df = df.loc[df['label'].astype('bool'), :] # handle empty labels
nwbfile.add_trial_column('condition', 'word emphasized')
nwbfile.add_trial_column(
'speak',
'if True, subject is speaking. If False, subject is listening')
for _, row in df.iterrows():
nwbfile.add_trial(start_time=row['start'],
stop_time=row['stop'],
speak=True,
condition=row['label'])
elif parse_transcript == 'MOCHA':
nwbfile = create_transcription(nwbfile, transcript_path, blockname)
# behavior
if include_pitch:
if behav_module is None:
behav_module = nwbfile.create_processing_module(
'behavior', 'processing about behavior')
if os.path.isfile(
os.path.join(blockpath, 'pitch_' + blockname + '.mat')):
fs, data = load_pitch(blockpath)
pitch_ts = TimeSeries(
data=data,
rate=fs,
unit='Hz',
name='pitch',
description=
'Pitch as extracted from Praat. NaNs mark unvoiced regions.')
behav_module.add_container(
BehavioralTimeSeries(name='pitch', time_series=pitch_ts))
else:
print('No pitch file for ' + blockname)
if include_intensity:
if behav_module is None:
behav_module = nwbfile.create_processing_module(
'behavior', 'processing about behavior')
if os.path.isfile(
os.path.join(blockpath, 'intensity_' + blockname + '.mat')):
fs, data = load_pitch(blockpath)
intensity_ts = TimeSeries(
data=data,
rate=fs,
unit='dB',
name='intensity',
description='Intensity of speech in dB extracted from Praat.')
behav_module.add_container(
BehavioralTimeSeries(name='intensity',
time_series=intensity_ts))
else:
print('No intensity file for ' + blockname)
# Export the NWB file
with NWBHDF5IO(outpath, manager=manager, mode='w') as io:
io.write(nwbfile)
if external_subject:
subj_read_io.close()
if hilb:
file.close()
# read check
with NWBHDF5IO(outpath, manager=manager, mode='r') as io:
io.read()
def nwb_copy_file(old_file, new_file, cp_objs={}, save_to_file=True):
"""
Copy fields defined in 'obj', from existing NWB file to new NWB file.
Parameters
----------
old_file : str, path, nwbfile
String or path to nwb file '/path/to/old_file.nwb'. Alternatively, the
nwbfile object.
new_file : str, path
String such as '/path/to/new_file.nwb'.
cp_objs : dict
Name:Value pairs (Group:Children) listing the groups and respective
children from the current NWB file to be copied. Children can be:
- Boolean, indicating an attribute (e.g. for institution, lab)
- List of strings, containing several children names
Example:
{'institution':True,
'lab':True,
'acquisition':['microphone'],
'ecephys':['LFP','DecompositionSeries']}
save_to_file: Boolean
If True, saves directly to new_file.nwb. If False, only returns nwb_new.
Returns:
--------
nwb_new : nwbfile object
"""
manager = get_manager()
# Get from nwbfile object in memory or from file
if isinstance(old_file, NWBFile):
nwb_old = old_file
io1 = False
else:
io1 = NWBHDF5IO(str(old_file),
'r',
manager=manager,
load_namespaces=True)
nwb_old = io1.read()
# Creates new file
nwb_new = NWBFile(
session_description=str(nwb_old.session_description),
identifier=id_generator(),
session_start_time=nwb_old.session_start_time,
)
with NWBHDF5IO(new_file, mode='w', manager=manager,
load_namespaces=False) as io2:
# Institution name ------------------------------------------------
if 'institution' in cp_objs:
nwb_new.institution = str(nwb_old.institution)
# Lab name --------------------------------------------------------
if 'lab' in cp_objs:
nwb_new.lab = str(nwb_old.lab)
# Session id ------------------------------------------------------
if 'session' in cp_objs:
nwb_new.session_id = nwb_old.session_id
# Devices ---------------------------------------------------------
if 'devices' in cp_objs:
for aux in list(nwb_old.devices.keys()):
dev = Device(nwb_old.devices[aux].name)
nwb_new.add_device(dev)
# Electrode groups ------------------------------------------------
if 'electrode_groups' in cp_objs and nwb_old.electrode_groups is not None:
for aux in list(nwb_old.electrode_groups.keys()):
nwb_new.create_electrode_group(
name=str(nwb_old.electrode_groups[aux].name),
description=str(nwb_old.electrode_groups[aux].description),
location=str(nwb_old.electrode_groups[aux].location),
device=nwb_new.get_device(
nwb_old.electrode_groups[aux].device.name))
# Electrodes ------------------------------------------------------
if 'electrodes' in cp_objs and nwb_old.electrodes is not None:
nElec = len(nwb_old.electrodes['x'].data[:])
for aux in np.arange(nElec):
nwb_new.add_electrode(
x=nwb_old.electrodes['x'][aux],
y=nwb_old.electrodes['y'][aux],
z=nwb_old.electrodes['z'][aux],
imp=nwb_old.electrodes['imp'][aux],
location=str(nwb_old.electrodes['location'][aux]),
filtering=str(nwb_old.electrodes['filtering'][aux]),
group=nwb_new.get_electrode_group(
nwb_old.electrodes['group'][aux].name),
group_name=str(nwb_old.electrodes['group_name'][aux]))
# if there are custom variables
new_vars = list(nwb_old.electrodes.colnames)
default_vars = [
'x', 'y', 'z', 'imp', 'location', 'filtering', 'group',
'group_name'
]
[new_vars.remove(var) for var in default_vars]
for var in new_vars:
if var == 'label':
var_data = [
str(elem) for elem in nwb_old.electrodes[var].data[:]
]
else:
var_data = np.array(nwb_old.electrodes[var].data[:])
nwb_new.add_electrode_column(
name=str(var),
description=str(nwb_old.electrodes[var].description),
data=var_data)
# If Bipolar scheme for electrodes
for v in nwb_old.lab_meta_data.values():
if isinstance(v, EcephysExt) and hasattr(
v, 'bipolar_scheme_table'):
bst_old = v.bipolar_scheme_table
bst_new = BipolarSchemeTable(
name=bst_old.name, description=bst_old.description)
ecephys_ext = EcephysExt(name=v.name)
ecephys_ext.bipolar_scheme_table = bst_new
nwb_new.add_lab_meta_data(ecephys_ext)
# Epochs ----------------------------------------------------------
if 'epochs' in cp_objs and nwb_old.epochs is not None:
nEpochs = len(nwb_old.epochs['start_time'].data[:])
for i in np.arange(nEpochs):
nwb_new.add_epoch(
start_time=nwb_old.epochs['start_time'].data[i],
stop_time=nwb_old.epochs['stop_time'].data[i])
# if there are custom variables
new_vars = list(nwb_old.epochs.colnames)
default_vars = ['start_time', 'stop_time', 'tags', 'timeseries']
[new_vars.remove(var) for var in default_vars if var in new_vars]
for var in new_vars:
nwb_new.add_epoch_column(
name=var,
description=nwb_old.epochs[var].description,
data=nwb_old.epochs[var].data[:])
# Invalid times ---------------------------------------------------
if 'invalid_times' in cp_objs and nwb_old.invalid_times is not None:
nInvalid = len(nwb_old.invalid_times['start_time'][:])
for aux in np.arange(nInvalid):
nwb_new.add_invalid_time_interval(
start_time=nwb_old.invalid_times['start_time'][aux],
stop_time=nwb_old.invalid_times['stop_time'][aux])
# Trials ----------------------------------------------------------
if 'trials' in cp_objs and nwb_old.trials is not None:
nTrials = len(nwb_old.trials['start_time'])
for aux in np.arange(nTrials):
nwb_new.add_trial(start_time=nwb_old.trials['start_time'][aux],
stop_time=nwb_old.trials['stop_time'][aux])
# if there are custom variables
new_vars = list(nwb_old.trials.colnames)
default_vars = ['start_time', 'stop_time']
[new_vars.remove(var) for var in default_vars]
for var in new_vars:
nwb_new.add_trial_column(
name=var,
description=nwb_old.trials[var].description,
data=nwb_old.trials[var].data[:])
# Intervals -------------------------------------------------------
if 'intervals' in cp_objs and nwb_old.intervals is not None:
all_objs_names = list(nwb_old.intervals.keys())
for obj_name in all_objs_names:
obj_old = nwb_old.intervals[obj_name]
# create and add TimeIntervals
obj = TimeIntervals(name=obj_old.name,
description=obj_old.description)
nInt = len(obj_old['start_time'])
for ind in np.arange(nInt):
obj.add_interval(start_time=obj_old['start_time'][ind],
stop_time=obj_old['stop_time'][ind])
# Add to file
nwb_new.add_time_intervals(obj)
# Stimulus --------------------------------------------------------
if 'stimulus' in cp_objs:
all_objs_names = list(nwb_old.stimulus.keys())
for obj_name in all_objs_names:
obj_old = nwb_old.stimulus[obj_name]
obj = TimeSeries(name=obj_old.name,
description=obj_old.description,
data=obj_old.data[:],
rate=obj_old.rate,
resolution=obj_old.resolution,
conversion=obj_old.conversion,
starting_time=obj_old.starting_time,
unit=obj_old.unit)
nwb_new.add_stimulus(obj)
# Processing modules ----------------------------------------------
if 'ecephys' in cp_objs:
interfaces = [
nwb_old.processing['ecephys'].data_interfaces[key]
for key in cp_objs['ecephys']
]
# Add ecephys module to NWB file
ecephys_module = ProcessingModule(
name='ecephys',
description='Extracellular electrophysiology data.')
nwb_new.add_processing_module(ecephys_module)
for interface_old in interfaces:
obj = copy_obj(interface_old, nwb_old, nwb_new)
if obj is not None:
ecephys_module.add_data_interface(obj)
if 'behavior' in cp_objs:
interfaces = [
nwb_old.processing['behavior'].data_interfaces[key]
for key in cp_objs['behavior']
]
if 'behavior' not in nwb_new.processing:
# Add behavior module to NWB file
behavior_module = ProcessingModule(
name='behavior', description='behavioral data.')
nwb_new.add_processing_module(behavior_module)
for interface_old in interfaces:
obj = copy_obj(interface_old, nwb_old, nwb_new)
if obj is not None:
behavior_module.add_data_interface(obj)
# Acquisition -----------------------------------------------------
# Can get raw ElecetricalSeries and Mic recording
if 'acquisition' in cp_objs:
for acq_name in cp_objs['acquisition']:
obj_old = nwb_old.acquisition[acq_name]
acq = copy_obj(obj_old, nwb_old, nwb_new)
nwb_new.add_acquisition(acq)
# Surveys ---------------------------------------------------------
if 'surveys' in cp_objs and 'behavior' in nwb_old.processing:
surveys_list = [
v for v in
nwb_old.processing['behavior'].data_interfaces.values()
if v.neurodata_type == 'SurveyTable'
]
if cp_objs['surveys'] and len(surveys_list) > 0:
if 'behavior' not in nwb_new.processing:
# Add behavior module to NWB file
behavior_module = ProcessingModule(
name='behavior', description='behavioral data.')
nwb_new.add_processing_module(behavior_module)
for obj_old in surveys_list:
srv = copy_obj(obj_old, nwb_old, nwb_new)
behavior_module.add_data_interface(srv)
# Subject ---------------------------------------------------------
if nwb_old.subject is not None:
if 'subject' in cp_objs:
try:
cortical_surfaces = CorticalSurfaces()
surfaces = nwb_old.subject.cortical_surfaces.surfaces
for sfc in list(surfaces.keys()):
cortical_surfaces.create_surface(
name=surfaces[sfc].name,
faces=surfaces[sfc].faces,
vertices=surfaces[sfc].vertices)
nwb_new.subject = ECoGSubject(
cortical_surfaces=cortical_surfaces,
subject_id=nwb_old.subject.subject_id,
age=nwb_old.subject.age,
description=nwb_old.subject.description,
genotype=nwb_old.subject.genotype,
sex=nwb_old.subject.sex,
species=nwb_old.subject.species,
weight=nwb_old.subject.weight,
date_of_birth=nwb_old.subject.date_of_birth)
except:
nwb_new.subject = Subject(**nwb_old.subject.fields)
# Write new file with copied fields
if save_to_file:
io2.write(nwb_new, link_data=False)
# Close old file and return new nwbfile object
if io1:
io1.close()
return nwb_new
'condition': ['a', 'b', 'c'],
'response_latency': [.3, .26, .31],
'response': ['y', 'n', 'y'],
'bad': [False, False, True]
})
for _, row in trials_df.iterrows():
nwbfile.add_trial(**{label: row[label] for label in trials_df})
# print(nwbfile.trials.to_dataframe())
# bad times
bad_times_data = [[5.4, 6.], [10.4, 11.]] # in seconds
for start, stop in bad_times_data:
nwbfile.add_invalid_time_interval(start_time=start,
stop_time=stop,
tags=('ECoG artifact', ),
timeseries=ecog_ts)
# Create units table for neurons from micro-array recordings
single_electrode_regions = [
nwbfile.create_electrode_table_region([i], 'electrode i')
for i in range(len(electrodes_df))
]
all_spike_times = [[1., 2., 3., 4.], [2., 3., 4.], [0.5, 1., 4., 10., 15.]]
all_electrodes = ((0, ), (0, ), (1, ))
waveform_means = [np.random.randn(30, 1) for _ in range(3)]
for spike_times, electrodes, waveform_mean in \
