def textgriddf_converter(text_df):
"""Converts data into TimeIntervals
For a given DataFrame this function converts the data into TimeIntervals
Parameters
----------
text_df : pandas.DataFrame
Data related to an item
Returns
----------
pynwb.epoch.TimeIntervals
"""
textgrid_sentences = TimeIntervals(
name='sentences',
description='desc'
)
textgrid_sentences.add_column('label', 'text of sentences')
for i in text_df.index:
textgrid_sentences.add_interval(label=text_df.iloc[i]['text'], start_time=float(text_df.iloc[i]['xmin']),
stop_time=float(text_df.iloc[i]['xmax']))
return textgrid_sentences
class TestAlignMultiTraceTimeSeriesByTrials(unittest.TestCase):
def setUp(self):
data = np.random.rand(100, 10)
timestamps = [0.0]
for _ in range(data.shape[0]):
timestamps.append(timestamps[-1] + 0.75 + 0.25 * np.random.rand())
self.ts_rate = TimeSeries(
name="test_timeseries_rate",
data=data,
unit="m",
starting_time=0.0,
rate=1.0,
)
self.ts_timestamps = TimeSeries(
name="test_timeseries_timestamps",
data=data,
unit="m",
timestamps=np.array(timestamps),
)
self.time_intervals = TimeIntervals(name="Test Time Interval")
n_intervals = 10
for start_time in np.linspace(0, 75, n_intervals + 1):
if start_time < 75:
stt = start_time + np.random.rand()
spt = stt + 7 - np.random.rand()
self.time_intervals.add_interval(start_time=stt, stop_time=spt)
self.time_intervals.add_column(
name="temp", description="desc", data=np.random.randint(2, size=n_intervals)
)
self.time_intervals.add_column(
name="temp2",
description="desc",
data=np.random.randint(10, size=n_intervals),
)
def test_align_by_timestamps(self):
amt = AlignMultiTraceTimeSeriesByTrialsVariable(
time_series=self.ts_timestamps, trials=self.time_intervals
)
gas = amt.controls['gas']
gas.group_dd.value = list(gas.categorical_columns.keys())[0]
gas.group_sm.value = (gas.group_sm.options[0],)
fig = amt.children[-1]
assert len(fig.data)==len(gas.group_sm.value)
def test_align_by_rate(self):
amt = AlignMultiTraceTimeSeriesByTrialsConstant(
time_series=self.ts_rate, trials=self.time_intervals
)
gas = amt.controls['gas']
gas.group_dd.value = list(gas.categorical_columns)[0]
gas.group_sm.value = (gas.group_sm.options[0],)
fig = amt.children[-1]
assert len(fig.data) == len(gas.group_sm.value)
def setUp(self):
super().setUp()
# add intervals to nwbfile
ti1 = TimeIntervals(name='intervals',
description='experimental intervals')
ti1.add_interval(start_time=0.0, stop_time=2.0)
ti1.add_interval(start_time=2.0, stop_time=4.0)
ti1.add_interval(start_time=4.0, stop_time=6.0)
ti1.add_interval(start_time=6.0, stop_time=8.0)
ti1.add_column(name='var1',
data=['a', 'b', 'a', 'b'],
description='no description')
self.nwbfile.add_time_intervals(ti1)
self.widget = ExtendedTimeIntervalSelector(
input_data=self.nwbfile.units)
class SpatialSeriesTrialsAlign(unittest.TestCase):
def setUp(self) -> None:
data = np.random.rand(100, 3)
timestamps = [0.0]
for _ in range(data.shape[0]):
timestamps.append(timestamps[-1] + 0.75 + 0.25 * np.random.rand())
self.spatial_series_rate = SpatialSeries(
name="position_rate",
data=data,
starting_time=0.0,
rate=1.0,
reference_frame="starting gate",
)
self.spatial_series_ts = SpatialSeries(
name="position_ts",
data=data,
timestamps=np.array(timestamps),
reference_frame="starting gate",
)
self.time_intervals = TimeIntervals(name="Test Time Interval")
n_intervals = 10
for start_time in np.linspace(0, 75, n_intervals + 1):
if start_time < 75:
stt = start_time + np.random.rand()
spt = stt + 7 - np.random.rand()
self.time_intervals.add_interval(start_time=stt, stop_time=spt)
self.time_intervals.add_column(name="temp",
description="desc",
data=np.random.randint(
2, size=n_intervals))
self.time_intervals.add_column(
name="temp2",
description="desc",
data=np.random.randint(10, size=n_intervals),
)
def test_spatial_series_trials_align_rate(self):
trial_align_spatial_series(self.spatial_series_rate,
self.time_intervals)
def test_spatial_series_trials_align_ts(self):
trial_align_spatial_series(self.spatial_series_ts, self.time_intervals)
####################
# Other time intervals
# ~~~~~~~~~~~~~~~~~~~~~~
# Both ``epochs`` and ``trials`` are of of data type :py:class:`~pynwb.epoch.TimeIntervals`, which is a type of
# ``DynamicTable`` for storing information about time intervals. ``"epochs"`` and ``"trials"``
# are the two default names for :py:class:`~pynwb.base.TimeIntervals` objects, but you can also add your own
from pynwb.epoch import TimeIntervals
sleep_stages = TimeIntervals(
name="sleep_stages",
description="intervals for each sleep stage as determined by EEG",
)
sleep_stages.add_column(name="stage", description="stage of sleep")
sleep_stages.add_column(name="confidence",
description="confidence in stage (0-1)")
sleep_stages.add_row(start_time=0.3, stop_time=0.5, stage=1, confidence=.5)
sleep_stages.add_row(start_time=0.7, stop_time=0.9, stage=2, confidence=.99)
sleep_stages.add_row(start_time=1.3, stop_time=3.0, stage=3, confidence=0.7)
nwbfile.add_time_intervals(sleep_stages)
####################
# .. _basic_units:
#
# Units
# ------
#
