def get_running_speed(self) -> RunningSpeed:
values = self.nwbfile.modules['running'].get_data_interface(
'speed').data[:]
timestamps = self.nwbfile.modules['running'].get_data_interface(
'speed').timestamps[:]
return RunningSpeed(
timestamps=timestamps,
values=values,
)
def add_running_data_df_to_nwbfile(nwbfile, running_data_df, unit_dict, index_key='timestamps'):
''' Adds running speed data to an NWBFile as timeseries in acquisition and processing
Parameters
----------
nwbfile : pynwb.NWBFile
File to which runnign speeds will be written
running_speed : pandas.DataFrame
Contains 'speed' and 'times', 'v_in', 'vsig', 'dx'
unit : str, optional
SI units of running speed values
Returns
-------
nwbfile : pynwb.NWBFile
'''
assert running_data_df.index.name == index_key
running_speed = RunningSpeed(timestamps=running_data_df.index.values,
values=running_data_df['speed'].values)
add_running_speed_to_nwbfile(nwbfile, running_speed, name='speed', unit=unit_dict['speed'])
running_mod = nwbfile.modules['running']
timestamps_ts = running_mod.get_data_interface('speed').timestamps
running_dx_series = TimeSeries(
name='dx',
data=running_data_df['dx'].values,
timestamps=timestamps_ts,
unit=unit_dict['dx']
)
v_sig = TimeSeries(
name='v_sig',
data=running_data_df['v_sig'].values,
timestamps=timestamps_ts,
unit=unit_dict['v_sig']
)
v_in = TimeSeries(
name='v_in',
data=running_data_df['v_in'].values,
timestamps=timestamps_ts,
unit=unit_dict['v_in']
)
running_mod.add_data_interface(running_dx_series)
nwbfile.add_acquisition(v_sig)
nwbfile.add_acquisition(v_in)
return nwbfile
def get_running_speed(self) -> RunningSpeed:
"""Get running speed using timestamps from
self.get_stimulus_timestamps.
NOTE: Do not correct for monitor delay.
:returns: RunningSpeed -- a NamedTuple containing the subject's
timestamps and running speeds (in cm/s)
"""
running_data_df = self.get_running_data_df()
if running_data_df.index.name != "timestamps":
raise DataFrameIndexError(
f"Expected index to be named 'timestamps' but got "
"'{running_data_df.index.name}'.")
return RunningSpeed(timestamps=running_data_df.index.values,
values=running_data_df.speed.values)
def get_running_speed(self, lowpass=True) -> RunningSpeed:
"""
Gets the running speed
Parameters
----------
lowpass: bool
Whether to return the running speed with lowpass filter applied or without
Returns
-------
RunningSpeed:
The running speed
"""
interface_name = 'speed' if lowpass else 'speed_unfiltered'
values = self.nwbfile.modules['running'].get_data_interface(
interface_name).data[:]
timestamps = self.nwbfile.modules['running'].get_data_interface(
interface_name).timestamps[:]
return RunningSpeed(
timestamps=timestamps,
values=values,
)
def test_get_running_speed(MockBehaviorDataLimsApi):
expected = RunningSpeed(timestamps=[0.0, 0.1, 0.2],
values=[8.0, 15.0, 16.0])
api = MockBehaviorDataLimsApi
actual = api.get_running_speed()
assert expected == actual
def get_running_speed(self):
running_data_df = self.get_running_data_df()
assert running_data_df.index.name == 'timestamps'
return RunningSpeed(timestamps=running_data_df.index.values,
values=running_data_df.speed.values)
def running_speed():
from allensdk.brain_observatory.running_speed import RunningSpeed
return RunningSpeed(timestamps=[1., 2., 3.], values=[4, 5, 6])