ibllib.io.extractors.fibrephotometry

Data extraction from fibrephotometry DAQ files.

Below is the expected folder structure for a fibrephotometry session:

subject/ ├─ 2021-06-30/ │ ├─ 001/ │ │ ├─ raw_photometry_data/ │ │ │ │ ├─ _neurophotometrics_fpData.raw.pqt │ │ │ │ ├─ _neurophotometrics_fpData.channels.csv │ │ │ │ ├─ _mcc_DAQdata.raw.tdms

fpData.raw.pqt is a copy of the ‘FPdata’ file, the output of the Neuophotometrics Bonsai workflow. fpData.channels.csv is table of frame flags for deciphering LED and GPIO states. The default table, copied from the Neurophotometrics manual can be found in iblscripts/deploy/fppc/ _mcc_DAQdata.raw.tdms is the DAQ tdms file, containing the pulses from bpod and from the neurophotometrics system

Module attributes

V_THRESHOLD

Neurophotometrics FP3002 specific information.

Functions

check_timestamps	Reads data file and checks that the number of timestamps check out with a tolerance of n_frames
read_daq_timestamps	From a tdms daq file, extracts the photometry frames and their tagging.
read_daq_voltage
sync_photometry_to_daq	param vdaq: dictionary of daq traces.

Classes

FibrePhotometry

V_THRESHOLD = 3

Neurophotometrics FP3002 specific information. The light source map refers to the available LEDs on the system. The flags refers to the byte encoding of led states in the system.

sync_photometry_to_daq(vdaq, fs, df_photometry, chmap={'bpod': 'AI1', 'photometry': 'AI0'}, v_threshold=3)

Parameters:

• vdaq – dictionary of daq traces.

• fs – sampling frequency

• df_photometry –

• chmap –

• v_threshold –

Returns:

read_daq_voltage(daq_file, chmap={'bpod': 'AI1', 'photometry': 'AI0'})

read_daq_timestamps(vdaq, v_threshold=3)

From a tdms daq file, extracts the photometry frames and their tagging.

Parameters:

vsaq – dictionary of the voltage traces from the DAQ. Each item has a key describing

the channel as per the channel map, and contains a single voltage trace. :param v_threshold: :return:

check_timestamps(daq_file, photometry_file, tolerance=20, chmap={'bpod': 'AI1', 'photometry': 'AI0'}, v_threshold=3)

Reads data file and checks that the number of timestamps check out with a tolerance of n_frames

Parameters:

• daq_file –

• photometry_file –

• tolerance – number of acceptable missing frames between the daq and the photometry file

• chmap –

• v_threshold –

Returns:

None

class FibrePhotometry(self.session_path, collection=self.collection)

Bases: BaseExtractor

save_names = 'photometry.signal.pqt'

The filenames of each extracted dataset, or None if array should not be saved.

Type:

tuple of str

var_names = 'df_out'

A list of names for the extracted variables. These become the returned output keys.

Type:

tuple of str

extract_timestamps(fp_data, **kwargs)

Extract the photometry.timestamps array.

This depends on the DAQ and task synchronization protocol.

Parameters:

fp_data (dict) – A Bunch of raw fibrephotometry data, with the keys (‘raw’, ‘channels’).

Returns:

An array of timestamps, one per frame.

Return type:

numpy.ndarray