def align_with_bpod(session_path):
"""
Reads in trials.intervals ALF dataset from bpod and fpga.
Asserts consistency between datasets and compute the median time difference
:param session_path:
:return: dt: median time difference of trial start times (fpga - bpod)
"""
ITI_DURATION = 0.5
# check consistency
output_path = Path(session_path) / 'alf'
trials = alf.io.load_object(output_path, '_ibl_trials')
if alf.io.check_dimensions(trials) != 0:
# patching things up if the bpod and FPGA don't have the same recording span
_logger.warning(
"BPOD/FPGA synchronization: Bpod and FPGA don't have the same amount of"
" trial start events. Patching alf files.")
_, _, ibpod, ifpga = raw.sync_trials_robust(
trials['intervals_bpod'][:, 0],
trials['intervals'][:, 0],
return_index=True)
if ibpod.size == 0:
raise err.SyncBpodFpgaException(
'Can not sync BPOD and FPGA - no matching sync pulses '
'found.')
for k in trials:
if 'bpod' in k:
trials[k] = trials[k][ibpod]
else:
trials[k] = trials[k][ibpod]
alf.io.save_object_npy(output_path, trials, '_ibl_trials')
assert (alf.io.check_dimensions(trials) == 0)
tlen = (np.diff(trials['intervals_bpod']) -
np.diff(trials['intervals']))[:-1] - ITI_DURATION
assert (np.all(np.abs(tlen[np.invert(np.isnan(tlen))])[:-1] < 5 * 1e-3))
# dt is the delta to apply to bpod times in order to be on the ephys clock
dt = trials['intervals'][:, 0] - trials['intervals_bpod'][:, 0]
# compute the clock drift bpod versus dt
ppm = np.polyfit(trials['intervals'][:, 0], dt, 1)[0] * 1e6
if ppm > BPOD_FPGA_DRIFT_THRESHOLD_PPM:
_logger.warning(
'BPOD/FPGA synchronization shows values greater than 150 ppm')
# plt.plot(trials['intervals'][:, 0], dt, '*')
# so far 2 datasets concerned: goCueTrigger_times_bpod and response_times_bpod
for k in trials:
if not k.endswith('_times_bpod'):
continue
np.save(output_path.joinpath(f'_ibl_trials.{k[:-5]}.npy'),
trials[k] + dt)
return interpolate.interp1d(trials['intervals_bpod'][:, 0],
trials['intervals'][:, 0],
fill_value="extrapolate")
def bpod_fpga_sync(bpod_intervals=None,
ephys_intervals=None,
iti_duration=None):
"""
Computes synchronization function from bpod to fpga
:param bpod_intervals
:param ephys_intervals
:return: interpolation function
"""
if iti_duration is None:
iti_duration = 0.5
# check consistency
if bpod_intervals.size != ephys_intervals.size:
# patching things up if the bpod and FPGA don't have the same recording span
_logger.warning(
"BPOD/FPGA synchronization: Bpod and FPGA don't have the same amount of"
" trial start events. Patching alf files.")
_, _, ibpod, ifpga = raw_data_loaders.sync_trials_robust(
bpod_intervals[:, 0], ephys_intervals[:, 0], return_index=True)
if ibpod.size == 0:
raise err.SyncBpodFpgaException(
'Can not sync BPOD and FPGA - no matching sync pulses '
'found.')
bpod_intervals = bpod_intervals[ibpod, :]
ephys_intervals = ephys_intervals[ifpga, :]
else:
ibpod, ifpga = [
np.arange(bpod_intervals.shape[0]) for _ in np.arange(2)
]
tlen = (np.diff(bpod_intervals) -
np.diff(ephys_intervals))[:-1] - iti_duration
assert np.all(np.abs(tlen[np.invert(np.isnan(tlen))])[:-1] < 5 * 1e-3)
# dt is the delta to apply to bpod times in order to be on the ephys clock
dt = bpod_intervals[:, 0] - ephys_intervals[:, 0]
# compute the clock drift bpod versus dt
ppm = np.polyfit(bpod_intervals[:, 0], dt, 1)[0] * 1e6
if ppm > BPOD_FPGA_DRIFT_THRESHOLD_PPM:
_logger.warning(
'BPOD/FPGA synchronization shows values greater than %i ppm',
BPOD_FPGA_DRIFT_THRESHOLD_PPM)
# plt.plot(trials['intervals'][:, 0], dt, '*')
# so far 2 datasets concerned: goCueTrigger_times_bpod and response_times_bpod
fcn_bpod2fpga = interpolate.interp1d(bpod_intervals[:, 0],
ephys_intervals[:, 0],
fill_value="extrapolate")
return ibpod, ifpga, fcn_bpod2fpga
def extract_behaviour_sync(sync,
chmap=None,
display=False,
bpod_trials=None,
tmax=np.inf):
"""
Extract wheel positions and times from sync fronts dictionary
:param sync: dictionary 'times', 'polarities' of fronts detected on sync trace for all 16 chans
:param chmap: dictionary containing channel index. Default to constant.
chmap = {'bpod': 7, 'frame2ttl': 12, 'audio': 15}
:param display: bool or matplotlib axes: show the full session sync pulses display
defaults to False
:return: trials dictionary
"""
bpod = _get_sync_fronts(sync, chmap['bpod'], tmax=tmax)
if bpod.times.size == 0:
raise err.SyncBpodFpgaException(
'No Bpod event found in FPGA. No behaviour extraction. '
'Check channel maps.')
frame2ttl = _get_sync_fronts(sync, chmap['frame2ttl'], tmax=tmax)
frame2ttl = _clean_frame2ttl(frame2ttl)
audio = _get_sync_fronts(sync, chmap['audio'], tmax=tmax)
# extract events from the fronts for each trace
t_trial_start, t_valve_open, t_iti_in = _assign_events_bpod(
bpod['times'], bpod['polarities'])
# one issue is that sometimes bpod pulses may not have been detected, in this case
# perform the sync bpod/FPGA, and add the start that have not been detected
if bpod_trials:
bpod_start = bpod_trials['intervals_bpod'][:, 0]
fcn, drift, ibpod, ifpga = dsp.utils.sync_timestamps(
bpod_start, t_trial_start, return_indices=True)
# if it's drifting too much
if drift > 200 and bpod_start.size != t_trial_start.size:
raise err.SyncBpodFpgaException("sync cluster f*ck")
missing_bpod = fcn(bpod_start[np.setxor1d(ibpod,
np.arange(len(bpod_start)))])
t_trial_start = np.sort(np.r_[t_trial_start, missing_bpod])
else:
_logger.warning(
"Deprecation Warning: calling FPGA trials extraction without a bpod trials"
" dictionary will result in an error.")
t_ready_tone_in, t_error_tone_in = _assign_events_audio(
audio['times'], audio['polarities'])
trials = Bunch({
'goCue_times':
_assign_events_to_trial(t_trial_start, t_ready_tone_in, take='first'),
'errorCue_times':
_assign_events_to_trial(t_trial_start, t_error_tone_in),
'valveOpen_times':
_assign_events_to_trial(t_trial_start, t_valve_open),
'stimFreeze_times':
_assign_events_to_trial(t_trial_start, frame2ttl['times'], take=-2),
'stimOn_times':
_assign_events_to_trial(t_trial_start,
frame2ttl['times'],
take='first'),
'stimOff_times':
_assign_events_to_trial(t_trial_start, frame2ttl['times']),
'itiIn_times':
_assign_events_to_trial(t_trial_start, t_iti_in)
})
# feedback times are valve open on good trials and error tone in on error trials
trials['feedback_times'] = np.copy(trials['valveOpen_times'])
ind_err = np.isnan(trials['valveOpen_times'])
trials['feedback_times'][ind_err] = trials['errorCue_times'][ind_err]
trials['intervals'] = np.c_[t_trial_start, trials['itiIn_times']]
if display:
width = 0.5
ymax = 5
if isinstance(display, bool):
plt.figure("Ephys FPGA Sync")
ax = plt.gca()
else:
ax = display
r0 = _get_sync_fronts(sync, chmap['rotary_encoder_0'])
plots.squares(bpod['times'],
bpod['polarities'] * 0.4 + 1,
ax=ax,
color='k')
plots.squares(frame2ttl['times'],
frame2ttl['polarities'] * 0.4 + 2,
ax=ax,
color='k')
plots.squares(audio['times'],
audio['polarities'] * 0.4 + 3,
ax=ax,
color='k')
plots.squares(r0['times'],
r0['polarities'] * 0.4 + 4,
ax=ax,
color='k')
plots.vertical_lines(t_ready_tone_in,
ymin=0,
ymax=ymax,
ax=ax,
label='goCue_times',
color='b',
linewidth=width)
plots.vertical_lines(t_trial_start,
ymin=0,
ymax=ymax,
ax=ax,
label='start_trial',
color='m',
linewidth=width)
plots.vertical_lines(t_error_tone_in,
ymin=0,
ymax=ymax,
ax=ax,
label='error tone',
color='r',
linewidth=width)
plots.vertical_lines(t_valve_open,
ymin=0,
ymax=ymax,
ax=ax,
label='valveOpen_times',
color='g',
linewidth=width)
plots.vertical_lines(trials['stimFreeze_times'],
ymin=0,
ymax=ymax,
ax=ax,
label='stimFreeze_times',
color='y',
linewidth=width)
plots.vertical_lines(trials['stimOff_times'],
ymin=0,
ymax=ymax,
ax=ax,
label='stim off',
color='c',
linewidth=width)
plots.vertical_lines(trials['stimOn_times'],
ymin=0,
ymax=ymax,
ax=ax,
label='stimOn_times',
color='tab:orange',
linewidth=width)
c = _get_sync_fronts(sync, chmap['left_camera'])
plots.squares(c['times'], c['polarities'] * 0.4 + 5, ax=ax, color='k')
c = _get_sync_fronts(sync, chmap['right_camera'])
plots.squares(c['times'], c['polarities'] * 0.4 + 6, ax=ax, color='k')
c = _get_sync_fronts(sync, chmap['body_camera'])
plots.squares(c['times'], c['polarities'] * 0.4 + 7, ax=ax, color='k')
ax.legend()
ax.set_yticklabels(['', 'bpod', 'f2ttl', 'audio', 're_0', ''])
ax.set_yticks([0, 1, 2, 3, 4, 5])
ax.set_ylim([0, 5])
return trials
def extract_behaviour_sync(sync,
output_path=None,
save=False,
chmap=None,
display=False,
tmax=np.inf):
"""
Extract wheel positions and times from sync fronts dictionary
:param sync: dictionary 'times', 'polarities' of fronts detected on sync trace for all 16 chans
:param output_path: where to save the data
:param save: True/False
:param chmap: dictionary containing channel index. Default to constant.
chmap = {'bpod': 7, 'frame2ttl': 12, 'audio': 15}
:param display: bool or matplotlib axes: show the full session sync pulses display
defaults to False
:return: trials dictionary
"""
bpod = _get_sync_fronts(sync, chmap['bpod'], tmax=tmax)
if bpod.times.size == 0:
raise err.SyncBpodFpgaException(
'No Bpod event found in FPGA. No behaviour extraction. '
'Check channel maps.')
frame2ttl = _get_sync_fronts(sync, chmap['frame2ttl'], tmax=tmax)
audio = _get_sync_fronts(sync, chmap['audio'], tmax=tmax)
# extract events from the fronts for each trace
t_trial_start, t_valve_open, t_iti_in = _bpod_events_extraction(
bpod['times'], bpod['polarities'])
t_ready_tone_in, t_error_tone_in = _audio_events_extraction(
audio['times'], audio['polarities'])
# stim off time is the first frame2ttl rise/fall after the trial start
# does not apply for 1st trial
ind = np.searchsorted(frame2ttl['times'], t_iti_in, side='left')
t_stim_off = frame2ttl['times'][np.minimum(ind, frame2ttl.times.size - 1)]
t_stim_freeze = frame2ttl['times'][np.maximum(ind - 1, 0)]
# stimOn_times: first fram2ttl change after trial start
trials = Bunch({
'ready_tone_in':
_assign_events_to_trial(t_trial_start, t_ready_tone_in, take='first'),
'error_tone_in':
_assign_events_to_trial(t_trial_start, t_error_tone_in),
'valve_open':
_assign_events_to_trial(t_trial_start, t_valve_open),
'stim_freeze':
_assign_events_to_trial(t_trial_start, t_stim_freeze),
'stimOn_times':
_assign_events_to_trial(t_trial_start,
frame2ttl['times'],
take='first'),
'stimOff_times':
_assign_events_to_trial(t_trial_start, t_stim_off),
'iti_in':
_assign_events_to_trial(t_trial_start, t_iti_in)
})
# goCue_times corresponds to the tone_in event
trials['goCue_times'] = np.copy(trials['ready_tone_in'])
# feedback times are valve open on good trials and error tone in on error trials
trials['feedback_times'] = np.copy(trials['valve_open'])
ind_err = np.isnan(trials['valve_open'])
trials['feedback_times'][ind_err] = trials['error_tone_in'][ind_err]
trials['intervals'] = np.c_[t_trial_start, trials['iti_in']]
if display:
width = 0.5
ymax = 5
if isinstance(display, bool):
plt.figure("Ephys FPGA Sync")
ax = plt.gca()
else:
ax = display
r0 = _get_sync_fronts(sync, chmap['rotary_encoder_0'])
plots.squares(bpod['times'],
bpod['polarities'] * 0.4 + 1,
ax=ax,
color='k')
plots.squares(frame2ttl['times'],
frame2ttl['polarities'] * 0.4 + 2,
ax=ax,
color='k')
plots.squares(audio['times'],
audio['polarities'] * 0.4 + 3,
ax=ax,
color='k')
plots.squares(r0['times'],
r0['polarities'] * 0.4 + 4,
ax=ax,
color='k')
plots.vertical_lines(t_ready_tone_in,
ymin=0,
ymax=ymax,
ax=ax,
label='ready tone in',
color='b',
linewidth=width)
plots.vertical_lines(t_trial_start,
ymin=0,
ymax=ymax,
ax=ax,
label='start_trial',
color='m',
linewidth=width)
plots.vertical_lines(t_error_tone_in,
ymin=0,
ymax=ymax,
ax=ax,
label='error tone',
color='r',
linewidth=width)
plots.vertical_lines(t_valve_open,
ymin=0,
ymax=ymax,
ax=ax,
label='valve open',
color='g',
linewidth=width)
plots.vertical_lines(t_stim_freeze,
ymin=0,
ymax=ymax,
ax=ax,
label='stim freeze',
color='y',
linewidth=width)
plots.vertical_lines(t_stim_off,
ymin=0,
ymax=ymax,
ax=ax,
label='stim off',
color='c',
linewidth=width)
plots.vertical_lines(trials['stimOn_times'],
ymin=0,
ymax=ymax,
ax=ax,
label='stim on',
color='tab:orange',
linewidth=width)
ax.legend()
ax.set_yticklabels(['', 'bpod', 'f2ttl', 'audio', 're_0', ''])
ax.set_ylim([0, 5])
if save and output_path:
output_path = Path(output_path)
np.save(output_path / '_ibl_trials.goCue_times.npy',
trials['goCue_times'])
np.save(output_path / '_ibl_trials.stimOn_times.npy',
trials['stimOn_times'])
np.save(output_path / '_ibl_trials.intervals.npy', trials['intervals'])
np.save(output_path / '_ibl_trials.feedback_times.npy',
trials['feedback_times'])
return trials
def extract_behaviour_sync(sync, chmap=None, display=False, tmax=np.inf):
"""
Extract wheel positions and times from sync fronts dictionary
:param sync: dictionary 'times', 'polarities' of fronts detected on sync trace for all 16 chans
:param chmap: dictionary containing channel index. Default to constant.
chmap = {'bpod': 7, 'frame2ttl': 12, 'audio': 15}
:param display: bool or matplotlib axes: show the full session sync pulses display
defaults to False
:return: trials dictionary
"""
bpod = _get_sync_fronts(sync, chmap['bpod'], tmax=tmax)
if bpod.times.size == 0:
raise err.SyncBpodFpgaException(
'No Bpod event found in FPGA. No behaviour extraction. '
'Check channel maps.')
frame2ttl = _get_sync_fronts(sync, chmap['frame2ttl'], tmax=tmax)
audio = _get_sync_fronts(sync, chmap['audio'], tmax=tmax)
# extract events from the fronts for each trace
t_trial_start, t_valve_open, t_iti_in = _assign_events_bpod(
bpod['times'], bpod['polarities'])
t_ready_tone_in, t_error_tone_in = _assign_events_audio(
audio['times'], audio['polarities'])
trials = Bunch({
'goCue_times':
_assign_events_to_trial(t_trial_start, t_ready_tone_in, take='first'),
'errorCue_times':
_assign_events_to_trial(t_trial_start, t_error_tone_in),
'valveOpen_times':
_assign_events_to_trial(t_trial_start, t_valve_open),
'stimFreeze_times':
_assign_events_to_trial(t_trial_start, frame2ttl['times'], take=-2),
'stimOn_times':
_assign_events_to_trial(t_trial_start,
frame2ttl['times'],
take='first'),
'stimOff_times':
_assign_events_to_trial(t_trial_start, frame2ttl['times']),
'itiIn_times':
_assign_events_to_trial(t_trial_start, t_iti_in)
})
# feedback times are valve open on good trials and error tone in on error trials
trials['feedback_times'] = np.copy(trials['valveOpen_times'])
ind_err = np.isnan(trials['valveOpen_times'])
trials['feedback_times'][ind_err] = trials['errorCue_times'][ind_err]
trials['intervals'] = np.c_[t_trial_start, trials['itiIn_times']]
if display:
width = 0.5
ymax = 5
if isinstance(display, bool):
plt.figure("Ephys FPGA Sync")
ax = plt.gca()
else:
ax = display
r0 = _get_sync_fronts(sync, chmap['rotary_encoder_0'])
plots.squares(bpod['times'],
bpod['polarities'] * 0.4 + 1,
ax=ax,
color='k')
plots.squares(frame2ttl['times'],
frame2ttl['polarities'] * 0.4 + 2,
ax=ax,
color='k')
plots.squares(audio['times'],
audio['polarities'] * 0.4 + 3,
ax=ax,
color='k')
plots.squares(r0['times'],
r0['polarities'] * 0.4 + 4,
ax=ax,
color='k')
plots.vertical_lines(t_ready_tone_in,
ymin=0,
ymax=ymax,
ax=ax,
label='goCue_times',
color='b',
linewidth=width)
plots.vertical_lines(t_trial_start,
ymin=0,
ymax=ymax,
ax=ax,
label='start_trial',
color='m',
linewidth=width)
plots.vertical_lines(t_error_tone_in,
ymin=0,
ymax=ymax,
ax=ax,
label='error tone',
color='r',
linewidth=width)
plots.vertical_lines(t_valve_open,
ymin=0,
ymax=ymax,
ax=ax,
label='valveOpen_times',
color='g',
linewidth=width)
plots.vertical_lines(trials['stimFreeze_times'],
ymin=0,
ymax=ymax,
ax=ax,
label='stimFreeze_times',
color='y',
linewidth=width)
plots.vertical_lines(trials['stimOff_times'],
ymin=0,
ymax=ymax,
ax=ax,
label='stim off',
color='c',
linewidth=width)
plots.vertical_lines(trials['stimOn_times'],
ymin=0,
ymax=ymax,
ax=ax,
label='stimOn_times',
color='tab:orange',
linewidth=width)
c = _get_sync_fronts(sync, chmap['left_camera'])
plots.squares(c['times'], c['polarities'] * 0.4 + 5, ax=ax, color='k')
c = _get_sync_fronts(sync, chmap['right_camera'])
plots.squares(c['times'], c['polarities'] * 0.4 + 6, ax=ax, color='k')
c = _get_sync_fronts(sync, chmap['body_camera'])
plots.squares(c['times'], c['polarities'] * 0.4 + 7, ax=ax, color='k')
ax.legend()
ax.set_yticklabels(['', 'bpod', 'f2ttl', 'audio', 're_0', ''])
ax.set_yticks([0, 1, 2, 3, 4, 5])
ax.set_ylim([0, 5])
return trials