def compare_wheel_fpga_behaviour(session_path, display=DISPLAY):
alf_path = session_path.joinpath('alf')
shutil.rmtree(alf_path, ignore_errors=True)
sync, chmap = ephys_fpga.get_main_probe_sync(session_path,
bin_exists=False)
fpga_t, fpga_pos = ephys_fpga.extract_wheel_sync(sync, chmap=chmap)
bpod_t, bpod_pos = training_wheel.get_wheel_position(session_path,
display=display)
data, _ = ephys_fpga.extract_all(session_path)
bpod2fpga = scipy.interpolate.interp1d(data['intervals_bpod'][:, 0],
data['intervals'][:, 0],
fill_value="extrapolate")
# resample both traces to the same rate and compute correlation coeff
bpod_t = bpod2fpga(bpod_t)
tmin = max([np.min(fpga_t), np.min(bpod_t)])
tmax = min([np.max(fpga_t), np.max(bpod_t)])
wheel = {'tscale': np.arange(tmin, tmax, 0.01)}
wheel['fpga'] = scipy.interpolate.interp1d(fpga_t,
fpga_pos)(wheel['tscale'])
wheel['bpod'] = scipy.interpolate.interp1d(bpod_t,
bpod_pos)(wheel['tscale'])
if display:
plt.figure()
plt.plot(fpga_t - bpod2fpga(0), fpga_pos, '*')
plt.plot(bpod_t - bpod2fpga(0), bpod_pos, '.')
raw_wheel = {
'fpga_t': fpga_t,
'fpga_pos': fpga_pos,
'bpod_t': bpod_t,
'bpod_pos': bpod_pos
}
return raw_wheel, wheel
def _qc_from_path(sess_path, display=True):
WHEEL = False
sess_path = Path(sess_path)
temp_alf_folder = sess_path.joinpath('fpga_test', 'alf')
temp_alf_folder.mkdir(parents=True, exist_ok=True)
raw_trials = raw_data_loaders.load_data(sess_path)
tmax = raw_trials[-1]['behavior_data']['States timestamps']['exit_state'][
0][-1] + 60
sync, chmap = ephys_fpga._get_main_probe_sync(sess_path, bin_exists=False)
_ = ephys_fpga.extract_all(sess_path,
output_path=temp_alf_folder,
save=True)
# check that the output is complete
fpga_trials = ephys_fpga.extract_behaviour_sync(
sync,
output_path=temp_alf_folder,
tmax=tmax,
chmap=chmap,
save=True,
display=display)
# align with the bpod
bpod2fpga = ephys_fpga.align_with_bpod(temp_alf_folder.parent)
alf_trials = alf.io.load_object(temp_alf_folder, 'trials')
shutil.rmtree(temp_alf_folder)
# do the QC
qcs, qct = qc_fpga_task(fpga_trials, alf_trials)
# do the wheel part
if WHEEL:
bpod_wheel = training_wheel.get_wheel_data(sess_path, save=False)
fpga_wheel = ephys_fpga.extract_wheel_sync(sync,
chmap=chmap,
save=False)
if display:
import matplotlib.pyplot as plt
t0 = max(np.min(bpod2fpga(bpod_wheel['re_ts'])),
np.min(fpga_wheel['re_ts']))
dy = np.interp(
t0, fpga_wheel['re_ts'], fpga_wheel['re_pos']) - np.interp(
t0, bpod2fpga(bpod_wheel['re_ts']), bpod_wheel['re_pos'])
fix, axes = plt.subplots(nrows=2, sharex='all', sharey='all')
# axes[0].plot(t, pos), axes[0].title.set_text('Extracted')
axes[0].plot(bpod2fpga(bpod_wheel['re_ts']),
bpod_wheel['re_pos'] + dy)
axes[0].plot(fpga_wheel['re_ts'], fpga_wheel['re_pos'])
axes[0].title.set_text('FPGA')
axes[1].plot(bpod2fpga(bpod_wheel['re_ts']),
bpod_wheel['re_pos'] + dy)
axes[1].title.set_text('Bpod')
return alf.io.dataframe({**fpga_trials, **alf_trials, **qct})
def validate_ttl_test(ses_path, display=False):
"""
For a mock session on the Ephys Choice world task, check the sync channels for all
device properly connected and perform a synchronization if dual probes to check that
all channels are recorded properly
:param ses_path: session path
:param display: show the probe synchronization plot if several probes
:return: True if tests pass, errors otherwise
"""
def _single_test(assertion, str_ok, str_ko):
if assertion:
_logger.info(str_ok)
return True
else:
_logger.error(str_ko)
return False
EXPECTED_RATES_HZ = {'left_camera': 60, 'right_camera': 150, 'body_camera': 30}
SYNC_RATE_HZ = 1
MIN_TRIALS_NB = 6
ok = True
ses_path = Path(ses_path)
if not ses_path.exists():
return False
rawsync, sync_map = fpga._get_main_probe_sync(ses_path)
last_time = rawsync['times'][-1]
# get upgoing fronts for each
sync = Bunch({})
for k in sync_map:
fronts = fpga._get_sync_fronts(rawsync, sync_map[k])
sync[k] = fronts['times'][fronts['polarities'] == 1]
wheel = fpga.extract_wheel_sync(rawsync, chmap=sync_map, save=False)
frame_rates = {'right_camera': np.round(1 / np.median(np.diff(sync.right_camera))),
'left_camera': np.round(1 / np.median(np.diff(sync.left_camera))),
'body_camera': np.round(1 / np.median(np.diff(sync.body_camera)))}
# check the camera frame rates
for lab in frame_rates:
expect = EXPECTED_RATES_HZ[lab]
ok &= _single_test(assertion=abs((1 - frame_rates[lab] / expect)) < 0.1,
str_ok=f'PASS: {lab} frame rate: {frame_rates[lab]} = {expect} Hz',
str_ko=f'FAILED: {lab} frame rate: {frame_rates[lab]} != {expect} Hz')
# check that the wheel has a minimum rate of activity on both channels
re_test = abs(1 - sync.rotary_encoder_1.size / sync.rotary_encoder_0.size) < 0.1
re_test &= len(wheel['re_pos']) / last_time > 5
ok &= _single_test(assertion=re_test,
str_ok="PASS: Rotary encoder", str_ko="FAILED: Rotary encoder")
# check that the frame 2 ttls has a minimum rate of activity
ok &= _single_test(assertion=len(sync.frame2ttl) / last_time > 0.2,
str_ok="PASS: Frame2TTL", str_ko="FAILED: Frame2TTL")
# the audio has to have at least one event per trial
ok &= _single_test(assertion=len(sync.bpod) > len(sync.audio) > MIN_TRIALS_NB,
str_ok="PASS: audio", str_ko="FAILED: audio")
# the bpod has to have at least twice the amount of min trial pulses
ok &= _single_test(assertion=len(sync.bpod) > MIN_TRIALS_NB * 2,
str_ok="PASS: Bpod", str_ko="FAILED: Bpod")
try:
# note: tried to depend as little as possible on the extraction code but for the valve...
behaviour = fpga.extract_behaviour_sync(rawsync, save=False, chmap=sync_map)
res = behaviour.valve_open.size > 1
except AssertionError:
res = False
# check that the reward valve is actionned at least once
ok &= _single_test(assertion=res,
str_ok="PASS: Valve open", str_ko="FAILED: Valve open not detected")
_logger.info('ALL CHECKS PASSED !')
# the imec sync is for 3B Probes only
if sync.get('imec_sync') is not None:
ok &= _single_test(assertion=np.all(1 - SYNC_RATE_HZ * np.diff(sync.imec_sync) < 0.1),
str_ok="PASS: imec sync", str_ko="FAILED: imec sync")
# second step is to test that we can make the sync. Assertions are whithin the synch code
if sync.get('imec_sync') is not None:
sync_result = sync_probes.version3B(ses_path, display=display)
else:
sync_result = sync_probes.version3A(ses_path, display=display)
ok &= _single_test(assertion=sync_result, str_ok="PASS: synchronisation",
str_ko="FAILED: probe synchronizations threshold exceeded")
if not ok:
raise ValueError('FAILED TTL test')
return ok
def load_data(self,
download_data: bool = None,
extract_times: bool = False,
load_video: bool = True) -> None:
"""Extract the data from raw data files
Extracts all the required task data from the raw data files.
Data keys:
- count (int array): the sequential frame number (n, n+1, n+2...)
- pin_state (): the camera GPIO pin; records the audio TTLs; should be one per frame
- audio (float array): timestamps of audio TTL fronts
- fpga_times (float array): timestamps of camera TTLs recorded by FPGA
- timestamps (float array): extracted video timestamps (the camera.times ALF)
- bonsai_times (datetime array): system timestamps of video PC; should be one per frame
- camera_times (float array): camera frame timestamps extracted from frame headers
- wheel (Bunch): rotary encoder timestamps, position and period used for wheel motion
- video (Bunch): video meta data, including dimensions and FPS
- frame_samples (h x w x n array): array of evenly sampled frames (1 colour channel)
:param download_data: if True, any missing raw data is downloaded via ONE.
Missing data will raise an AssertionError
:param extract_times: if True, the camera.times are re-extracted from the raw data
:param load_video: if True, calls the load_video_data method
"""
assert self.session_path, 'no session path set'
if download_data is not None:
self.download_data = download_data
if self.download_data and self.eid and self.one and not self.one.offline:
self.ensure_required_data()
_log.info('Gathering data for QC')
# Get frame count and pin state
self.data['count'], self.data['pin_state'] = \
raw.load_embedded_frame_data(self.session_path, self.label, raw=True)
# Load the audio and raw FPGA times
if self.type == 'ephys':
sync, chmap = ephys_fpga.get_main_probe_sync(self.session_path)
audio_ttls = ephys_fpga.get_sync_fronts(sync, chmap['audio'])
self.data['audio'] = audio_ttls['times'] # Get rises
# Load raw FPGA times
cam_ts = extract_camera_sync(sync, chmap)
self.data['fpga_times'] = cam_ts[self.label]
else:
bpod_data = raw.load_data(self.session_path)
_, audio_ttls = raw.load_bpod_fronts(self.session_path, bpod_data)
self.data['audio'] = audio_ttls['times']
# Load extracted frame times
alf_path = self.session_path / 'alf'
try:
assert not extract_times
self.data['timestamps'] = alfio.load_object(
alf_path, f'{self.label}Camera', short_keys=True)['times']
except AssertionError: # Re-extract
kwargs = dict(video_path=self.video_path, labels=self.label)
if self.type == 'ephys':
kwargs = {**kwargs, 'sync': sync, 'chmap': chmap} # noqa
outputs, _ = extract_all(self.session_path,
self.type,
save=False,
**kwargs)
self.data['timestamps'] = outputs[
f'{self.label}_camera_timestamps']
except ALFObjectNotFound:
_log.warning('no camera.times ALF found for session')
# Get audio and wheel data
wheel_keys = ('timestamps', 'position')
try:
self.data['wheel'] = alfio.load_object(alf_path,
'wheel',
short_keys=True)
except ALFObjectNotFound:
# Extract from raw data
if self.type == 'ephys':
wheel_data = ephys_fpga.extract_wheel_sync(sync, chmap)
else:
wheel_data = training_wheel.get_wheel_position(
self.session_path)
self.data['wheel'] = Bunch(zip(wheel_keys, wheel_data))
# Find short period of wheel motion for motion correlation.
if data_for_keys(
wheel_keys,
self.data['wheel']) and self.data['timestamps'] is not None:
self.data['wheel'].period = self.get_active_wheel_period(
self.data['wheel'])
# Load Bonsai frame timestamps
try:
ssv_times = raw.load_camera_ssv_times(self.session_path,
self.label)
self.data['bonsai_times'], self.data['camera_times'] = ssv_times
except AssertionError:
_log.warning('No Bonsai video timestamps file found')
# Gather information from video file
if load_video:
_log.info('Inspecting video file...')
self.load_video_data()