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Changed how stimulus times are extracted from photodoides #7

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Changed how stimulus times are extracted from photodoides #7

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90a192e
Changed how stimulus times are extracted from photodoides
minseungchoi Sep 5, 2022
e661a07
threshold is no longer a tuple
minseungchoi Sep 5, 2022
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21 changes: 12 additions & 9 deletions brainsss/visual.py
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Original file line number Diff line number Diff line change
Expand Up @@ -189,7 +189,7 @@ def parse_visual_stimulation_metadata(file):
return metadata

def extract_stim_times_from_pd(photodiode_trace, time_vector):
threshold=0.8,
threshold=0.8
command_frame_rate=120
sample_rate = 10000
minimum_epoch_separation = 0.9 * (1 + 0) * sample_rate
Expand All @@ -199,17 +199,20 @@ def extract_stim_times_from_pd(photodiode_trace, time_vector):
photodiode_trace = photodiode_trace / np.max(photodiode_trace)

# find frame flip times
V_orig = photodiode_trace[0:-2]
V_shift = photodiode_trace[1:-1]
ups = np.where(np.logical_and(V_orig < threshold, V_shift >= threshold))[0] + 1
downs = np.where(np.logical_and(V_orig >= threshold, V_shift < threshold))[0] + 1
# V_orig = photodiode_trace[0:-2]
# V_shift = photodiode_trace[1:-1]
# ups = np.where(np.logical_and(V_orig < threshold, V_shift >= threshold))[0] + 1
# downs = np.where(np.logical_and(V_orig >= threshold, V_shift < threshold))[0] + 1
photodiode_diff = np.diff(photodiode_trace)
ups = np.where(photodiode_diff > threshold)[0] + 1
downs = np.where(photodiode_diff < -threshold)[0] + 1
frame_times = np.sort(np.append(ups, downs))

# Use frame flip times to find stimulus start times
stimulus_start_frames = np.append(0, np.where(np.diff(frame_times) > minimum_epoch_separation)[0] + 1)
stimulus_end_frames = np.append(np.where(np.diff(frame_times) > minimum_epoch_separation)[0], len(frame_times)-1)
stimulus_start_times = frame_times[stimulus_start_frames] / sample_rate # datapoints -> sec
stimulus_end_times = frame_times[stimulus_end_frames] / sample_rate # datapoints -> sec
stimulus_start_times = time_vector[frame_times[stimulus_start_frames]]
# stimulus_end_frames = np.append(np.where(np.diff(frame_times) > minimum_epoch_separation)[0], len(frame_times)-1)
# stimulus_end_times = frame_times[stimulus_end_frames] / sample_rate # datapoints -> sec

stim_durations = stimulus_end_times - stimulus_start_times # sec
# stim_durations = stimulus_end_times - stimulus_start_times # sec
return stimulus_start_times