From c6254eac59611593ebc7460e0b0ce171d94930a8 Mon Sep 17 00:00:00 2001
From: Till Raab <till.raab@uni-tuebingen.de>
Date: Thu, 27 Apr 2023 15:40:44 +0200
Subject: [PATCH] LED_detect.py needs to be done for all recordings. next we
need to check if trial_analysis.py does everything we need.
---
LED_detect.py | 5 ++-
complete_analysis.py | 96 ++++++++++++++++++++++++++++++++++++++++----
2 files changed, 92 insertions(+), 9 deletions(-)
diff --git a/LED_detect.py b/LED_detect.py
index a8f34db..35f2510 100644
--- a/LED_detect.py
+++ b/LED_detect.py
@@ -63,6 +63,7 @@ def main(file_path, check, x, y):
LED_frames = np.arange(len(LED_val)-1)[(LED_val[:-1] < light_th) & (LED_val[1:] > light_th)]
np.save(os.path.join(folder, 'LED_frames.npy'), LED_frames)
+
fig, ax = plt.subplots()
ax.plot(np.arange(len(LED_val)), LED_val, color='k')
ax.plot(LED_frames, np.ones(len(LED_frames))*light_th, 'o', color='firebrick')
@@ -73,8 +74,8 @@ if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Detect frames of blinking LED in video recordings.')
parser.add_argument('file', type=str, help='video file to be analyzed')
parser.add_argument("-c", '--check', action="store_true", help="check if LED pos is correct")
- parser.add_argument('-x', type=int, nargs=2, default=[1240, 1250], help='x-borders of LED detect area (in pixels)')
- parser.add_argument('-y', type=int, nargs=2, default=[1504, 1526], help='y-borders of LED area (in pixels)')
+ parser.add_argument('-x', type=int, nargs=2, default=[675, 695], help='x-borders of LED detect area (in pixels)')
+ parser.add_argument('-y', type=int, nargs=2, default=[350, 360], help='y-borders of LED area (in pixels)')
args = parser.parse_args()
import glob
diff --git a/complete_analysis.py b/complete_analysis.py
index 3fca243..6de31bd 100644
--- a/complete_analysis.py
+++ b/complete_analysis.py
@@ -1,15 +1,78 @@
+import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import os
import sys
+import glob
from IPython import embed
+def load_frame_times(trial_path):
+ t_filepath = glob.glob(os.path.join(trial_path, '*.dat'))
+ if len(t_filepath) == 0:
+ return np.array([])
+ else:
+ t_filepath = t_filepath[0]
+ f = open(t_filepath, 'r')
+ frame_t = []
+ for line in f.readlines():
+ t = sum(x * float(t) for x, t in zip([3600, 60, 1], line.replace('\n', '').split(":")))
+ frame_t.append(t)
+ return np.array(frame_t)
+
+def load_and_converete_boris_events(trial_path, recording, sr, video_stated_FPS=25):
+ def converte_video_frames_to_grid_idx(event_frames, led_frames, led_idx):
+ event_idx_grid = (event_frames - led_frames[0]) / (led_frames[-1] - led_frames[0]) * (led_idx[-1] - led_idx[0]) + led_idx[0]
+ return event_idx_grid
+
+ # idx in grid-recording
+ led_idx = pd.read_csv(os.path.join(trial_path, 'led_idxs.csv'), header=None).iloc[:, 0].to_numpy()
+ # frames where LED gets switched on
+ led_frames = np.load(os.path.join(trial_path, 'LED_frames.npy'))
+
+ times, behavior, t_ag_on_off, t_contact = load_boris(trial_path, recording)
+
+ contact_frame = np.array(np.round(t_contact * video_stated_FPS), dtype=int)
+ ag_on_off_frame = np.array(np.round(t_ag_on_off * video_stated_FPS), dtype=int)
+
+ # led_t_GRID = led_idx / sr
+ contact_t_GRID = converte_video_frames_to_grid_idx(contact_frame, led_frames, led_idx) / sr
+ ag_on_off_t_GRID = converte_video_frames_to_grid_idx(ag_on_off_frame, led_frames, led_idx) / sr
+
+ return contact_t_GRID, ag_on_off_t_GRID, led_idx, led_frames
+
+def load_boris(trial_path, recording):
+ boris_file = '-'.join(recording.split('-')[:3]) + '.csv'
+
+ data = pd.read_csv(os.path.join(trial_path, boris_file))
+ times = data['Start (s)']
+ behavior = data['Behavior']
+
+ t_ag_on = times[behavior == 0]
+ t_ag_off = times[behavior == 1]
+
+ t_ag_on_off = []
+ for t in t_ag_on:
+ t1 = np.array(t_ag_off)[t_ag_off > t]
+ if len(t1) >= 1:
+ t_ag_on_off.append(np.array([t, t1[0]]))
+
+ t_contact = times[behavior == 2]
+
+ return times, behavior, np.array(t_ag_on_off), t_contact.to_numpy()
+
def main(data_folder=None):
+
+
trials_meta = pd.read_csv('order_meta.csv')
+ video_stated_FPS = 25. # cap.get(cv2.CAP_PROP_FPS)
+
+ sr = 20_000
for trial_idx in range(len(trials_meta)):
group = trials_meta['group'][trial_idx]
recording = trials_meta['recording'][trial_idx][1:-1]
+ rec_id1 = trials_meta['rec_id1'][trial_idx]
+ rec_id2 = trials_meta['rec_id2'][trial_idx]
if group < 3:
continue
@@ -21,18 +84,37 @@ def main(data_folder=None):
if not os.path.exists(os.path.join(trial_path, 'led_idxs.csv')):
continue
- print(group, recording)
+ if not os.path.exists(os.path.join(trial_path, 'LED_frames.npy')):
+ continue
+
+ contact_t_GRID, ag_on_off_t_GRID, led_idx, led_frames = \
+ load_and_converete_boris_events(trial_path, recording, sr)
+
+ fund_v = np.load(os.path.join(trial_path, 'fund_v.npy'))
+ ident_v = np.load(os.path.join(trial_path, 'ident_v.npy'))
+ idx_v = np.load(os.path.join(trial_path, 'idx_v.npy'))
+ times = np.load(os.path.join(trial_path, 'times.npy'))
+
+ if len(uid:=np.unique(ident_v[~np.isnan(ident_v)])) >2:
+ print(f'to many ids: {len(uid)}')
+ print(f'ids in recording: {uid[0]:.0f} {uid[1]:.0f}')
+ print(f'ids in meta: {rec_id1:.0f} {rec_id2:.0f}')
+
+ fig, ax = plt.subplots(figsize=(30/2.54, 18/2.54))
+ for id in uid:
+ ax.plot(times[idx_v[ident_v == id]] / 3600, fund_v[ident_v == id], marker='.')
+
+ ax.plot(contact_t_GRID / 3600, np.ones_like(contact_t_GRID) * 1050, '|', markersize=20, color='k')
+ ax.plot(ag_on_off_t_GRID[:, 0] / 3600, np.ones_like(ag_on_off_t_GRID[:, 0]) * 1150, '|', markersize=20, color='red')
+ ax.set_ylim(400, 1200)
+ plt.show()
- LED_on_idx_DF = pd.read_csv(os.path.join(trial_path, 'led_idxs.csv'))
- i0 = np.array([int(LED_on_idx_DF.keys()[0])])
- LED_on_idx_DATA = np.concatenate((i0, np.array(LED_on_idx_DF).T[0]))
- LED_on_time_BORIS = np.load(os.path.join(trial_path, 'LED_on_time.npy'), allow_pickle=True)
- print(len(LED_on_idx_DATA), len(LED_on_time_BORIS))
embed()
quit()
pass
if __name__ == '__main__':
- main("/home/raab/data/mount_data/")
\ No newline at end of file
+ # main("/home/raab/data/mount_data/")
+ main("/home/raab/data/2020_competition_mount")
\ No newline at end of file