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Till Raab 2023-06-16 11:14:59 +02:00
parent cabb3bd2c9
commit d11c83b46f
1 changed files with 6 additions and 2 deletions
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8
ethogram.py
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@ -130,14 +130,18 @@ def main(base_path):
event_times = np.array(event_times)[time_sorter]
event_labels = np.array(event_labels)[time_sorter]
marcov_matrix = np.zeros((len(loop_labels), len(loop_labels)))
marcov_matrix = np.zeros((len(loop_labels)+1, len(loop_labels)+1))
for enu_ori, label_ori in enumerate(loop_labels):
for enu_tar, label_tar in enumerate(loop_labels):
n = len(event_times[:-1][(event_labels[:-1] == label_ori) & (event_labels[1:] == label_tar) & (np.diff(event_times) <= 5)])
marcov_matrix[enu_ori, enu_tar] = n
for enu_tar, label_tar in enumerate(loop_labels):
n = len(event_times[:-1][(event_labels[1:] == label_tar) & (np.diff(event_times) > 5)])
marcov_matrix[-1, enu_tar] = n
embed()
quit()
### get those cases where ag_on does not point to event and no event points to corresponding ag_off ... add thise cases in marcov matrix
chase_on_idx = np.where(event_labels == loop_labels[4])[0]
chase_off_idx = np.where(event_labels == loop_labels[5])[0]