raab/GP2023_chirp_detection
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adding behaviour plot

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This commit is contained in:
wendtalexander 2023-01-19 15:56:42 +01:00
parent 90c6a15433
commit 8d790ad89c
1 changed files with 23 additions and 8 deletions
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31
code/behavior.py
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@ -3,6 +3,7 @@ import os
import numpy as np
from IPython import embed
from pandas import read_csv
import matplotlib.pyplot as plt
@ -27,12 +28,15 @@ class Behavior:
"""
def __init__(self, folder_path: str) -> None:
self.file = os.path.join(datapath, "traces-grid1.raw")
LED_on_time_BORIS = np.load(os.path.join(folder_path, 'LED_on_time.npy'), allow_pickle=True)
self.time = np.load(datapath + "times.npy", allow_pickle=True)
self.dataframe = read_csv(os.path.join(folder_path, self.file[1:-7] + '.csv'))
self.time = np.load(os.path.join(folder_path, "times.npy"), allow_pickle=True)
csv_filename = [f for f in os.listdir(folder_path) if f.endswith('.csv')][0] # check if there are more than one csv file
self.dataframe = read_csv(os.path.join(folder_path, csv_filename))
self.chirps = np.load(os.path.join(folder_path, 'chirps.npy'), allow_pickle=True)
self.chirps_ids = np.load(os.path.join(folder_path, 'chirps_ids.npy'), allow_pickle=True)
for k, key in enumerate(self.dataframe.keys()):
key = key.lower()
if ' ' in key:
@ -41,12 +45,13 @@ class Behavior:
key = key.replace('(', '')
key = key.replace(')', '')
setattr(self, key, np.array(self.dataframe[self.dataframe.keys()[k]]))
last_LED_t_BORIS = LED_on_time_BORIS[-1]
real_time_range = self.time[-1] - self.time[0]
factor = 1.034141
self.shift = last_LED_t_BORIS - real_time_range * factor
self.start_s = (self.start_s - self.shift) / factor
self.stop_s = (self.stop_s - self.shift) / factor
shift = last_LED_t_BORIS - real_time_range * factor
self.start_s = (self.start_s - shift) / factor
self.stop_s = (self.stop_s - shift) / factor
@ -79,7 +84,17 @@ temporal encpding needs to be corrected ... not exactly 25FPS.
def main(datapath: str):
# behabvior is pandas dataframe with all the data
behavior = Behavior(datapath)
bh = Behavior(datapath)
fig, ax = plt.subplots()
ax.plot(bh.chirps, np.ones_like(bh.chirps), marker='o')
ax.plot(bh.start_s, np.ones_like(bh.start_s)*2, marker='*')
plt.show()
embed()
exit()
if __name__ == '__main__':