jgrewe/gp_neurobio
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

buh

Browse Source
This commit is contained in:
efish 2018-11-28 10:56:14 +01:00
parent e6fafa2f72
commit 350dc24ad5
2 changed files with 14 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

20
code/eod_freq_normal.py
View File

@ -4,21 +4,27 @@ import matplotlib.pyplot as plt
import numpy as np
data_dir = '../data'
dataset = '2018-11-09-ad-invivo-1'
#dataset = '2018-11-09-ad-invivo-1'
data = ["2018-11-09-ad-invivo-1", "2018-11-13-aa-invivo-1", "2018-11-13-ad-invivo-1", "2018-11-13-ah-invivo-1", "2018-11-13-ai-invivo-1", "2018-11-13-ak-invivo-1", "2018-11-13-al-invivo-1", "2018-11-14-ac-invivo-1", "2018-11-14-af-invivo-1", "2018-11-14-ag-invivo-1", "2018-11-14-ak-invivo-1", "2018-11-14-al-invivo-1", "2018-11-14-am-invivo-1", "2018-11-14-an-invivo-1", "2018-11-20-ab-invivo-1", "2018-11-20-ac-invivo-1", "2018-11-20-ad-invivo-1", "2018-11-20-af-invivo-1", "2018-11-20-ag-invivo-1", "2018-11-20-ah-invivo-1", "2018-11-20-ai-invivo-1"]
for dataset in data:
# read eod and time of baseline
time, eod = read_baseline_eod(os.path.join(data_dir, dataset))
time, eod = read_baseline_eod(os.path.join(data_dir, dataset))
eod_norm = eod - np.mean(eod)
eod_norm = eod - np.mean(eod)
# calculate eod times and indices by zero crossings
threshold = 0
shift_eod = np.roll(eod_norm, 1)
eod_times = time[(eod_norm >= threshold) & (shift_eod < threshold)]
threshold = 0
shift_eod = np.roll(eod_norm, 1)
eod_times = time[(eod_norm >= threshold) & (shift_eod < threshold)]
## normal
eod_freq_normal = 1/np.diff(eod_times)
eod_freq_normal = 1/np.diff(eod_times)
overallfreq = np.mean(eod_freq_normal)
print(overallfreq)
exit()
kernel = np.ones(7)/7
smooth_eod_freq_normal = np.convolve(eod_freq_normal, kernel, mode = 'valid')

2
code/repetition_firingrate.py
View File

@ -8,7 +8,7 @@ from IPython import embed
# define sampling rate and data path
sampling_rate = 40 #kHz
data_dir = "../data"
dataset = "2018-11-09-ad-invivo-1"
dataset = "2018-11-13-aj-invivo-1"
inch_factor = 2.54
# parameters for binning, smoothing and plotting
cut_window = 60