def preproc(x, fs, rej=None):
x = dc_blocker(x)
x = fft_filter(x, fs, band=(0, 45))
if rej is not None:
x = np.dot(x, rej)
return x
def preproc(x, fs, rej=None):
x = dc_blocker(x)
x = fft_filter(x, fs, band=(3, 45))
if rej is not None:
x = np.dot(x, rej)
return x
import pylab as plt
import pandas as pd
import seaborn as sns
import numpy as np
cm = sns.color_palette()
file_path = r'/media/nikolai/D27ECFCB7ECFA697/Users/Nikolai/PycharmProjects/nfb/pynfb/results/delay-p4_02-20_11-38-03/experiment_data.h5'
df, fs, p_names, channels = load_data(file_path)
signals = load_signals_data(file_path)
print(signals)
print('*****', p_names)
data = pd.DataFrame()
data['p4'] = dc_blocker(df['P4'])
data['signal'] = signals['Signal']
data['block_name'] = df['block_name']
data['block_number'] = df['block_number']
data.to_csv('alpha-delayed-20-02-18.csv')
labels = []
handles = []
b_names = list(data['block_name'].unique())
data.index = np.arange(len(data)) / fs
for k in data['block_number'].unique():
x = data.loc[data['block_number'] == k]
name = x['block_name'].iloc[0]
print(name)
h, = plt.plot(x['signal'].rolling(fs * 30, center=True).mean(),