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(),