| import scipy |
| from scipy import signal |
| import os |
| import lmdb |
| import pickle |
| import numpy as np |
| import mne |
|
|
| useless_ch = ['M1', 'M2', 'VEO', 'HEO'] |
| trials_of_sessions = { |
| '1': {'start': [30, 132, 287, 555, 773, 982, 1271, 1628, 1730, 2025, 2227, 2435, 2667, 2932, 3204], |
| 'end': [102, 228, 524, 742, 920, 1240, 1568, 1697, 1994, 2166, 2401, 2607, 2901, 3172, 3359]}, |
|
|
| '2': {'start': [30, 299, 548, 646, 836, 1000, 1091, 1392, 1657, 1809, 1966, 2186, 2333, 2490, 2741], |
| 'end': [267, 488, 614, 773, 967, 1059, 1331, 1622, 1777, 1908, 2153, 2302, 2428, 2709, 2817]}, |
|
|
| '3': {'start': [30, 353, 478, 674, 825, 908, 1200, 1346, 1451, 1711, 2055, 2307, 2457, 2726, 2888], |
| 'end': [321, 418, 643, 764, 877, 1147, 1284, 1418, 1679, 1996, 2275, 2425, 2664, 2857, 3066]}, |
| } |
| labels_of_sessions = { |
| '1': [4, 1, 3, 2, 0, 4, 1, 3, 2, 0, 4, 1, 3, 2, 0, ], |
| '2': [2, 1, 3, 0, 4, 4, 0, 3, 2, 1, 3, 4, 1, 2, 0, ], |
| '3': [2, 1, 3, 0, 4, 4, 0, 3, 2, 1, 3, 4, 1, 2, 0, ], |
| } |
|
|
| root_dir = '/data/datasets/BigDownstream/SEED-V/files' |
| files = [file for file in os.listdir(root_dir)] |
| files = sorted(files) |
| print(files) |
|
|
| trials_split = { |
| 'train': range(5), |
| 'val': range(5, 10), |
| 'test': range(10, 15), |
| } |
|
|
| dataset = { |
| 'train': list(), |
| 'val': list(), |
| 'test': list(), |
| } |
|
|
| db = lmdb.open('/data/datasets/BigDownstream/SEED-V/processed', map_size=15614542346) |
|
|
| for file in files: |
| raw = mne.io.read_raw_cnt(os.path.join(root_dir, file), preload=True) |
| raw.drop_channels(useless_ch) |
| |
| raw.resample(200) |
| raw.filter(l_freq=0.3, h_freq=75) |
| data_matrix = raw.get_data(units='uV') |
| session_index = file.split('_')[1] |
| data_trials = [ |
| data_matrix[:, |
| trials_of_sessions[session_index]['start'][j] * 200:trials_of_sessions[session_index]['end'][j] * 200] |
| for j in range(15)] |
| labels = labels_of_sessions[session_index] |
| for mode in trials_split.keys(): |
| for index in trials_split[mode]: |
| data = data_trials[index] |
| label = labels[index] |
| print(data.shape) |
| data = data.reshape(62, -1, 1, 200) |
| data = data.transpose(1, 0, 2, 3) |
| print(data.shape) |
| for i, sample in enumerate(data): |
| sample_key = f'{file}-{index}-{i}' |
| data_dict = { |
| 'sample': sample, 'label': label |
| } |
| txn = db.begin(write=True) |
| txn.put(key=sample_key.encode(), value=pickle.dumps(data_dict)) |
| txn.commit() |
| dataset[mode].append(sample_key) |
|
|
| txn = db.begin(write=True) |
| txn.put(key='__keys__'.encode(), value=pickle.dumps(dataset)) |
| txn.commit() |
| db.close() |
|
|
