def load_X(X_signals_paths):
"""
Given attribute (train or test) of feature, read all 9 features into an
np ndarray of shape [sample_sequence_idx, time_step, feature_num]
argument: X_signals_paths str attribute of feature: 'train' or 'test'
return: np ndarray, tensor of features
"""
X_signals = []
for signal_type_path in X_signals_paths:
file = open(signal_type_path, 'rb')
# Read dataset from disk, dealing with text files' syntax
X_signals.append(
[np.array(serie, dtype=np.float32) for serie in [
row.replace(' ', ' ').strip().split(' ') for row in file
]]
)
file.close()
return np.transpose(np.array(X_signals), (1, 2, 0))
config_dataset_HAR_6_classes.py 文件源码
python
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