def _preprocess_to_padded_matrix()

in ludwig/utils/audio_utils.py [0:0]

• 18 lines of code
• 5 McCabe index (conditional complexity)

def _preprocess_to_padded_matrix(data, window_length_in_samp,
                                 window_shift_in_samp, zero_mean_offset=False):
    num_input = data.shape[0]
    num_output = get_num_output_padded_to_fit_input(num_input,
                                                    window_length_in_samp,
                                                    window_shift_in_samp)
    zero_padded_matrix = np.zeros((num_output, window_length_in_samp),
                                  dtype=np.float)
    for num_output_idx in range(num_output):
        start_idx = window_shift_in_samp * num_output_idx
        is_last_output = num_output_idx == num_output - 1
        end_idx = start_idx + window_length_in_samp if not is_last_output else num_input
        end_padded_idx = window_length_in_samp if not is_last_output else end_idx - start_idx
        window_data = data[start_idx:end_idx]
        if zero_mean_offset:
            window_data = window_data - np.mean(window_data)
        zero_padded_matrix[num_output_idx, :end_padded_idx] = window_data
    return zero_padded_matrix