def dict2array(self, directory_files_feature_dict: dict, label_list: list, normalize: bool):
"""
:param directory_files_feature_dict:
:param label_list:
:param normalize:
:return: expert_feature_2d_array: Extracted feature with expert system (Numpy 2D array)
:return mel_spectrogram_array: Extracted mel-spectrogram (Numpy 3D array)
:return list_array: Labels in numpy array
"""
# Convert extracted feature and label to numpy array
expert_feature_array, mel_spectrogram_array = self.AFE.dict2array(directory_files_feature_dict)
label_array = np.array(label_list)
# Normalize expert feature
if normalize is True:
# Remove NaNs from array
expert_feature_array, mel_spectrogram_array, label_array = DataProcess.remove_nan_from_array(expert_feature_array,
mel_spectrogram_array,
label_array)
# Take stats from expert feature
DataProcess.take_dataset_stats(expert_feature_array, 'backend/expert_feature_mean_list.txt')
expert_feature_array = DataProcess.min_max_normalize(expert_feature_array)
# Convert dimension of mel-spectrogram array
mel_spectrogram_array = mel_spectrogram_array.reshape(mel_spectrogram_array.shape[0],
mel_spectrogram_array.shape[1],
mel_spectrogram_array.shape[2],
1)
return expert_feature_array, mel_spectrogram_array, label_array
def save_data(self, expert_feature_array, mel_spectrogram_array, label_array):
"""
Save extracted feature into directories.
:param expert_feature_array: Extracted feature with expert system (Numpy 2D array)
:param mel_spectrogram_array: Extracted mel-spectrogram (Numpy 3D array)
:param label_array:
:return:
"""
# Remove NaNs from array
expert_feature_array = DataProcess.remove_nan_from_array(expert_feature_array)
# Take stats from expert feature
DataProcess.take_dataset_stats(expert_feature_array, 'backend/normalized_expert_feature_mean_list.txt')
# Save data
np.save(os.path.join('backend/feature/expert', "data"), expert_feature_array)
np.save(os.path.join('backend/feature/expert', "label"), label_array)
np.save(os.path.join('backend/feature/mel_spectrogram', "data"), expert_feature_array)
np.save(os.path.join('backend/feature/mel_spectrogram', "label"), label_array)
return expert_feature_array, mel_spectrogram_array, label_array