def get_normalisation_params(self, dir_out, file_name=None):
"""
Read the mean std_dev values from a file.
Save them in self.norm_params.
:param dir_out: Directory containing the normalisation file.
:param file_name: Prefix of normalisation file.
Expects file to be named <file_name-><MeanStdDevExtractor.file_name_appendix>.bin
:return: Tuple of normalisation parameters (mean, std_dev).
"""
if not self.add_deltas:
# Collect all means and std_devs in a list.
all_mean = list()
all_std_dev = list()
full_file_name = (
file_name + "-" if file_name is not None else
"") + MeanStdDevExtractor.file_name_appendix + ".bin"
# Load normalisation parameters for all features.
for dir_feature in [
self.dir_coded_sps, self.dir_lf0, self.dir_bap
]:
mean, std_dev = MeanStdDevExtractor.load(
os.path.join(dir_out, dir_feature, full_file_name))
all_mean.append(np.atleast_2d(mean))
all_std_dev.append(np.atleast_2d(std_dev))
# Manually set vuv normalisation paramters.
all_mean.insert(-1, np.atleast_2d(0.0))
all_std_dev.insert(-1, np.atleast_2d(1.0))
# Save the concatenated normalisation parameters locally.
self.norm_params = np.concatenate(
all_mean, axis=1), np.concatenate(all_std_dev, axis=1)
else:
full_file_name = (
file_name + "-" if file_name is not None else ""
) + MeanCovarianceExtractor.file_name_appendix # + "_" + self.dir_coded_sps + ".bin"
# Load the normalisation parameters.
mean_coded_sp, self.cov_coded_sp, std_dev_coded_sp = MeanCovarianceExtractor.load(
os.path.join(
dir_out, self.dir_deltas,
full_file_name + "_" + self.dir_coded_sps + ".bin"))
mean_lf0, self.cov_lf0, std_dev_lf0 = MeanCovarianceExtractor.load(
os.path.join(dir_out, self.dir_deltas,
full_file_name + "_" + self.dir_lf0 + ".bin"))
mean_bap, self.cov_bap, std_dev_bap = MeanCovarianceExtractor.load(
os.path.join(dir_out, self.dir_deltas,
full_file_name + "_" + self.dir_bap + ".bin"))
self.norm_params = (np.concatenate(
(mean_coded_sp, mean_lf0, np.atleast_1d(0.0), mean_bap)),
np.concatenate(
(std_dev_coded_sp, std_dev_lf0,
np.atleast_1d(1.0), std_dev_bap)))
return self.norm_params
def get_normalisation_params(self, dir_out, file_name=None):
"""
Read the mean std_dev values from a file.
Save them in self.norm_params.
:param dir_out: Directory containing the normalisation file.
:param file_name: Prefix of normalisation file.
Expects file to be named <file_name-><MeanStdDevExtractor.file_name_appendix>.bin
:return: Tuple of normalisation parameters (mean, std_dev).
"""
full_file_name = (file_name + "-" if file_name is not None else "") + MeanStdDevExtractor.file_name_appendix + ".bin"
if not self.add_deltas:
# Collect all means and std_devs in a list.
all_mean = list()
all_std_dev = list()
# Load normalisation parameters for all features.
mean, std_dev = MeanStdDevExtractor.load(os.path.join(dir_out, self.dir_lf0, full_file_name))
all_mean.append(np.atleast_2d(mean))
all_std_dev.append(np.atleast_2d(std_dev))
# Manually set vuv normalisation parameters.
# Note that vuv normalisation parameters are not saved in gen_data method (except for add_deltas=True).
all_mean.append(np.atleast_2d(0.0))
all_std_dev.append(np.atleast_2d(1.0))
# for dir_feature in [self.dir_lf0, self.dir_vuv]:
# mean, std_dev = MeanStdDevExtractor.load(os.path.join(dir_out, dir_feature, full_file_name))
# all_mean.append(np.atleast_2d(mean))
# all_std_dev.append(np.atleast_2d(std_dev))
# Save the concatenated normalisation parameters locally.
self.norm_params = np.concatenate(all_mean, axis=1), np.concatenate(all_std_dev, axis=1)
else:
# Save the normalisation parameters locally.
# VUV normalisation parameters are manually set to mean=0 and std_dev=1 in gen_data method.
self.norm_params = MeanStdDevExtractor.load(os.path.join(dir_out, self.dir_deltas, full_file_name))
return self.norm_params
def get_normalisation_params(self, dir_out, file_name=None):
"""
Read mean std_dev values from a file.
Save them in self.norm_params
:param dir_out: Directory containing the normalisation file.
:param file_name: Prefix of normalisation file.
Expects file to be named <file_name-><MeanStdDevExtractor.file_name_appendix>.bin
:return: Tuple of normalisation parameters (mean, std_dev).
"""
full_file_name = (file_name + "-" if file_name is not None else
"") + MeanStdDevExtractor.file_name_appendix + ".bin"
self.norm_params = MeanStdDevExtractor.load(
os.path.join(self.dir_labels, full_file_name))
return self.norm_params
def get_normalisation_params(self, dir_out, file_name=None):
"""
Read the mean std_dev values from a file.
Save them in self.norm_params.
:param dir_out: Directory containing the normalisation file, usually the atom directory.
:param file_name: Prefix of normalisation file.
Expects file to be named <file_name-><MeanStdDevExtractor.file_name_appendix>.bin
:return: Tuple of normalisation parameters (mean, std_dev).
"""
full_file_name = (file_name + "-" if file_name is not None else "") + MeanStdDevExtractor.file_name_appendix + ".bin"
# Use the same normalisation parameters for the LF0 curve without phrase curve
# as for atoms. The phrase directory is the same as the atom directory.
mean, std_dev = MeanStdDevExtractor.load(os.path.join(self.dir_phrase, full_file_name))
mean, std_dev = mean[:, 0:1], std_dev[:, 0:1] # Dimension of both is 1 x 2(atom amplitude, theta).
# Manually set V/UV normalisation parameters and save the concatenated normalisation parameters locally.
self.norm_params = np.concatenate((mean, np.zeros((1, 1))), axis=1),\
np.concatenate((std_dev, np.ones((1, 1))), axis=1)
return self.norm_params