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add input_array and sample_rate_in arguments to stat, stats and power… #146

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44 changes: 35 additions & 9 deletions sox/transform.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3131,7 +3131,9 @@ def speed(self, factor: float):
return self

def stat(self,
input_filepath: Union[str, Path],
input_filepath: Optional[Union[str, Path]] = None,
input_array: Optional[np.ndarray] = None,
sample_rate_in: Optional[float] = None,
scale: Optional[float] = None,
rms: Optional[bool] = False):
'''Display time and frequency domain statistical information about the
Expand All @@ -3145,8 +3147,13 @@ def stat(self,

Parameters
----------
input_filepath : str
input_filepath : str or None
Path to input file to compute stats on.
input_array : np.ndarray or None
A np.ndarray of an waveform with shape (n_samples, n_channels)
or None
sample_rate_in : int or None
Sample rate of input_array or None
scale : float or None, default=None
If not None, scales the input by the given scale factor.
rms : bool, default=False
Expand All @@ -3171,7 +3178,8 @@ def stat(self,
effect_args.append('-rms')

_, _, stat_output = self.build(
input_filepath, '-n', extra_args=effect_args, return_output=True
input_filepath=input_filepath, input_array=input_array, sample_rate_in=sample_rate_in,
output_filepath='-n', extra_args=effect_args, return_output=True
)

stat_dict = {}
Expand All @@ -3186,16 +3194,24 @@ def stat(self,

return stat_dict

def power_spectrum(self, input_filepath: Union[str, Path]):
def power_spectrum(self,
input_filepath: Optional[Union[str, Path]] = None,
input_array: Optional[np.ndarray] = None,
sample_rate_in: Optional[float] = None):
'''Calculates the power spectrum (4096 point DFT). This method
internally invokes the stat command with the -freq option.

Note: The file is downmixed to mono prior to computation.

Parameters
----------
input_filepath : str
input_filepath : str or None
Path to input file to compute stats on.
input_array : np.ndarray or None
A np.ndarray of an waveform with shape (n_samples, n_channels)
or None
sample_rate_in : int or None
Sample rate of input_array or None

Returns
-------
Expand All @@ -3209,7 +3225,8 @@ def power_spectrum(self, input_filepath: Union[str, Path]):
effect_args = ['channels', '1', 'stat', '-freq']

_, _, stat_output = self.build(
input_filepath, '-n', extra_args=effect_args, return_output=True
input_filepath=input_filepath, input_array=input_array, sample_rate_in=sample_rate_in,
output_filepath='-n', extra_args=effect_args, return_output=True
)

power_spectrum = []
Expand All @@ -3224,7 +3241,10 @@ def power_spectrum(self, input_filepath: Union[str, Path]):

return power_spectrum

def stats(self, input_filepath: Union[str, Path]):
def stats(self,
input_filepath: Optional[Union[str, Path]] = None,
input_array: Optional[np.ndarray] = None,
sample_rate_in: Optional[float] = None):
'''Display time domain statistical information about the audio
channels. Audio is passed unmodified through the SoX processing chain.
Statistics are calculated and displayed for each audio channel
Expand All @@ -3237,8 +3257,13 @@ def stats(self, input_filepath: Union[str, Path]):

Parameters
----------
input_filepath : str
input_filepath : str or None
Path to input file to compute stats on.
input_array : np.ndarray or None
A np.ndarray of an waveform with shape (n_samples, n_channels)
or None
sample_rate_in : int or None
Sample rate of input_array or None

Returns
-------
Expand All @@ -3252,7 +3277,8 @@ def stats(self, input_filepath: Union[str, Path]):
effect_args = ['channels', '1', 'stats']

_, _, stats_output = self.build(
input_filepath, '-n', extra_args=effect_args, return_output=True
input_filepath=input_filepath, input_array=input_array, sample_rate_in=sample_rate_in,
output_filepath='-n', extra_args=effect_args, return_output=True
)

stats_dict = {}
Expand Down