gapnet.data_creation.calibration.spectrum

module documentation

(source)

Functions for calibration using spectrum

Function	`get_impulse_response_from_spectrum`	Undocumented
Function	`get_signal`	Reverse of get_spectrum
Function	`get_spectrum`	Compute spectrum and show positive frequency space in SPL
Function	`get_spectrum_from_path`	Undocumented
Function	`get_spectrum_fs`	Compute spectrum and show positive frequency space in SPL
Function	`normalise_by_spectrum_level`	Normalises a given signal by its spectrum level within a defined frequency range. If
Function	`normalise_by_spectrum_level_fs`	Normalises a given signal by its spectrum level within a defined frequency range. If
Function	`spectrum_level`	Computes the spectrum level within a given frequency range
Function	`spectrum_level_from_signal`	Undocumented
Function	`spectrum_level_from_signal_fs`	Undocumented

def get_impulse_response_from_spectrum(f, x): (source) ¶

Undocumented

Reverse of get_spectrum

def get_spectrum(t, x, get_abs=False): (source) ¶

Compute spectrum and show positive frequency space in SPL

Parameters
t:`np.ndarray`	time vector
x:`np.ndarray`	signal
get_abs:`bool`	whether to return the absolute value of the spectrum or not
Returns
`Tuple[np.ndarray, np.ndarray]`	Tuple(frequency vector, spectrum)

@check_annotations
def get_spectrum_from_path(t, path): (source) ¶

Undocumented

Parameters
t:`np.ndarray`	Undocumented
path:`Annotated[str, PathExists]`	Undocumented
Returns
`Tuple[np.ndarray, np.ndarray]`	Undocumented

def get_spectrum_fs(x, fs, get_abs=False): (source) ¶

Compute spectrum and show positive frequency space in SPL

Parameters
x:`np.ndarray`	signal
fs:`Union[float, int]`	sampling frequency (only used for frequency vector)
get_abs:`bool`	whether to return the absolute value of the spectrum or not
Returns
`Tuple[np.ndarray, np.ndarray]`	Tuple(frequency vector, spectrum)

def normalise_by_spectrum_level(t, x, target_level, frequency_range=None): (source) ¶

Normalises a given signal by its spectrum level within a defined frequency range. If

Parameters
t:`np.ndarray`	time vector
x:`np.ndarray`	signal
target_level:`float`	target spectrum level in dB SPL
frequency_range	frequency range for spectrum level calculation
Returns
`np.ndarray`	normalised signal

def normalise_by_spectrum_level_fs(x, fs, target_level, frequency_range=None): (source) ¶

Normalises a given signal by its spectrum level within a defined frequency range. If

Parameters
x:`np.ndarray`	signal
fs:`Union[float, int]`	sampling frequency
target_level:`float`	target spectrum level in dB SPL
frequency_range	frequency range for spectrum level calculation
Returns
`np.ndarray`	normalised signal

def spectrum_level(f, spectrum, frequency_range): (source) ¶

Computes the spectrum level within a given frequency range

Parameters
f:`np.ndarray`	frequency vector
spectrum:`np.ndarray`	spectrum vector
frequency_range:`Union[None, Annotated[list[float], 2]]`	frequency range to compute spectrum level from, if None, the full spectrum is used
Returns
`Union[float, np.ndarray]`

def spectrum_level_from_signal(t, x, frequency_range=None): (source) ¶

Undocumented

Parameters
t:`np.ndarray`	Undocumented
x:`np.ndarray`	Undocumented
frequency_range:`Union[None, Annotated[list[float], 2]]`	Undocumented
Returns
`float\|np.ndarray`	Undocumented

def spectrum_level_from_signal_fs(x, fs, frequency_range=None): (source) ¶

Undocumented

Parameters
x:`np.ndarray`	Undocumented
fs:`Union[float, int]`	Undocumented
frequency_range:`Union[None, Annotated[list[float], 2]]`	Undocumented
Returns
`float\|np.ndarray`	Undocumented