pyrasa.utils.fit_funcs.KneeFitFun

class pyrasa.utils.fit_funcs.KneeFitFun(freq: ndarray, aperiodic_spectrum: ndarray, scale_factor: int | float)

A model for fitting aperiodic activity in power spectra with a spectral knee.

The KneeFitFun class extends AbstractFitFun to model aperiodic activity in power spectra using a function that includes a spectral knee. This model is particularly useful for cases where the aperiodic component of the spectrum has a break or knee, representing a transition between two different spectral slopes.

label

A label to identify this fitting model. Default is ‘knee’.

Type:

str

log10_aperiodic

Indicates whether to log-transform the aperiodic spectrum. Default is True.

Type:

bool

func(x: np.ndarray, Offset: float, Knee: float, Exponent_1: float, Exponent_2: float) → np.ndarray

Defines the model function for aperiodic activity with a spectral knee and pre-knee slope.

add_infos_to_df(df_params: pd.DataFrame) → pd.DataFrame

Adds calculated knee frequency to the DataFrame of fit parameters.

curve_kwargs() → dict[str, Any]

Generates initial guess parameters and other keyword arguments for curve fitting.

Attributes:

aperiodic_spectrum

curve_kwargs

freq

scale_factor

Methods

func(x, Offset, Knee, Exponent_1, Exponent_2)

Model aperiodic activity with a spectral knee and a pre-knee slope.

add_infos_to_df
fit_func
handle_scaling

__hash__ = None

func(x: ndarray, Offset: float, Knee: float, Exponent_1: float, Exponent_2: float) → ndarray

Model aperiodic activity with a spectral knee and a pre-knee slope. Use this to model aperiodic activity with a spectral knee