Source code for fooof.data.data

"""Data objects for FOOOF.

Notes on FOOOF data objects:
- these data objects are NamedTuples, immutable data types with attribute labels
- the namedtuples are wrapped as classes (they are still immutable when doing this)
- wrapping in objects helps to be able to render well formed documentation for them.
- setting `__slots__` as empty voids the dynamic dictionary that usually stores attributes
    - this means no additional attributes can be defined (which is more memory efficient)
"""

from collections import namedtuple

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[docs]class FOOOFSettings(namedtuple('FOOOFSettings', ['peak_width_limits', 'max_n_peaks', 'min_peak_height', 'peak_threshold', 'aperiodic_mode'])): """User defined settings for the fitting algorithm. Parameters ---------- peak_width_limits : tuple of (float, float) Limits on possible peak width, in Hz, as (lower_bound, upper_bound). max_n_peaks : int Maximum number of peaks to fit. min_peak_height : float Absolute threshold for detecting peaks, in units of the input data. peak_threshold : float Relative threshold for detecting peaks, in units of standard deviation of the input data. aperiodic_mode : {'fixed', 'knee'} Which approach to take for fitting the aperiodic component. Notes ----- This object is a data object, based on a NamedTuple, with immutable data attributes. """ __slots__ = ()
[docs]class FOOOFMetaData(namedtuple('FOOOFMetaData', ['freq_range', 'freq_res'])): """Metadata information about a power spectrum. Parameters ---------- freq_range : list of [float, float] Frequency range of the power spectrum, as [lowest_freq, highest_freq]. freq_res : float Frequency resolution of the power spectrum. Notes ----- This object is a data object, based on a NamedTuple, with immutable data attributes. """ __slots__ = ()
[docs]class FOOOFResults(namedtuple('FOOOFResults', ['aperiodic_params', 'peak_params', 'r_squared', 'error', 'gaussian_params'])): """Model results from parameterizing a power spectrum. Parameters ---------- aperiodic_params : 1d array Parameters that define the aperiodic fit. As [Offset, (Knee), Exponent]. The knee parameter is only included if aperiodic is fit with knee. peak_params : 2d array Fitted parameter values for the peaks. Each row is a peak, as [CF, PW, BW]. r_squared : float R-squared of the fit between the full model fit and the input data. error : float Error of the full model fit. gaussian_params : 2d array Parameters that define the gaussian fit(s). Each row is a gaussian, as [mean, height, standard deviation]. Notes ----- This object is a data object, based on a NamedTuple, with immutable data attributes. """ __slots__ = ()
[docs]class SimParams(namedtuple('SimParams', ['aperiodic_params', 'periodic_params', 'nlv'])): """Parameters that define a simulated power spectrum. Parameters ---------- aperiodic_params : list Parameters that define the aperiodic component. periodic_params : list or list of lists Parameters that define the periodic component. nlv : float Noise level added to simulated spectrum. Notes ----- This object is a data object, based on a NamedTuple, with immutable data attributes. """ __slots__ = ()