specparam.SpectralModel¶

class specparam.SpectralModel(peak_width_limits=(0.5, 12.0), max_n_peaks=inf, min_peak_height=0.0, peak_threshold=2.0, aperiodic_mode='fixed', verbose=True, **model_kwargs)[source]¶

Model a power spectrum as a combination of aperiodic and periodic components.

WARNING: frequency and power values inputs must be in linear space.

Passing in logged frequencies and/or power spectra is not detected, and will silently produce incorrect results.

Parameters:

peak_width_limitstuple of (float, float), optional, default: (0.5, 12.0): Limits on possible peak width, in Hz, as (lower_bound, upper_bound).
max_n_peaksint, optional, default: inf: Maximum number of peaks to fit.
min_peak_heightfloat, optional, default: 0: Absolute threshold for detecting peaks. This threshold is defined in absolute units of the power spectrum (log power).
peak_thresholdfloat, optional, default: 2.0: Relative threshold for detecting peaks. This threshold is defined in relative units of the power spectrum (standard deviation).
aperiodic_mode{‘fixed’, ‘knee’}: Which approach to take for fitting the aperiodic component.
verbosebool, optional, default: True: Verbosity mode. If True, prints out warnings and general status updates.

Notes

Commonly used abbreviations used in this module include: CF: center frequency, PW: power, BW: Bandwidth, AP: aperiodic
Input power spectra must be provided in linear scale. Internally they are stored in log10 scale, as this is what the model operates upon.
Input power spectra should be smooth, as overly noisy power spectra may lead to bad fits. For example, raw FFT inputs are not appropriate. Where possible and appropriate, use longer time segments for power spectrum calculation to get smoother power spectra, as this will give better model fits.
The gaussian params are those that define the gaussian of the fit, where as the peak params are a modified version, in which the CF of the peak is the mean of the gaussian, the PW of the peak is the height of the gaussian over and above the aperiodic component, and the BW of the peak, is 2*std of the gaussian (as ‘two sided’ bandwidth).

Attributes:

freqs1d array: Frequency values for the power spectrum.
power_spectrum1d array: Power values, stored internally in log10 scale.
freq_rangelist of [float, float]: Frequency range of the power spectrum, as [lowest_freq, highest_freq].
freq_resfloat: Frequency resolution of the power spectrum.
modeled_spectrum_1d array: The full model fit of the power spectrum, in log10 scale.
aperiodic_params_1d array: Parameters that define the aperiodic fit. As [Offset, (Knee), Exponent]. The knee parameter is only included if aperiodic component is fit with a knee.
peak_params_2d array: Fitted parameter values for the peaks. Each row is a peak, as [CF, PW, BW].
gaussian_params_2d array: Parameters that define the gaussian fit(s). Each row is a gaussian, as [mean, height, standard deviation].
r_squared_float: R-squared of the fit between the input power spectrum and the full model fit.
error_float: Error of the full model fit.
n_peaks_int: How many peaks were fit in the model.
has_databool: Indicator for if the object contains data.
has_modelbool: Indicator for if the object contains a model fit.

__init__(peak_width_limits=(0.5, 12.0), max_n_peaks=inf, min_peak_height=0.0, peak_threshold=2.0, aperiodic_mode='fixed', verbose=True, **model_kwargs)[source]¶: Initialize model object.

Methods

`__init__`([peak_width_limits, max_n_peaks, ...])	Initialize model object.
`add_data`(freqs, power_spectrum[, ...])	Add data (frequencies, and power spectrum values) to the current object.
`add_meta_data`(meta_data)	Add data information into object from a SpectrumMetaData object.
`add_results`(results)	Add results data into object from a FitResults object.
`add_settings`(settings)	Add settings into object from a ModelSettings object.
`copy`()	Return a copy of the current object.
`fit`([freqs, power_spectrum, freq_range])	Fit a power spectrum as a combination of periodic and aperiodic components.
`get_data`([component, space])	Get a data component.
`get_meta_data`()	Return data information from the current object.
`get_model`([component, space])	Get a model component.
`get_params`(name[, col])	Return model fit parameters for specified feature(s).
`get_results`()	Return model fit parameters and goodness of fit metrics.
`get_run_modes`()	Return run modes of the current object.
`get_settings`()	Return user defined settings of the current object.
`load`(file_name[, file_path, regenerate])	Load in a data file to the current object.
`plot`([plot_peaks, plot_aperiodic, freqs, ...])	Plot the power spectrum and model fit results from a model object.
`print_report_issue`([concise])	Prints instructions on how to report bugs and/or problematic fits.
`print_results`([concise])	Print out model fitting results.
`print_settings`([description, concise])	Print out the current settings.
`report`([freqs, power_spectrum, freq_range, ...])	Run model fit, and display a report, which includes a plot, and printed results.
`save`(file_name[, file_path, append, ...])	Save out data, results and/or settings from a model object into a JSON file.
`save_report`(file_name[, file_path, add_settings])	Generate and save out a PDF report for a power spectrum model fit.
`set_check_modes`([check_freqs, check_data])	Set check modes, which controls if an error is raised based on check on the inputs.
`set_debug_mode`(debug)	Set debug mode, which controls if an error is raised if model fitting is unsuccessful.
`set_run_modes`(debug, check_freqs, check_data)	Simultaneously set all run modes.
`to_df`(peak_org)	Convert and extract the model results as a pandas object.

Attributes

`has_data`	Indicator for if the object contains data.
`has_model`	Indicator for if the object contains a model fit.
`n_peaks_`	How many peaks were fit in the model.

add_data(freqs, power_spectrum, freq_range=None, clear_results=True)¶

Add data (frequencies, and power spectrum values) to the current object.

Parameters:

% copied in from Data object
clear_resultsbool, optional, default: True: Whether to clear prior results, if any are present in the object. This should only be set to False if data for the current results are being re-added.

Notes

% copied in from Data object

add_meta_data(meta_data)¶

Add data information into object from a SpectrumMetaData object.

Parameters:

meta_dataSpectrumMetaData: A meta data object containing meta data information.

add_results(results)¶

Add results data into object from a FitResults object.

Parameters:

resultsFitResults: A data object containing the results from fitting a power spectrum model.

add_settings(settings)¶

Add settings into object from a ModelSettings object.

Parameters:

settingsModelSettings: A data object containing the settings for a power spectrum model.

copy()¶: Return a copy of the current object.

fit(freqs=None, power_spectrum=None, freq_range=None)¶

Fit a power spectrum as a combination of periodic and aperiodic components.

Parameters:

freqs1d array, optional: Frequency values for the power spectrum, in linear space.
power_spectrum1d array, optional: Power values, which must be input in linear space.
freq_rangelist of [float, float], optional: Frequency range to restrict power spectrum to. If not provided, keeps the entire range.

Raises:

NoDataError: If no data is available to fit.
FitError: If model fitting fails to fit. Only raised in debug mode.

Notes

Data is optional, if data has already been added to the object.

get_data(component='full', space='log')¶

Get a data component.

Parameters:

component{‘full’, ‘aperiodic’, ‘peak’}

Which data component to return.: ‘full’ - full power spectrum ‘aperiodic’ - isolated aperiodic data component ‘peak’ - isolated peak data component

space{‘log’, ‘linear’}

Which space to return the data component in.: ‘log’ - returns in log10 space. ‘linear’ - returns in linear space.

Returns:

output1d array: Specified data component, in specified spacing.

Notes

The ‘space’ parameter doesn’t just define the spacing of the data component values, but rather defines the space of the additive data definition such that power_spectrum = aperiodic_component + peak_component. With space set as ‘log’, this combination holds in log space. With space set as ‘linear’, this combination holds in linear space.

get_meta_data()¶

Return data information from the current object.

Returns:

SpectrumMetaData: Object containing meta data from the current object.

get_model(component='full', space='log')¶

Get a model component.

Parameters:

component{‘full’, ‘aperiodic’, ‘peak’}

Which model component to return.: ‘full’ - full model ‘aperiodic’ - isolated aperiodic model component ‘peak’ - isolated peak model component

space{‘log’, ‘linear’}

Which space to return the model component in.: ‘log’ - returns in log10 space. ‘linear’ - returns in linear space.

Returns:

output1d array: Specified model component, in specified spacing.

Notes

The ‘space’ parameter doesn’t just define the spacing of the model component values, but rather defines the space of the additive model such that model = aperiodic_component + peak_component. With space set as ‘log’, this combination holds in log space. With space set as ‘linear’, this combination holds in linear space.

get_params(name, col=None)[source]¶

Return model fit parameters for specified feature(s).

Parameters:

name{‘aperiodic_params’, ‘peak_params’, ‘gaussian_params’, ‘error’, ‘r_squared’}: Name of the data field to extract.
col{‘CF’, ‘PW’, ‘BW’, ‘offset’, ‘knee’, ‘exponent’} or int, optional: Column name / index to extract from selected data, if requested. Only used for name of {‘aperiodic_params’, ‘peak_params’, ‘gaussian_params’}.

Returns:

outfloat or 1d array: Requested data.

Raises:

NoModelError: If there are no model fit parameters available to return.

Notes

If there are no fit peak (no peak parameters), this method will return NaN.

get_results()¶

Return model fit parameters and goodness of fit metrics.

Returns:

FitResults: Object containing the model fit results from the current object.

get_run_modes()¶

Return run modes of the current object.

Returns:

ModelRunModes: Object containing the run modes from the current object.

get_settings()¶

Return user defined settings of the current object.

Returns:

ModelSettings: Object containing the settings from the current object.

property has_data¶: Indicator for if the object contains data.

property has_model¶

Indicator for if the object contains a model fit.

Notes

This check uses the aperiodic params, which are:

nan if no model has been fit
necessarily defined, as floats, if model has been fit

load(file_name, file_path=None, regenerate=True)¶

Load in a data file to the current object.

Parameters:

file_namestr or FileObject: File to load data from.
file_pathPath or str, optional: Path to directory to load from. If None, loads from current directory.
regeneratebool, optional, default: True: Whether to regenerate the model fit from the loaded data, if data is available.

property n_peaks_¶: How many peaks were fit in the model.

plot(plot_peaks=None, plot_aperiodic=True, freqs=None, power_spectrum=None, freq_range=None, plt_log=False, add_legend=True, ax=None, data_kwargs=None, model_kwargs=None, aperiodic_kwargs=None, peak_kwargs=None, **plot_kwargs)[source]¶

Plot the power spectrum and model fit results from a model object.

Parameters:

plot_peaksNone or {‘shade’, ‘dot’, ‘outline’, ‘line’}, optional: What kind of approach to take to plot peaks. If None, peaks are not specifically plotted. Can also be a combination of approaches, separated by ‘-’, for example: ‘shade-line’.
plot_aperiodicboolean, optional, default: True: Whether to plot the aperiodic component of the model fit.
freqs1d array, optional: Frequency values of the power spectrum to plot, in linear space. If provided, this overrides the values in the model object.
power_spectrum1d array, optional: Power values to plot, in linear space. If provided, this overrides the values in the model object.
freq_rangelist of [float, float], optional: Frequency range to plot, defined in linear space.
plt_logboolean, optional, default: False: Whether to plot the frequency values in log10 spacing.
add_legendboolean, optional, default: False: Whether to add a legend describing the plot components.
axmatplotlib.Axes, optional: Figure axes upon which to plot.
data_kwargs, model_kwargs, aperiodic_kwargs, peak_kwargsNone or dict, optional: Keyword arguments to pass into the plot call for each plot element.
**plot_kwargs: Additional plot related keyword arguments, with styling options managed by style_plot.

Notes

The y-axis (power) is plotted in log spacing by default.

static print_report_issue(concise=False)[source]¶

Prints instructions on how to report bugs and/or problematic fits.

Parameters:

concisebool, optional, default: False: Whether to print the report in a concise mode, or not.

print_results(concise=False)[source]¶

Print out model fitting results.

Parameters:

concisebool, optional, default: False: Whether to print the report in a concise mode, or not.

print_settings(description=False, concise=False)[source]¶

Print out the current settings.

Parameters:

descriptionbool, optional, default: False: Whether to print out a description with current settings.
concisebool, optional, default: False: Whether to print the report in a concise mode, or not.

report(freqs=None, power_spectrum=None, freq_range=None, plt_log=False, plot_full_range=False, **plot_kwargs)[source]¶

Run model fit, and display a report, which includes a plot, and printed results.

Parameters:

freqs1d array, optional: Frequency values for the power spectrum.
power_spectrum1d array, optional: Power values, which must be input in linear space.
freq_rangelist of [float, float], optional: Frequency range to fit the model to. If not provided, fits across the entire given range.
plt_logbool, optional, default: False: Whether or not to plot the frequency axis in log space.
plot_full_rangebool, default: False: If True, plots the full range of the given power spectrum. Only relevant / effective if freqs and power_spectrum passed in in this call.
**plot_kwargs: Keyword arguments to pass into the plot method. Plot options with a name conflict be passed by pre-pending ‘plot_’. e.g. freqs, power_spectrum and freq_range.

Notes

Data is optional, if data has already been added to the object.

save(file_name, file_path=None, append=False, save_results=False, save_settings=False, save_data=False)¶

Save out data, results and/or settings from a model object into a JSON file.

Parameters:

file_namestr or FileObject: File to save data to.
file_pathPath or str, optional: Path to directory to save to. If None, saves to current directory.
appendbool, optional, default: False: Whether to append to an existing file, if available. This option is only valid (and only used) if ‘file_name’ is a str.
save_resultsbool, optional: Whether to save out model fit results.
save_settingsbool, optional: Whether to save out settings.
save_databool, optional: Whether to save out input data.

Raises:

ValueError: If the save file is not understood.

save_report(file_name, file_path=None, add_settings=True, **plot_kwargs)[source]¶

Generate and save out a PDF report for a power spectrum model fit.

Parameters:

file_namestr: Name to give the saved out file.
file_pathPath or str, optional: Path to directory to save to. If None, saves to current directory.
add_settingsbool, optional, default: True: Whether to add a print out of the model settings to the end of the report.
plot_kwargskeyword arguments: Keyword arguments to pass into the plot method.

set_check_modes(check_freqs=None, check_data=None)¶

Set check modes, which controls if an error is raised based on check on the inputs.

Parameters:

check_freqsbool, optional: Whether to run in check freqs mode, which checks the frequency data.
check_databool, optional: Whether to run in check data mode, which checks the power spectrum values data.

set_debug_mode(debug)¶

Set debug mode, which controls if an error is raised if model fitting is unsuccessful.

Parameters: