specparam.SpectralGroupModel¶

class specparam.SpectralGroupModel(*args, **kwargs)[source]¶

Model a group of power spectra 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).
The group object inherits from the model object. As such it also has data attributes (power_spectrum & modeled_spectrum_), and parameter attributes (aperiodic_params_, peak_params_, gaussian_params_, r_squared_, error_) which are defined in the context of individual model fits. These attributes are used during the fitting process, but in the group context do not store results post-fitting. Rather, all model fit results are collected and stored into the group_results attribute. To access individual parameters of the fit, use the get_params method.

Attributes:

freqs1d array: Frequency values for the power spectra.
power_spectra2d array: Power values for the group of power spectra, as [n_power_spectra, n_freqs]. Power values are stored internally in log10 scale.
freq_rangelist of [float, float]: Frequency range of the power spectra, as [lowest_freq, highest_freq].
freq_resfloat: Frequency resolution of the power spectra.
group_resultslist of FitResults: Results of the model fit for each power spectrum.
has_databool: Indicator for if the object contains data.
has_modelbool: Indicator for if the object contains model fits.
n_peaks_int: How many peaks were fit for each model.
n_null_int: How many model fits are null.
null_inds_list of int: The indices for model fits that are null.

__init__(*args, **kwargs)[source]¶: Initialize base model object

Methods

`__init__`(args, *kwargs)	Initialize base model object
`add_data`(freqs, power_spectra[, freq_range, ...])	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.
`add_settings`(settings)	Add settings into object from a ModelSettings object.
`copy`()	Return a copy of the current object.
`drop`(inds)	Drop one or more model fit results from the object.
`fit`([freqs, power_spectra, freq_range, ...])	Fit a group of power spectra.
`get_data`([component, space])	Get a data component.
`get_group`(inds)	Get a Group model object with the specified sub-selection of model fits.
`get_meta_data`()	Return data information from the current object.
`get_model`(ind[, regenerate])	Get a model fit object for a specified index.
`get_params`(name[, col])	Return model fit parameters for specified feature(s).
`get_results`()	Return the results run across a group of power spectra.
`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])	Load group data from file.
`plot`(**plot_kwargs)	Plot a figure with subplots visualizing the parameters from a group model object.
`print_results`([concise])	Print out the group results.
`report`([freqs, power_spectra, freq_range, ...])	Fit a group of power spectra and display a report, with a plot and printed results.
`save`(file_name[, file_path, append, ...])	Save out results and/or settings from group object.
`save_model_report`(index, file_name[, ...])	"Save out an individual model report for a specified model fit.
`save_report`(file_name[, file_path, add_settings])	Generate and save out a PDF report for models of a group of power spectra.
`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 model fits.
`n_null_`	How many model fits are null.
`n_peaks_`	How many peaks were fit for each model.
`null_inds_`	The indices for model fits that are null.

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

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

Parameters:

freqs1d array: Frequency values for the power spectra, in linear space.
power_spectra2d array, shape=[n_power_spectra, n_freqs]: Matrix of power values, in linear space.
freq_rangelist of [float, float], optional: Frequency range to restrict power spectra to. If not provided, keeps the entire range.
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

If called on an object with existing data and/or results these will be cleared by this method call.

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.

Parameters:

resultslist of list of FitResults: List of data objects containing the results from fitting power spectrum models.

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.

drop(inds)¶

Drop one or more model fit results from the object.

Parameters:

indsint or array_like of int or array_like of bool: Indices to drop model fit results for.

Notes

This method sets the model fits as null, and preserves the shape of the model fits.

fit(freqs=None, power_spectra=None, freq_range=None, n_jobs=1, progress=None)¶

Fit a group of power spectra.

Parameters:

freqs1d array, optional: Frequency values for the power_spectra, in linear space.
power_spectra2d array, shape: [n_power_spectra, n_freqs], optional: Matrix of power spectrum values, in linear space.
freq_rangelist of [float, float], optional: Frequency range to fit the model to. If not provided, fits the entire given range.
n_jobsint, optional, default: 1: Number of jobs to run in parallel. 1 is no parallelization. -1 uses all available cores.
progress{None, ‘tqdm’, ‘tqdm.notebook’}, optional: Which kind of progress bar to use. If None, no progress bar is used.

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_group(inds)¶

Get a Group model object with the specified sub-selection of model fits.

Parameters:

indsarray_like of int or array_like of bool: Indices to extract from the object.

Returns:

groupSpectralGroupModel: The requested selection of results data loaded into a new group model object.

get_meta_data()¶

Return data information from the current object.

Returns:

SpectrumMetaData: Object containing meta data from the current object.

get_model(ind, regenerate=True)¶

Get a model fit object for a specified index.

Parameters:

indint: The index of the model from group_results to access.
regeneratebool, optional, default: False: Whether to regenerate the model fits for the requested model.

Returns:

modelSpectralModel: The FitResults data loaded into a model object.

get_params(name, col=None)¶

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 across the group.
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:

outndarray: Requested data.

Raises:

NoModelError: If there are no model fit results available.
ValueError: If the input for the col input is not understood.

Notes

When extracting peak information (‘peak_params’ or ‘gaussian_params’), an additional column is appended to the returned array, indicating the index that the peak came from.

get_results()¶: Return the results run across a group of power spectra.

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 model fits.

load(file_name, file_path=None)¶

Load group data from file.

Parameters:

file_namestr: File to load data from.
file_pathPath or str, optional: Path to directory to load from. If None, loads from current directory.

property n_null_¶: How many model fits are null.

property n_peaks_¶: How many peaks were fit for each model.

property null_inds_¶: The indices for model fits that are null.

plot(**plot_kwargs)[source]¶

Plot a figure with subplots visualizing the parameters from a group model object.

Parameters:

**plot_kwargs: Additional plot related keyword arguments, with styling options managed by style_plot.

Raises:

NoModelError: If the model object does not have model fit data available to plot.

print_results(concise=False)[source]¶

Print out the group results.

Parameters:

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

report(freqs=None, power_spectra=None, freq_range=None, n_jobs=1, progress=None, **plot_kwargs)[source]¶

Fit a group of power spectra and display a report, with a plot and printed results.

Parameters:

freqs1d array, optional: Frequency values for the power_spectra, in linear space.
power_spectra2d array, shape: [n_power_spectra, n_freqs], optional: Matrix of power spectrum values, in linear space.
freq_rangelist of [float, float], optional: Frequency range to fit the model to. If not provided, fits the entire given range.
n_jobsint, optional, default: 1: Number of jobs to run in parallel. 1 is no parallelization. -1 uses all available cores.
progress{None, ‘tqdm’, ‘tqdm.notebook’}, optional: Which kind of progress bar to use. If None, no progress bar is used.
**plot_kwargs: Keyword arguments to pass into the plot method.

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 results and/or settings from group object. Saves out to a JSON file.

Parameters:

file_namestr or FileObject: File to save data to.
file_pathPath or str, optional: Path to directory to load from. 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 power spectra data.

Raises:

ValueError: If the data or save file specified are not understood.

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

“Save out an individual model report for a specified model fit.

Parameters:

indexint: Index of the model fit to save out.
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.

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

Generate and save out a PDF report for models of a group of power spectra.

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.

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: