timescales.fit.ACF

class timescales.fit.ACF(lags=None, corrs=None, fs=None)

Autocorrelation function class.

Parameters:

lags1d array

Time lag definitions.

corrs1d or 2d array

Autocorrelation coefficients.

fsfloat

Sampling rate, in Hz.

Attributes:

corrs_fit1d array

Autocorrelation full fit.

params1d array

Optimized parameters.

param_nameslist of str

Parameter names in order of params.

rsqfloat

R-squared of the full fit.

guesslist, optional, default: None

Estimated parameters as either: [tau, height, offset] when with_cos is False, or [exp_tau, osc_tau, osc_gamma, osc_freq, amp_ratio, height, offset].

boundslist, optional, default: None

Parameters bounds as [(*lower_bounds), (*upper_bounds)].

Notes

Parameters may be set on initialization or using the compute_acf method.

__init__(lags=None, corrs=None, fs=None)

Initialize object.

Methods

__init__([lags, corrs, fs])	Initialize object.
compute_acf(sig, fs[, nlags, n_jobs, progress])	Compute autocorrelation.
fit([lags, corrs, gen_fits, gen_components, ...])	Fit without an oscillitory component.
gen_corrs_fit([gen_components])	Generate fit and r-squared.
plot([ax, title])	Plot ACF.

compute_acf(sig, fs, nlags=None, n_jobs=-1, progress=None)

Compute autocorrelation.

Parameters:

sig1d or 2d array

Voltage time series or spike counts.

fsfloat

Sampling rate, in Hz.

nlagsint, optional, default: None

Number of lags to compute. None defaults to the sampling rate, fs.

n_jobsint, optional, default: -1

Number of jobs to run in parralel, when corrs is 2d. Default is equal to multiprocessing’s cpu_count().

progress{None, ‘tqdm’, ‘tqdm.notebook’}

Specify whether to display a progress bar. Uses ‘tqdm’, if installed.

fit(lags=None, corrs=None, gen_fits=True, gen_components=False, with_cos=False, guess=None, bounds=None, maxfev=1000, n_jobs=-1, progress=None)

Fit without an oscillitory component.

Parameters:

lags1d array

Time lag definitions.

corrs1d or 2d array

Autocorrelation coefficients.

gen_fitsbool, optional, default: False

Generates fit array and r-squared when True. Does not generate full fits when False to prevent OOM.

gen_componentsbool, optional, default: False

When gen_fits and with_cos are True, the exponential decay and cosine components are be generated separately when this parameter is True.

with_cosbool, optional, default: False

Includes oscillatory component as a damped cosine.

guesslist, optional, default: None

Estimated parameters as either: [tau, height, offset] when with_cos is False, or [exp_tau, osc_tau, osc_gamma, osc_freq, amp_ratio, height, offset].

boundslist, optional, default: None

Parameters bounds as [(*lower_bounds), (*upper_bounds)].

maxfevint

Maximum number of fitting iterations.

n_jobsint

Number of jobs to run in parralel, when corrs is 2d.

progress{None, ‘tqdm’, ‘tqdm.notebook’}

Specify whether to display a progress bar. Uses ‘tqdm’, if installed.

gen_corrs_fit(gen_components=False)

Generate fit and r-squared.

Parameters:

gen_componentsbool, optional, default: True

Generates oscillatory and exponential components separately, in additon to combined, when True.

plot(ax=None, title=None)

Plot ACF.

Parameters:

axAxesSubplot, optional, default: None

Axis to plot on.