Signal

class mutis.signal.Signal(times, values, dvalues=None, fgen=None)[source]

Bases: object

Analysis and generation of a signal.

Description goes here.

Parameters

timesnumpy.ndarray or pandas.Series: Values of the time axis.
valuesnumpy.ndarray or pandas.Series: Values of the signal axis.
fgenstr: Method used to generate the synthetic signal.

Methods Summary

`OU_fit`([bins, rang, a, b])	Fit the signal to an OU stochastic process, using several statistical approaches.
`check_gen`([fgen, fgen_params, fpsd])	Check the generation of synthetic signals.
`gen_synth`(samples)	Description goes here.
`pdf`(xx, ll, mu)	Helper func to fit pdf as a curve.
`plot`([ax])

Methods Documentation

OU_fit(bins=None, rang=None, a=1e-05, b=100)[source]

Fit the signal to an OU stochastic process, using several statistical approaches.

This function tries to fit the signal to an OU stochastic process using both basic curve fitting and the Maximum Likelihood Estimation method, and returns some plots of the signals and its properties, and the estimated parameters.

check_gen(fgen=None, fgen_params=None, fpsd='lombscargle', **axes)[source]

Check the generation of synthetic signals.

This function checks the generation of a synthetic light curve.

gen_synth(samples)[source]: Description goes here.

static pdf(xx, ll, mu)[source]: Helper func to fit pdf as a curve.

plot(ax=None)[source]