Signal
- class mutis.signal.Signal(times, values, dvalues=None, fgen=None)[source]
Bases:
objectAnalysis and generation of a signal.
Class for a generic signal.
- Attributes
- times
numpy.ndarrayorpandas.Series Values of the time axis.
- values
numpy.ndarrayorpandas.Series Values of the signal axis.
- fgen
str Method to generate the synthetic signal.
- times
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)Generate synthethic light curves for this signal.
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.
- Parameters
- fgen: :str:
A valid fgen method name.
- fgen_params: :dict:
Parameters for fgen (e.g. for fgen=’lc_gen_ou’, a dict containing values for theta, mu and sigma).
- Returns
- axes: :tuple:
Tuple of three axes, on which: - The first plot show both the original signal and the synthetic one. - The second plot shows the histogram of the values taken by both signals. - The third plot shows their PSD.