LightCurve¶

class gammapy.time.LightCurve(table)[source]¶

Bases: object

Lightcurve container.

The lightcurve data is stored in table.

For now we only support times stored in MJD format!

TODO: specification of format is work in progress See https://github.com/open-gamma-ray-astro/gamma-astro-data-formats/pull/61

Usage: Lightcurve

Parameters:	table : `Table` Table with lightcurve data

Attributes Summary

`time`	Time (`Time`).
`time_delta`	Time bin width (`TimeDelta`).
`time_format`	Time format (str).
`time_max`	Time bin end (`Time`).
`time_mid`	Time bin center (`Time`).
`time_min`	Time bin start (`Time`).
`time_scale`	Time scale (str).

Methods Summary

`compute_chisq`()	Calculate the chi-square test for `LightCurve`.
`compute_fvar`()	Calculate the fractional excess variance.
`plot`([ax, time_format, flux_unit])	Plot flux points.
`read`(filename, **kwargs)	Read from file.
`write`(filename, **kwargs)	Write to file.

Attributes Documentation

time¶: Time (Time).

time_delta¶: Time bin width (TimeDelta).

time_format¶: Time format (str).

time_max¶: Time bin end (Time).

time_mid¶: Time bin center (Time).

time_min¶: Time bin start (Time).

time_scale¶

Time scale (str).

Taken from table “TIMESYS” header. Common values: “TT” or “UTC”. Assumed default is “UTC”.

Methods Documentation

compute_chisq()[source]¶

Calculate the chi-square test for LightCurve.

Chisquare test is a variability estimator. It computes deviations from the expected value here mean value

Returns:	ChiSq, P-value : tuple of float or `ndarray` Tuple of Chi-square and P-value

compute_fvar()[source]¶

Calculate the fractional excess variance.

This method accesses the the FLUX and FLUX_ERR columns from the lightcurve data.

The fractional excess variance \(F_{var}\), an intrinsic variability estimator, is given by

\[F_{var} = \sqrt{\frac{S^{2} - \bar{\sigma^{2}}}{\bar{x}^{2}}}.\]

It is the excess variance after accounting for the measurement errors on the light curve \(\sigma\). \(S\) is the variance.

Returns:	fvar, fvar_err : `ndarray` Fractional excess variance.

References

[Vaughan2003]

“On characterizing the variability properties of X-ray light curves from active galaxies”, Vaughan et al. (2003) http://adsabs.harvard.edu/abs/2003MNRAS.345.1271V

plot(ax=None, time_format='mjd', flux_unit='cm-2 s-1', **kwargs)[source]¶

Plot flux points.

Parameters:

ax : Axes, optional.: The Axes object to be drawn on. If None, uses the current Axes.
time_format : {‘mjd’, ‘iso’}, optional: If ‘iso’, the x axis will contain Matplotlib dates. For formatting these dates see: https://matplotlib.org/gallery/ticks_and_spines/date_demo_rrule.html
flux_unit : str, Unit, optional: Unit of the flux axis
kwargs : dict: Keyword arguments passed to matplotlib.pyplot.errorbar()

Returns:

ax : Axes: Axis object

classmethod read(filename, **kwargs)[source]¶

Read from file.

Parameters:	filename : str Filename kwargs : dict Keyword arguments passed to `astropy.table.Table.read`.

write(filename, **kwargs)[source]¶

Write to file.

Parameters:	filename : str Filename kwargs : dict Keyword arguments passed to `astropy.table.Table.write`.