QLLightCurve#

class stixpy.timeseries.quicklook.QLLightCurve(data, meta=None, units=None, **kwargs)[source]#

Bases: GenericTimeSeries

Quicklook X-ray time series.

Nominally the quicklook data files contain the STIX timeseries data in five energy bands from 4-150 keV which are obtained by summing counts for all masked detectors and pixels into five predefined energy ranges. They are double buffered with default integration time of 4s and depth of 32 bits. Maximum rate is approximately 1MHz with one summed live time counter for the appropriate detectors.

Examples

>>> from stixpy.data import test
>>> from sunpy.timeseries import TimeSeries
>>> from stixpy.timeseries.quicklook import QLLightCurve
>>> ql_lc = TimeSeries("https://pub099.cs.technik.fhnw.ch/fits/L1/2020/05/06/QL/solo_L1_stix-ql-lightcurve_20200506_V02.fits")
>>> ql_lc
QLLightCurve
       <sunpy.time.timerange.TimeRange object at ...>
    Start: 2020-05-06 00:00:01
    End:   2020-05-06 23:59:57
    Center:2020-05-06 11:59:59
    Duration:0.9999538194444444 days or
           23.998891666666665 hours or
           1439.9334999999999 minutes or
           86396.01 seconds

Methods Summary

is_datasource_for(**kwargs)

Determines if the file corresponds to a STIX QL LightCurve TimeSeries.

plot([axes, columns])

Show a plot of the data.

Methods Documentation

classmethod is_datasource_for(**kwargs)[source]#

Determines if the file corresponds to a STIX QL LightCurve TimeSeries.

plot(axes=None, columns=None, **plot_args)[source]#

Show a plot of the data.

Parameters:

  • axes (Axes, optional) – If provided the image will be plotted on the given axes. Defaults to None, so the current axes will be used.

  • columns (list, optional) – Columns to plot, defaults to ‘counts’.

  • **plot_args (dict, optional) – Additional plot keyword arguments that are handed to pandas.DataFrame.plot().

Returns:

axes (Axes) – The plot axes.