QLBackground#

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

Bases: GenericTimeSeries

Quicklook X-ray time series from the background detector.

Nominally QL background files contain counts from the background detector summed over five specified energy ranges. These QL data are double buffered into accumulators of 32bit depth. Maximum rate is approximately 30kHz and one live time counter is available. Integration time is parameter with default value of 32s

Examples

>>> from stixpy.data import test
>>> from sunpy.timeseries import TimeSeries
>>> from stixpy.timeseries.quicklook import QLLightCurve
>>> ql_bg = TimeSeries("https://pub099.cs.technik.fhnw.ch/fits/L1/2020/05/06/QL/"
...                    "solo_L1_stix-ql-background_20200506_V02.fits")
>>> ql_bg
<stixpy.timeseries.quicklook.QLBackground object at ...
SunPy TimeSeries
----------------
 Observatory:                SOLO/STIX
 Instrument:                 STIX
 Channel(s):                 control_index<br>timedel<br>triggers<br>triggers_err<br>4.0-10.0<br>10.0-15.0<br>15.0-25.0<br>25.0-50.0<br>50.0-150.0<br>4.0-10.0_err<br>10.0-15.0_err<br>15.0-25.0_err<br>25.0-50.0_err<br>50.0-150.0_err
 Start Date:                 2020-05-06 00:00:04
 End Date:           2020-05-06 23:59:56
 Center Date:                2020-05-06 11:59:59
 Resolution:                 8.03 s
 Samples per Channel:                10758
 Data Range(s):              control_index    1.60E+01<br>timedel          0.00E+00<br>triggers         1.10E+03<br>triggers_err     3.23E+01<br>4.0-10.0         7.72E+01<br>10.0-15.0        1.34E+02<br>15.0-25.0        6.07E+01<br>25.0-50.0        2.17E+01<br>50.0-150.0       4.95E+00<br>4.0-10.0_err     9.25E+00<br>10.0-15.0_err    1.85E+01<br>15.0-25.0_err    1.85E+01<br>25.0-50.0_err    1.85E+01<br>50.0-150.0_err   9.25E+00
 Units:              None<br>ct<br>s
                          control_index  timedel  ...  25.0-50.0_err  50.0-150.0_err
 time                                             ...
 2020-05-06 00:00:03.531              3      800  ...       2.345208        0.707107
 2020-05-06 00:00:11.531              3      800  ...       2.345208        0.707107
 2020-05-06 00:00:19.531              3      800  ...       2.345208        0.000000
 2020-05-06 00:00:27.531              3      800  ...       2.345208        0.000000
 2020-05-06 00:00:35.531              3      800  ...       2.345208        0.000000
 ...                                ...      ...  ...            ...             ...
 2020-05-06 23:59:23.531              2      800  ...       0.707107        1.224745
 2020-05-06 23:59:31.531              2      800  ...       0.000000        2.345208
 2020-05-06 23:59:39.531              2      800  ...       0.000000        4.636809
 2020-05-06 23:59:47.531              2      800  ...       0.000000        1.224745
 2020-05-06 23:59:55.531              2      800  ...       0.707107        2.345208

 [10758 rows x 14 columns]

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 (str, 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.

QLBackground#

This Page