FlareList#

class stixpy.product.sources.FlareList(*, meta, control, data, energies=None, idb_versions=None)[source]#

Bases: GenericProduct

STIX L3 Flare List product with reconstructed source locations.

Examples

>>> from stixpy.data import test
>>> from stixpy.product import Product
>>> fl = Product(test.STIX_L3_FLARELIST_SEP2024)
>>> fl
FlareList
   <sunpy.time.timerange.TimeRange object at ...
    Start: 2024-09-01 00:06:44
    End:   2024-10-01 00:47:10
    Center:2024-09-16 00:26:57
    Duration:30.028079074074075 days or
           720.6738977777778 hours or
           43240.433866666666 minutes or
           2594426.032 seconds

    2360 flares

Generic product composed of meta, control, data and optionally idb, and energy information

Parameters:

control (stix_parser.products.quicklook.Control) – Table containing control information
data (stix_parser.products.quicklook.Data) – Table containing data

Attributes Summary

`attenuator_in`
`duration`
`end_time`
`energies`
`flare_id`
`flare_location`	Flare location in ICRS.
`flare_location_hgs`	Flare location in HeliographicStonyhurst.
`goes_class`
`goes_flux`
`level`
`peak_time`
`service_subtype`	Service subtype
`service_type`	Service type
`solo_location_hgs`	Solar Orbiter location in HeliographicStonyhurst at the time of location determination.
`ssid`	Science Structure ID for product
`start_time`
`time_range`
`visible_from_earth`

Methods Summary

`concatenate`(others)	Concatenate two or more FlareList products into one.
`is_datasource_for`(, meta, *kwargs)
`plot_locations`([observer, axes])	Plot flare locations on sky.
`plot_timeseries`([axes])	Scatter plot of per-flare peak counts per energy band vs peak time.

Attributes Documentation

attenuator_in#

duration#

end_time#

energies#

flare_id#

flare_location#: Flare location in ICRS. Entries without a solution have NaN coordinates.

flare_location_hgs#: Flare location in HeliographicStonyhurst. Entries without a solution have NaN coordinates.

goes_class#

goes_flux#

level#

peak_time#

service_subtype#: Service subtype

service_type#: Service type

solo_location_hgs#: Solar Orbiter location in HeliographicStonyhurst at the time of location determination.

ssid#: Science Structure ID for product

start_time#

time_range#

visible_from_earth#

Methods Documentation

concatenate(others)[source]#

Concatenate two or more FlareList products into one.

Parameters:: others (FlareList or list of FlareList)
Returns:: FlareList

classmethod is_datasource_for(*, meta, **kwargs)[source]#

plot_locations(observer='earth', axes=None, **scatter_kwargs)[source]#

Plot flare locations on sky.

Parameters:

observer ({"earth", "solo", "hgs", "carrington"}) –
Reference frame / point of view:
- "hgs" – Heliographic Stonyhurst lon/lat (Earth-anchored prime meridian)
- "earth" – Helioprojective (Tx/Ty) as seen from Earth
- "solo" – Helioprojective (Tx/Ty) as seen from Solar Orbiter
- "carrington" – Heliographic Carrington lon/lat (alias "hgc"); the prime meridian rotates with the Sun, so an active region keeps the same longitude across many days — useful when the catalogue spans weeks or months, where solar rotation otherwise smears persistent sources into streaks. The HGC transform uses each flare’s own Solar Orbiter position as the observer.
axes (matplotlib.axes.Axes, optional)
**scatter_kwargs – Passed to scatter.

Returns:

matplotlib.axes.Axes

plot_timeseries(axes=None, **scatter_kwargs)[source]#

Scatter plot of per-flare peak counts per energy band vs peak time.

A scatter (rather than line) plot is used because flares are discrete events — connecting them with a line would imply a continuity that doesn’t exist.

Parameters:

axes (matplotlib.axes.Axes, optional)
**scatter_kwargs – Passed to scatter.

Returns:

list of matplotlib.collections.PathCollection