FluxPoints¶

class gammapy.estimators.FluxPoints(table)[source]¶

Bases: object

Flux points container.

The supported formats are described here: SED

In summary, the following formats and minimum required columns are:

Format dnde: columns e_ref and dnde
Format e2dnde: columns e_ref, e2dnde
Format flux: columns e_min, e_max, flux
Format eflux: columns e_min, e_max, eflux

Parameters

tableTable: Table with flux point data

Examples

The FluxPoints object is most easily created by reading a file with flux points given in one of the formats documented above:

from gammapy.estimators import FluxPoints
filename = '$GAMMAPY_DATA/hawc_crab/HAWC19_flux_points.fits'
flux_points = FluxPoints.read(filename)
flux_points.plot()

An instance of FluxPoints can also be created by passing an instance of astropy.table.Table, which contains the required columns, such as 'e_ref' and 'dnde'. The corresponding sed_type has to be defined in the meta data of the table:

from astropy import units as u
from astropy.table import Table
from gammapy.estimators import FluxPoints
from gammapy.modeling.models import PowerLawSpectralModel

table = Table()
pwl = PowerLawSpectralModel()
e_ref = np.logspace(0, 2, 7) * u.TeV
table['e_ref'] = e_ref
table['dnde'] = pwl(e_ref)
table.meta['SED_TYPE'] = 'dnde'

flux_points = FluxPoints(table)
flux_points.plot()

If you have flux points in a different data format, the format can be changed by renaming the table columns and adding meta data:

from astropy import units as u
from astropy.table import Table
from gammapy.estimators import FluxPoints

table = Table.read('$GAMMAPY_DATA/tests/spectrum/flux_points/flux_points_ctb_37b.txt',
                   format='ascii.csv', delimiter=' ', comment='#')
table.meta['SED_TYPE'] = 'dnde'
table.rename_column('Differential_Flux', 'dnde')
table['dnde'].unit = 'cm-2 s-1 TeV-1'

table.rename_column('lower_error', 'dnde_errn')
table['dnde_errn'].unit = 'cm-2 s-1 TeV-1'

table.rename_column('upper_error', 'dnde_errp')
table['dnde_errp'].unit = 'cm-2 s-1 TeV-1'

table.rename_column('E', 'e_ref')
table['e_ref'].unit = 'TeV'

flux_points = FluxPoints(table)
flux_points.plot()

Note: In order to reproduce the example you need the tests datasets folder. You may download it with the command gammapy download datasets --tests --out $GAMMAPY_DATA

Attributes

tableTable: Table with flux point data

Attributes Summary

`energy_edges`	Edges of the energy bin.
`energy_max`	Upper bound of energy bin.
`energy_min`	Lower bound of energy bin.
`energy_ref`	Reference energy.
`is_ul`
`sed_type`	SED type (str).
`table_formatted`	Return formatted version of the flux points table.

Methods Summary

`drop_ul`()	Drop upper limit flux points.
`plot`([ax, energy_unit, flux_unit, energy_power])	Plot flux points.
`plot_ts_profiles`([ax, energy_unit, …])	Plot fit statistic SED profiles as a density plot.
`read`(filename, **kwargs)	Read flux points.
`stack`(flux_points)	Create flux points by stacking list of flux points.
`to_sed_type`(sed_type[, method, model, …])	Convert to a different SED type (return new `FluxPoints`).
`write`(filename, **kwargs)	Write flux points.

Attributes Documentation

energy_edges¶

Edges of the energy bin.

Returns

energy_edgesQuantity: Energy edges.

energy_max¶

Upper bound of energy bin.

Defined by energy_max column in table.

Returns

energy_maxQuantity: Upper bound of energy bin.

energy_min¶

Lower bound of energy bin.

Defined by energy_min column in FluxPoints.table.

Returns

energy_minQuantity: Lower bound of energy bin.

energy_ref¶

Reference energy.

Defined by energy_ref column in FluxPoints.table or computed as log center, if energy_min and energy_max columns are present in FluxPoints.table.

Returns

energy_refQuantity: Reference energy.

is_ul¶

sed_type¶

SED type (str).

One of: {‘dnde’, ‘e2dnde’, ‘flux’, ‘eflux’}

table_formatted¶: Return formatted version of the flux points table. Used for pretty printing

Methods Documentation

drop_ul()[source]¶

Drop upper limit flux points.

Returns

flux_pointsFluxPoints: Flux points with upper limit points removed.

Examples

>>> from gammapy.estimators import FluxPoints
>>> filename = '$GAMMAPY_DATA/tests/spectrum/flux_points/flux_points.fits'
>>> flux_points = FluxPoints.read(filename)
>>> print(flux_points)
FluxPoints(sed_type="flux", n_points=24)
>>> print(flux_points.drop_ul())
FluxPoints(sed_type="flux", n_points=19)

Note: In order to reproduce the example you need the tests datasets folder. You may download it with the command gammapy download datasets --tests --out $GAMMAPY_DATA

plot(ax=None, energy_unit='TeV', flux_unit=None, energy_power=0, **kwargs)[source]¶

Plot flux points.

Parameters

axAxes: Axis object to plot on.
energy_unitstr, Unit, optional: Unit of the energy axis
flux_unitstr, Unit, optional: Unit of the flux axis
energy_powerint: Power of energy to multiply y axis with
kwargsdict: Keyword arguments passed to matplotlib.pyplot.errorbar()

Returns

axAxes: Axis object

plot_ts_profiles(ax=None, energy_unit='TeV', add_cbar=True, y_values=None, y_unit=None, **kwargs)[source]¶

Plot fit statistic SED profiles as a density plot.

Parameters

axAxes: Axis object to plot on.
energy_unitstr, Unit, optional: Unit of the energy axis
y_valuesastropy.units.Quantity: Array of y-values to use for the fit statistic profile evaluation.
y_unitstr or astropy.units.Unit: Unit to use for the y-axis.
add_cbarbool: Whether to add a colorbar to the plot.
kwargsdict: Keyword arguments passed to matplotlib.pyplot.pcolormesh()

Returns

axAxes: Axis object

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

Read flux points.

Parameters

filenamestr: Filename
kwargsdict: Keyword arguments passed to astropy.table.Table.read.

classmethod stack(flux_points)[source]¶

Create flux points by stacking list of flux points.

The first FluxPoints object in the list is taken as a reference to infer column names and units for the stacked object.

Parameters

flux_pointslist of FluxPoints: List of flux points to stack.

Returns

flux_pointsFluxPoints: Flux points without upper limit points.

to_sed_type(sed_type, method='log_center', model=None, pwl_approx=False)[source]¶

Convert to a different SED type (return new FluxPoints).

See: https://ui.adsabs.harvard.edu/abs/1995NIMPA.355..541L for details on the 'lafferty' method.

Parameters

sed_type{‘dnde’}

SED type to convert to.

modelSpectralModel

Spectral model assumption. Note that the value of the amplitude parameter does not matter. Still it is recommended to use something with the right scale and units. E.g. amplitude = 1e-12 * u.Unit('cm-2 s-1 TeV-1')

method{‘lafferty’, ‘log_center’, ‘table’}

Flux points energy_ref estimation method:

'laferty' Lafferty & Wyatt model-based energy_ref

'log_center' log bin center energy_ref

'table' using column ‘energy_ref’ from input flux_points

pwl_approxbool

Use local power law appoximation at energy_ref to compute differential flux from the integral flux. This method is used by the Fermi-LAT catalogs.

Returns

flux_pointsFluxPoints: Flux points including differential quantity columns dnde and dnde_err (optional), dnde_ul (optional).

Examples

>>> from gammapy.estimators import FluxPoints
>>> from gammapy.modeling.models import PowerLawSpectralModel
>>> filename = '$GAMMAPY_DATA/tests/spectrum/flux_points/flux_points.fits'
>>> flux_points = FluxPoints.read(filename)
>>> model = PowerLawSpectralModel(index=2.2)
>>> flux_points_dnde = flux_points.to_sed_type('dnde', model=model)

Note: In order to reproduce the example you need the tests datasets folder. You may download it with the command gammapy download datasets --tests --out $GAMMAPY_DATA

write(filename, **kwargs)[source]¶

Write flux points.

Parameters

filenamestr: Filename
kwargsdict: Keyword arguments passed to astropy.table.Table.write.