FluxMaps

class gammapy.estimators.FluxMaps(data, reference_model, meta=None, gti=None, filter_success_nan=True)

Bases: object

A flux map / points container.

It contains a set of Map objects that store the estimated flux as a function of energy as well as associated quantities (typically errors, upper limits, delta TS and possibly raw quantities such counts, excesses etc). It also contains a reference model to convert the flux values in different formats. Usually, this should be the model used to produce the flux map.

The associated map geometry can use a RegionGeom to store the equivalent of flux points, or a WcsGeom/HpxGeom to store an energy dependent flux map.

The container relies internally on the ‘Likelihood’ SED type defined in SED and offers convenience properties to convert to other flux formats, namely: dnde, flux, eflux or e2dnde. The conversion is done according to the reference model spectral shape.

Parameters

datadict of Map

the maps dictionary. Expected entries are the following: * norm : the norm factor * norm_err : optional, the error on the norm factor. * norm_errn : optional, the negative error on the norm factor. * norm_errp : optional, the positive error on the norm factor. * norm_ul : optional, the upper limit on the norm factor. * norm_scan : optional, the norm values of the test statistic scan. * stat_scan : optional, the test statistic scan values. * ts : optional, the delta TS associated with the flux value. * sqrt_ts : optional, the square root of the TS, when relevant. * success : optional, a boolean tagging the validity of the estimation

reference_modelSkyModel, optional

the reference model to use for conversions. If None, a model consisting of a point source with a power law spectrum of index 2 is assumed.

metadict, optional

Dict of metadata.

gtiGTI, optional

Maps GTI information.

filter_success_nanboolean, optional

Set fitted norm and error to NaN when the fit has not succeeded.

Attributes Summary

available_quantities	Available quantities
counts	Predicted counts null hypothesis
dnde	Return differential flux (dnde) SED values.
dnde_err	Return differential flux (dnde) SED errors.
dnde_errn	Return differential flux (dnde) SED negative errors.
dnde_errp	Return differential flux (dnde) SED positive errors.
dnde_ref	Reference differential flux
dnde_ul	Return differential flux (dnde) SED upper limit.
e2dnde	Return differential energy flux (e2dnde) SED values.
e2dnde_err	Return differential energy flux (e2dnde) SED errors.
e2dnde_errn	Return differential energy flux (e2dnde) SED negative errors.
e2dnde_errp	Return differential energy flux (e2dnde) SED positive errors.
e2dnde_ref	Reference differential flux * energy ** 2
e2dnde_ul	Return differential energy flux (e2dnde) SED upper limit.
eflux	Return energy flux (eflux) SED values.
eflux_err	Return energy flux (eflux) SED errors.
eflux_errn	Return energy flux (eflux) SED negative errors.
eflux_errp	Return energy flux (eflux) SED positive errors.
eflux_ref	Reference energy flux
eflux_ul	Return energy flux (eflux) SED upper limits.
energy_axis	Energy axis (MapAxis)
energy_max	Energy max
energy_min	Energy min
energy_ref	Reference energy.
filter_success_nan
flux	Return integral flux (flux) SED values.
flux_err	Return integral flux (flux) SED values.
flux_errn	Return integral flux (flux) SED negative errors.
flux_errp	Return integral flux (flux) SED positive errors.
flux_ref	Reference integral flux
flux_ul	Return integral flux (flux) SED upper limits.
geom	Reference map geometry (Geom)
has_any_ts	Whether the flux estimate has either sqrt(ts) or ts defined
has_stat_profiles	Whether the flux estimate has stat profiles
has_success	Whether the flux estimate has the fit status
has_ul	Whether the flux estimate has either sqrt(ts) or ts defined
is_ul	Whether data is an upper limit
n_sigma	n sigma UL
n_sigma_ul	n sigma UL
niter	Number of iterations of fit
norm	Norm values
norm_err	Norm error
norm_errn	Negative norm error
norm_errp	Positive norm error
norm_ul	Norm upper limit
npred	Predicted counts from best fit hypothesis
npred_background	Predicted background counts from best fit hypothesis
npred_excess	Predicted excess count rom best fit hypothesis
npred_excess_err	Predicted excess counts error
npred_excess_errn	Predicted excess counts negative error
npred_excess_errp	Predicted excess counts positive error
npred_excess_ref	Predicted excess reference counts
npred_excess_ul	Predicted excess counts upper limits
reference_model	Reference model (SkyModel)
reference_model_default	Reference model default (SkyModel)
reference_spectral_model	Reference spectral model (SpectralModel)
sed_type_init	Initial sed type
sqrt_ts	sqrt(TS) as defined by:
sqrt_ts_threshold_ul	sqrt(TS) threshold for upper limits
stat	Fit statistic value
stat_null	Fit statistic value for the null hypothesis
stat_scan	Fit statistic scan value
success	Fit success flag
ts	ts map (Map)
ts_scan	ts scan (Map)

Methods Summary

all_quantities(sed_type)	All quantities allowed for a given sed type.
from_hdulist(hdulist[, hdu_bands, sed_type])	Create flux map dataset from list of HDUs.
from_maps(maps[, sed_type, reference_model, …])	Create FluxMaps from a dictionary of maps.
from_stack(maps, axis[, meta])	Create flux points by stacking list of flux points.
get_flux_points([position])	Extract flux point at a given position.
read(filename)	Read map dataset from file.
slice_by_idx(slices)	Slice flux maps by idx
to_hdulist([sed_type, hdu_bands])	Convert flux map to list of HDUs.
to_maps([sed_type])	Return maps in a given SED type.
write(filename[, filename_model, overwrite, …])	Write flux map to file.

Attributes Documentation

available_quantities

Available quantities

counts

Predicted counts null hypothesis

dnde

Return differential flux (dnde) SED values.

dnde_err

Return differential flux (dnde) SED errors.

dnde_errn

Return differential flux (dnde) SED negative errors.

dnde_errp

Return differential flux (dnde) SED positive errors.

dnde_ref

Reference differential flux

dnde_ul

Return differential flux (dnde) SED upper limit.

e2dnde

Return differential energy flux (e2dnde) SED values.

e2dnde_err

Return differential energy flux (e2dnde) SED errors.

e2dnde_errn

Return differential energy flux (e2dnde) SED negative errors.

e2dnde_errp

Return differential energy flux (e2dnde) SED positive errors.

e2dnde_ref

Reference differential flux * energy ** 2

e2dnde_ul

Return differential energy flux (e2dnde) SED upper limit.

eflux

Return energy flux (eflux) SED values.

eflux_err

Return energy flux (eflux) SED errors.

eflux_errn

Return energy flux (eflux) SED negative errors.

eflux_errp

Return energy flux (eflux) SED positive errors.

eflux_ref

Reference energy flux

eflux_ul

Return energy flux (eflux) SED upper limits.

energy_axis

Energy axis (MapAxis)

energy_max

Energy max

Returns

energy_maxQuantity

Upper bound of energy bin.

energy_min

Energy min

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 FluxEstimate.data.

Returns

energy_refQuantity

Reference energy.

filter_success_nan

flux

Return integral flux (flux) SED values.

flux_err

Return integral flux (flux) SED values.

flux_errn

Return integral flux (flux) SED negative errors.

flux_errp

Return integral flux (flux) SED positive errors.

flux_ref

Reference integral flux

flux_ul

Return integral flux (flux) SED upper limits.

geom

Reference map geometry (Geom)

has_any_ts

Whether the flux estimate has either sqrt(ts) or ts defined

has_stat_profiles

Whether the flux estimate has stat profiles

has_success

Whether the flux estimate has the fit status

has_ul

Whether the flux estimate has either sqrt(ts) or ts defined

is_ul

Whether data is an upper limit

n_sigma

n sigma UL

n_sigma_ul

n sigma UL

niter

Number of iterations of fit

norm

Norm values

norm_err

Norm error

norm_errn

Negative norm error

norm_errp

Positive norm error

norm_ul

Norm upper limit

npred

Predicted counts from best fit hypothesis

npred_background

Predicted background counts from best fit hypothesis

npred_excess

Predicted excess count rom best fit hypothesis

npred_excess_err

Predicted excess counts error

npred_excess_errn

Predicted excess counts negative error

npred_excess_errp

Predicted excess counts positive error

npred_excess_ref

Predicted excess reference counts

npred_excess_ul

Predicted excess counts upper limits

reference_model

Reference model (SkyModel)

reference_model_default

Reference model default (SkyModel)

reference_spectral_model

Reference spectral model (SpectralModel)

sed_type_init

Initial sed type

sqrt_ts

sqrt(TS) as defined by:

\[\begin{split}\sqrt{TS} = \left \{ \begin{array}{ll} -\sqrt{TS} & : \text{if} \ norm < 0 \\ \sqrt{TS} & : \text{else} \end{array} \right.\end{split}\]

Returns

sqrt_tsMap

sqrt(TS) map

sqrt_ts_threshold_ul

sqrt(TS) threshold for upper limits

stat

Fit statistic value

stat_null

Fit statistic value for the null hypothesis

stat_scan

Fit statistic scan value

success

Fit success flag

ts

ts map (Map)

ts_scan

ts scan (Map)

Methods Documentation

static all_quantities(sed_type)

All quantities allowed for a given sed type.

Parameters

sed_type{“likelihood”, “dnde”, “e2dnde”, “flux”, “eflux”}

Sed type.

Returns

listlist of str

All allowed quantities for a given sed type.

classmethod from_hdulist(hdulist, hdu_bands=None, sed_type=None)

Create flux map dataset from list of HDUs.

Parameters

hdulistHDUList

List of HDUs.

hdu_bandsstr

Name of the HDU with the BANDS table. Default is ‘BANDS’ If set to None, each map should have its own hdu_band

sed_type{“dnde”, “flux”, “e2dnde”, “eflux”, “likelihood”}

Sed type

Returns

flux_mapsFluxMaps

Flux maps object.

classmethod from_maps(maps, sed_type=None, reference_model=None, gti=None, meta=None)

Create FluxMaps from a dictionary of maps.

Parameters

mapsMaps

Maps object containing the input maps.

sed_typestr

SED type of the input maps. Default is Likelihood

reference_modelSkyModel, optional

Reference model to use for conversions. Default in None. If None, a model consisting of a point source with a power law spectrum of index 2 is assumed.

gtiGTI

Maps GTI information. Default is None.

metadict

Meta dict.

Returns

flux_mapsFluxMaps

Flux maps object.

classmethod from_stack(maps, axis, meta=None)

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

mapslist of FluxMaps

List of maps to stack.

axisMapAxis

New axis to create

Returns

flux_mapsFluxMaps

Stacked flux maps along axis.

get_flux_points(position=None)

Extract flux point at a given position.

Parameters

positionSkyCoord

Position where the flux points are extracted.

Returns

flux_pointsFluxPoints

Flux points object

classmethod read(filename)

Read map dataset from file.

Parameters

filenamestr

Filename to read from.

Returns

flux_mapsFluxMaps

Flux maps object.

slice_by_idx(slices)

Slice flux maps by idx

Parameters

slicesdict

Dict of axes names and integers or slice object pairs. Contains one element for each non-spatial dimension. For integer indexing the corresponding axes is dropped from the map. Axes not specified in the dict are kept unchanged.

Returns

flux_mapsFluxMaps

Sliced flux maps object.

to_hdulist(sed_type='likelihood', hdu_bands=None)

Convert flux map to list of HDUs.

For now, one cannot export the reference model.

Parameters

sed_typestr

sed type to convert to. Default is Likelihood

hdu_bandsstr

Name of the HDU with the BANDS table. Default is ‘BANDS’ If set to None, each map will have its own hdu_band

Returns

hdulistHDUList

Map dataset list of HDUs.

to_maps(sed_type='likelihood')

Return maps in a given SED type.

Parameters

sed_type{“likelihood”, “dnde”, “e2dnde”, “flux”, “eflux”}

sed type to convert to. Default is Likelihood

Returns

mapsMaps

Maps object containing the requested maps.

write(filename, filename_model=None, overwrite=False, sed_type='likelihood')

Write flux map to file.

Parameters

filenamestr

Filename to write to.

filename_modelstr

Filename of the model (yaml format). If None, keep string before ‘.’ and add ‘_model.yaml’ suffix

overwritebool

Overwrite file if it exists.

sed_typestr

sed type to convert to. Default is likelihood