FluxMaps#

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

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 norm_ul defined
`is_convertible_to_flux_sed_type`	Check whether differential sed type is convertible to integral sed type
`is_ul`	Whether data is an upper limit
`n_sigma`	n sigma
`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 from 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
`sed_type_plot_default`	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.
`iter_by_axis`(axis_name[, keepdims])	Create a set of FluxMaps by splitting along an axis.
`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 norm_ul defined

is_convertible_to_flux_sed_type#: Check whether differential sed type is convertible to integral sed type

is_ul#: Whether data is an upper limit

n_sigma#: n sigma

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 from 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

sed_type_plot_default#: 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)[source]#

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)[source]#

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)[source]#

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)[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

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)[source]#

Extract flux point at a given position.

Parameters

positionSkyCoord: Position where the flux points are extracted.

Returns

flux_pointsFluxPoints: Flux points object

iter_by_axis(axis_name, keepdims=False)[source]#

Create a set of FluxMaps by splitting along an axis.

Parameters

axis_namestr: Name of the axis to split on
keepdimsbool: Whether to keep the split axis with a single bin

Returns

flux_mapsFluxMap: FluxMap iteration

classmethod read(filename)[source]#

Read map dataset from file.

Parameters

filenamestr: Filename to read from.

Returns

flux_mapsFluxMaps: Flux maps object.

slice_by_idx(slices)[source]#

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=None, hdu_bands=None)[source]#

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=None)[source]#

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=None)[source]#

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