MapDataset¶
-
class
gammapy.datasets.
MapDataset
(models=None, counts=None, exposure=None, mask_fit=None, psf=None, edisp=None, name=None, evaluation_mode='local', mask_safe=None, gti=None)[source]¶ Bases:
gammapy.datasets.Dataset
Perform sky model likelihood fit on maps.
- Parameters
- models
Models
Source sky models.
- counts
WcsNDMap
Counts cube
- exposure
WcsNDMap
Exposure cube
- mask_fit
WcsNDMap
Mask to apply to the likelihood for fitting.
- psf
PSFKernel
orPSFMap
PSF kernel
- edisp
EDispKernel
orEDispMap
Energy dispersion kernel
- evaluation_mode{“local”, “global”}
Model evaluation mode. The “local” mode evaluates the model components on smaller grids to save computation time. This mode is recommended for local optimization algorithms. The “global” evaluation mode evaluates the model components on the full map. This mode is recommended for global optimization algorithms.
- mask_safe
WcsNDMap
Mask defining the safe data range.
- gti
GTI
GTI of the observation or union of GTI if it is a stacked observation
- models
Attributes Summary
Shape of the counts or background data (tuple)
Model evaluators
Combined fit and safe mask
Models (
Models
).Methods Summary
copy
(self[, name])A deep copy.
create
(geom[, energy_axis_true, migra_axis, …])Create a MapDataset object with zero filled maps.
cutout
(self, position, width[, mode, name])Cutout map dataset.
fake
(self[, random_state])Simulate fake counts for the current model and reduced IRFs.
from_dict
(data, models)Create from dicts and models list generated from YAML serialization.
from_geoms
(geom, geom_exposure, geom_psf, …)Create a MapDataset object with zero filled maps according to the specified geometries
from_hdulist
(hdulist[, name])Create map dataset from list of HDUs.
npred
(self)Predicted source and background counts (
Map
).plot_residuals
(self[, method, …])Plot spatial and spectral residuals.
read
(filename[, name])Read map dataset from file.
residuals
(self[, method])Compute residuals map.
stack
(self, other)Stack another dataset in place.
stat_array
(self)Likelihood per bin given the current model parameters
stat_sum
(self)Total likelihood given the current model parameters.
to_dict
(self[, filename])Convert to dict for YAML serialization.
to_hdulist
(self)Convert map dataset to list of HDUs.
to_image
(self[, spectrum, name])Create images by summing over the energy axis.
to_spectrum_dataset
(self, on_region[, …])Return a ~gammapy.spectrum.SpectrumDataset from on_region.
write
(self, filename[, overwrite])Write map dataset to file.
Attributes Documentation
-
data_shape
¶ Shape of the counts or background data (tuple)
-
evaluators
¶ Model evaluators
-
mask
¶ Combined fit and safe mask
-
name
¶
-
stat_type
= 'cash'¶
-
tag
= 'MapDataset'¶
Methods Documentation
-
copy
(self, name=None)¶ A deep copy.
-
classmethod
create
(geom, energy_axis_true=None, migra_axis=None, rad_axis=None, binsz_irf=None, reference_time='2000-01-01', name=None, **kwargs)[source]¶ Create a MapDataset object with zero filled maps.
- Parameters
- geom
WcsGeom
Reference target geometry in reco energy, used for counts and background maps
- energy_axis_true
MapAxis
True energy axis used for IRF maps
- migra_axis
MapAxis
Migration axis for the energy dispersion map
- rad_axis
MapAxis
Rad axis for the psf map
- binsz_irffloat
IRF Map pixel size in degrees.
- reference_time
Time
the reference time to use in GTI definition
- namestr
Name of the returned dataset.
- geom
- Returns
- empty_maps
MapDataset
A MapDataset containing zero filled maps
- empty_maps
-
cutout
(self, position, width, mode='trim', name=None)[source]¶ Cutout map dataset.
- Parameters
- position
SkyCoord
Center position of the cutout region.
- widthtuple of
Angle
Angular sizes of the region in (lon, lat) in that specific order. If only one value is passed, a square region is extracted.
- mode{‘trim’, ‘partial’, ‘strict’}
Mode option for Cutout2D, for details see
Cutout2D
.- namestr
Name of the new dataset.
- position
- Returns
- cutout
MapDataset
Cutout map dataset.
- cutout
-
fake
(self, random_state='random-seed')[source]¶ Simulate fake counts for the current model and reduced IRFs.
This method overwrites the counts defined on the dataset object.
- Parameters
- random_state{int, ‘random-seed’, ‘global-rng’,
RandomState
} Defines random number generator initialisation. Passed to
get_random_state
.
- random_state{int, ‘random-seed’, ‘global-rng’,
-
classmethod
from_dict
(data, models)[source]¶ Create from dicts and models list generated from YAML serialization.
-
classmethod
from_geoms
(geom, geom_exposure, geom_psf, geom_edisp, reference_time='2000-01-01', name=None, **kwargs)[source]¶ Create a MapDataset object with zero filled maps according to the specified geometries
- Parameters
- geom
Geom
geometry for the counts and background maps
- geom_exposure
Geom
geometry for the exposure map
- geom_psf
Geom
geometry for the psf map
- geom_edisp
Geom
geometry for the energy dispersion map
- reference_time
Time
the reference time to use in GTI definition
- namestr
Name of the returned dataset.
- geom
- Returns
- empty_maps
MapDataset
A MapDataset containing zero filled maps
- empty_maps
-
classmethod
from_hdulist
(hdulist, name=None)[source]¶ Create map dataset from list of HDUs.
- Parameters
- hdulist
HDUList
List of HDUs.
- namestr
Name of the new dataset.
- hdulist
- Returns
- dataset
MapDataset
Map dataset.
- dataset
-
plot_residuals
(self, method='diff', smooth_kernel='gauss', smooth_radius='0.1 deg', region=None, figsize=(12, 4), **kwargs)[source]¶ Plot spatial and spectral residuals.
The spectral residuals are extracted from the provided region, and the normalization used for the residuals computation can be controlled using the method parameter. If no region is passed, only the spatial residuals are shown.
- Parameters
- method{“diff”, “diff/model”, “diff/sqrt(model)”}
Method used to compute the residuals, see
MapDataset.residuals()
- smooth_kernel{‘gauss’, ‘box’}
Kernel shape.
- smooth_radius: `~astropy.units.Quantity`, str or float
Smoothing width given as quantity or float. If a float is given it is interpreted as smoothing width in pixels.
- region: `~regions.Region`
Region (pixel or sky regions accepted)
- figsizetuple
Figure size used for the plotting.
- **kwargsdict
Keyword arguments passed to
imshow
.
- Returns
- ax_image, ax_spec
Axes
, Image and spectrum axes.
- ax_image, ax_spec
-
classmethod
read
(filename, name=None)[source]¶ Read map dataset from file.
- Parameters
- filenamestr
Filename to read from.
- namestr
Name of the new dataset.
- Returns
- dataset
MapDataset
Map dataset.
- dataset
-
residuals
(self, method='diff')[source]¶ Compute residuals map.
- Parameters
- method: {“diff”, “diff/model”, “diff/sqrt(model)”}
- Method used to compute the residuals. Available options are:
“diff” (default): data - model
“diff/model”: (data - model) / model
“diff/sqrt(model)”: (data - model) / sqrt(model)
- Returns
- residuals
gammapy.maps.WcsNDMap
Residual map.
- residuals
-
stack
(self, other)[source]¶ Stack another dataset in place.
- Parameters
- other: `~gammapy.cube.MapDataset` or `~gammapy.cube.MapDatasetOnOff`
Map dataset to be stacked with this one. If other is an on-off dataset alpha * counts_off is used as a background model.
-
to_hdulist
(self)[source]¶ Convert map dataset to list of HDUs.
- Returns
- hdulist
HDUList
Map dataset list of HDUs.
- hdulist
-
to_image
(self, spectrum=None, name=None)[source]¶ Create images by summing over the energy axis.
Exposure is weighted with an assumed spectrum, resulting in a weighted mean exposure image.
Currently the PSFMap and EdispMap are dropped from the resulting image dataset.
- Parameters
- spectrum
SpectralModel
Spectral model to compute the weights. Default is power-law with spectral index of 2.
- namestr
Name of the new dataset.
- spectrum
- Returns
- dataset
MapDataset
Map dataset containing images.
- dataset
-
to_spectrum_dataset
(self, on_region, containment_correction=False, name=None)[source]¶ Return a ~gammapy.spectrum.SpectrumDataset from on_region.
Counts and background are summed in the on_region.
Effective area is taken from the average exposure divided by the livetime. Here we assume it is the sum of the GTIs.
The energy dispersion kernel is obtained at the on_region center. Only regions with centers are supported.
The model is not exported to the ~gammapy.spectrum.SpectrumDataset. It must be set after the dataset extraction.
- Parameters
- on_region
SkyRegion
the input ON region on which to extract the spectrum
- containment_correctionbool
Apply containment correction for point sources and circular on regions
- namestr
Name of the new dataset.
- on_region
- Returns
- dataset
SpectrumDataset
the resulting reduced dataset
- dataset