CombinedModel3D¶

class gammapy.cube.CombinedModel3D(spatial_model, spectral_model)[source]¶

Bases: object

Combine spatial and spectral model into a 3D model.

TODO: give move infos and an example how spatial models must be normalised to integrate to 1 and caveats about binning effects, i.e. how too small bins or very small sources will lead to incorrect spectral results!

At the moment this model has no built-in integration. I.e. it’s left up to callers to:

integrate over energy bins
integrate over spatial pixels

TODO: This is a prototype, and the evaluation scheme might change! Feedback on what you’d like to do and whether this class is working for you or not is highly welcome!!!

Parameters:

spatial_model : SpatialModel

Spatial model (must be normalised to integrate to 1)

spectral_model : SpectralModel

Spectral model

Examples

Create a CombinedModel3D, i.e. one that factors into a spatial and position-independent spectral part:

import astropy.units as u
from gammapy.image.models import Shell2D
from gammapy.spectrum.models import PowerLaw
from gammapy.cube.models import CombinedModel3D

spatial_model = Shell2D(
    amplitude=1, x_0=3, y_0=4, r_in=5, width=6, normed=True,
)
spectral_model = PowerLaw(
    index=2, amplitude=1 * u.Unit('cm-2 s-1 TeV-1'), reference=1 * u.Unit('TeV'),
)
model = CombinedModel3D(spatial_model, spectral_model)

Look at the model you created:

>>> model
CombinedModel3D(spatial_model=<Shell2D(amplitude=1.0, x_0=3.0, y_0=4.0, r_in=5.0, width=6.0)>, spectral_model=PowerLaw())
>>> print(model.spectral_model)
PowerLaw

Parameters:

       name     value   error       unit      min  max  frozen
    --------- --------- ----- --------------- ---- ---- ------
        index 2.000e+00   nan                    0 None  False
    amplitude 1.000e+00   nan 1 / (cm2 s TeV)    0 None  False
    reference 1.000e+00   nan             TeV None None   True

>>> print(model.spatial_model)
Model: Shell2D
Inputs: ('x', 'y')
Outputs: ('z',)
Model set size: 1
Parameters:
    amplitude x_0 y_0 r_in width
    --------- --- --- ---- -----
          1.0 3.0 4.0  5.0   6.0

Evaluate the model at a given point:

>>> import astropy.units as u
>>> model.evaluate(lon=0.1 * u.deg, lat=0.2 * u.deg, energy='1 TeV')
<Quantity [[[ 0.00334177]]] 1 / (cm2 deg2 s TeV)>

Evaluate the model on a sky cube:

>>> # TODO: add example.

Methods Summary

`evaluate`(lon, lat, energy)	Evaluate the model at given points.
`evaluate_cube`(ref_cube)	Evaluate the model on coordinates given by a reference sky cube.

Methods Documentation

evaluate(lon, lat, energy)[source]¶

Evaluate the model at given points.

Return differential surface brightness cube. At the moment in units: cm-2 s-1 TeV-1 sr-1

TODO: currently spatial models don’t support units, and we have hard-coded in this evaluate the assumption that they return their result in unit deg-2

Parameters:

lon, lat : Quantity

Spatial coordinates

energy : Quantity

Energy coordinate

Returns:

value : Quantity

Model value at the given point.

evaluate_cube(ref_cube)[source]¶

Evaluate the model on coordinates given by a reference sky cube.

Parameters:

ref_cube : SkyCube

Reference sky cube

Returns:

model_cube : SkyCube

Sky cube with data filled with evaluated model values. Units: cm-2 s-1 TeV-1 sr-1

Navigation

CombinedModel3D¶