MorphModelImageCreator

class gammapy.image.models.MorphModelImageCreator(cfg_file, exposure, psf_file=None, apply_psf=True, background=None, flux_factor=1e-12, compute_excess=True)

Bases: object

Create model images from a HGPS pipeline source config file.

Uses astropy to evaluate the source model, with oversampling or integrating over pixels.

Parameters:

cfg_file : str

Config file with all the sources listed.

exposure : str

Fits image file with the exposure.

psf_file : str (optional)

Json file with PSF information.

background : str (optional)

Fits image file with the background.

apply_psf : bool

Whether the psf should be applied.

compute_excess : bool

Whether to compute an excess image.

flux_factor : float

Flux conversion factor.

Examples

Here is an example how to use MorphModelImageCreator:

>>> from gammapy.image.models import MorphModelImageCreator
>>> model_image_creator = MorphModelImageCreator(cfg_file='input_sherpa.cfg',
...                                              exposure='exposure.fits',
...                                              psf_file='psf.json')
>>> model_image_creator.evaluate_model(mode='center')
>>> model_image_creator.save('model_image.fits')

Methods Summary

evaluate_model(**kwargs)	Evaluate model by oversampling or taking the value at the center of the pixel.
fake_counts(N[, random_state])	Fake measurement data by adding Poisson noise to the model image.
save(filename, **kwargs)	Save model image to file.

Methods Documentation

evaluate_model(**kwargs)

Evaluate model by oversampling or taking the value at the center of the pixel.

fake_counts(N, random_state='random-seed', **kwargs)

Fake measurement data by adding Poisson noise to the model image.

Parameters:

N : int

Number of measurements to fake.

random_state : {int, ‘random-seed’, ‘global-rng’, RandomState}

Defines random number generator initialisation. Passed to get_random_state.

save(filename, **kwargs)

Save model image to file.