lenstronomy.Sampling.Likelihoods package¶
Submodules¶
lenstronomy.Sampling.Likelihoods.image_likelihood module¶
- class lenstronomy.Sampling.Likelihoods.image_likelihood.ImageLikelihood(multi_band_list, multi_band_type, kwargs_model, bands_compute=None, image_likelihood_mask_list=None, source_marg=False, linear_prior=None, check_positive_flux=False, kwargs_pixelbased=None)[source]¶
Bases:
object
manages imaging data likelihoods
- logL(kwargs_lens=None, kwargs_source=None, kwargs_lens_light=None, kwargs_ps=None, kwargs_special=None, kwargs_extinction=None)[source]¶
- Parameters
kwargs_lens – lens model keyword argument list according to LensModel module
kwargs_source – source light keyword argument list according to LightModel module
kwargs_lens_light – deflector light (not lensed) keyword argument list according to LightModel module
kwargs_ps – point source keyword argument list according to PointSource module
kwargs_special – special keyword argument list as part of the Param module
kwargs_extinction – extinction parameter keyword argument list according to LightModel module
- Returns
log likelihood of the data given the model
- property num_data¶
- Returns
number of image data points
lenstronomy.Sampling.Likelihoods.position_likelihood module¶
- class lenstronomy.Sampling.Likelihoods.position_likelihood.PositionLikelihood(point_source_class, image_position_uncertainty=0.005, astrometric_likelihood=False, image_position_likelihood=False, ra_image_list=None, dec_image_list=None, source_position_likelihood=False, check_matched_source_position=False, source_position_tolerance=0.001, source_position_sigma=0.001, force_no_add_image=False, restrict_image_number=False, max_num_images=None)[source]¶
Bases:
object
likelihood of positions of multiply imaged point sources
- static astrometric_likelihood(kwargs_ps, kwargs_special, sigma)[source]¶
evaluates the astrometric uncertainty of the model plotted point sources (only available for ‘LENSED_POSITION’ point source model) and predicted image position by the lens model including an astrometric correction term.
- Parameters
kwargs_ps – point source model kwargs list
kwargs_special – kwargs list, should include the astrometric corrections ‘delta_x’, ‘delta_y’
sigma – 1-sigma Gaussian uncertainty in the astrometry
- Returns
log likelihood of the astrometirc correction between predicted image positions and model placement of the point sources
- check_additional_images(kwargs_ps, kwargs_lens)[source]¶
checks whether additional images have been found and placed in kwargs_ps of the first point source model #TODO check for all point source models :param kwargs_ps: point source kwargs :return: bool, True if more image positions are found than originally been assigned
- image_position_likelihood(kwargs_ps, kwargs_lens, sigma)[source]¶
computes the likelihood of the model predicted image position relative to measured image positions with an astrometric error. This routine requires the ‘ra_image_list’ and ‘dec_image_list’ being declared in the initiation of the class
- Parameters
kwargs_ps – point source keyword argument list
kwargs_lens – lens model keyword argument list
sigma – 1-sigma uncertainty in the measured position of the images
- Returns
log likelihood of the model predicted image positions given the data/measured image positions.
- logL(kwargs_lens, kwargs_ps, kwargs_special, verbose=False)[source]¶
- Parameters
kwargs_lens – lens model parameter keyword argument list
kwargs_ps – point source model parameter keyword argument list
kwargs_special – special keyword arguments
verbose – bool
- Returns
log likelihood of the optional likelihoods being computed
- property num_data¶
- Returns
integer, number of data points associated with the class instance
- source_position_likelihood(kwargs_lens, kwargs_ps, sigma, hard_bound_rms=None, verbose=False)[source]¶
computes a likelihood/punishing factor of how well the source positions of multiple images match given the image position and a lens model. The likelihood level is computed in respect of a displacement in the image plane and transposed through the Hessian into the source plane.
- Parameters
kwargs_lens – lens model keyword argument list
kwargs_ps – point source keyword argument list
sigma – 1-sigma Gaussian uncertainty in the image plane
hard_bound_rms – hard bound deviation between the mapping of the images back to the source plane (in source frame)
verbose – bool, if True provides print statements with useful information.
- Returns
log likelihood of the model reproducing the correct image positions given an image position uncertainty
lenstronomy.Sampling.Likelihoods.prior_likelihood module¶
- class lenstronomy.Sampling.Likelihoods.prior_likelihood.PriorLikelihood(prior_lens=None, prior_source=None, prior_lens_light=None, prior_ps=None, prior_special=None, prior_extinction=None, prior_lens_kde=None, prior_source_kde=None, prior_lens_light_kde=None, prior_ps_kde=None, prior_special_kde=None, prior_extinction_kde=None, prior_lens_lognormal=None, prior_source_lognormal=None, prior_lens_light_lognormal=None, prior_ps_lognormal=None, prior_special_lognormal=None, prior_extinction_lognormal=None)[source]¶
Bases:
object
class containing additional Gaussian priors to be folded into the likelihood
lenstronomy.Sampling.Likelihoods.time_delay_likelihood module¶
- class lenstronomy.Sampling.Likelihoods.time_delay_likelihood.TimeDelayLikelihood(time_delays_measured, time_delays_uncertainties, lens_model_class, point_source_class)[source]¶
Bases:
object
class to compute the likelihood of a model given a measurement of time delays
- logL(kwargs_lens, kwargs_ps, kwargs_cosmo)[source]¶
routine to compute the log likelihood of the time delay distance :param kwargs_lens: lens model kwargs list :param kwargs_ps: point source kwargs list :param kwargs_cosmo: cosmology and other kwargs :return: log likelihood of the model given the time delay data
- property num_data¶
- Returns
number of time delay measurements