lenstronomy.SimulationAPI package¶
Subpackages¶
Submodules¶
lenstronomy.SimulationAPI.data_api module¶
- class lenstronomy.SimulationAPI.data_api.DataAPI(numpix, **kwargs_single_band)[source]¶
Bases:
lenstronomy.SimulationAPI.observation_api.SingleBand
This class is a wrapper of the general description of data in SingleBand() to translate those quantities into configurations in the core lenstronomy Data modules to simulate images according to those quantities. This class is meant to be an example of a wrapper. More possibilities in terms of PSF and data type options are available. Have a look in the specific modules if you are interested in.
- property data_class¶
creates a Data() instance of lenstronomy based on knowledge of the observation
- Returns
instance of Data() class
- property kwargs_data¶
- Returns
keyword arguments for ImageData class instance
lenstronomy.SimulationAPI.model_api module¶
- class lenstronomy.SimulationAPI.model_api.ModelAPI(lens_model_list=[], z_lens=None, z_source=None, lens_redshift_list=None, source_light_model_list=[], lens_light_model_list=[], point_source_model_list=[], source_redshift_list=None, cosmo=None, z_source_convention=None)[source]¶
Bases:
object
This class manages the model choices. The role is to return instances of the lenstronomy LightModel, LensModel, PointSource modules according to the options chosen by the user. Currently, all other model choices are equivalent to the ones provided by LightModel, LensModel, PointSource. The current options of the class instance only describe a subset of possibilities.
- property lens_light_model_class¶
- Returns
instance of lenstronomy LightModel class describing the non-lensed light profiles
- property lens_model_class¶
- Returns
instance of lenstronomy LensModel class
- physical2lensing_conversion(kwargs_mass)[source]¶
- Parameters
kwargs_mass – list of keyword arguments of all the lens models. Einstein radius ‘theta_E’ are replaced by ‘sigma_v’, velocity dispersion in km/s, ‘alpha_Rs’ and ‘Rs’ of NFW profiles are replaced by ‘M200’ and ‘concentration’
- Returns
kwargs_lens in reduced deflection angles compatible with the lensModel instance of this module
- property point_source_model_class¶
- Returns
instance of lenstronomy PointSource class describing the point sources (lensed and unlensed)
- property source_model_class¶
- Returns
instance of lenstronomy LightModel class describing the source light profiles
lenstronomy.SimulationAPI.observation_api module¶
- class lenstronomy.SimulationAPI.observation_api.Instrument(pixel_scale, read_noise=None, ccd_gain=None)[source]¶
Bases:
object
basic access points to instrument properties
- class lenstronomy.SimulationAPI.observation_api.Observation(exposure_time, sky_brightness=None, seeing=None, num_exposures=1, psf_type='GAUSSIAN', kernel_point_source=None, truncation=5, point_source_supersampling_factor=1)[source]¶
Bases:
object
basic access point to observation properties
- property exposure_time¶
total exposure time
- Returns
summed exposure time
- property psf_class¶
creates instance of PSF() class based on knowledge of the observations For the full possibility of how to create such an instance, see the PSF() class documentation
- Returns
instance of PSF() class
- update_observation(exposure_time=None, sky_brightness=None, seeing=None, num_exposures=None, psf_type=None, kernel_point_source=None)[source]¶
updates class instance with new properties if specific argument is not None
- Parameters
exposure_time – exposure time per image (in seconds)
sky_brightness – sky brightness (in magnitude per square arcseconds)
seeing – full width at half maximum of the PSF (if not specific psf_model is specified)
num_exposures – number of exposures that are combined
psf_type – string, type of PSF (‘GAUSSIAN’ and ‘PIXEL’ supported)
kernel_point_source – 2d numpy array, model of PSF centered with odd number of pixels per axis (optional when psf_type=’PIXEL’ is chosen)
- Returns
None, updated class instance
- class lenstronomy.SimulationAPI.observation_api.SingleBand(pixel_scale, exposure_time, magnitude_zero_point, read_noise=None, ccd_gain=None, sky_brightness=None, seeing=None, num_exposures=1, psf_type='GAUSSIAN', kernel_point_source=None, truncation=5, point_source_supersampling_factor=1, data_count_unit='e-', background_noise=None)[source]¶
Bases:
lenstronomy.SimulationAPI.observation_api.Instrument
,lenstronomy.SimulationAPI.observation_api.Observation
class that combines Instrument and Observation
- property background_noise¶
Gaussian sigma of noise level per pixel in counts (e- or ADU) per second
- Returns
sqrt(variance) of background noise level in data units
- estimate_noise(image)[source]¶
- Parameters
image – noisy data, background subtracted
- Returns
estimated noise map sqrt(variance) for each pixel as estimated from the instrument and observation
- flux_iid(flux_per_second)[source]¶
IID counts. This can be used by lenstronomy to estimate the Poisson errors keeping the assumption that the counts are IIDs (even if they are not).
- Parameters
flux_per_second – flux count per second in the units set in this class (ADU or e-)
- Returns
IID count number
- flux_noise(flux)[source]¶
- Parameters
flux – float or array, units of count_unit/seconds, needs to be positive semi-definite in the flux value
- Returns
Gaussian approximation of Poisson statistics in IIDs sqrt(variance)
- magnitude2cps(magnitude)[source]¶
converts an apparent magnitude to counts per second (in units of the data)
The zero point of an instrument, by definition, is the magnitude of an object that produces one count (or data number, DN) per second. The magnitude of an arbitrary object producing DN counts in an observation of length EXPTIME is therefore: m = -2.5 x log10(DN / EXPTIME) + ZEROPOINT
- Parameters
magnitude – magnitude of object
- Returns
counts per second of object
- noise_for_model(model, background_noise=True, poisson_noise=True, seed=None)[source]¶
- Parameters
model – 2d numpy array of modelled image (with pixels in units of data specified in class)
background_noise – bool, if True, adds background noise
poisson_noise – bool, if True, adds Poisson noise of modelled flux
seed – int, seed number to be used to render the noise properties. If None, then uses the current numpy.random seed to render the noise properties.
- Returns
noise realization corresponding to the model
- property sky_brightness¶
- Returns
sky brightness (counts per square arcseconds in unit of data (e- or ADU’s) per unit time)
lenstronomy.SimulationAPI.observation_constructor module¶
- lenstronomy.SimulationAPI.observation_constructor.observation_constructor(instrument_name, observation_name)[source]¶
- Parameters
instrument_name – string, name of instrument referenced in this file
observation_name – string, name of observation referenced in this file
- Returns
instance of the SimulationAPI.data_type instance
lenstronomy.SimulationAPI.point_source_variability module¶
- class lenstronomy.SimulationAPI.point_source_variability.PointSourceVariability(source_x, source_y, variability_func, numpix, kwargs_single_band, kwargs_model, kwargs_numerics, kwargs_lens, kwargs_source_mag=None, kwargs_lens_light_mag=None, kwargs_ps_mag=None)[source]¶
Bases:
object
This class enables to plug in a variable point source in the source plane to be added on top of a fixed lens and extended surface brightness model. The class inherits SimAPI and additionally requires the lens and light model parameters as well as a position in the source plane.
The intrinsic source variability can be defined by the user and additional uncorrelated variability in the image plane can be plugged in as well (e.g. due to micro-lensing)
- property delays¶
- Returns
time delays
- property image_bkg¶
- Returns
2d numpy array, image of the extended light components without the variable source
lenstronomy.SimulationAPI.sim_api module¶
- class lenstronomy.SimulationAPI.sim_api.SimAPI(numpix, kwargs_single_band, kwargs_model)[source]¶
Bases:
lenstronomy.SimulationAPI.data_api.DataAPI
,lenstronomy.SimulationAPI.model_api.ModelAPI
This class manages the model parameters in regard of the data specified in SingleBand. In particular, this API translates models specified in units of astronomical magnitudes into the amplitude parameters used in the LightModel module of lenstronomy. Optionally, this class can also handle inputs with cosmology dependent lensing quantities and translates them to the optical quantities being used in the lenstronomy LensModel module. All other model choices are equivalent to the ones provided by LightModel, LensModel, PointSource modules
- image_model_class(kwargs_numerics=None)[source]¶
- Parameters
kwargs_numerics – keyword arguments list of Numerics module
- Returns
instance of the ImageModel class with all the specified configurations
- magnitude2amplitude(kwargs_lens_light_mag=None, kwargs_source_mag=None, kwargs_ps_mag=None)[source]¶
‘magnitude’ definition are in APPARENT magnitudes as observed on the sky, not intrinsic!
- Parameters
kwargs_lens_light_mag – keyword argument list as for LightModel module except that ‘amp’ parameters are ‘magnitude’ parameters.
kwargs_source_mag – keyword argument list as for LightModel module except that ‘amp’ parameters are ‘magnitude’ parameters.
kwargs_ps_mag – keyword argument list as for PointSource module except that ‘amp’ parameters are ‘magnitude’ parameters.
- Returns
value of the lenstronomy ‘amp’ parameter such that the total flux of the profile type results in this magnitude for all the light models. These keyword arguments conform with the lenstronomy LightModel syntax.