lenstronomy.PointSource package

Subpackages

• lenstronomy.PointSource.Types package
  • Submodules
  • lenstronomy.PointSource.Types.base_ps module
    • PSBase
      • PSBase.__init__()
      • PSBase.image_position()
      • PSBase.source_position()
      • PSBase.image_amplitude()
      • PSBase.source_amplitude()
      • PSBase.update_lens_model()
  • lenstronomy.PointSource.Types.lensed_position module
    • LensedPositions
      • LensedPositions.image_position()
      • LensedPositions.source_position()
      • LensedPositions.image_amplitude()
      • LensedPositions.source_amplitude()
  • lenstronomy.PointSource.Types.source_position module
    • SourcePositions
      • SourcePositions.image_position()
      • SourcePositions.source_position()
      • SourcePositions.image_amplitude()
      • SourcePositions.source_amplitude()
  • lenstronomy.PointSource.Types.unlensed module
    • Unlensed
      • Unlensed.image_position()
      • Unlensed.source_position()
      • Unlensed.image_amplitude()
      • Unlensed.source_amplitude()
  • Module contents

Submodules

lenstronomy.PointSource.point_source module

class PointSource(point_source_type_list, lens_model=None, fixed_magnification_list=None, additional_images_list=None, flux_from_point_source_list=None, magnification_limit=None, save_cache=False, kwargs_lens_eqn_solver=None, index_lens_model_list=None, point_source_frame_list=None)

Bases: object

__init__(point_source_type_list, lens_model=None, fixed_magnification_list=None, additional_images_list=None, flux_from_point_source_list=None, magnification_limit=None, save_cache=False, kwargs_lens_eqn_solver=None, index_lens_model_list=None, point_source_frame_list=None)

Parameters:

• point_source_type_list – list of point source types

• lens_model – instance of the LensModel() class

• fixed_magnification_list – list of booleans (same length as point_source_type_list). If True, magnification ratio of point sources is fixed to the one given by the lens model. This option then requires to provide a ‘source_amp’ amplitude of the source brightness instead of ‘point_amp’ the list of image brightnesses.

• additional_images_list – list of booleans (same length as point_source_type_list). If True, search for additional images of the same source is conducted.

• flux_from_point_source_list – list of booleans (optional), if set, will only return image positions (for imaging modeling) for the subset of the point source lists that =True. This option enables to model imaging data with transient point sources, when the point source positions are measured and present at a different time than the imaging data

• magnification_limit – float >0 or None, if float is set and additional images are computed, only those images will be computed that exceed the lensing magnification (absolute value) limit

• save_cache – bool, saves image positions and only if delete_cache is executed, a new solution of the lens equation is conducted with the lens model parameters provided. This can increase the speed as multiple times the image positions are requested for the same lens model. Attention in usage!

• kwargs_lens_eqn_solver – keyword arguments specifying the numerical settings for the lens equation solver see LensEquationSolver() class for details, such as: min_distance=0.01, search_window=5, precision_limit=10**(-10), num_iter_max=100

• index_lens_model_list – list (length of different patches/bands) of integer lists, e.g., [[0, 1], [2, 3]]; evaluating a subset of the lens models per individual bands. If this keyword is set, the image positions need to have a specified band/frame assigned to it

• point_source_frame_list – list of lists mirroring the structure of the image positions. Integers correspond to the i’th list entry of index_lens_model_list indicating in which frame/band the image is appearing, e.g., four images and four cutouts, you can do [[0], [1], [2], [3]] when the frames (ordered as the list) are in the same order as the point sources (indices)

update_search_window(search_window, x_center, y_center, min_distance=None, only_from_unspecified=False)

Update the search area for the lens equation solver.

Parameters:

• search_window – search_window: window size of the image position search with the lens equation solver.

• x_center – center of search window

• y_center – center of search window

• min_distance – minimum search distance

• only_from_unspecified – bool, if True, only sets keywords that previously have not been set

Returns:

updated self instances

update_lens_model(lens_model_class)

Parameters:

lens_model_class – instance of LensModel class

Returns:

update instance of lens model class

delete_lens_model_cache()

Deletes the variables saved for a specific lens model.

Returns:

None

set_save_cache(save_cache)

Set the save cache boolean to new value.

Parameters:

save_cache – bool, if True, saves (or uses a previously saved) values

Returns:

updated class and sub-class instances to either save or not save the point source information in cache

k_list(k)

Parameters:

k – index of point source model

Returns:

list of lengths of images with corresponding lens models in the frame (or None if not multi-frame)

source_position(kwargs_ps, kwargs_lens)

Intrinsic source positions of the point sources.

Parameters:

• kwargs_ps – keyword argument list of point source models

• kwargs_lens – keyword argument list of lens models

Returns:

list of source positions for each point source model

image_position(kwargs_ps, kwargs_lens, k=None, original_position=False, additional_images=False)

Image positions as observed on the sky of the point sources.

Parameters:

• kwargs_ps – point source parameter keyword argument list

• kwargs_lens – lens model keyword argument list

• k – None, int or boolean list; only returns a subset of the model predictions

• original_position – boolean (only applies to ‘LENSED_POSITION’ models), returns the image positions in the model parameters and does not re-compute images (which might be differently ordered) in case of the lens equation solver

• additional_images (bool) – if True, solves the lens equation for additional images

Returns:

list of: list of image positions per point source model component

point_source_list(kwargs_ps, kwargs_lens, k=None, with_amp=True)

Returns the coordinates and amplitudes of all point sources in a single array.

Parameters:

• kwargs_ps – point source keyword argument list

• kwargs_lens – lens model keyword argument list

• k – None, int or list of int’s to select a subset of the point source models in the return

• with_amp – bool, if False, ignores the amplitude parameters in the return and instead provides ones for each point source image

Returns:

ra_array, dec_array, amp_array

num_basis(kwargs_ps, kwargs_lens)

Number of basis functions for linear inversion.

Parameters:

• kwargs_ps – point source keyword argument list

• kwargs_lens – lens model keyword argument list

Returns:

int

image_amplitude(kwargs_ps, kwargs_lens, k=None)

Returns the image amplitudes.

Parameters:

• kwargs_ps – point source keyword argument list

• kwargs_lens – lens model keyword argument list

• k – None, int or list of int’s to select a subset of the point source models in the return

Returns:

list of image amplitudes per model component

source_amplitude(kwargs_ps, kwargs_lens)

Intrinsic (unlensed) point source amplitudes.

Parameters:

• kwargs_ps – point source keyword argument list

• kwargs_lens – lens model keyword argument list

Returns:

list of intrinsic (unlensed) point source amplitudes

linear_response_set(kwargs_ps, kwargs_lens=None, with_amp=False)

Parameters:

• kwargs_ps – point source keyword argument list

• kwargs_lens – lens model keyword argument list

• with_amp – bool, if True returns the image amplitude derived from kwargs_ps, otherwise the magnification of the lens model

Returns:

ra_pos, dec_pos, amp, n

update_linear(param, i, kwargs_ps, kwargs_lens)

Parameters:

• param – list of floats corresponding ot the parameters being sampled

• i – index of the first parameter relevant for this class

• kwargs_ps – point source keyword argument list

• kwargs_lens – lens model keyword argument list

Returns:

kwargs_ps with updated linear parameters, index of the next parameter relevant for another class

linear_param_from_kwargs(kwargs_list)

Inverse function of update_linear() returning the linear amplitude list for the keyword argument list.

Parameters:

kwargs_list (list of keyword arguments) – model parameters including the linear amplitude parameters

Returns:

list of linear amplitude parameters

Return type:

list

check_image_positions(kwargs_ps, kwargs_lens, tolerance=0.001)

Checks whether the point sources in kwargs_ps satisfy the lens equation with a tolerance (computed by ray-tracing in the source plane)

Parameters:

• kwargs_ps – point source keyword argument list

• kwargs_lens – lens model keyword argument list

• tolerance – Euclidian distance between the source positions ray-traced backwards to be tolerated

Returns:

bool: True, if requirement on tolerance is fulfilled, False if not.

set_amplitudes(amp_list, kwargs_ps)

Translates the amplitude parameters into the convention of the keyword argument list currently only used in SimAPI to transform magnitudes to amplitudes in the lenstronomy conventions.

Parameters:

• amp_list – list of model amplitudes for each point source model

• kwargs_ps – list of point source keywords

Returns:

overwrites kwargs_ps with new amplitudes

classmethod check_positive_flux(kwargs_ps)

Check whether inferred linear parameters are positive.

Parameters:

kwargs_ps – point source keyword argument list

Returns:

bool, True, if all ‘point_amp’ parameters are positive semi-definite

lenstronomy.PointSource.point_source_cached module

class PointSourceCached(point_source_model, save_cache=False)

Bases: object

This class is the same as PointSource() except that it saves image and source positions in cache.

This speeds-up repeated calls for the same source and lens model and avoids duplicating the lens equation solving. Attention: cache needs to be deleted before calling functions with different lens and point source parameters.

__init__(point_source_model, save_cache=False)

delete_lens_model_cache()

set_save_cache(save_bool)

update_lens_model(lens_model_class)

image_position(kwargs_ps, kwargs_lens=None, magnification_limit=None, kwargs_lens_eqn_solver=None, additional_images=False)

On-sky image positions.

Parameters:

• kwargs_ps – keyword arguments of the point source model

• kwargs_lens – keyword argument list of the lens model(s), only used when requiring the lens equation solver

• magnification_limit – float >0 or None, if float is set and additional images are computed, only those images will be computed that exceed the lensing magnification (absolute value) limit

• kwargs_lens_eqn_solver – keyword arguments specifying the numerical settings for the lens equation solver see LensEquationSolver() class for details

• additional_images (bool) – if True, solves the lens equation for additional images

Returns:

image positions in x, y as arrays

source_position(kwargs_ps, kwargs_lens=None)

Original source position (prior to lensing)

Parameters:

• kwargs_ps – point source keyword arguments

• kwargs_lens – lens model keyword argument list (only used when required)

Returns:

x, y position

image_amplitude(kwargs_ps, kwargs_lens=None, magnification_limit=None, kwargs_lens_eqn_solver=None)

Image brightness amplitudes.

Parameters:

• kwargs_ps – keyword arguments of the point source model

• kwargs_lens – keyword argument list of the lens model(s), only used when requiring the lens equation solver

• magnification_limit – float >0 or None, if float is set and additional images are computed, only those images will be computed that exceed the lensing magnification (absolute value) limit

• kwargs_lens_eqn_solver – keyword arguments specifying the numerical settings for the lens equation solver see LensEquationSolver() class for details

Returns:

array of image amplitudes

source_amplitude(kwargs_ps, kwargs_lens=None)

Intrinsic brightness amplitude of point source.

Parameters:

• kwargs_ps – keyword arguments of the point source model

• kwargs_lens – keyword argument list of the lens model(s), only used when positions are defined in image plane and have to be ray-traced back

Returns:

brightness amplitude (as numpy array)

lenstronomy.PointSource.point_source_param module

class PointSourceParam(model_list, kwargs_fixed, num_point_source_list=None, linear_solver=True, fixed_magnification_list=None, kwargs_lower=None, kwargs_upper=None)

Bases: object

Point source parameters.

__init__(model_list, kwargs_fixed, num_point_source_list=None, linear_solver=True, fixed_magnification_list=None, kwargs_lower=None, kwargs_upper=None)

Parameters:

• model_list – list of point source model names

• kwargs_fixed – list of keyword arguments with parameters to be held fixed

• num_point_source_list – list of number of point sources per point source model class

• linear_solver – bool, if True, does not return linear parameters for the sampler (will be solved linearly instead)

• fixed_magnification_list – list of booleans, if entry is True, keeps one overall scaling among the point sources in this class

get_params(args, i)

Parameters:

• args – sorted list of floats corresponding to the parameters being sampled

• i – int, index of first entry relevant for being managed by this class

Returns:

keyword argument list of point sources, index relevant for the next class

set_params(kwargs_list)

Parameters:

kwargs_list – keyword argument list

Returns:

sorted list of parameters being sampled extracted from kwargs_list

num_param()

Number of parameters and their names.

Returns:

int, list of parameter names

add_fix_linear(kwargs_fixed)

Updates fixed keyword argument list with linear parameters.

Parameters:

kwargs_fixed – list of keyword arguments held fixed during sampling

Returns:

updated keyword argument list

num_param_linear()

Returns:

number of linear parameters

Module contents