Source code for lenstronomy.LensModel.Solver.solver

from lenstronomy.LensModel.Solver.solver2point import Solver2Point
from lenstronomy.LensModel.Solver.solver4point import Solver4Point
import numpy as np

__all__ = ['Solver']


[docs]class Solver(object): """ joint solve class to manage with type of solver to be executed and checks whether the requirements are fulfilled. """ def __init__(self, solver_type, lensModel, num_images): """ :param solver_type: string, option for specific solver type see detailed instruction of the Solver4Point and Solver2Point classes :param lensModel: instance of a LensModel() class :param num_images: int, number of images to be solved for """ self._num_images = num_images self._lensModel = lensModel if self._num_images == 4: self._solver = Solver4Point(lensModel, solver_type=solver_type) elif self. _num_images == 2: self._solver = Solver2Point(lensModel, solver_type=solver_type) else: raise ValueError("%s number of images is not valid. Use 2 or 4!" % self._num_images)
[docs] def constraint_lensmodel(self, x_pos, y_pos, kwargs_list, xtol=1.49012e-12): """ :param x_pos: :param y_pos: :param kwargs_list: :return: """ return self._solver.constraint_lensmodel(x_pos, y_pos, kwargs_list, xtol=xtol)
[docs] def update_solver(self, kwargs_lens, x_pos, y_pos): """ :param kwargs_lens: :param x_pos: :param y_pos: :return: """ if not len(x_pos) == self._num_images: raise ValueError("Point source number %s must be as specified by the solver with number of images %s" % (len(x_pos), self._num_images)) kwargs_lens, precision = self.constraint_lensmodel(x_pos, y_pos, kwargs_lens) return kwargs_lens
[docs] def check_solver(self, image_x, image_y, kwargs_lens): """ returns the precision of the solver to match the image position :param kwargs_lens: full lens model (including solved parameters) :param image_x: point source in image :param image_y: point source in image :return: precision of Euclidean distances between the different rays arriving at the image positions """ source_x, source_y = self._lensModel.ray_shooting(image_x, image_y, kwargs_lens) dist = np.sqrt((source_x - source_x[0]) ** 2 + (source_y - source_y[0]) ** 2) return dist
[docs] def add_fixed_lens(self, kwargs_fixed_lens, kwargs_lens_init): """ returns kwargs that are kept fixed during run, depending on options :param kwargs_fixed_lens: keyword argument list of fixed parameters (indicated by fitting argument of the user) :param kwargs_lens_init: Initial values of the full lens model keyword arguments :return: updated kwargs_fixed_lens, added fixed parameters being added (and replaced later on) by the non-linear solver. """ kwargs_fixed_lens = self._solver.add_fixed_lens(kwargs_fixed_lens, kwargs_lens_init) return kwargs_fixed_lens