Source code for lenstronomy.LensModel.Profiles.point_mass

__author__ = "sibirrer"


import numpy as np
from lenstronomy.LensModel.Profiles.base_profile import LensProfileBase

__all__ = ["PointMass"]




class PointMass(LensProfileBase):
    """Class to compute the physical deflection angle of a point mass, given as an
    Einstein radius."""

    param_names = ["theta_E", "center_x", "center_y"]
    lower_limit_default = {"theta_E": 0, "center_x": -100, "center_y": -100}
    upper_limit_default = {"theta_E": 100, "center_x": 100, "center_y": 100}



    def __init__(self):
        self.r_min = 10 ** (-25)
        super(PointMass, self).__init__()

        # alpha = 4*const.G * (mass*const.M_sun)/const.c**2/(r*const.Mpc)



    def function(self, x, y, theta_E, center_x=0, center_y=0):
        """

        :param x: x-coord (in angles)
        :param y: y-coord (in angles)
        :param theta_E: Einstein radius (in angles)
        :return: lensing potential
        """
        x_ = x - center_x
        y_ = y - center_y
        a = np.sqrt(x_**2 + y_**2)
        if isinstance(a, int) or isinstance(a, float):
            r = max(self.r_min, a)
        else:
            r = np.empty_like(a)
            r[a > self.r_min] = a[a > self.r_min]  # in the SIS regime
            r[a <= self.r_min] = self.r_min
        phi = theta_E**2 * np.log(r)
        return phi




    def derivatives(self, x, y, theta_E, center_x=0, center_y=0):
        """

        :param x: x-coord (in angles)
        :param y: y-coord (in angles)
        :param theta_E: Einstein radius (in angles)
        :return: deflection angle (in angles)
        """
        x_ = x - center_x
        y_ = y - center_y
        a = np.sqrt(x_**2 + y_**2)
        if isinstance(a, int) or isinstance(a, float):
            r = max(self.r_min, a)
        else:
            r = np.empty_like(a)
            r[a > self.r_min] = a[a > self.r_min]  # in the SIS regime
            r[a <= self.r_min] = self.r_min
        alpha = theta_E**2 / r
        return alpha * x_ / r, alpha * y_ / r




    def hessian(self, x, y, theta_E, center_x=0, center_y=0):
        """

        :param x: x-coord (in angles)
        :param y: y-coord (in angles)
        :param theta_E: Einstein radius (in angles)
        :return: hessian matrix (in angles)
        """
        x_ = x - center_x
        y_ = y - center_y
        C = theta_E**2
        a = x_**2 + y_**2
        if isinstance(a, int) or isinstance(a, float):
            r2 = max(self.r_min**2, a)
        else:
            r2 = np.empty_like(a)
            r2[a > self.r_min**2] = a[a > self.r_min**2]  # in the SIS regime
            r2[a <= self.r_min**2] = self.r_min**2
        f_xx = C * (y_**2 - x_**2) / r2**2
        f_yy = C * (x_**2 - y_**2) / r2**2
        f_xy = -C * 2 * x_ * y_ / r2**2
        return f_xx, f_xy, f_xy, f_yy