autogalaxy.profiles.mass.SersicGradient#

class SersicGradient[source]#

Bases: AbstractSersic

Setup a Sersic mass and light profiles.

Parameters:

centre (Tuple[float, float]) – The (y,x) arc-second coordinates of the profile centre.
ell_comps (Tuple[float, float]) – The first and second ellipticity components of the elliptical coordinate system.
intensity (float) – Overall flux intensity normalisation in the light profiles (electrons per second).
effective_radius (float) – The circular radius containing half the light of this profile.
sersic_index (float) – Controls the concentration of the profile (lower -> less concentrated, higher -> more concentrated).
mass_to_light_ratio (float) – The mass-to-light ratio of the light profile.
mass_to_light_gradient (float) – The mass-to-light radial gradient.

Methods

`angle`	The position angle in degrees of the major-axis of the ellipse defined by profile, defined counter clockwise from the positive x-axis (0.0 > angle > 180.0).
`angle_radians`	The position angle in radians of the major-axis of the ellipse defined by profile, defined counter clockwise from the positive x-axis (0.0 > angle > 2pi).
`angle_to_profile_grid_from`	The angle between each angle theta on the grid and the profile, in radians.
`axis_ratio`	The ratio of the minor-axis to major-axis (b/a) of the ellipse defined by profile (0.0 > q > 1.0).
`convergence_2d_from`	Calculate the projected convergence at a given set of arc-second gridded coordinates.
`convergence_2d_via_cse_from`	Calculate the projected 2D convergence from a grid of (y,x) arc second coordinates, by computing and summing the convergence of each individual cse used to decompose the mass profile.
`convergence_cse_1d_from`	One dimensional function which is solved to decompose a convergence profile in cored steep ellipsoids, given by equation (14) of Oguri 2021 (https://arxiv.org/abs/2106.11464).
`convergence_func`	Returns the convergence of the mass profile as a function of the radial coordinate.
`decompose_convergence_via_cse`	Decompose the convergence of the Sersic profile into singular isothermal elliptical (sie) profiles.
`decompose_convergence_via_mge`
`deflections_2d_via_cse_from`	Calculate the projected 2D deflection angles from a grid of (y,x) arc second coordinates, by computing and summing the convergence of each individual cse used to decompose the mass profile.
`deflections_2d_via_potential_2d_from`	Returns the 2D deflection angles of the mass profile by numerically differentiating the lensing potential on the input grid.
`deflections_via_cse_from`	Returns the deflection angles of a 1d cored steep ellisoid (CSE) profile, given by equation (19) and (20) of Oguri 2021 (https://arxiv.org/abs/2106.11464).
`deflections_yx_2d_from`	Returns the 2D deflection angles of the mass profile from a 2D grid of Cartesian (y,x) coordinates.
`density_between_circular_annuli`	Calculate the mass between two circular annuli and compute the density by dividing by the annuli surface area.
`eccentric_radii_grid_from`	Convert a grid of (y,x) coordinates to an eccentric radius: :math: axis_ratio^0.5 (x^2 + (y^2/q))^0.5
`elliptical_radii_grid_from`	Convert a grid of (y,x) coordinates to their elliptical radii values: :math: (x^2 + (y^2/q))^0.5
`extract_attribute`	Returns an attribute of a class and its children profiles in the galaxy as a ValueIrregular or Grid2DIrregular object.
`has`	Returns True if any attribute of this profile is an instance of the input class cls, else False.
`image_2d_via_radii_from`	Returns the intensity of the profile at a given radius.
`mass_angular_within_circle_from`	Integrate the mass profiles's convergence profile to compute the total mass within a circle of specified radius.
`mass_integral`	Integrand used by mass_angular_within_circle_from to compute the total projected mass within a circle.
`potential_2d_from`	Returns the 2D lensing potential of the mass profile from a 2D grid of Cartesian (y,x) coordinates.
`potential_func`	Returns the integrand of the lensing potential at a single point, used in numerical integration schemes for computing the potential from the mass profile's convergence.
`radial_deflection_from`
`radial_grid_from`	Convert a grid of (y, x) coordinates, to their radial distances from the profile centre (e.g. :math: r = sqrt(x2 + y2)).
`rotated_grid_from_reference_frame_from`	Rotate a grid of (y,x) coordinates which have been transformed to the elliptical reference frame of a profile back to the original unrotated coordinate grid reference frame.
`transformed_from_reference_frame_grid_from`	Transform a grid of (y,x) coordinates from the reference frame of the profile to the original observer reference frame.
`transformed_to_reference_frame_grid_from`	Transform a grid of (y,x) coordinates to the reference frame of the profile.
`vmapped_deflections_from`

Attributes

`average_convergence_of_1_radius`	The radius a critical curve forms for this mass profile, e.g. where the mean convergence is equal to 1.0.
`elliptical_effective_radius`	The effective_radius of a Sersic light profile is defined as the circular effective radius.
`ellipticity_rescale`	A rescaling factor applied to account for the ellipticity of the mass profile when computing the Einstein radius from the average convergence equals unity criterion.
`sersic_constant`	A parameter derived from Sersic index which ensures that effective radius contains 50% of the profile's total integrated light.

convergence_2d_from(grid, xp=<module 'numpy' from '/home/docs/checkouts/readthedocs.org/user_builds/pyautogalaxy/envs/latest/lib/python3.11/site-packages/numpy/__init__.py'>, **kwargs)[source]#

Calculate the projected convergence at a given set of arc-second gridded coordinates.

Parameters:: grid (Union[ndarray, Grid2D, Grid2DIrregular]) – The grid of (y,x) arc-second coordinates the convergence is computed on.

convergence_func(grid_radius, xp=<module 'numpy' from '/home/docs/checkouts/readthedocs.org/user_builds/pyautogalaxy/envs/latest/lib/python3.11/site-packages/numpy/__init__.py'>)[source]#

Returns the convergence of the mass profile as a function of the radial coordinate.

This is used to integrate the convergence profile to compute enclosed masses and the Einstein radius.

Parameters:: grid_radius (float) – The radial distance from the profile centre at which the convergence is evaluated.
Returns:: The convergence at the input radial distance.
Return type:: float

decompose_convergence_via_mge(**kwargs)[source]#

decompose_convergence_via_cse(grid_radii)[source]#

Decompose the convergence of the Sersic profile into singular isothermal elliptical (sie) profiles.

This decomposition uses the standard 2d profile of a Sersic mass profile.

Parameters:

func – The function representing the profile that is decomposed into CSEs.
radii_min – The minimum radius to fit
radii_max – The maximum radius to fit
total_sies – The number of SIEs used to approximate the input func.
sample_points (int (should be larger than 'total_sies')) – The number of data points to fit

Returns:

A list of amplitudes and core radii of every singular isothernal ellipsoids (sie) the mass profile is decomposed into.

Return type:

Tuple[List, List]