SersicModel

jeanspy.model.SersicModel

See methods and properties for individual lookup pages, or the alphabetical API dictionary to search all classes. The full class contract and existing member anchors are retained below.

class jeanspy.model.SersicModel(*args, deprojection_method='auto', **kwargs)

Bases: jeanspy.model.StellarModel

Projected Sérsic stellar model with selectable 3-D deprojection.

The numerical Abel inversion is the reference implementation. Fast approximations remain explicitly selectable, while "auto" uses the Vitral & Mamon (2021) hybrid where supported and falls back to the numerical reference outside the approximation domain.

Notes

Inputs and units. re_pc is projected half-light radius (pc); n is dimensionless Sersic index; deprojection_method is auto/lgm/vm20/vm20bis/numerical. Other constructor arguments follow Model.

Returns and shape. density_2d and density_3d return pc^-2 and pc^-3 with input shape. cdf_R returns the dimensionless projected radial CDF; half_light_radius returns pc. mean_density_2d is mean surface density within R. density_2d_normalized_re is the dimensionless ratio Sigma(R)/Sigma(re).

Validity. Supply positive finite scales and real nonnegative radii. Use NumPy arrays for array inputs. A central cusp may diverge at zero. The older elementary density formulas do not uniformly validate domains. The bundled b_n interpolator covers n from about 0.02 to 15.17; numerical deprojection does not remove that table limit. VM20 and VM20bis have the stricter n/r domains specified by their methods.

Errors. Unknown parameter names raise ValueError in Model.update. Invalid values in elementary profile formulas can produce NaN/inf; successful construction alone does not validate a physical profile.

Backend. NumPy/SciPy CPU; stateful components, with no JAX tracing.

Differentiation. No physical-parameter automatic differentiation on this API.

Examples. examples/docs_profiles.py

Parameters:

deprojection_method (str)

property b

Return the dimensionless Sersic b_n from the bundled interpolation table.

The supported n domain is the table range stated in the class contract.

property b_CB

Ciotti & Bertin (1999) approximation to the Sérsic b_n.

property b_linear

Return the linear approximation b_n = 2*n - 0.324.

This helper does not impose a validity interval and is not the tabulated b_n used by the normalized surface-density formula.

cdf_R(R_pc)

Return \(\int_0^R 2\pi R'\Sigma(R')\,dR'\).

Notes

Inputs and units. R_pc is a scalar or NumPy array of projected radii in pc.

Returns and shape. Dimensionless cumulative probability with input radius shape.

density(distance_from_center, dimension)

Dispatch to the projected or intrinsic normalized tracer density.

distance_from_center is a radius in pc. dimension must be ‘2d’ or ‘3d’, returning pc^-2 or pc^-3 respectively with the concrete profile’s input shape. An unsupported dimension raises ValueError.

density_2d(R_pc)

Evaluate normalized projected tracer density.

Notes

Inputs and units. R_pc is a scalar or NumPy array of projected radii in pc.

Returns and shape. pc^-2 with input radius shape.

density_2d_normalized_re(R_pc)

Return the dimensionless projected density ratio Sigma(R)/Sigma(re).

R_pc is a scalar or NumPy array in pc; output follows its shape. The stored re_pc and n must lie in the supported positive domain.

density_2d_truncated(R_pc, R_trunc_pc)

Return the normalized 2-D density truncated at R_trunc_pc.

The normalization satisfies

\[\int_0^{R_\mathrm{trunc}} 2\pi R\,\Sigma_\mathrm{trunc}(R)\,dR = 1.\]

Notes

Inputs and units. R_pc is a nonnegative finite scalar/array in pc; R_trunc_pc is a positive finite scalar cutoff in pc.

Returns and shape. Normalized surface density in pc^-2 with radius shape, zero for R>``R_trunc_pc``.

Validity. Requires a concrete density_2d and cdf_R with positive CDF at the cutoff.

density_3d(r_pc, method=None)

Return the 3-D density using the requested deprojection method.

Notes

Inputs and units. r_pc is a scalar or NumPy array of intrinsic radii in pc. method is auto/lgm/vm20/vm20bis/numerical; None uses the constructor selection. lgm is the Lima Neto–Gerbal–Márquez approximation (0.5 <= n <= 10), with normalization lgm_norm_3d.

Returns and shape. pc^-3 with input radius shape.

Parameters:

method (str | None)

density_3d_LGM(r_pc)

Lima Neto–Gerbal–Márquez Sérsic deprojection.

Notes

Inputs and units. r_pc is scalar or an array in pc; n and re_pc come from stored parameters.

Returns and shape. Unit-integral tracer density in pc^-3 with input shape.

Validity. Requires 0.5 <= n <= 10 (otherwise ValueError). This approximate deprojection is not a general central-limit formula.

density_3d_VM20(r_pc)

Vitral & Mamon (2020) 3-D Sérsic density approximation.

Notes

Inputs and units. r_pc is scalar or an array in pc; n and re_pc come from stored parameters.

Returns and shape. Unit-integral tracer density in pc^-3 with input shape.

Validity. 0.5<=n<=10; 1e-3<=r/re<=1e3; positive finite r.

density_3d_VM20bis(r_pc)

Official Vitral & Mamon (2021) VM20bis density approximation.

Notes

Inputs and units. r_pc is scalar or an array in pc; n and re_pc come from stored parameters.

Returns and shape. Unit-integral tracer density in pc^-3 with input shape.

Validity. 0.5<=n<=3.4; 1e-4<=r/re<=1e3; positive finite r.

density_3d_auto(r_pc)

Safely choose a fast literature approximation or numerical Abel.

Notes

Inputs and units. r_pc is scalar or an array in pc; n and re_pc come from stored parameters.

Returns and shape. Unit-integral tracer density in pc^-3 with input shape.

Validity. Uses VM20bis, SP04 or numerical Abel inversion according to the documented n/r domain.

density_3d_numerical(r_pc, *, epsrel=1e-06, epsabs=0.0, limit=200)

Deproject the Sérsic surface density by numerical Abel inversion.

Notes

Inputs and units. Nonnegative r_pc in pc; epsrel/epsabs are adaptive-integral tolerances; limit is the subdivision limit.

Returns and shape. pc^-3 with radius shape; infinity at r=0 for n>=1, a finite analytic center for n<1, zero at +infinity.

Validity. Positive finite re_pc and supported interpolation-table n. At r>0 integrate over theta in [0,pi/2].

Errors. Negative/NaN radii raise ValueError; SciPy convergence warnings can propagate. The returned value is not accompanied by a certified deprojection error.

Parameters:

• epsrel (float)

• epsabs (float)

• limit (int)

half_light_radius()

Return the projected half-light radius.

Notes

Inputs and units. No arguments; reads the stored tracer scales.

Returns and shape. Scalar radius in pc, equal to the stored re_pc.

is_required_param_names(param_names_candidates)

Test a sequence of names against this component’s required parameters.

Returns a list of bool with the same length and order as param_names_candidates. Submodel requirements are not included.

property lgm_norm_3d

Return the LGM approximate deprojection normalization in pc^3.

Uses the stored n, re_pc, b_CB and p_LGM. This is the LGM approximation normalization, not the numerical Abel-deprojection normalization.

mean_density_2d(R_pc)

Average surface density inside a circular aperture.

Notes

Inputs and units. Positive projected radius R_pc in pc, scalar or NumPy array.

Returns and shape. cdf_R(R)/(pi*R**2), in pc^-2 with radius shape.

Validity. Use R>0; the elementary ratio is not a numerically regularized central limit.

name = 'SersicModel'

property norm

Return the projected Sersic normalization in pc^2 for stored n and re_pc.

property p_LGM

Return the dimensionless LGM approximate deprojection exponent for stored n.

property params_all

Return a flattened Parameters copy of this model and its submodels.

Values retain their physical units. Later submodels overwrite duplicate names; use params_all_with_model_name to retain role-qualified names.

property params_all_with_model_name

Return a new Parameters mapping with submodel-role prefixes.

Nested names use role:parameter notation. Values retain their physical units; this operation copies the mapping, not nested mutable values.

required_models = {}

required_param_names = ['re_pc', 'n']

property required_param_names_combined

Return this model’s and all nested submodels’ required parameter names.

The result is a list in traversal order; duplicate names are retained.

sampling_identity(sampled_names=())

Configuration and fixed parameters, excluding changing MCMC coordinates.

update(new_params=None, **kwargs)

Replace named parameters in the owning components.

Notes

Inputs and units. new_params is an optional mapping/Parameters/Series; keyword values are additional replacements. Names are physical names declared by this model and its components. Unknown names raise ValueError before any parameters are changed.

Returns and shape. None; mutates component parameters. params_all returns the resulting flattened copy.