DSphModel#

jeanspy.model.DSphModel

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.DSphModel(show_init=False, submodels=None, **params)#

Bases: jeanspy.model.Model

Composite spherical Jeans model for dwarf spheroidal systems.

Notes

Inputs and units. submodels must contain StellarModel, DMModel and AnisotropyModel; vmem_kms sets mean velocity. sigmalos2 and sigmalos use method="dequad" by default, with n outer and n_kernel inner nodes. R_pc is scalar or nonempty 1-D projected radius; r_pc is intrinsic radius (pc).

Returns and shape. sigmar2 and sigmat2 return intrinsic radial and one-component tangential variances in (km/s)^2. sigmalos2 returns LOS variance arrays with input shape, or a scalar for scalar input. sigmalos returns the corresponding dispersion in km/s. integrand_sigmalos2(u, R_pc) has shape (N_R, N_u).

Validity. Finite positive projected radii; no central-limit LOS solver. Tracer has vanishing outer pressure. Numerical orders and adaptive tolerances are part of the analysis configuration.

Errors. Malformed/invalid projected radii or nonphysical mass, density and integrand values raise ValueError. Adaptive reference integration may issue SciPy integration warnings.

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

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

Examples. examples/docs_spherical.py

integrand_sigmalos2(u, R_pc, n_kernel=128)[source]#

Return the LOS-dispersion integrand.

The integration variable is \(u=r/R\), with domain \(1 < u < \infty\).

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.

name = 'DSphModel'#
ncpu = 4#
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 = {'AnisotropyModel': <class 'jeanspy.model.AnisotropyModel'>, 'DMModel': <class 'jeanspy.model.DMModel'>, 'StellarModel': <class 'jeanspy.model.StellarModel'>}#
required_param_names = ['vmem_kms']#
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.

sigmalos(R_pc, n=1024, n_kernel=128, ignore_RuntimeWarning=True, *, method='dequad')[source]#

Return the LOS velocity dispersion in km/s.

Accepts the same radii, integration method and numerical controls as sigmalos2() and returns its square root. The result is scalar for scalar input, otherwise shape (N,). method="dequad" is the default and currently the only supported choice. The same validity checks and errors apply. This is a NumPy/SciPy calculation without JAX tracing.

sigmalos2(R_pc, n=1024, n_kernel=128, ignore_RuntimeWarning=True, *, method='dequad')[source]#

Return the LOS velocity variance using the selected integration method.

Parameters:

  • R_pc (float or array_like) – Positive finite projected radius in pc; scalar or nonempty 1-D array. The model-dependent central limit at R=0 is not supported.

  • n (int, optional) – Outer quadrature order, default 1024.

  • n_kernel (int, optional) – Anisotropy-kernel quadrature order, default 128.

  • ignore_RuntimeWarning (bool, optional) – Suppress NumPy runtime warnings during integration, default true. Invalid integrands and nonfinite or negative variances still raise.

  • method ({"dequad"}, keyword-only, optional) – Integration method. The fixed double-exponential rule is currently the only supported choice and remains the default.

Returns:

scalar or ndarray – LOS velocity variance in (km/s)^2; scalar for scalar input, otherwise shape (N,).

Raises:

ValueError – Unsupported method, invalid projected radii, or nonphysical density, mass, integrand or variance.

Notes

This NumPy/SciPy calculation reads the stored model parameters. Refine n and n_kernel to check numerical convergence. The NumPy/SciPy inference model uses this entry point with its defaults; no extra callable or closure is needed when passing it to emcee.

sigmar2(r_pc)[source]#

Return the radial velocity dispersion squared at r_pc.

Notes

Inputs and units. r_pc is a scalar or NumPy array of positive intrinsic radii in pc.

Returns and shape. Variance in (km/s)^2, following input shape; scalar input is a zero-dimensional NumPy array.

Validity. Uses adaptive integration to infinite radius with vanishing outer pressure. The intrinsic helpers do not apply all LOS input validation checks.

sigmat2(r_pc)[source]#

Return the tangential velocity dispersion squared at r_pc.

Notes

Inputs and units. r_pc is a scalar or NumPy array of positive intrinsic radii in pc.

Returns and shape. Variance in (km/s)^2, following input shape; scalar input is a zero-dimensional NumPy array.

Validity. Uses adaptive integration to infinite radius with vanishing outer pressure. The intrinsic helpers do not apply all LOS input validation checks.

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.