AnisotropyModel

jeanspy.model.AnisotropyModel

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.AnisotropyModel(show_init=False, submodels=None, **params)

Bases: jeanspy.model.Model

Subclassing interface for spherical anisotropy.

Notes

Inputs and units. Implement beta(r_pc), f(r_pc) and kernel(u,``R_pc``,n) consistently; radii use pc and u=r/R.

Returns and shape. Dimensionless beta/kernel and an arbitrary-normalization integrating factor f.

Validity. Steady spherical Jeans closure; beta is distinct from axisymmetric beta_z.

Errors. Abstract methods raise NotImplementedError.

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

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

Examples. examples/docs_profiles.py

abstractmethod beta(r)

Evaluate dimensionless spherical anisotropy at radius r in pc.

Subclasses must implement this interface; the base method raises NotImplementedError. Concrete models define scalar/array broadcasting.

abstractmethod f(r)

Evaluate the Jeans integrating factor at radius r in pc.

Its overall normalization cancels in the Jeans solution. Subclasses must implement this interface; the base method raises NotImplementedError.

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.

abstractmethod kernel(u, R, **kwargs)

Evaluate the dimensionless LOS kernel for u=r/R and projected radius R.

Use u>=1, R>0 in pc and broadcastable arrays. Subclasses define numerical kwargs; the base method raises NotImplementedError.

name = 'AnisotropyModel'

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.

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.