binny.nz package

Submodules

• binny.nz.calibration module
  • calibrate_depth_smail_from_mock()
  • eval_ngal_of_maglim()
  • eval_z0_of_maglim()
  • fit_ngal_of_maglim_from_mock()
  • fit_smail_params_from_mock()
  • fit_z0_of_maglim_from_mock()
• binny.nz.models module
  • gamma_distribution()
  • gaussian_distribution()
  • gaussian_mixture_distribution()
  • lognormal_distribution()
  • luminosity_function_distribution()
  • schechter_like_distribution()
  • shifted_smail_distribution()
  • skew_normal_distribution()
  • smail_like_distribution()
  • student_t_distribution()
  • tabulated_distribution()
  • tophat_distribution()
• binny.nz.registry module
  • available_models()
  • get_model()
  • nz_model()

Module contents

binny.nz.available_models() → list[str]

Lists the supported redshift-distribution model names.

Returns:

A sorted list of registry keys that can be passed to get_model or nz_model.

binny.nz.get_model(name: str) → Callable[[...], ndarray[tuple[Any, ...], dtype[float64]]]

Gets a registered redshift-distribution model by name.

Parameters:

name – Model name. The lookup is case-insensitive.

Returns:

The callable model associated with name.

Raises:

ValueError – If name is not a known model key.

binny.nz.nz_model(name: str, z: Any, /, **params: Any) → ndarray[tuple[Any, ...], dtype[float64]]

Evaluates a named redshift-distribution model on a redshift grid.

This is a convenience wrapper around get_model that also ensures z and the returned array are np.float64.

Parameters:

• name – Model name. Must be one of available_models().

• z – Redshift grid. Any array-like input accepted by np.asarray.

• **params – Model-specific keyword parameters forwarded to the model.

Returns:

The model evaluated on z as a float64 NumPy array.

Raises:

ValueError – If name is not a known model key.