lib.theory.evaluation.ModelEvaluation¶

class lib.theory.evaluation.ModelEvaluation(data_vector, projs=None, model_bases=None, integration=None)¶

Bases: cosmopipe.lib.utils.BaseClass

Class evaluating theory model(s) at given points, optionally performing some integration (e.g. against Legendre polynomials).

Initialize ModelEvaluation.

Parameters

data_vector (DataVector) – Data vector to project onto.
projs (list, ProjectionNameCollection, default=None) – Projection names. If None, defaults to data_vector.get_projs(), i.e. projections within data view. Theory model(s) are matched to each of these projections (using ProjectionBasisCollection.get_by_proj())
model_bases (ProjectionBasis, ProjectionBasisCollection) – Projection basis of input model(s). If single projection basis, a single model is expected in __call__().
integration (dict) – Options for model integration. See set_model_evaluation().

Methods

`copy`	Return shallow copy of `self`.
`deepcopy`
`from_state`	Instantiate and initalize class with state dictionary.
`is_mpi_broadcast`
`is_mpi_gathered`
`is_mpi_root`
`is_mpi_scattered`
`load`	Load class in numpy binary format from disk.
`load_auto`	If different formats are possible, this method should between them based on file name extension.
`log_critical`
`log_debug`
`log_error`
`log_info`
`log_warning`
`propose_out`	Propose output projection names given proposed input projection names `projsin`.
`save`	Save class to disk.
`save_auto`	If different formats are possible, this method should between them based on file name extension.
`set_model_evaluation`	Set engine for model evaluation on projection `proj`.
`to_data_vector`	Same as `__call__()`, but returning `DataVector` instance.

Attributes

`logger`
`mpiattrs`	MPI attributes
`mpicomm`
`mpiroot`
`mpistate`

__call__(models, concatenate=True, remove_shotnoise=True, **kwargs)¶

Project input models onto data vector, returning y-coordinates.

Parameters

models (BaseModel, ModelCollection) – Model callable(s). A single model is expected if a single model basis was provided in __init__().
concatenate (bool, default=True) – If True, concatenates output y-coordinates over all projections. Else, returns a list of arrays corresponding to each projs.
remove_shotnoise (bool, default=True) – For power spectrum models (model.basis.space is 'power'), remove model.basis.shotnoise (defaults to 0).
kwargs (dict) – Arguments for input model(s).

Returns

toret – y-coordinates. If input concatenate is True, single array concatenated over all projections. Else, a list of arrays corresponding to each projs.

Return type

list, array

copy()¶: Return shallow copy of self.

classmethod from_state(state, mpiroot=0, mpicomm=None)¶: Instantiate and initalize class with state dictionary.

classmethod load(filename, mpiroot=0, mpicomm=None)¶: Load class in numpy binary format from disk. If the loaded state contains __class__ and that exists in cls._registry, return instance of cls._registry[__class__] (instead of cls).

load_auto(*args, **kwargs)¶: If different formats are possible, this method should between them based on file name extension.

property mpiattrs¶: MPI attributes

classmethod propose_out(model_bases=None)¶

Propose output projection names given proposed input projection names projsin.

Parameters

projsin (list, ProjectionNameCollection) – Input projections.
model_bases (ProjectionBasis, ProjectionBasisCollection) – Projection basis of input model(s).

Returns

toret – Proposed projection names.

Return type

ProjectionNameCollection

save(filename)¶: Save class to disk.

save_auto(*args, **kwargs)¶: If different formats are possible, this method should between them based on file name extension.

set_model_evaluation(data_vector, proj, model_basis, integration=None)¶

Set engine for model evaluation on projection proj.

Parameters

data_vector (DataVector) – Data vector to project onto.
proj (ProjectionName) – Projection name to project onto.
model_basis (ProjectionBasis) – Model projection basis.
integration (dict) –
Options for model integration:
- MultipoleIntegration if input model lives in \((x,\mu)\) space and proj is a multipole.
- MuWedgeIntegration if input model lives in \((x,\mu)\) space and proj is a \(\mu\)-wedge.

to_data_vector(models, **kwargs)¶: Same as __call__(), but returning DataVector instance.