lib.survey_selection.projection.ModelProjection¶

class lib.survey_selection.projection.ModelProjection(data_vector, projs=None, model_bases=None, integration=None)¶

Bases: cosmopipe.lib.utils.BaseClass

Class projecting theory model onto data vector by chaining several matrix operations, accounting for the various survey selection effects: wide-angle, window function etc.

model_bases¶

Projection bases of input theory models.

Type: ProjectionBasisCollection

data_vector¶

Data vector to project onto.

Type: DataVector

projs¶

Projection names.

Type: ProjectionNameCollection

operations¶

List of successive matrix operations to apply.

Type: list

Initialize ModelProjection.

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.
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 evaluation / integration, see ModelEvaluation.

Methods

`append`	Append operation to the list of operations `operations`.
`copy`	Return shallow-copy of model projection, including internal list of operations `operations`.
`deepcopy`
`from_state`	Instantiate and initalize class with state dictionary.
`insert`	Insert operation at index `index` in list of operations `operations`.
`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`
`save`	Save class to disk.
`save_auto`	If different formats are possible, this method should between them based on file name extension.
`set_data_vector`	Set `data_vector`.
`set_projs`	Set `projs`.
`setup`	Compile all operations of `operations` into a single matrix transform.
`to_data_vector`	Same as `__call__()`, but returning `DataVector` instance.

Attributes

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

__call__(models, concatenate=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.
kwargs (dict) – Arguments for ModelEvaluation.__call__().

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

append(operation)¶: Append operation to the list of operations operations.

copy(copy_operations=True)¶: Return shallow-copy of model projection, including internal list of operations operations. If copy_operations is True, further shallow-copy each operation.

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

insert(index, operation)¶: Insert operation at index index in list of operations operations.

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

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_data_vector(data_vector)¶: Set data_vector.

set_projs(projs)¶: Set projs.

setup(data_vector=None, projs=None)¶

Compile all operations of operations into a single matrix transform.

Parameters

data_vector (DataVector, default=None) – Data vector to project onto. If not None, replace current data_vector.
projs (list, ProjectionNameCollection) – Projection names. If not None, replace current projs.

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