lib.survey_selection.base.BaseRegularMatrix¶

class lib.survey_selection.base.BaseRegularMatrix¶

Base class to represent a linear transform of the theory model, with same array size for each input and output projections.

x-coordinates, same for each input and output projections.

Methods

`compute`	Apply transform to input array.
`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 input and 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.

Attributes

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.

propose_out(projsin)¶: Propose input and output projection names given proposed input projection names projsin.

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