lib.survey_selection.window_convolution.CorrelationWindowMatrix¶

class lib.survey_selection.window_convolution.CorrelationWindowMatrix(window=None, sum_wa=True, default_zero=False)¶

Bases: lib.survey_selection.base.BaseRegularMatrix

Class computing matrix for window product in configuration space.

projmatrix¶

Array of shape (len(self.projsout),len(self.projsin),len(self.x)) to convert input array from one basis to another (e.g. multipoles to wedges).

Type: array

Initialize CorrelationWindowMatrix.

Parameters

window (WindowFunction) – Window function to multiply correlation function with.
sum_wa (bool, default=True) – Whether to perform summation over wide-angle orders. Always set to True except for debugging purposes.
default_zero (bool, default=False) – If a given projection is not provided in window function, set to 0. Else an IndexError is raised.

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.
`setup`	Set up transform, i.e. compute matrix:.

Attributes

`basis`
`logger`
`matrix`	Return 2D array of shape `(len(self.projsout)len(self.x),len(self.projsin)len(self.x))` corresponding to `projmatrix`.
`mpiattrs`	MPI attributes
`mpicomm`
`mpiroot`
`mpistate`
`regularin`
`regularout`
`s`	x-coordinates are s-separations.
`xin`	Input x-coordinates.
`xout`	Output x-coordinates.

compute(array)¶: Apply transform to input 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 matrix¶: Return 2D array of shape (len(self.projsout)*len(self.x),len(self.projsin)*len(self.x)) corresponding to projmatrix.

property mpiattrs¶: MPI attributes

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

property s¶: x-coordinates are s-separations.

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.

setup(s, projsin, projsout=None)¶

Set up transform, i.e. compute matrix:

\[W_{\ell,\ell^{\prime}}^{(n,n^{\prime})}(s) = \delta_{n n^{\prime}} \sum_{L} C_{\ell \ell^{\prime} L} Q_{L}^{(n)}(s)\]

with \(\ell\) multipole order corresponding to projout.proj and \(\ell^{\prime}\) to projin.proj, \(n\) wide angle order corresponding to projout.wa_order and \(n^{\prime}\) to projin.wa_order. If sum_wa is True, or output projout.wa_order is None, sum over \(n\) (always the case except for debugging purposes).

Parameters

s (array) – Input (and ouput) separations.
projsin (list, ProjectionNameCollection) – Input projections.
projsout (list, ProjectionNameCollection, default=None) – Output projections. Defaults to propose_out(projsin)[-1].

property xin¶: Input x-coordinates.

property xout¶: Output x-coordinates.