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bundles / scipy latest / scipy / optimize / _nonlin / LowRankMatrix / svd_reduce

function

scipy.optimize._nonlin:LowRankMatrix.svd_reduce

source: /scipy/optimize/_nonlin.py :767

Signature

def   svd_reduce ( self ,  max_rank ,  to_retain = None )

Summary

Reduce the rank of the matrix by retaining some SVD components.

Extended Summary

This corresponds to the "Broyden Rank Reduction Inverse" algorithm described in [1].

Note that the SVD decomposition can be done by solving only a problem whose size is the effective rank of this matrix, which is viable even for large problems.

Parameters

max_rank : int

Maximum rank of this matrix after reduction.

to_retain : int, optional

Number of SVD components to retain when reduction is done (ie. rank > max_rank). Default is max_rank - 2.

Aliases

  • scipy.optimize._nonlin.LowRankMatrix.svd_reduce