<reponame>evgueni-ovtchinnikov/raleigh<filename>raleigh/interfaces/__init__.py
'''Driver routines for RALEIGH solver. Provide user friendly SciPy-style
   interfaces to RALEIGH abstract solver.

lra:
    Implements a class for handling the computation of lower rank approximations
    of dense matrices.

partial_hevp:
    Computes several eigenpairs of sparse real symmetric/Hermitian eigenvalue
    problems using either shift-invert or preconditioning technique.
    Requires MKL 10.3 or later (needs mkl_rt.dll on Windows, libmkl_rt.so on
    Linux).

partial_svd:
    Computes several extreme singular values of a dense matrix and corresponding
    singular vectors. On CPU, performs better if MKL 10.3 or later is available.
    Can also run on GPU.

pca:
    Performs principal component analysis for the set of data items represented
    by rows of a dense matrix.

truncated_svd:
    Computes truncated Singular Value Decomposition of a dense matrix.
'''

'''Driver routines for RALEIGH solver. Provide user friendly SciPy-style
   interfaces to RALEIGH abstract solver.

lra:
    Implements a class for handling the computation of lower rank approximations
    of dense matrices.

partial_hevp:
    Computes several eigenpairs of sparse real symmetric/Hermitian eigenvalue
    problems using either shift-invert or preconditioning technique.
    Requires MKL 10.3 or later (needs mkl_rt.dll on Windows, libmkl_rt.so on
    Linux).

partial_svd:
    Computes several extreme singular values of a dense matrix and corresponding
    singular vectors. On CPU, performs better if MKL 10.3 or later is available.
    Can also run on GPU.

pca:
    Performs principal component analysis for the set of data items represented
    by rows of a dense matrix.

truncated_svd:
    Computes truncated Singular Value Decomposition of a dense matrix.
'''
Driver routines for RALEIGH solver. Provide user friendly SciPy-style    interfaces to RALEIGH abstract solver.  lra:     Implements a class for handling the computation of lower rank approximations     of dense matrices.  partial_hevp:     Computes several eigenpairs of sparse real symmetric/Hermitian eigenvalue     problems using either shift-invert or preconditioning technique.     Requires MKL 10.3 or later (needs mkl_rt.dll on Windows, libmkl_rt.so on     Linux).  partial_svd:     Computes several extreme singular values of a dense matrix and corresponding     singular vectors. On CPU, performs better if MKL 10.3 or later is available.     Can also run on GPU.  pca:     Performs principal component analysis for the set of data items represented     by rows of a dense matrix.  truncated_svd:     Computes truncated Singular Value Decomposition of a dense matrix.