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To remove in the future –– scipy.linalg.blas

Low-level BLAS functions (:mod:`scipy.linalg.blas`)

This module contains low-level functions from the BLAS library.

versionadded
note

The common overwrite_<> option in many routines, allows the input arrays to be overwritten to avoid extra memory allocation. However this requires the array to satisfy two conditions which are memory order and the data type to match exactly the order and the type expected by the routine.

As an example, if you pass a double precision float array to any S.... routine which expects single precision arguments, f2py will create an intermediate array to match the argument types and overwriting will be performed on that intermediate array.

Similarly, if a C-contiguous array is passed, f2py will pass a FORTRAN-contiguous array internally. Please make sure that these details are satisfied. More information can be found in the f2py documentation.

warning

These functions do little to no error checking. It is possible to cause crashes by mis-using them, so prefer using the higher-level routines in :None:None:`scipy.linalg`.

Finding functions

.. autosummary:: 
    :toctree:generated/
    get_blas_funcs
    find_best_blas_type

BLAS Level 1 functions

.. autosummary:: 
    :toctree:generated/
    caxpy
    ccopy
    cdotc
    cdotu
    crotg
    cscal
    csrot
    csscal
    cswap
    dasum
    daxpy
    dcopy
    ddot
    dnrm2
    drot
    drotg
    drotm
    drotmg
    dscal
    dswap
    dzasum
    dznrm2
    icamax
    idamax
    isamax
    izamax
    sasum
    saxpy
    scasum
    scnrm2
    scopy
    sdot
    snrm2
    srot
    srotg
    srotm
    srotmg
    sscal
    sswap
    zaxpy
    zcopy
    zdotc
    zdotu
    zdrot
    zdscal
    zrotg
    zscal
    zswap

BLAS Level 2 functions

.. autosummary:: 
    :toctree:generated/
    sgbmv
    sgemv
    sger
    ssbmv
    sspr
    sspr2
    ssymv
    ssyr
    ssyr2
    stbmv
    stpsv
    strmv
    strsv
    dgbmv
    dgemv
    dger
    dsbmv
    dspr
    dspr2
    dsymv
    dsyr
    dsyr2
    dtbmv
    dtpsv
    dtrmv
    dtrsv
    cgbmv
    cgemv
    cgerc
    cgeru
    chbmv
    chemv
    cher
    cher2
    chpmv
    chpr
    chpr2
    ctbmv
    ctbsv
    ctpmv
    ctpsv
    ctrmv
    ctrsv
    csyr
    zgbmv
    zgemv
    zgerc
    zgeru
    zhbmv
    zhemv
    zher
    zher2
    zhpmv
    zhpr
    zhpr2
    ztbmv
    ztbsv
    ztpmv
    ztrmv
    ztrsv
    zsyr

BLAS Level 3 functions

.. autosummary:: 
    :toctree:generated/
    sgemm
    ssymm
    ssyr2k
    ssyrk
    strmm
    strsm
    dgemm
    dsymm
    dsyr2k
    dsyrk
    dtrmm
    dtrsm
    cgemm
    chemm
    cher2k
    cherk
    csymm
    csyr2k
    csyrk
    ctrmm
    ctrsm
    zgemm
    zhemm
    zher2k
    zherk
    zsymm
    zsyr2k
    zsyrk
    ztrmm
    ztrsm

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.linalg.blas.find_best_blas_type

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


GitHub : /scipy/linalg/blas.py#0
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