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"""
Low-level LAPACK functions (:mod:`scipy.linalg.lapack`)
=======================================================
This module contains low-level functions from the LAPACK library.
The `*gegv` family of routines have been removed from LAPACK 3.6.0
and have been deprecated in SciPy 0.17.0. They will be removed in
a future release.
.. versionadded:: 0.12.0
.. 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 `scipy.linalg`.
Finding functions
-----------------
.. autosummary::
:toctree: generated/
get_lapack_funcs
All functions
-------------
.. autosummary::
:toctree: generated/
sgbsv
dgbsv
cgbsv
zgbsv
sgbtrf
dgbtrf
cgbtrf
zgbtrf
sgbtrs
dgbtrs
cgbtrs
zgbtrs
sgebal
dgebal
cgebal
zgebal
sgecon
dgecon
cgecon
zgecon
sgeequ
dgeequ
cgeequ
zgeequ
sgeequb
dgeequb
cgeequb
zgeequb
sgees
dgees
cgees
zgees
sgeev
dgeev
cgeev
zgeev
sgeev_lwork
dgeev_lwork
cgeev_lwork
zgeev_lwork
sgegv
dgegv
cgegv
zgegv
sgehrd
dgehrd
cgehrd
zgehrd
sgehrd_lwork
dgehrd_lwork
cgehrd_lwork
zgehrd_lwork
sgejsv
dgejsv
sgels
dgels
cgels
zgels
sgels_lwork
dgels_lwork
cgels_lwork
zgels_lwork
sgelsd
dgelsd
cgelsd
zgelsd
sgelsd_lwork
dgelsd_lwork
cgelsd_lwork
zgelsd_lwork
sgelss
dgelss
cgelss
zgelss
sgelss_lwork
dgelss_lwork
cgelss_lwork
zgelss_lwork
sgelsy
dgelsy
cgelsy
zgelsy
sgelsy_lwork
dgelsy_lwork
cgelsy_lwork
zgelsy_lwork
sgeqp3
dgeqp3
cgeqp3
zgeqp3
sgeqrf
dgeqrf
cgeqrf
zgeqrf
sgeqrf_lwork
dgeqrf_lwork
cgeqrf_lwork
zgeqrf_lwork
sgeqrfp
dgeqrfp
cgeqrfp
zgeqrfp
sgeqrfp_lwork
dgeqrfp_lwork
cgeqrfp_lwork
zgeqrfp_lwork
sgerqf
dgerqf
cgerqf
zgerqf
sgesdd
dgesdd
cgesdd
zgesdd
sgesdd_lwork
dgesdd_lwork
cgesdd_lwork
zgesdd_lwork
sgesv
dgesv
cgesv
zgesv
sgesvd
dgesvd
cgesvd
zgesvd
sgesvd_lwork
dgesvd_lwork
cgesvd_lwork
zgesvd_lwork
sgesvx
dgesvx
cgesvx
zgesvx
sgetrf
dgetrf
cgetrf
zgetrf
sgetc2
dgetc2
cgetc2
zgetc2
sgetri
dgetri
cgetri
zgetri
sgetri_lwork
dgetri_lwork
cgetri_lwork
zgetri_lwork
sgetrs
dgetrs
cgetrs
zgetrs
sgesc2
dgesc2
cgesc2
zgesc2
sgges
dgges
cgges
zgges
sggev
dggev
cggev
zggev
sgglse
dgglse
cgglse
zgglse
sgglse_lwork
dgglse_lwork
cgglse_lwork
zgglse_lwork
sgtsv
dgtsv
cgtsv
zgtsv
sgtsvx
dgtsvx
cgtsvx
zgtsvx
chbevd
zhbevd
chbevx
zhbevx
checon
zhecon
cheequb
zheequb
cheev
zheev
cheev_lwork
zheev_lwork
cheevd
zheevd
cheevd_lwork
zheevd_lwork
cheevr
zheevr
cheevr_lwork
zheevr_lwork
cheevx
zheevx
cheevx_lwork
zheevx_lwork
chegst
zhegst
chegv
zhegv
chegv_lwork
zhegv_lwork
chegvd
zhegvd
chegvx
zhegvx
chegvx_lwork
zhegvx_lwork
chesv
zhesv
chesv_lwork
zhesv_lwork
chesvx
zhesvx
chesvx_lwork
zhesvx_lwork
chetrd
zhetrd
chetrd_lwork
zhetrd_lwork
chetrf
zhetrf
chetrf_lwork
zhetrf_lwork
chfrk
zhfrk
slamch
dlamch
slange
dlange
clange
zlange
slarf
dlarf
clarf
zlarf
slarfg
dlarfg
clarfg
zlarfg
slartg
dlartg
clartg
zlartg
slasd4
dlasd4
slaswp
dlaswp
claswp
zlaswp
slauum
dlauum
clauum
zlauum
sorcsd
dorcsd
sorcsd_lwork
dorcsd_lwork
sorghr
dorghr
sorghr_lwork
dorghr_lwork
sorgqr
dorgqr
sorgrq
dorgrq
sormqr
dormqr
sormrz
dormrz
sormrz_lwork
dormrz_lwork
spbsv
dpbsv
cpbsv
zpbsv
spbtrf
dpbtrf
cpbtrf
zpbtrf
spbtrs
dpbtrs
cpbtrs
zpbtrs
spftrf
dpftrf
cpftrf
zpftrf
spftri
dpftri
cpftri
zpftri
spftrs
dpftrs
cpftrs
zpftrs
spocon
dpocon
cpocon
zpocon
spstrf
dpstrf
cpstrf
zpstrf
spstf2
dpstf2
cpstf2
zpstf2
sposv
dposv
cposv
zposv
sposvx
dposvx
cposvx
zposvx
spotrf
dpotrf
cpotrf
zpotrf
spotri
dpotri
cpotri
zpotri
spotrs
dpotrs
cpotrs
zpotrs
sppcon
dppcon
cppcon
zppcon
sppsv
dppsv
cppsv
zppsv
spptrf
dpptrf
cpptrf
zpptrf
spptri
dpptri
cpptri
zpptri
spptrs
dpptrs
cpptrs
zpptrs
sptsv
dptsv
cptsv
zptsv
sptsvx
dptsvx
cptsvx
zptsvx
spttrf
dpttrf
cpttrf
zpttrf
spttrs
dpttrs
cpttrs
zpttrs
spteqr
dpteqr
cpteqr
zpteqr
crot
zrot
ssbev
dsbev
ssbevd
dsbevd
ssbevx
dsbevx
ssfrk
dsfrk
sstebz
dstebz
sstein
dstein
sstemr
dstemr
sstemr_lwork
dstemr_lwork
ssterf
dsterf
sstev
dstev
ssycon
dsycon
csycon
zsycon
ssyconv
dsyconv
csyconv
zsyconv
ssyequb
dsyequb
csyequb
zsyequb
ssyev
dsyev
ssyev_lwork
dsyev_lwork
ssyevd
dsyevd
ssyevd_lwork
dsyevd_lwork
ssyevr
dsyevr
ssyevr_lwork
dsyevr_lwork
ssyevx
dsyevx
ssyevx_lwork
dsyevx_lwork
ssygst
dsygst
ssygv
dsygv
ssygv_lwork
dsygv_lwork
ssygvd
dsygvd
ssygvx
dsygvx
ssygvx_lwork
dsygvx_lwork
ssysv
dsysv
csysv
zsysv
ssysv_lwork
dsysv_lwork
csysv_lwork
zsysv_lwork
ssysvx
dsysvx
csysvx
zsysvx
ssysvx_lwork
dsysvx_lwork
csysvx_lwork
zsysvx_lwork
ssytf2
dsytf2
csytf2
zsytf2
ssytrd
dsytrd
ssytrd_lwork
dsytrd_lwork
ssytrf
dsytrf
csytrf
zsytrf
ssytrf_lwork
dsytrf_lwork
csytrf_lwork
zsytrf_lwork
stbtrs
dtbtrs
ctbtrs
ztbtrs
stfsm
dtfsm
ctfsm
ztfsm
stfttp
dtfttp
ctfttp
ztfttp
stfttr
dtfttr
ctfttr
ztfttr
stgsen
dtgsen
ctgsen
ztgsen
stpttf
dtpttf
ctpttf
ztpttf
stpttr
dtpttr
ctpttr
ztpttr
strsyl
dtrsyl
ctrsyl
ztrsyl
strtri
dtrtri
ctrtri
ztrtri
strtrs
dtrtrs
ctrtrs
ztrtrs
strttf
dtrttf
ctrttf
ztrttf
strttp
dtrttp
ctrttp
ztrttp
stzrzf
dtzrzf
ctzrzf
ztzrzf
stzrzf_lwork
dtzrzf_lwork
ctzrzf_lwork
ztzrzf_lwork
cunghr
zunghr
cunghr_lwork
zunghr_lwork
cungqr
zungqr
cungrq
zungrq
cunmqr
zunmqr
sgeqrt
dgeqrt
cgeqrt
zgeqrt
sgemqrt
dgemqrt
cgemqrt
zgemqrt
sgttrf
dgttrf
cgttrf
zgttrf
sgttrs
dgttrs
cgttrs
zgttrs
stpqrt
dtpqrt
ctpqrt
ztpqrt
stpmqrt
dtpmqrt
ctpmqrt
ztpmqrt
cuncsd
zuncsd
cuncsd_lwork
zuncsd_lwork
cunmrz
zunmrz
cunmrz_lwork
zunmrz_lwork
ilaver
"""
#
# Author: Pearu Peterson, March 2002
#
import numpy as _np
from .blas import _get_funcs, _memoize_get_funcs
from scipy.linalg import _flapack
from re import compile as regex_compile
try:
from scipy.linalg import _clapack
except ImportError:
_clapack = None
try:
from scipy.linalg import _flapack_64
HAS_ILP64 = True
except ImportError:
HAS_ILP64 = False
_flapack_64 = None
# Backward compatibility
from scipy._lib._util import DeprecatedImport as _DeprecatedImport
clapack = _DeprecatedImport("scipy.linalg.blas.clapack", "scipy.linalg.lapack")
flapack = _DeprecatedImport("scipy.linalg.blas.flapack", "scipy.linalg.lapack")
# Expose all functions (only flapack --- clapack is an implementation detail)
empty_module = None
from scipy.linalg._flapack import *
del empty_module
__all__ = ['get_lapack_funcs']
_dep_message = """The `*gegv` family of routines has been deprecated in
LAPACK 3.6.0 in favor of the `*ggev` family of routines.
The corresponding wrappers will be removed from SciPy in
a future release."""
cgegv = _np.deprecate(cgegv, old_name='cgegv', message=_dep_message)
dgegv = _np.deprecate(dgegv, old_name='dgegv', message=_dep_message)
sgegv = _np.deprecate(sgegv, old_name='sgegv', message=_dep_message)
zgegv = _np.deprecate(zgegv, old_name='zgegv', message=_dep_message)
# Modify _flapack in this scope so the deprecation warnings apply to
# functions returned by get_lapack_funcs.
_flapack.cgegv = cgegv
_flapack.dgegv = dgegv
_flapack.sgegv = sgegv
_flapack.zgegv = zgegv
# some convenience alias for complex functions
_lapack_alias = {
'corghr': 'cunghr', 'zorghr': 'zunghr',
'corghr_lwork': 'cunghr_lwork', 'zorghr_lwork': 'zunghr_lwork',
'corgqr': 'cungqr', 'zorgqr': 'zungqr',
'cormqr': 'cunmqr', 'zormqr': 'zunmqr',
'corgrq': 'cungrq', 'zorgrq': 'zungrq',
}
# Place guards against docstring rendering issues with special characters
p1 = regex_compile(r'with bounds (?P<b>.*?)( and (?P<s>.*?) storage){0,1}\n')
p2 = regex_compile(r'Default: (?P<d>.*?)\n')
def backtickrepl(m):
if m.group('s'):
return ('with bounds ``{}`` with ``{}`` storage\n'
''.format(m.group('b'), m.group('s')))
else:
return 'with bounds ``{}``\n'.format(m.group('b'))
for routine in [ssyevr, dsyevr, cheevr, zheevr,
ssyevx, dsyevx, cheevx, zheevx,
ssygvd, dsygvd, chegvd, zhegvd]:
if routine.__doc__:
routine.__doc__ = p1.sub(backtickrepl, routine.__doc__)
routine.__doc__ = p2.sub('Default ``\\1``\n', routine.__doc__)
else:
continue
del regex_compile, p1, p2, backtickrepl
@_memoize_get_funcs
def get_lapack_funcs(names, arrays=(), dtype=None, ilp64=False):
"""Return available LAPACK function objects from names.
Arrays are used to determine the optimal prefix of LAPACK routines.
Parameters
----------
names : str or sequence of str
Name(s) of LAPACK functions without type prefix.
arrays : sequence of ndarrays, optional
Arrays can be given to determine optimal prefix of LAPACK
routines. If not given, double-precision routines will be
used, otherwise the most generic type in arrays will be used.
dtype : str or dtype, optional
Data-type specifier. Not used if `arrays` is non-empty.
ilp64 : {True, False, 'preferred'}, optional
Whether to return ILP64 routine variant.
Choosing 'preferred' returns ILP64 routine if available, and
otherwise the 32-bit routine. Default: False
Returns
-------
funcs : list
List containing the found function(s).
Notes
-----
This routine automatically chooses between Fortran/C
interfaces. Fortran code is used whenever possible for arrays with
column major order. In all other cases, C code is preferred.
In LAPACK, the naming convention is that all functions start with a
type prefix, which depends on the type of the principal
matrix. These can be one of {'s', 'd', 'c', 'z'} for the NumPy
types {float32, float64, complex64, complex128} respectively, and
are stored in attribute ``typecode`` of the returned functions.
Examples
--------
Suppose we would like to use '?lange' routine which computes the selected
norm of an array. We pass our array in order to get the correct 'lange'
flavor.
>>> import scipy.linalg as LA
>>> a = np.random.rand(3,2)
>>> x_lange = LA.get_lapack_funcs('lange', (a,))
>>> x_lange.typecode
'd'
>>> x_lange = LA.get_lapack_funcs('lange',(a*1j,))
>>> x_lange.typecode
'z'
Several LAPACK routines work best when its internal WORK array has
the optimal size (big enough for fast computation and small enough to
avoid waste of memory). This size is determined also by a dedicated query
to the function which is often wrapped as a standalone function and
commonly denoted as ``###_lwork``. Below is an example for ``?sysv``
>>> import scipy.linalg as LA
>>> a = np.random.rand(1000,1000)
>>> b = np.random.rand(1000,1)*1j
>>> # We pick up zsysv and zsysv_lwork due to b array
... xsysv, xlwork = LA.get_lapack_funcs(('sysv', 'sysv_lwork'), (a, b))
>>> opt_lwork, _ = xlwork(a.shape[0]) # returns a complex for 'z' prefix
>>> udut, ipiv, x, info = xsysv(a, b, lwork=int(opt_lwork.real))
"""
if isinstance(ilp64, str):
if ilp64 == 'preferred':
ilp64 = HAS_ILP64
else:
raise ValueError("Invalid value for 'ilp64'")
if not ilp64:
return _get_funcs(names, arrays, dtype,
"LAPACK", _flapack, _clapack,
"flapack", "clapack", _lapack_alias,
ilp64=False)
else:
if not HAS_ILP64:
raise RuntimeError("LAPACK ILP64 routine requested, but Scipy "
"compiled only with 32-bit BLAS")
return _get_funcs(names, arrays, dtype,
"LAPACK", _flapack_64, None,
"flapack_64", None, _lapack_alias,
ilp64=True)
_int32_max = _np.iinfo(_np.int32).max
_int64_max = _np.iinfo(_np.int64).max
def _compute_lwork(routine, *args, **kwargs):
"""
Round floating-point lwork returned by lapack to integer.
Several LAPACK routines compute optimal values for LWORK, which
they return in a floating-point variable. However, for large
values of LWORK, single-precision floating point is not sufficient
to hold the exact value --- some LAPACK versions (<= 3.5.0 at
least) truncate the returned integer to single precision and in
some cases this can be smaller than the required value.
Examples
--------
>>> from scipy.linalg import lapack
>>> n = 5000
>>> s_r, s_lw = lapack.get_lapack_funcs(('sysvx', 'sysvx_lwork'))
>>> lwork = lapack._compute_lwork(s_lw, n)
>>> lwork
32000
"""
dtype = getattr(routine, 'dtype', None)
int_dtype = getattr(routine, 'int_dtype', None)
ret = routine(*args, **kwargs)
if ret[-1] != 0:
raise ValueError("Internal work array size computation failed: "
"%d" % (ret[-1],))
if len(ret) == 2:
return _check_work_float(ret[0].real, dtype, int_dtype)
else:
return tuple(_check_work_float(x.real, dtype, int_dtype)
for x in ret[:-1])
def _check_work_float(value, dtype, int_dtype):
"""
Convert LAPACK-returned work array size float to integer,
carefully for single-precision types.
"""
if dtype == _np.float32 or dtype == _np.complex64:
# Single-precision routine -- take next fp value to work
# around possible truncation in LAPACK code
value = _np.nextafter(value, _np.inf, dtype=_np.float32)
value = int(value)
if int_dtype.itemsize == 4:
if value < 0 or value > _int32_max:
raise ValueError("Too large work array required -- computation "
"cannot be performed with standard 32-bit"
" LAPACK.")
elif int_dtype.itemsize == 8:
if value < 0 or value > _int64_max:
raise ValueError("Too large work array required -- computation"
" cannot be performed with standard 64-bit"
" LAPACK.")
return value