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flapack_gen.pyf.src
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flapack_gen.pyf.src
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! Signatures for f2py-wrappers of FORTRAN LAPACK General Matrix functions.
!
subroutine <prefix>gebal(scale,permute,n,a,m,lo,hi,pivscale,info)
!
! ba,lo,hi,pivscale,info = gebal(a,scale=0,permute=0,overwrite_a=0)
! Balance general matrix a.
! hi,lo are such that ba[i][j]==0 if i>j and j=0...lo-1 or i=hi+1..n-1
! pivscale([0:lo], [lo:hi+1], [hi:n+1]) = (p1,d,p2) where (p1,p2)[j] is
! the index of the row and column interchanged with row and column j.
! d[j] is the scaling factor applied to row and column j.
! The order in which the interchanges are made is n-1 to hi+1, then 0 to lo-1.
!
! P * A * P = [[T1,X,Y],[0,B,Z],[0,0,T2]]
! BA = [[T1,X*D,Y],[0,inv(D)*B*D,ind(D)*Z],[0,0,T2]]
! where D = diag(d), T1,T2 are upper triangular matrices.
! lo,hi mark the starting and ending columns of submatrix B.
callstatement { (*f2py_func)((permute?(scale?"B":"P"):(scale?"S":"N")),&n,a,&m,&lo,&hi,pivscale,&info); hi--; lo--; }
callprotoargument char*,int*,<ctype>*,int*,int*,int*,<ctypereal>*,int*
integer intent(in),optional :: permute = 0
integer intent(in),optional :: scale = 0
integer intent(hide),depend(a,n) :: m = shape(a,0)
integer intent(hide),depend(a) :: n = shape(a,1)
check(m>=n) m
integer intent(out) :: hi,lo
<ftypereal> dimension(n),intent(out),depend(n) :: pivscale
<ftype> dimension(m,n),intent(in,out,copy,out=ba) :: a
integer intent(out) :: info
end subroutine <prefix>gebal
subroutine <prefix>gehrd(n,lo,hi,a,tau,work,lwork,info)
!
! hq,tau,info = gehrd(a,lo=0,hi=n-1,lwork=n,overwrite_a=0)
! Reduce general matrix A to upper Hessenberg form H by unitary similarity
! transform Q^H * A * Q = H
!
! Q = H(lo) * H(lo+1) * ... * H(hi-1)
! H(i) = I - tau * v * v^H
! v[0:i+1] = 0, v[i+1]=1, v[hi+1:n] = 0
! v[i+2:hi+1] is stored in hq[i+2:hi+i,i]
! tau is tau[i]
!
! hq for n=7,lo=1,hi=5:
! [a a h h h h a
! a h h h h a
! h h h h h h
! v2h h h h h
! v2v3h h h h
! v2v3v4h h h
! a]
!
callstatement { hi++; lo++; (*f2py_func)(&n,&lo,&hi,a,&n,tau,work,&lwork,&info); }
callprotoargument int*,int*,int*,<ctype>*,int*,<ctype>*,<ctype>*,int*,int*
integer intent(hide),depend(a) :: n = shape(a,0)
<ftype> dimension(n,n),intent(in,out,copy,out=ht,aligned8),check(shape(a,0)==shape(a,1)) :: a
integer intent(in),optional :: lo = 0
integer intent(in),optional,depend(n) :: hi = n-1
<ftype> dimension(n-1),intent(out),depend(n) :: tau
<ftype> dimension(lwork),intent(cache,hide),depend(lwork) :: work
integer intent(in),optional,depend(n),check(lwork>=MAX(n,1)) :: lwork = MAX(n,1)
integer intent(out) :: info
end subroutine <prefix>gehrd
subroutine <prefix>gehrd_lwork(n,lo,hi,a,tau,work,lwork,info)
! LWORK computation for GEHRD
fortranname <prefix>gehrd
callstatement { hi++; lo++; (*f2py_func)(&n,&lo,&hi,&a,&n,&tau,&work,&lwork,&info); }
callprotoargument int*,int*,int*,<ctype>*,int*,<ctype>*,<ctype>*,int*,int*
integer intent(in) :: n
<ftype> intent(hide) :: a
integer intent(in),optional :: lo = 0
integer intent(in),optional,depend(n) :: hi = n-1
<ftype> intent(hide) :: tau
<ftype> intent(out) :: work
integer intent(hide) :: lwork = -1
integer intent(out) :: info
end subroutine <prefix>gehrd_lwork
subroutine <prefix>gesv(n,nrhs,a,piv,b,info)
! lu,piv,x,info = gesv(a,b,overwrite_a=0,overwrite_b=0)
! Solve A * X = B.
! A = P * L * U
! U is upper diagonal triangular, L is unit lower triangular,
! piv pivots columns.
callstatement {int i;(*f2py_func)(&n,&nrhs,a,&n,piv,b,&n,&info);for(i=0;i\<n;--piv[i++]);}
callprotoargument int*,int*,<ctype>*,int*,int*,<ctype>*,int*,int*
integer depend(a),intent(hide):: n = shape(a,0)
integer depend(b),intent(hide):: nrhs = shape(b,1)
<ftype> dimension(n,n),check(shape(a,0)==shape(a,1)) :: a
integer dimension(n),depend(n),intent(out) :: piv
<ftype> dimension(n,nrhs),check(shape(a,0)==shape(b,0)),depend(n) :: b
integer intent(out)::info
intent(in,out,copy,out=x) b
intent(in,out,copy,out=lu) a
end subroutine <prefix>gesv
subroutine <prefix2>gesvx(fact,trans,n,nrhs,a,lda,af,ldaf,ipiv,equed,r,c,b,ldb,x,ldx,rcond,ferr,berr,work,iwork,info)
! Solve A * X = B using LU decomposition
! The expert driver of ?GESV with condition number, backward/forward error estimates, and iterative refinement
! This part takes care of the data types, single and double reals (sgesvx and dgesvx)
threadsafe
callstatement {int i;(*f2py_func)(fact,trans,&n,&nrhs,a,&lda,af,&ldaf,ipiv,equed,r,c,b,&ldb,x,&ldx,&rcond,ferr,berr,work,iwork,&info);for(i=0;i\<n;--ipiv[i++]);}
callprotoargument char*,char*,int*,int*,<ctype2>*,int*,<ctype2>*,int*,int*,char*,<ctype2>*,<ctype2>*,<ctype2>*,int*,<ctype2>*,int*,<ctype2>*,<ctype2>*,<ctype2>*,<ctype2>*,int*,int*
character optional,intent(in):: trans = "N"
character optional,intent(in):: fact = "E"
integer depend(a),intent(hide):: n = shape(a,0)
integer depend(b),intent(hide):: nrhs = shape(b,1)
<ftype2> dimension(n,n),check(shape(a,0)==shape(a,1)),intent(in,out,copy,out=as):: a
integer depend(a),intent(hide):: lda = shape(a,0)
<ftype2> optional,dimension(n,n),intent(in,out,out=lu):: af
integer optional,depend(af),intent(hide):: ldaf = shape(af,0)
integer optional,dimension(n),depend(n),intent(in,out):: ipiv
character optional,intent(in,out):: equed = "B"
<ftype2> optional,dimension(n),depend(n),intent(in,out,out=rs):: r
<ftype2> optional,dimension(n),depend(n),intent(in,out,out=cs):: c
<ftype2> depend(n),dimension(n,nrhs),intent(in,out,copy,out=bs):: b
integer depend(b),intent(hide):: ldb = shape(b,0)
<ftype2> dimension(n,nrhs),depend(n,nrhs),intent(out):: x
integer depend(n),intent(hide):: ldx = n
<ftype2> intent(out):: rcond
<ftype2> intent(out),dimension(nrhs),depend(nrhs):: ferr
<ftype2> intent(out),dimension(nrhs),depend(nrhs):: berr
<ftype2> dimension(4*n),depend(n),intent(hide,cache):: work
integer intent(hide,cache),dimension(n),depend(n) :: iwork
integer intent(out):: info
end subroutine <prefix2>gesvx
subroutine <prefix2c>gesvx(fact,trans,n,nrhs,a,lda,af,ldaf,ipiv,equed,r,c,b,ldb,x,ldx,rcond,ferr,berr,work,rwork,info)
! Solve A * X = B using LU decomposition
! The expert driver of ?GESV with condition number, backward/forward error estimates, and iterative refinement
! This part takes care of the data types, complex and double complex (cgesvx and zgesvx)
threadsafe
callstatement {int i;(*f2py_func)(fact,trans,&n,&nrhs,a,&lda,af,&ldaf,ipiv,equed,r,c,b,&ldb,x,&ldx,&rcond,ferr,berr,work,rwork,&info);for(i=0;i\<n;--ipiv[i++]);}
callprotoargument char*,char*,int*,int*,<ctype2c>*,int*,<ctype2c>*,int*,int*,char*,<ctype2>*,<ctype2>*,<ctype2c>*,int*,<ctype2c>*,int*,<ctype2>*,<ctype2>*,<ctype2>*,<ctype2c>*,<ctype2>*,int*
character optional,intent(in):: trans = "N"
character optional,intent(in):: fact = "E"
integer depend(a),intent(hide):: n = shape(a,0)
integer depend(b),intent(hide):: nrhs = shape(b,1)
<ftype2c> dimension(n,n),check(shape(a,0)==shape(a,1)),intent(in,out,copy,out=as):: a
integer depend(a),intent(hide):: lda = shape(a,0)
<ftype2c> optional,dimension(n,n),depend(n),intent(in,out,out=lu):: af
integer optional,depend(af),intent(hide):: ldaf = shape(af,0)
integer optional,dimension(n),depend(n),intent(in,out):: ipiv
character optional,intent(in,out):: equed = "B"
<ftype2> optional,dimension(n),depend(n),intent(in,out,out=rs):: r
<ftype2> optional,dimension(n),depend(n),intent(in,out,out=cs):: c
<ftype2c> depend(n),dimension(n,nrhs),intent(in,out,copy,out=bs):: b
integer depend(b),intent(hide):: ldb = shape(b,0)
<ftype2c> dimension(n,nrhs),depend(n,nrhs),intent(out):: x
integer depend(n),intent(hide):: ldx = n
<ftype2> intent(out):: rcond
<ftype2> intent(out),dimension(nrhs),depend(nrhs):: ferr
<ftype2> intent(out),dimension(nrhs),depend(nrhs):: berr
<ftype2c> dimension(2*n),depend(n),intent(hide,cache):: work
<ftype2> intent(hide,cache),dimension(2*n),depend(n) :: rwork
integer intent(out):: info
end subroutine <prefix2c>gesvx
subroutine <prefix>gecon(norm,n,a,lda,anorm,rcond,work,irwork,info)
! Computes the 1- or inf- norm reciprocal condition number estimate.
threadsafe
callstatement (*f2py_func)(norm,&n,a,&lda,&anorm,&rcond,work,irwork,&info)
callprotoargument char*,int*,<ctype>*,int*,<ctypereal>*,<ctypereal>*,<ctype>*,<int,int,float,double>*,int*
character optional,intent(in):: norm = '1'
integer depend(a),intent(hide):: n = shape(a,0)
<ftype> dimension(n,n),check(shape(a,0)==shape(a,1)),intent(in):: a
integer depend(a),intent(hide):: lda = shape(a,0)
<ftypereal> intent(in):: anorm
<ftypereal> intent(out):: rcond
<ftype> depend(n),dimension(<4*n,4*n,2*n,2*n>),intent(hide,cache):: work
<integer,integer,real, double precision> depend(n),dimension(<n,n,2*n,2*n>),intent(hide,cache):: irwork
integer intent(out):: info
end subroutine <prefix>gecon
subroutine <prefix>getrf(m,n,a,piv,info)
! lu,piv,info = getrf(a,overwrite_a=0)
! Compute an LU factorization of a general M-by-N matrix A.
! A = P * L * U
threadsafe
callstatement {int i;(*f2py_func)(&m,&n,a,&m,piv,&info);for(i=0,n=MIN(m,n);i\<n;--piv[i++]);}
callprotoargument int*,int*,<ctype>*,int*,int*,int*
integer depend(a),intent(hide):: m = shape(a,0)
integer depend(a),intent(hide):: n = shape(a,1)
<ftype> dimension(m,n),intent(in,out,copy,out=lu) :: a
integer dimension(MIN(m,n)),depend(m,n),intent(out) :: piv
integer intent(out):: info
end subroutine <prefix>getrf
subroutine <prefix>getrs(n,nrhs,lu,piv,b,info,trans)
! x,info = getrs(lu,piv,b,trans=0,overwrite_b=0)
! Solve A * X = B if trans=0
! Solve A^T * X = B if trans=1
! Solve A^H * X = B if trans=2
! A = P * L * U
threadsafe
callstatement {int i;for(i=0;i\<n;++piv[i++]);(*f2py_func)((trans?(trans==2?"C":"T"):"N"),&n,&nrhs,lu,&n,piv,b,&n,&info);for(i=0;i\<n;--piv[i++]);}
callprotoargument char*,int*,int*,<ctype>*,int*,int*,<ctype>*,int*,int*
integer optional,intent(in),check(trans>=0 && trans <=2) :: trans = 0
integer depend(lu),intent(hide):: n = shape(lu,0)
integer depend(b),intent(hide):: nrhs = shape(b,1)
<ftype> dimension(n,n),intent(in) :: lu
check(shape(lu,0)==shape(lu,1)) :: lu
integer dimension(n),intent(in),depend(n) :: piv
<ftype> dimension(n,nrhs),intent(in,out,copy,out=x),depend(n),check(shape(lu,0)==shape(b,0)) :: b
integer intent(out):: info
end subroutine <prefix>getrs
subroutine <prefix>getri(n,lu,piv,work,lwork,info)
! inv_a,info = getri(lu,piv,lwork=3*n,overwrite_lu=0)
! Find A inverse A^-1.
! A = P * L * U
callstatement {int i;for(i=0;i\<n;++piv[i++]);(*f2py_func)(&n,lu,&n,piv,work,&lwork,&info);for(i=0;i\<n;--piv[i++]);}
callprotoargument int*,<ctype>*,int*,int*,<ctype>*,int*,int*
integer depend(lu),intent(hide):: n = shape(lu,0)
<ftype> dimension(n,n),intent(in,out,copy,out=inv_a) :: lu
check(shape(lu,0)==shape(lu,1)) :: lu
integer dimension(n),intent(in),depend(n) :: piv
integer intent(out):: info
integer optional,intent(in),depend(n),check(lwork>=n) :: lwork=max(3*n,1)
<ftype> dimension(lwork),intent(hide,cache),depend(lwork) :: work
end subroutine <prefix>getri
subroutine <prefix>getri_lwork(n,lu,piv,work,lwork,info)
! *GETRI LWORK query
fortranname <prefix>getri
callstatement (*f2py_func)(&n,&lu,&n,&piv,&work,&lwork,&info)
callprotoargument int*,<ctype>*,int*,int*,<ctype>*,int*,int*
integer intent(in):: n
<ftype> intent(hide) :: lu
integer intent(hide) :: piv
integer intent(out):: info
integer intent(hide) :: lwork=-1
<ftype> intent(out) :: work
end subroutine <prefix>getri_lwork
subroutine <prefix2>gesdd(m,n,minmn,u0,u1,vt0,vt1,a,compute_uv,full_matrices,u,s,vt,work,lwork,iwork,info)
! u,s,vt,info = gesdd(a,compute_uv=1,lwork=..,overwrite_a=0)
! Compute the singular value decomposition (SVD) using divide and conquer:
! A = U * SIGMA * transpose(V)
! A - M x N matrix
! U - M x M matrix or min(M,N) x N if full_matrices=False
! SIGMA - M x N zero matrix with a main diagonal filled with min(M,N)
! singular values
! transpose(V) - N x N matrix or N x min(M,N) if full_matrices=False
callstatement (*f2py_func)((compute_uv?(full_matrices?"A":"S"):"N"),&m,&n,a,&m,s,u,&u0,vt,&vt0,work,&lwork,iwork,&info)
callprotoargument char*,int*,int*,<ctype2>*,int*,<ctype2>*,<ctype2>*,int*,<ctype2>*,int*,<ctype2>*,int*,int*,int*
integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1
integer intent(in),optional,check(full_matrices==0||full_matrices==1):: full_matrices = 1
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
integer intent(hide),depend(m,n):: minmn = MIN(m,n)
integer intent(hide),depend(compute_uv,minmn) :: u0 = (compute_uv?m:1)
integer intent(hide),depend(compute_uv,minmn, full_matrices) :: u1 = (compute_uv?(full_matrices?m:minmn):1)
integer intent(hide),depend(compute_uv,minmn, full_matrices) :: vt0 = (compute_uv?(full_matrices?n:minmn):1)
integer intent(hide),depend(compute_uv,minmn) :: vt1 = (compute_uv?n:1)
<ftype2> dimension(m,n),intent(in,copy,aligned8) :: a
<ftype2> dimension(minmn),intent(out),depend(minmn) :: s
<ftype2> dimension(u0,u1),intent(out),depend(u0, u1) :: u
<ftype2> dimension(vt0,vt1),intent(out),depend(vt0, vt1) :: vt
<ftype2> dimension(lwork),intent(hide,cache),depend(lwork) :: work
integer optional,intent(in),depend(minmn,compute_uv) &
:: lwork = max((compute_uv?4*minmn*minmn+MAX(m,n)+9*minmn:MAX(14*minmn+4,10*minmn+2+25*(25+8))+MAX(m,n)),1)
integer intent(hide,cache),dimension(8*minmn),depend(minmn) :: iwork
integer intent(out)::info
end subroutine <prefix2>gesdd
subroutine <prefix2>gesdd_lwork(m,n,minmn,u0,vt0,a,compute_uv,full_matrices,u,s,vt,work,lwork,iwork,info)
! LWORK computation for (S/D)GESDD
fortranname <prefix2>gesdd
callstatement (*f2py_func)((compute_uv?(full_matrices?"A":"S"):"N"),&m,&n,&a,&m,&s,&u,&u0,&vt,&vt0,&work,&lwork,&iwork,&info)
callprotoargument char*,int*,int*,<ctype2>*,int*,<ctype2>*,<ctype2>*,int*,<ctype2>*,int*,<ctype2>*,int*,int*,int*
integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1
integer intent(in),optional,check(full_matrices==0||full_matrices==1):: full_matrices = 1
integer intent(in) :: m
integer intent(in) :: n
integer intent(hide),depend(m,n):: minmn = MIN(m,n)
integer intent(hide),depend(compute_uv,minmn) :: u0 = (compute_uv?m:1)
integer intent(hide),depend(compute_uv,minmn, full_matrices) :: vt0 = (compute_uv?(full_matrices?n:minmn):1)
<ftype2> intent(hide) :: a
<ftype2> intent(hide) :: s
<ftype2> intent(hide) :: u
<ftype2> intent(hide) :: vt
<ftype2> intent(out) :: work
integer intent(hide) :: lwork = -1
integer intent(hide) :: iwork
integer intent(out) :: info
end subroutine <prefix2>gesdd_lwork
subroutine <prefix2c>gesdd(m,n,minmn,u0,u1,vt0,vt1,a,compute_uv,full_matrices,u,s,vt,work,rwork,lwork,iwork,info)
! u,s,vt,info = gesdd(a,compute_uv=1,lwork=..,overwrite_a=0)
! Compute the singular value decomposition (SVD) using divide and conquer:
! A = U * SIGMA * conjugate-transpose(V)
! A - M x N matrix
! U - M x M matrix or min(M,N) x N if full_matrices=False
! SIGMA - M x N zero matrix with a main diagonal filled with min(M,N)
! singular values
! transpose(V) - N x N matrix or N x min(M,N) if full_matrices=False
callstatement (*f2py_func)((compute_uv?(full_matrices?"A":"S"):"N"),&m,&n,a,&m,s,u,&u0,vt,&vt0,work,&lwork,rwork,iwork,&info)
callprotoargument char*,int*,int*,<ctype2c>*,int*,<ctype2>*,<ctype2c>*,int*,<ctype2c>*,int*,<ctype2c>*,int*,<ctype2>*,int*,int*
integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1
integer intent(in),optional,check(full_matrices==0||full_matrices==1):: full_matrices = 1
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
integer intent(hide),depend(m,n):: minmn = MIN(m,n)
integer intent(hide),depend(compute_uv,minmn) :: u0 = (compute_uv?m:1)
integer intent(hide),depend(compute_uv,minmn, full_matrices) :: u1 = (compute_uv?(full_matrices?m:minmn):1)
integer intent(hide),depend(compute_uv,minmn, full_matrices) :: vt0 = (compute_uv?(full_matrices?n:minmn):1)
integer intent(hide),depend(compute_uv,minmn) :: vt1 = (compute_uv?n:1)
<ftype2c> dimension(m,n),intent(in,copy) :: a
<ftype2> dimension(minmn),intent(out),depend(minmn) :: s
<ftype2c> dimension(u0,u1),intent(out),depend(u0,u1) :: u
<ftype2c> dimension(vt0,vt1),intent(out),depend(vt0,vt1) :: vt
<ftype2c> dimension(lwork),intent(hide,cache),depend(lwork) :: work
<ftype2> dimension((compute_uv?minmn*MAX(5*minmn+7, 2*MAX(m,n)+2*minmn+1):7*minmn)),intent(hide,cache),depend(minmn,compute_uv) :: rwork
integer optional,intent(in),depend(minmn,compute_uv) &
:: lwork = max((compute_uv?2*minmn*minmn+MAX(m,n)+2*minmn:2*minmn+MAX(m,n)),1)
integer intent(hide,cache),dimension(8*minmn),depend(minmn) :: iwork
integer intent(out)::info
end subroutine <prefix2c>gesdd
subroutine <prefix2c>gesdd_lwork(m,n,minmn,u0,vt0,a,compute_uv,full_matrices,u,s,vt,work,rwork,lwork,iwork,info)
! (C/Z)GESDD call with LWORK=-1 -- copypaste of above gesdd with dummy arrays
fortranname <prefix2c>gesdd
callstatement (*f2py_func)((compute_uv?(full_matrices?"A":"S"):"N"),&m,&n,&a,&m,&s,&u,&u0,&vt,&vt0,&work,&lwork,&rwork,&iwork,&info)
callprotoargument char*,int*,int*,<ctype2c>*,int*,<ctype2>*,<ctype2c>*,int*,<ctype2c>*,int*,<ctype2c>*,int*,<ctype2>*,int*,int*
integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1
integer intent(in),optional,check(full_matrices==0||full_matrices==1):: full_matrices = 1
integer intent(in),depend(a):: m
integer intent(in),depend(a):: n
integer intent(hide),depend(m,n):: minmn = MIN(m,n)
integer intent(hide),depend(compute_uv,minmn) :: u0 = (compute_uv?m:1)
integer intent(hide),depend(compute_uv,minmn, full_matrices) :: vt0 = (compute_uv?(full_matrices?n:minmn):1)
<ftype2c> intent(hide) :: a
<ftype2> intent(hide) :: s
<ftype2c> intent(hide) :: u
<ftype2c> intent(hide) :: vt
<ftype2c> intent(out) :: work
<ftype2> intent(hide) :: rwork
integer intent(hide) :: lwork = -1
integer intent(hide) :: iwork
integer intent(out) :: info
end subroutine <prefix2c>gesdd_lwork
subroutine <prefix2>gesvd(m,n,minmn,u0,u1,vt0,vt1,a,compute_uv,full_matrices,u,s,vt,work,lwork,info)
! u,s,vt,info = gesvd(a,compute_uv=1,lwork=..,overwrite_a=0)
! Compute the singular value decomposition (SVD):
! A = U * SIGMA * transpose(V)
! A - M x N matrix
! U - M x M matrix or min(M,N) x N if full_matrices=False
! SIGMA - M x N zero matrix with a main diagonal filled with min(M,N)
! singular values
! transpose(V) - N x N matrix or N x min(M,N) if full_matrices=False
callstatement (*f2py_func)((compute_uv?(full_matrices?"A":"S"):"N"),(compute_uv?(full_matrices?"A":"S"):"N"),&m,&n,a,&m,s,u,&u0,vt,&vt0,work,&lwork,&info)
callprotoargument char*,char*,int*,int*,<ctype2>*,int*,<ctype2>*,<ctype2>*,int*,<ctype2>*,int*,<ctype2>*,int*,int*
integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1
integer intent(in),optional,check(full_matrices==0||full_matrices==1):: full_matrices = 1
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
integer intent(hide),depend(m,n):: minmn = MIN(m,n)
integer intent(hide),depend(compute_uv,minmn) :: u0 = (compute_uv?m:1)
integer intent(hide),depend(compute_uv,minmn, full_matrices) :: u1 = (compute_uv?(full_matrices?m:minmn):1)
integer intent(hide),depend(compute_uv,minmn, full_matrices) :: vt0 = (compute_uv?(full_matrices?n:minmn):1)
integer intent(hide),depend(compute_uv,minmn) :: vt1 = (compute_uv?n:1)
<ftype2> dimension(m,n),intent(in,copy,aligned8) :: a
<ftype2> dimension(minmn),intent(out),depend(minmn) :: s
<ftype2> dimension(u0,u1),intent(out),depend(u0, u1) :: u
<ftype2> dimension(vt0,vt1),intent(out),depend(vt0, vt1) :: vt
<ftype2> dimension(lwork),intent(hide,cache),depend(lwork) :: work
integer optional,intent(in),depend(minmn) :: lwork = max(MAX(3*minmn+MAX(m,n),5*minmn),1)
integer intent(out) :: info
end subroutine <prefix2>gesvd
subroutine <prefix2>gesvd_lwork(m,n,minmn,u0,vt0,a,compute_uv,full_matrices,u,s,vt,work,lwork,info)
! LWORK computation for (S/D)GESVD
fortranname <prefix2>gesvd
callstatement (*f2py_func)((compute_uv?(full_matrices?"A":"S"):"N"),(compute_uv?(full_matrices?"A":"S"):"N"),&m,&n,&a,&m,&s,&u,&u0,&vt,&vt0,&work,&lwork,&info)
callprotoargument char*,char*,int*,int*,<ctype2>*,int*,<ctype2>*,<ctype2>*,int*,<ctype2>*,int*,<ctype2>*,int*,int*
integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1
integer intent(in),optional,check(full_matrices==0||full_matrices==1):: full_matrices = 1
integer intent(in) :: m
integer intent(in) :: n
integer intent(hide),depend(m,n):: minmn = MIN(m,n)
integer intent(hide),depend(compute_uv,minmn) :: u0 = (compute_uv?m:1)
integer intent(hide),depend(compute_uv,minmn, full_matrices) :: vt0 = (compute_uv?(full_matrices?n:minmn):1)
<ftype2> intent(hide) :: a
<ftype2> intent(hide) :: s
<ftype2> intent(hide) :: u
<ftype2> intent(hide) :: vt
integer intent(hide) :: lwork = -1
<ftype2> intent(out) :: work
integer intent(out) :: info
end subroutine <prefix2>gesvd_lwork
subroutine <prefix2c>gesvd(m,n,minmn,u0,u1,vt0,vt1,a,compute_uv,full_matrices,u,s,vt,work,rwork,lwork,info)
! u,s,vt,info = gesvd(a,compute_uv=1,lwork=..,overwrite_a=0)
! Compute the singular value decomposition (SVD):
! A = U * SIGMA * conjugate-transpose(V)
! A - M x N matrix
! U - M x M matrix or min(M,N) x N if full_matrices=False
! SIGMA - M x N zero matrix with a main diagonal filled with min(M,N)
! singular values
! transpose(V) - N x N matrix or N x min(M,N) if full_matrices=False
callstatement (*f2py_func)((compute_uv?(full_matrices?"A":"S"):"N"),(compute_uv?(full_matrices?"A":"S"):"N"),&m,&n,a,&m,s,u,&u0,vt,&vt0,work,&lwork,rwork,&info)
callprotoargument char*,char*,int*,int*,<ctype2c>*,int*,<ctype2>*,<ctype2c>*,int*,<ctype2c>*,int*,<ctype2c>*,int*,<ctype2>*,int*
integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1
integer intent(in),optional,check(full_matrices==0||full_matrices==1):: full_matrices = 1
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
integer intent(hide),depend(m,n):: minmn = MIN(m,n)
integer intent(hide),depend(compute_uv,minmn) :: u0 = (compute_uv?m:1)
integer intent(hide),depend(compute_uv,minmn, full_matrices) :: u1 = (compute_uv?(full_matrices?m:minmn):1)
integer intent(hide),depend(compute_uv,minmn, full_matrices) :: vt0 = (compute_uv?(full_matrices?n:minmn):1)
integer intent(hide),depend(compute_uv,minmn) :: vt1 = (compute_uv?n:1)
<ftype2c> dimension(m,n),intent(in,copy) :: a
<ftype2> dimension(minmn),intent(out),depend(minmn) :: s
<ftype2c> dimension(u0,u1),intent(out),depend(u0,u1) :: u
<ftype2c> dimension(vt0,vt1),intent(out),depend(vt0,vt1) :: vt
<ftype2c> dimension(lwork),intent(hide,cache),depend(lwork) :: work
<ftype2> dimension((MAX(1,5*minmn))),intent(hide,cache),depend(minmn) :: rwork
integer optional,intent(in),depend(minmn) :: lwork = MAX(2*minmn+MAX(m,n),1)
integer intent(out) :: info
end subroutine <prefix2c>gesvd
subroutine <prefix2c>gesvd_lwork(m,n,minmn,u0,vt0,a,compute_uv,full_matrices,u,s,vt,work,rwork,lwork,info)
! (C/Z)GESVD call with LWORK=-1 -- copypaste of above gesvd with dummy arrays
fortranname <prefix2c>gesvd
callstatement (*f2py_func)((compute_uv?(full_matrices?"A":"S"):"N"),(compute_uv?(full_matrices?"A":"S"):"N"),&m,&n,&a,&m,&s,&u,&u0,&vt,&vt0,&work,&lwork,&rwork,&info)
callprotoargument char*,char*,int*,int*,<ctype2c>*,int*,<ctype2>*,<ctype2c>*,int*,<ctype2c>*,int*,<ctype2c>*,int*,<ctype2>*,int*
integer intent(in),optional,check(compute_uv==0||compute_uv==1):: compute_uv = 1
integer intent(in),optional,check(full_matrices==0||full_matrices==1):: full_matrices = 1
integer intent(in),depend(a):: m
integer intent(in),depend(a):: n
integer intent(hide),depend(m,n):: minmn = MIN(m,n)
integer intent(hide),depend(compute_uv,minmn) :: u0 = (compute_uv?m:1)
integer intent(hide),depend(compute_uv,minmn, full_matrices) :: vt0 = (compute_uv?(full_matrices?n:minmn):1)
integer intent(hide) :: lwork = -1
<ftype2c> intent(hide) :: a
<ftype2> intent(hide) :: s
<ftype2c> intent(hide) :: u
<ftype2c> intent(hide) :: vt
<ftype2c> intent(out) :: work
<ftype2> intent(hide) :: rwork
integer intent(out) :: info
end subroutine <prefix2c>gesvd_lwork
subroutine <prefix>gels(trans,m,n,nrhs,a,lda,b,ldb,work,lwork,info)
! lqr,x,info = gels(a,b,lwork=..,overwrite_a=False,overwrite_b=False)
! Solve Minimize 2-norm(A * X - B).
callstatement (*f2py_func)(trans,&m,&n,&nrhs,a,&lda,b,&ldb,work,&lwork,&info)
callprotoargument char*,int*,int*,int*,<ctype>*,int*,<ctype>*,int*,<ctype>*,int*,int*
character optional,intent(in),check(*trans=='N'||*trans==<'T',\0,'C',\2>):: trans = 'N'
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
integer intent(hide),depend(b):: nrhs = shape(b,1)
<ftype> dimension(m,n),intent(in,out,copy,out=lqr):: a
integer intent(hide),depend(a):: lda = MAX(1,shape(a,0))
<ftype> intent(in,out,copy,out=x),depend(trans,m,n),dimension(MAX(m,n),nrhs),check(shape(b,0)==MAX(m,n)) :: b
integer depend(b),intent(hide):: ldb = MAX(1,MAX(m,n))
integer optional,intent(in),depend(nrhs,m,n),check(lwork>=1||lwork==-1)::lwork=MAX(MIN(m,n)+MAX(MIN(m,n),nrhs),1)
<ftype> depend(lwork),dimension(MAX(1,lwork)),intent(hide,cache):: work
integer intent(out)::info
end subroutine <prefix>gels
subroutine <prefix>gels_lwork(trans,m,n,nrhs,a,lda,b,ldb,work,lwork,info)
! ?GELS LWORK Query for optimal block size
fortranname <prefix>gels
callstatement (*f2py_func)(trans,&m,&n,&nrhs,&a,&lda,&b,&ldb,&work,&lwork,&info)
callprotoargument char*,int*,int*,int*,<ctype>*,int*,<ctype>*,int*,<ctype>*,int*,int*
character optional,intent(in),check(*trans=='N'||*trans==<'T',\0,'C',\2>):: trans = 'N'
integer intent(in),check(m>=0) :: m
integer intent(in),check(n>=0) :: n
integer intent(in),check(nrhs>=0) :: nrhs
<ftype> intent(hide):: a
integer intent(hide):: lda = MAX(1,m)
<ftype> intent(hide):: b
integer intent(hide):: ldb = MAX(1,MAX(m,n))
integer intent(hide):: lwork=-1
<ftype> intent(out):: work
integer intent(out)::info
end subroutine <prefix>gels_lwork
subroutine <prefix2>gelss(m,n,minmn,maxmn,nrhs,a,b,s,cond,r,work,lwork,info)
! v,x,s,rank,work,info = gelss(a,b,cond=-1.0,overwrite_a=0,overwrite_b=0)
! Solve Minimize 2-norm(A * X - B).
callstatement (*f2py_func)(&m,&n,&nrhs,a,&m,b,&maxmn,s,&cond,&r,work,&lwork,&info)
callprotoargument int*,int*,int*,<ctype2>*,int*,<ctype2>*,int*,<ctype2>*,<ctype2>*,int*,<ctype2>*,int*,int*
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
integer intent(hide),depend(m,n):: minmn = MIN(m,n)
integer intent(hide),depend(m,n):: maxmn = MAX(m,n)
<ftype2> dimension(m,n),intent(in,out,copy,out=v) :: a
integer depend(b),intent(hide):: nrhs = shape(b,1)
<ftype2> dimension(maxmn,nrhs),check(maxmn==shape(b,0)),depend(maxmn) :: b
intent(in,out,copy,out=x) b
<ftype2> intent(in),optional :: cond = -1.0
integer intent(out,out=rank) :: r
<ftype2> intent(out),dimension(minmn),depend(minmn) :: s
integer optional,intent(in),depend(nrhs,minmn,maxmn),&
check(lwork>=1||lwork==-1) &
:: lwork=max(3*minmn+MAX(2*minmn,MAX(maxmn,nrhs)),1)
!check(lwork>=3*minmn+MAX(2*minmn,MAX(maxmn,nrhs)))
<ftype2> dimension(MAX(lwork,1)),intent(out),depend(lwork) :: work
integer intent(out)::info
end subroutine <prefix2>gelss
subroutine <prefix2>gelss_lwork(m,n,maxmn,nrhs,a,b,s,cond,r,work,lwork,info)
! work,info = gelss_lwork(m,n,nrhs,cond=-1.0)
! Query for optimal lwork size
fortranname <prefix2>gelss
callstatement (*f2py_func)(&m,&n,&nrhs,&a,&m,&b,&maxmn,&s,&cond,&r,&work,&lwork,&info)
callprotoargument int*,int*,int*,<ctype2>*,int*,<ctype2>*,int*,<ctype2>*,<ctype2>*,int*,<ctype2>*,int*,int*
integer intent(in):: m
integer intent(in):: n
integer intent(hide),depend(m,n):: maxmn = MAX(m,n)
<ftype2> intent(hide) :: a
integer intent(in):: nrhs
<ftype2> intent(hide) :: b
<ftype2> intent(in),optional :: cond = -1.0
integer intent(hide) :: r
<ftype2> intent(hide) :: s
integer optional,intent(in) :: lwork=-1
<ftype2> intent(out) :: work
integer intent(out)::info
end subroutine <prefix2>gelss_lwork
subroutine <prefix2c>gelss(m,n,minmn,maxmn,nrhs,a,b,s,cond,r,work,rwork,lwork,info)
! v,x,s,rank,work,info = gelss(a,b,cond=-1.0,overwrite_a=0,overwrite_b=0)
! Solve Minimize 2-norm(A * X - B).
callstatement (*f2py_func)(&m,&n,&nrhs,a,&m,b,&maxmn,s,&cond,&r,work,&lwork,rwork,&info)
callprotoargument int*,int*,int*,<ctype2c>*,int*,<ctype2c>*,int*,<ctype2>*,<ctype2>*,int*,<ctype2c>*,int*,<ctype2>*,int*
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
integer intent(hide),depend(m,n):: minmn = MIN(m,n)
integer intent(hide),depend(m,n):: maxmn = MAX(m,n)
<ftype2c> dimension(m,n),intent(in,out,copy,out=v) :: a
integer depend(b),intent(hide):: nrhs = shape(b,1)
<ftype2c> dimension(maxmn,nrhs),check(maxmn==shape(b,0)),depend(maxmn) :: b
intent(in,out,copy,out=x) b
<ftype2> intent(in),optional :: cond = -1.0
integer intent(out,out=rank) :: r
<ftype2> intent(out),dimension(minmn),depend(minmn) :: s
integer optional,intent(in),depend(nrhs,minmn,maxmn),&
check(lwork>=1||lwork==-1) &
:: lwork=max(2*minmn+MAX(maxmn,nrhs),1)
! check(lwork>=2*minmn+MAX(maxmn,nrhs))
<ftype2c> dimension(MAX(lwork,1)),intent(out),depend(lwork) :: work
<ftype2> dimension(5*minmn),intent(hide),depend(lwork) :: rwork
integer intent(out)::info
end subroutine <prefix2c>gelss
subroutine <prefix2c>gelss_lwork(m,n,maxmn,nrhs,a,b,s,cond,r,work,rwork,lwork,info)
! work,info = gelss_lwork(m,n,nrhs,cond=-1.0)
! Query for optimal lwork size
fortranname <prefix2c>gelss
callstatement (*f2py_func)(&m,&n,&nrhs,&a,&m,&b,&maxmn,&s,&cond,&r,&work,&lwork,&rwork,&info)
callprotoargument int*,int*,int*,<ctype2c>*,int*,<ctype2c>*,int*,<ctype2>*,<ctype2>*,int*,<ctype2c>*,int*,<ctype2>*,int*
integer intent(in):: m
integer intent(in):: n
integer intent(hide),depend(m,n):: maxmn = MAX(m,n)
<ftype2c> intent(hide) :: a
integer intent(in):: nrhs
<ftype2c> intent(hide) :: b
<ftype2> intent(in),optional :: cond = -1.0
integer intent(hide) :: r
<ftype2> intent(hide) :: s
integer optional,intent(in) :: lwork=-1
<ftype2c> intent(out) :: work
<ftype2> intent(hide) :: rwork
integer intent(out)::info
end subroutine <prefix2>gelss_lwork
subroutine <prefix2>gelsy(m,n,maxmn,minmn,nrhs,a,b,jptv,cond,r,work,lwork,info)
! v,x,j,rank,info = dgelsy(a,b,jptv,cond,lwork,overwrite_a=True,overwrite_b=True)
! Solve Minimize 2-norm(A * X - B).
callstatement (*f2py_func)(&m,&n,&nrhs,a,&m,b,&maxmn,jptv,&cond,&r,work,&lwork,&info)
callprotoargument int*,int*,int*,<ctype2>*,int*,<ctype2>*,int*,int*,<ctype2>*,int*,<ctype2>*,int*,int*
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
integer intent(hide),depend(m,n):: maxmn = MAX(m,n)
integer intent(hide),depend(m,n):: minmn = MIN(m,n)
<ftype2> dimension(m,n),intent(in,out,copy,out=v) :: a
integer depend(b),intent(hide):: nrhs = shape(b,1)
<ftype2> dimension(maxmn,nrhs),check(maxmn==shape(b,0)),depend(maxmn) :: b
intent(in,out,copy,out=x) b
<ftype2> intent(in) :: cond
integer intent(out,out=rank) :: r
integer intent(in,out,out=j),dimension(n),depend(n) :: jptv
! LWORK is obtained by the query call
integer intent(in),depend(nrhs,m,n,minmn) :: lwork
check(lwork>=MAX(minmn+3*n+1, 2*minmn+nrhs)) :: lwork
<ftype2> dimension(lwork),intent(cache,hide),depend(lwork) :: work
integer intent(out)::info
end subroutine <prefix2>gelsy
subroutine <prefix2>gelsy_lwork(m,n,maxmn,nrhs,a,b,jptv,cond,r,work,lwork,info)
! work,info = dgelsy_lwork(m,n,nrhs,cond)
! Query for optimal lwork size
fortranname <prefix2>gelsy
callstatement (*f2py_func)(&m,&n,&nrhs,&a,&m,&b,&maxmn,&jptv,&cond,&r,&work,&lwork,&info)
callprotoargument int*,int*,int*,<ctype2>*,int*,<ctype2>*,int*,int*,<ctype2>*,int*,<ctype2>*,int*,int*
integer intent(in) :: m
integer intent(in) :: n
integer intent(hide),depend(m,n):: maxmn = MAX(m,n)
<ftype2> intent(hide) :: a
integer intent(in):: nrhs
<ftype2> intent(hide):: b
<ftype2> intent(in) :: cond
integer intent(hide) :: r
integer intent(hide):: jptv
integer intent(in),optional :: lwork = -1
<ftype2> intent(out) :: work
integer intent(out)::info
end subroutine <prefix2>gelsy_lwork
subroutine <prefix2c>gelsy(m,n,maxmn,minmn,nrhs,a,b,jptv,cond,r,work,lwork,rwork,info)
! v,x,j,rank,info = zgelsy(a,b,jptv,cond,lwork,overwrite_a=True,overwrite_b=True)
! Solve Minimize 2-norm(A * X - B).
callstatement (*f2py_func)(&m,&n,&nrhs,a,&m,b,&maxmn,jptv,&cond,&r,work,&lwork,rwork,&info)
callprotoargument int*,int*,int*,<ctype2c>*,int*,<ctype2c>*,int*,int*,<ctype2>*,int*,<ctype2c>*,int*,<ctype2>*,int*
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
integer intent(hide),depend(m,n):: maxmn = MAX(m,n)
integer intent(hide), depend(m,n) :: minmn = MIN(m,n)
<ftype2c> dimension(m,n),intent(in,out,copy,out=v) :: a
integer depend(b),intent(hide):: nrhs = shape(b,1)
<ftype2c> dimension(maxmn,nrhs),check(maxmn==shape(b,0)),depend(maxmn) :: b
intent(in,out,copy,out=x) b
<ftype2> intent(in) :: cond
integer intent(out,out=rank) :: r
integer intent(in,out,out=j),dimension(n),depend(n) :: jptv
! LWORK is obtained by the query call
integer intent(in),depend(nrhs,m,n,minmn) :: lwork
check(lwork>=minmn+MAX(MAX(2*minmn, n+1), minmn+nrhs)) :: lwork
<ftype2c> dimension(lwork),intent(hide,cache),depend(lwork) :: work
<ftype2> dimension(2*n),intent(hide,cache),depend(n) :: rwork
integer intent(out)::info
end subroutine <prefix2c>gelsy
subroutine <prefix2c>gelsy_lwork(m,n,maxmn,nrhs,a,b,jptv,cond,r,work,lwork,rwork,info)
! work,info = zgelsy_lwork(m,n,nrhs,cond)
! Query for optimal lwork size
fortranname <prefix2c>gelsy
callstatement (*f2py_func)(&m,&n,&nrhs,&a,&m,&b,&maxmn,&jptv,&cond,&r,&work,&lwork,&rwork,&info)
callprotoargument int*,int*,int*,<ctype2c>*,int*,<ctype2c>*,int*,int*,<ctype2>*,int*,<ctype2c>*,int*,<ctype2>*,int*
integer intent(in) :: m
integer intent(in) :: n
integer intent(hide) :: maxmn = MAX(m,n)
<ftype2c> intent(hide) :: a
integer intent(in):: nrhs
<ftype2c> intent(hide) :: b
<ftype2> intent(in) :: cond
integer intent(hide) :: r
integer intent(hide) :: jptv
integer intent(in),optional :: lwork = -1
<ftype2c> intent(out) :: work
<ftype2> intent(hide) :: rwork
integer intent(out)::info
end subroutine <prefix2c>gelsy_lwork
subroutine <prefix2>gelsd(m,n,minmn,maxmn,nrhs,a,b,s,cond,r,work,lwork,size_iwork,iwork,info)
! x,s,rank,info = dgelsd(a,b,lwork,size_iwork,cond=-1.0,overwrite_a=True,overwrite_b=True)
! Solve Minimize 2-norm(A * X - B).
callstatement (*f2py_func)(&m,&n,&nrhs,a,&m,b,&maxmn,s,&cond,&r,work,&lwork,iwork,&info)
callprotoargument int*,int*,int*,<ctype2>*,int*,<ctype2>*,int*,<ctype2>*,<ctype2>*,int*,<ctype2>*,int*,int*,int*
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
integer intent(hide),depend(m,n):: minmn = MIN(m,n)
integer intent(hide),depend(m,n):: maxmn = MAX(m,n)
<ftype2> dimension(m,n),intent(in,copy) :: a
integer depend(b),intent(hide):: nrhs = shape(b,1)
<ftype2> dimension(maxmn,nrhs),check(maxmn==shape(b,0)),depend(maxmn) :: b
intent(in,out,copy,out=x) b
<ftype2> intent(in),optional :: cond=-1.0
integer intent(out,out=rank) :: r
<ftype2> intent(out),dimension(minmn),depend(minmn) :: s
integer intent(in),check(lwork>=1) :: lwork
! Impossible to calculate lwork explicitly, need to obtain it from query call first
! Same for size_iwork
<ftype2> dimension(lwork),intent(cache,hide),depend(lwork) :: work
integer intent(in) :: size_iwork
integer intent(cache,hide),dimension(MAX(1,size_iwork)),depend(size_iwork) :: iwork
integer intent(out)::info
end subroutine <prefix2>gelsd
subroutine <prefix2>gelsd_lwork(m,n,maxmn,nrhs,a,b,s,cond,r,work,lwork,iwork,info)
! work,iwork,info = dgelsd_lwork(m,n,nrhs,cond=-1.0)
! Query for optimal lwork size
fortranname <prefix2>gelsd
callstatement (*f2py_func)(&m,&n,&nrhs,&a,&m,&b,&maxmn,&s,&cond,&r,&work,&lwork,&iwork,&info)
callprotoargument int*,int*,int*,<ctype2>*,int*,<ctype2>*,int*,<ctype2>*,<ctype2>*,int*,<ctype2>*,int*,int*,int*
integer intent(in) :: m
integer intent(in) :: n
integer intent(hide),depend(m,n):: maxmn = MAX(m,n)
<ftype2> intent(hide) :: a
integer intent(in):: nrhs
<ftype2> intent(hide) :: b
<ftype2> intent(in),optional :: cond=-1.0
integer intent(hide) :: r
<ftype2> intent(hide) :: s
integer intent(in),optional :: lwork = -1
<ftype2> intent(out) :: work
integer intent(out) :: iwork
integer intent(out)::info
end subroutine <prefix2>gelsd_lwork
subroutine <prefix2c>gelsd(m,n,minmn,maxmn,nrhs,a,b,s,cond,r,work,lwork,size_rwork,rwork, size_iwork,iwork,info)
! x,s,rank,info = zgelsd(a,b,lwork,size_rwork,size_iwork,cond=-1.0,overwrite_a=True,overwrite_b=True)
! Solve Minimize 2-norm(A * X - B).
callstatement (*f2py_func)(&m,&n,&nrhs,a,&m,b,&maxmn,s,&cond,&r,work,&lwork, rwork, iwork,&info)
callprotoargument int*,int*,int*,<ctype2c>*,int*,<ctype2c>*,int*,<ctype2>*,<ctype2>*,int*, <ctype2c>*,int*,<ctype2>*,int*,int*
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
integer intent(hide),depend(m,n):: minmn = MIN(m,n)
integer intent(hide),depend(m,n):: maxmn = MAX(m,n)
<ftype2c> dimension(m,n),intent(in,copy) :: a
integer depend(b),intent(hide):: nrhs = shape(b,1)
<ftype2c> dimension(maxmn,nrhs),check(maxmn==shape(b,0)),depend(maxmn) :: b
intent(in,out,copy,out=x) b
<ftype2> intent(in),optional :: cond=-1.0
integer intent(out,out=rank) :: r
<ftype2> intent(out),dimension(minmn),depend(minmn) :: s
integer intent(in),check(lwork>=1||lwork==-1) :: lwork
! Impossible to calculate lwork explicitly, need to obtain it from query call first
! Same for size_rwork, size_iwork
<ftype2c> dimension(MAX(lwork,1)),intent(cache,hide),depend(lwork) :: work
integer intent(in) :: size_rwork
<ftype2> intent(cache,hide),dimension(MAX(1,size_rwork)),depend(size_rwork) :: rwork
integer intent(in) :: size_iwork
integer intent(cache,hide),dimension(MAX(1,size_iwork)),depend(size_iwork) :: iwork
integer intent(out)::info
end subroutine <prefix2c>gelsd
subroutine <prefix2c>gelsd_lwork(m,n,maxmn,nrhs,a,b,s,cond,r,work,lwork,rwork,iwork,info)
! work,rwork,iwork,info = zgelsd_lwork(m,n,nrhs,lwork=-1.0,cond=-1.0)
! Query for optimal lwork size
fortranname <prefix2c>gelsd
callstatement (*f2py_func)(&m,&n,&nrhs,&a,&m,&b,&maxmn,&s,&cond,&r,&work,&lwork, &rwork, &iwork,&info)
callprotoargument int*,int*,int*,<ctype2c>*,int*,<ctype2c>*,int*,<ctype2>*,<ctype2>*,int*, <ctype2c>*,int*,<ctype2>*,int*,int*
integer intent(in) :: m
integer intent(in) :: n
integer intent(hide),depend(m,n):: maxmn = MAX(m,n)
<ftype2c> intent(hide) :: a
integer intent(in):: nrhs
<ftype2c> intent(hide) :: b
<ftype2> intent(in),optional :: cond=-1.0
integer intent(hide) :: r
<ftype2> intent(hide) :: s
integer intent(in),optional :: lwork = -1
<ftype2c> intent(out) :: work
<ftype2> intent(out) :: rwork
integer intent(out) :: iwork
integer intent(out)::info
end subroutine <prefix2c>gelsd_lwork
subroutine <prefix2>geqp3(m,n,a,jpvt,tau,work,lwork,info)
! qr_a,jpvt,tau,work,info = geqp3(a,lwork=3*(n+1),overwrite_a=0)
! Compute a QR factorization of a real M-by-N matrix A with column pivoting:
! A * P = Q * R.
threadsafe
callstatement (*f2py_func)(&m,&n,a,&m,jpvt,tau,work,&lwork,&info)
callprotoargument int*,int*,<ctype2>*,int*,int*,<ctype2>*,<ctype2>*,int*,int*
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
<ftype2> dimension(m,n),intent(in,out,copy,out=qr,aligned8) :: a
integer dimension(n),intent(out) :: jpvt
<ftype2> dimension(MIN(m,n)),intent(out) :: tau
integer optional,intent(in),depend(n),check(lwork>=n||lwork==-1) :: lwork=max(3*(n+1),1)
<ftype2> dimension(MAX(lwork,1)),intent(out),depend(lwork) :: work
integer intent(out) :: info
end subroutine <prefix2>geqp3
subroutine <prefix2c>geqp3(m,n,a,jpvt,tau,work,lwork,rwork,info)
! qr_a,jpvt,tau,work,info = geqp3(a,lwork,overwrite_a=0)
! Compute a QR factorization of a complex M-by-N matrix A with column pivoting:
! A * P = Q * R.
threadsafe
callstatement (*f2py_func)(&m,&n,a,&m,jpvt,tau,work,&lwork,rwork,&info)
callprotoargument int*,int*,<ctype2c>*,int*,int*,<ctype2c>*,<ctype2c>*,int*,<ctype2>*,int*
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
<ftype2c> dimension(m,n),intent(in,out,copy,out=qr,aligned8) :: a
integer dimension(n),intent(out) :: jpvt
<ftype2c> dimension(MIN(m,n)),intent(out) :: tau
integer optional,intent(in),depend(n),check(lwork>=n||lwork==-1) :: lwork=max(3*(n+1),1)
<ftype2c> dimension(MAX(lwork,1)),intent(out),depend(lwork) :: work
<ftype2> dimension(2*n),intent(hide),depend(n) :: rwork
integer intent(out) :: info
end subroutine <prefix2c>geqp3
subroutine <prefix>geqrf(m,n,a,tau,work,lwork,info)
! qr_a,tau,work,info = geqrf(a,lwork=3*n,overwrite_a=0)
! Compute a QR factorization of a real M-by-N matrix A:
! A = Q * R.
threadsafe
callstatement (*f2py_func)(&m,&n,a,&m,tau,work,&lwork,&info)
callprotoargument int*,int*,<ctype>*,int*,<ctype>*,<ctype>*,int*,int*
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
<ftype> dimension(m,n),intent(in,out,copy,out=qr,aligned8) :: a
<ftype> dimension(MIN(m,n)),intent(out) :: tau
integer optional,intent(in),depend(n),check(lwork>=n||lwork==-1) :: lwork=max(3*n,1)
<ftype> dimension(MAX(lwork,1)),intent(out),depend(lwork) :: work
integer intent(out) :: info
end subroutine <prefix>geqrf
subroutine <prefix>gerqf(m,n,a,tau,work,lwork,info)
! rq_a,tau,work,info = gerqf(a,lwork=3*n,overwrite_a=0)
! Compute an RQ factorization of a real M-by-N matrix A:
! A = R * Q.
threadsafe
callstatement (*f2py_func)(&m,&n,a,&m,tau,work,&lwork,&info)
callprotoargument int*,int*,<ctype>*,int*,<ctype>*,<ctype>*,int*,int*
integer intent(hide),depend(a):: m = shape(a,0)
integer intent(hide),depend(a):: n = shape(a,1)
<ftype> dimension(m,n),intent(in,out,copy,out=qr,aligned8) :: a
<ftype> dimension(MIN(m,n)),intent(out) :: tau
integer optional,intent(in),depend(m),check(lwork>=m||lwork==-1) :: lwork=max(3*m,1)
<ftype> dimension(MAX(lwork,1)),intent(out),depend(lwork) :: work
integer intent(out) :: info
end subroutine <prefix>gerqf
subroutine <prefix2>geev(compute_vl,compute_vr,n,a,wr,wi,vl,ldvl,vr,ldvr,work,lwork,info)
! wr,wi,vl,vr,info = geev(a,compute_vl=1,compute_vr=1,lwork=4*n,overwrite_a=0)
callstatement {(*f2py_func)((compute_vl?"V":"N"),(compute_vr?"V":"N"),&n,a,&n,wr,wi,vl,&ldvl,vr,&ldvr,work,&lwork,&info);}
callprotoargument char*,char*,int*,<ctype2>*,int*,<ctype2>*,<ctype2>*,<ctype2>*,int*,<ctype2>*,int*,<ctype2>*,int*,int*
integer optional,intent(in):: compute_vl = 1
check(compute_vl==1||compute_vl==0) compute_vl
integer optional,intent(in):: compute_vr = 1
check(compute_vr==1||compute_vr==0) compute_vr
integer intent(hide),depend(a) :: n = shape(a,0)
<ftype2> dimension(n,n),intent(in,copy,aligned8) :: a
check(shape(a,0)==shape(a,1)) :: a
<ftype2> dimension(n),intent(out),depend(n) :: wr
<ftype2> dimension(n),intent(out),depend(n) :: wi
<ftype2> dimension(ldvl,n),intent(out) :: vl
integer intent(hide),depend(n,compute_vl) :: ldvl=(compute_vl?n:1)
<ftype2> dimension(ldvr,n),intent(out) :: vr
integer intent(hide),depend(n,compute_vr) :: ldvr=(compute_vr?n:1)
integer optional,intent(in),depend(n,compute_vl,compute_vr) :: lwork=max(4*n,1)
check(lwork>=((compute_vl||compute_vr)?4*n:3*n)) :: lwork
<ftype2> dimension(lwork),intent(hide,cache),depend(lwork) :: work
integer intent(out):: info
end subroutine <prefix2>geev
subroutine <prefix2>geev_lwork(compute_vl,compute_vr,n,a,wr,wi,vl,ldvl,vr,ldvr,work,lwork,info)
! LWORK=-1 call for (S/D)GEEV --- keep in sync with above (S/D)GEEV definition
fortranname <prefix2>geev
callstatement {(*f2py_func)((compute_vl?"V":"N"),(compute_vr?"V":"N"),&n,&a,&n,&wr,&wi,&vl,&ldvl,&vr,&ldvr,&work,&lwork,&info);}