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BSfactor(3)
Compute the incomplete factor of a matrix
BSsetup_factor(3)
Set up the communication for factorization
HPL_pdfact(3)
recursive panel factorization
HPL_pdgesv0(3)
Factor an N x N+1 matrix
HPL_pdgesvK1(3)
Factor an N x N+1 matrix
HPL_pdgesvK2(3)
Factor an N x N+1 matrix
HPL_pdpancrN(3)
Crout panel factorization
HPL_pdpancrT(3)
Crout panel factorization
HPL_pdpanllN(3)
Left-looking panel factorization
HPL_pdpanllT(3)
Left-looking panel factorization
HPL_pdpanrlN(3)
Right-looking panel factorization
HPL_pdpanrlT(3)
Right-looking panel factorization
HPL_pdrpancrN(3)
Crout recursive panel factorization
HPL_pdrpancrT(3)
Crout recursive panel factorization
HPL_pdrpanllN(3)
Left-looking recursive panel factorization
HPL_pdrpanllT(3)
Left-looking recursive panel factorization
HPL_pdrpanrlN(3)
Right-looking recursive panel factorization
HPL_pdrpanrlT(3)
Right-looking recursive panel factorization
PS_rotate(3)
Sets rotation factor
PS_scale(3)
Sets scaling factor
SoHandleBoxManip(3iv)
transform node with 3D Interface for Editing ScaleFactor and Translation
all_sf(nged)
obtain shape factors between named regions of an entire mged database
cdbtf2(l), CDBTF2(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting with row interchanges
cdbtrf(l), CDBTRF(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting or row interchanges
cdttrf(l), CDTTRF(l)
compute an LU factorization of a complex tridiagonal matrix A using elimination without partial pivoting
cgbsvx(l), CGBSVX(l)
uses the LU factorization to compute the solution to a complex system of linear equations A * X = B, A**T * X = B, or A**H * X = B,
cgbsvxx(l), CGBSVXX(l)
CGBSVXX use the LU factorization to compute the solution to a complex system of linear equations A * X = B, where A is an N-by-N matrix and X and B are N-by-NRHS matrices
cgbtf2(l), CGBTF2(l)
computes an LU factorization of a complex m-by-n band matrix A using partial pivoting with row interchanges
cgbtrf(l), CGBTRF(l)
computes an LU factorization of a complex m-by-n band matrix A using partial pivoting with row interchanges
cgbtrs(l), CGBTRS(l)
solves a system of linear equations A * X = B, A**T * X = B, or A**H * X = B with a general band matrix A using the LU factorization computed by CGBTRF
cgecon(l), CGECON(l)
estimates the reciprocal of the condition number of a general complex matrix A, in either the 1-norm or the infinity-norm, using the LU factorization computed by CGETRF
cgelq2(l), CGELQ2(l)
computes an LQ factorization of a complex m by n matrix A
cgelqf(l), CGELQF(l)
computes an LQ factorization of a complex M-by-N matrix A
cgels(l), CGELS(l)
solves overdetermined or underdetermined complex linear systems involving an M-by-N matrix A, or its conjugate-transpose, using a QR or LQ factorization of A
cgeql2(l), CGEQL2(l)
computes a QL factorization of a complex m by n matrix A
cgeqlf(l), CGEQLF(l)
computes a QL factorization of a complex M-by-N matrix A
cgeqp3(l), CGEQP3(l)
computes a QR factorization with column pivoting of a matrix A
cgeqr2(l), CGEQR2(l)
computes a QR factorization of a complex m by n matrix A
cgeqrf(l), CGEQRF(l)
computes a QR factorization of a complex M-by-N matrix A
cgerq2(l), CGERQ2(l)
computes an RQ factorization of a complex m by n matrix A
cgerqf(l), CGERQF(l)
computes an RQ factorization of a complex M-by-N matrix A
cgesc2(l), CGESC2(l)
solves a system of linear equations A * X = scale* RHS with a general N-by-N matrix A using the LU factorization with complete pivoting computed by CGETC2
cgesvx(l), CGESVX(l)
uses the LU factorization to compute the solution to a complex system of linear equations A * X = B,
cgesvxx(l), CGESVXX(l)
CGESVXX use the LU factorization to compute the solution to a complex system of linear equations A * X = B, where A is an N-by-N matrix and X and B are N-by-NRHS matrices
cgetc2(l), CGETC2(l)
computes an LU factorization, using complete pivoting, of the n-by-n matrix A
cgetf2(l), CGETF2(l)
computes an LU factorization of a general m-by-n matrix A using partial pivoting with row interchanges
cgetrf(l), CGETRF(l)
computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges
cgetri(l), CGETRI(l)
computes the inverse of a matrix using the LU factorization computed by CGETRF
cgetrs(l), CGETRS(l)
solves a system of linear equations A * X = B, A**T * X = B, or A**H * X = B with a general N-by-N matrix A using the LU factorization computed by CGETRF
cggqrf(l), CGGQRF(l)
computes a generalized QR factorization of an N-by-M matrix A and an N-by-P matrix B
cggrqf(l), CGGRQF(l)
computes a generalized RQ factorization of an M-by-N matrix A and a P-by-N matrix B
cgtcon(l), CGTCON(l)
estimates the reciprocal of the condition number of a complex tridiagonal matrix A using the LU factorization as computed by CGTTRF
cgtsvx(l), CGTSVX(l)
uses the LU factorization to compute the solution to a complex system of linear equations A * X = B, A**T * X = B, or A**H * X = B,
cgttrf(l), CGTTRF(l)
computes an LU factorization of a complex tridiagonal matrix A using elimination with partial pivoting and row interchanges
chan_mult(1)
multiply columns of data by a given factor chan_add - add a given value to columns of data
checon(l), CHECON(l)
estimates the reciprocal of the condition number of a complex Hermitian matrix A using the factorization A = U*D*U**H or A = L*D*L**H computed by CHETRF
chesvx(l), CHESVX(l)
uses the diagonal pivoting factorization to compute the solution to a complex system of linear equations A * X = B,
chesvxx(l), CHESVXX(l)
CHESVXX use the diagonal pivoting factorization to compute the solution to a complex system of linear equations A * X = B, where A is an N-by-N symmetric matrix and X and B are N-by-NRHS matrices
chetf2(l), CHETF2(l)
computes the factorization of a complex Hermitian matrix A using the Bunch-Kaufman diagonal pivoting method
chetrf(l), CHETRF(l)
computes the factorization of a complex Hermitian matrix A using the Bunch-Kaufman diagonal pivoting method
chetri(l), CHETRI(l)
computes the inverse of a complex Hermitian indefinite matrix A using the factorization A = U*D*U**H or A = L*D*L**H computed by CHETRF
chetrs(l), CHETRS(l)
solves a system of linear equations A*X = B with a complex Hermitian matrix A using the factorization A = U*D*U**H or A = L*D*L**H computed by CHETRF
chpcon(l), CHPCON(l)
estimates the reciprocal of the condition number of a complex Hermitian packed matrix A using the factorization A = U*D*U**H or A = L*D*L**H computed by CHPTRF
chpsvx(l), CHPSVX(l)
uses the diagonal pivoting factorization A = U*D*U**H or A = L*D*L**H to compute the solution to a complex system of linear equations A * X = B, where A is an N-by-N Hermitian matrix stored in packed format and X and B are N-by-NRHS matrices
chptrf(l), CHPTRF(l)
computes the factorization of a complex Hermitian packed matrix A using the Bunch-Kaufman diagonal pivoting method
chptri(l), CHPTRI(l)
computes the inverse of a complex Hermitian indefinite matrix A in packed storage using the factorization A = U*D*U**H or A = L*D*L**H computed by CHPTRF
chptrs(l), CHPTRS(l)
solves a system of linear equations A*X = B with a complex Hermitian matrix A stored in packed format using the factorization A = U*D*U**H or A = L*D*L**H computed by CHPTRF
clahef(l), CLAHEF(l)
computes a partial factorization of a complex Hermitian matrix A using the Bunch-Kaufman diagonal pivoting method
clals0(l), CLALS0(l)
applies back the multiplying factors of either the left or the right singular vector matrix of a diagonal matrix appended by a row to the right hand side matrix B in solving the least squares problem using the divide-and-conquer SVD approach
clanv2(l), CLANV2(l)
compute the Schur factorization of a complex 2-by-2 nonhermitian matrix in standard form
claqgb(l), CLAQGB(l)
equilibrates a general M by N band matrix A with KL subdiagonals and KU superdiagonals using the row and scaling factors in the vectors R and C
claqge(l), CLAQGE(l)
equilibrates a general M by N matrix A using the row and column scaling factors in the vectors R and C
claqhb(l), CLAQHB(l)
equilibrates an Hermitian band matrix A using the scaling factors in the vector S
claqhe(l), CLAQHE(l)
equilibrates a Hermitian matrix A using the scaling factors in the vector S
claqhp(l), CLAQHP(l)
equilibrates a Hermitian matrix A using the scaling factors in the vector S
claqp2(l), CLAQP2(l)
computes a QR factorization with column pivoting of the block A(OFFSET+1:M,1:N)
claqps(l), CLAQPS(l)
computes a step of QR factorization with column pivoting of a complex M-by-N matrix A by using Blas-3
claqsb(l), CLAQSB(l)
equilibrates a symmetric band matrix A using the scaling factors in the vector S
claqsp(l), CLAQSP(l)
equilibrates a symmetric matrix A using the scaling factors in the vector S
claqsy(l), CLAQSY(l)
equilibrates a symmetric matrix A using the scaling factors in the vector S
clarft(l), CLARFT(l)
forms the triangular factor T of a complex block reflector H of order n, which is defined as a product of k elementary reflectors
clarzt(l), CLARZT(l)
forms the triangular factor T of a complex block reflector H of order > n, which is defined as a product of k elementary reflectors
clasyf(l), CLASYF(l)
computes a partial factorization of a complex symmetric matrix A using the Bunch-Kaufman diagonal pivoting method
clatrz(l), CLATRZ(l)
factors the M-by-(M+L) complex upper trapezoidal matrix [ A1 A2 ] = [ A(1:M,1:M) A(1:M,N-L+1:N) ] as ( R 0 ) * Z by means of unitary transformations, where Z is an (M+L)-by-(M+L) unitary matrix and, R and A1 are M-by-M upper triangular matrices
clauu2(l), CLAUU2(l)
computes the product U * U(aq or L(aq * L, where the triangular factor U or L is stored in the upper or lower triangular part of the array A
clauum(l), CLAUUM(l)
computes the product U * U(aq or L(aq * L, where the triangular factor U or L is stored in the upper or lower triangular part of the array A
cpbcon(l), CPBCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a complex Hermitian positive definite band matrix using the Cholesky factorization A = U**H*U or A = L*L**H computed by CPBTRF
cpbstf(l), CPBSTF(l)
computes a split Cholesky factorization of a complex Hermitian positive definite band matrix A
cpbsvx(l), CPBSVX(l)
uses the Cholesky factorization A = U**H*U or A = L*L**H to compute the solution to a complex system of linear equations A * X = B,
cpbtf2(l), CPBTF2(l)
computes the Cholesky factorization of a complex Hermitian positive definite band matrix A
cpbtrf(l), CPBTRF(l)
computes the Cholesky factorization of a complex Hermitian positive definite band matrix A
cpbtrs(l), CPBTRS(l)
solves a system of linear equations A*X = B with a Hermitian positive definite band matrix A using the Cholesky factorization A = U**H*U or A = L*L**H computed by CPBTRF
cpftrf(l), CPFTRF(l)
computes the Cholesky factorization of a complex Hermitian positive definite matrix A
cpftri(l), CPFTRI(l)
computes the inverse of a complex Hermitian positive definite matrix A using the Cholesky factorization A = U**H*U or A = L*L**H computed by CPFTRF
cpftrs(l), CPFTRS(l)
solves a system of linear equations A*X = B with a Hermitian positive definite matrix A using the Cholesky factorization A = U**H*U or A = L*L**H computed by CPFTRF
cpocon(l), CPOCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a complex Hermitian positive definite matrix using the Cholesky factorization A = U**H*U or A = L*L**H computed by CPOTRF
cposvx(l), CPOSVX(l)
uses the Cholesky factorization A = U**H*U or A = L*L**H to compute the solution to a complex system of linear equations A * X = B,
cposvxx(l), CPOSVXX(l)
CPOSVXX use the Cholesky factorization A = U**T*U or A = L*L**T to compute the solution to a complex system of linear equations A * X = B, where A is an N-by-N symmetric positive definite matrix and X and B are N-by-NRHS matrices
cpotf2(l), CPOTF2(l)
computes the Cholesky factorization of a complex Hermitian positive definite matrix A
cpotrf(l), CPOTRF(l)
computes the Cholesky factorization of a complex Hermitian positive definite matrix A
cpotri(l), CPOTRI(l)
computes the inverse of a complex Hermitian positive definite matrix A using the Cholesky factorization A = U**H*U or A = L*L**H computed by CPOTRF
cpotrs(l), CPOTRS(l)
solves a system of linear equations A*X = B with a Hermitian positive definite matrix A using the Cholesky factorization A = U**H*U or A = L*L**H computed by CPOTRF
cppcon(l), CPPCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a complex Hermitian positive definite packed matrix using the Cholesky factorization A = U**H*U or A = L*L**H computed by CPPTRF
cppsvx(l), CPPSVX(l)
uses the Cholesky factorization A = U**H*U or A = L*L**H to compute the solution to a complex system of linear equations A * X = B,
cpptrf(l), CPPTRF(l)
computes the Cholesky factorization of a complex Hermitian positive definite matrix A stored in packed format
cpptri(l), CPPTRI(l)
computes the inverse of a complex Hermitian positive definite matrix A using the Cholesky factorization A = U**H*U or A = L*L**H computed by CPPTRF
cpptrs(l), CPPTRS(l)
solves a system of linear equations A*X = B with a Hermitian positive definite matrix A in packed storage using the Cholesky factorization A = U**H*U or A = L*L**H computed by CPPTRF
cpstf2(l), CPSTF2(l)
computes the Cholesky factorization with complete pivoting of a complex Hermitian positive semidefinite matrix A
cpstrf(l), CPSTRF(l)
computes the Cholesky factorization with complete pivoting of a complex Hermitian positive semidefinite matrix A
cptcon(l), CPTCON(l)
computes the reciprocal of the condition number (in the 1-norm) of a complex Hermitian positive definite tridiagonal matrix using the factorization A = L*D*L**H or A = U**H*D*U computed by CPTTRF
cpteqr(l), CPTEQR(l)
computes all eigenvalues and, optionally, eigenvectors of a symmetric positive definite tridiagonal matrix by first factoring the matrix using SPTTRF and then calling CBDSQR to compute the singular values of the bidiagonal factor
cptsvx(l), CPTSVX(l)
uses the factorization A = L*D*L**H to compute the solution to a complex system of linear equations A*X = B, where A is an N-by-N Hermitian positive definite tridiagonal matrix and X and B are N-by-NRHS matrices
cpttrf(l), CPTTRF(l)
computes the L*D*L(aq factorization of a complex Hermitian positive definite tridiagonal matrix A
cpttrs(l), CPTTRS(l)
solves a tridiagonal system of the form A * X = B using the factorization A = U(aq*D*U or A = L*D*L(aq computed by CPTTRF
cptts2(l), CPTTS2(l)
solves a tridiagonal system of the form A * X = B using the factorization A = U(aq*D*U or A = L*D*L(aq computed by CPTTRF
cscout(1)
C code analyzer and refactoring browser
cspcon(l), CSPCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a complex symmetric packed matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by CSPTRF
cspsvx(l), CSPSVX(l)
uses the diagonal pivoting factorization A = U*D*U**T or A = L*D*L**T to compute the solution to a complex system of linear equations A * X = B, where A is an N-by-N symmetric matrix stored in packed format and X and B are N-by-NRHS matrices
csptrf(l), CSPTRF(l)
computes the factorization of a complex symmetric matrix A stored in packed format using the Bunch-Kaufman diagonal pivoting method
csptri(l), CSPTRI(l)
computes the inverse of a complex symmetric indefinite matrix A in packed storage using the factorization A = U*D*U**T or A = L*D*L**T computed by CSPTRF
csptrs(l), CSPTRS(l)
solves a system of linear equations A*X = B with a complex symmetric matrix A stored in packed format using the factorization A = U*D*U**T or A = L*D*L**T computed by CSPTRF
csycon(l), CSYCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a complex symmetric matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by CSYTRF
csysvx(l), CSYSVX(l)
uses the diagonal pivoting factorization to compute the solution to a complex system of linear equations A * X = B,
csysvxx(l), CSYSVXX(l)
CSYSVXX use the diagonal pivoting factorization to compute the solution to a complex system of linear equations A * X = B, where A is an N-by-N symmetric matrix and X and B are N-by-NRHS matrices
csytf2(l), CSYTF2(l)
computes the factorization of a complex symmetric matrix A using the Bunch-Kaufman diagonal pivoting method
csytrf(l), CSYTRF(l)
computes the factorization of a complex symmetric matrix A using the Bunch-Kaufman diagonal pivoting method
csytri(l), CSYTRI(l)
computes the inverse of a complex symmetric indefinite matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by CSYTRF
csytrs(l), CSYTRS(l)
solves a system of linear equations A*X = B with a complex symmetric matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by CSYTRF
ctrexc(l), CTREXC(l)
reorders the Schur factorization of a complex matrix A = Q*T*Q**H, so that the diagonal element of T with row index IFST is moved to row ILST
ctrsen(l), CTRSEN(l)
reorders the Schur factorization of a complex matrix A = Q*T*Q**H, so that a selected cluster of eigenvalues appears in the leading positions on the diagonal of the upper triangular matrix T, and the leading columns of Q form an orthonormal basis of the corresponding right invariant subspace
ddbtf2(l), DDBTF2(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting with row interchanges
ddbtrf(l), DDBTRF(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting or row interchanges
ddttrf(l), DDTTRF(l)
compute an LU factorization of a complex tridiagonal matrix A using elimination without partial pivoting
dgbsvx(l), DGBSVX(l)
uses the LU factorization to compute the solution to a real system of linear equations A * X = B, A**T * X = B, or A**H * X = B,
dgbsvxx(l), DGBSVXX(l)
DGBSVXX use the LU factorization to compute the solution to a double precision system of linear equations A * X = B, where A is an N-by-N matrix and X and B are N-by-NRHS matrices
dgbtf2(l), DGBTF2(l)
computes an LU factorization of a real m-by-n band matrix A using partial pivoting with row interchanges
dgbtrf(l), DGBTRF(l)
computes an LU factorization of a real m-by-n band matrix A using partial pivoting with row interchanges
dgbtrs(l), DGBTRS(l)
solves a system of linear equations A * X = B or A(aq * X = B with a general band matrix A using the LU factorization computed by DGBTRF
dgecon(l), DGECON(l)
estimates the reciprocal of the condition number of a general real matrix A, in either the 1-norm or the infinity-norm, using the LU factorization computed by DGETRF
dgelq2(l), DGELQ2(l)
computes an LQ factorization of a real m by n matrix A
dgelqf(l), DGELQF(l)
computes an LQ factorization of a real M-by-N matrix A
dgels(l), DGELS(l)
solves overdetermined or underdetermined real linear systems involving an M-by-N matrix A, or its transpose, using a QR or LQ factorization of A
dgeql2(l), DGEQL2(l)
computes a QL factorization of a real m by n matrix A
dgeqlf(l), DGEQLF(l)
computes a QL factorization of a real M-by-N matrix A
dgeqp3(l), DGEQP3(l)
computes a QR factorization with column pivoting of a matrix A
dgeqr2(l), DGEQR2(l)
computes a QR factorization of a real m by n matrix A
dgeqrf(l), DGEQRF(l)
computes a QR factorization of a real M-by-N matrix A
dgerq2(l), DGERQ2(l)
computes an RQ factorization of a real m by n matrix A
dgerqf(l), DGERQF(l)
computes an RQ factorization of a real M-by-N matrix A
dgesc2(l), DGESC2(l)
solves a system of linear equations A * X = scale* RHS with a general N-by-N matrix A using the LU factorization with complete pivoting computed by DGETC2
dgesvx(l), DGESVX(l)
uses the LU factorization to compute the solution to a real system of linear equations A * X = B,
dgesvxx(l), DGESVXX(l)
DGESVXX use the LU factorization to compute the solution to a double precision system of linear equations A * X = B, where A is an N-by-N matrix and X and B are N-by-NRHS matrices
dgetc2(l), DGETC2(l)
computes an LU factorization with complete pivoting of the n-by-n matrix A
dgetf2(l), DGETF2(l)
computes an LU factorization of a general m-by-n matrix A using partial pivoting with row interchanges
dgetrf(l), DGETRF(l)
computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges
dgetri(l), DGETRI(l)
computes the inverse of a matrix using the LU factorization computed by DGETRF
dgetrs(l), DGETRS(l)
solves a system of linear equations A * X = B or A(aq * X = B with a general N-by-N matrix A using the LU factorization computed by DGETRF
dggqrf(l), DGGQRF(l)
computes a generalized QR factorization of an N-by-M matrix A and an N-by-P matrix B
dggrqf(l), DGGRQF(l)
computes a generalized RQ factorization of an M-by-N matrix A and a P-by-N matrix B
dgtcon(l), DGTCON(l)
estimates the reciprocal of the condition number of a real tridiagonal matrix A using the LU factorization as computed by DGTTRF
dgtsvx(l), DGTSVX(l)
uses the LU factorization to compute the solution to a real system of linear equations A * X = B or A**T * X = B,
dgttrf(l), DGTTRF(l)
computes an LU factorization of a real tridiagonal matrix A using elimination with partial pivoting and row interchanges
dla_gbrcond(l), DLA_GBRCOND(l)
DLA_GERCOND Estimate the Skeel condition number of op(A) * op2(C) where op2 is determined by CMODE as follows CMODE = 1 op2(C) = C CMODE = 0 op2(C) = I CMODE = -1 op2(C) = inv(C) The Skeel condition number cond(A) = norminf( |inv(A)||A| ) is computed by computing scaling factors R such that diag(R)*A*op2(C) is row equilibrated and computing the standard infinity-norm condition number
dla_gercond(l), DLA_GERCOND(l)
DLA_GERCOND estimate the Skeel condition number of op(A) * op2(C) where op2 is determined by CMODE as follows CMODE = 1 op2(C) = C CMODE = 0 op2(C) = I CMODE = -1 op2(C) = inv(C) The Skeel condition number cond(A) = norminf( |inv(A)||A| ) is computed by computing scaling factors R such that diag(R)*A*op2(C) is row equilibrated and computing the standard infinity-norm condition number
dla_porcond(l), DLA_PORCOND(l)
DLA_PORCOND Estimate the Skeel condition number of op(A) * op2(C) where op2 is determined by CMODE as follows CMODE = 1 op2(C) = C CMODE = 0 op2(C) = I CMODE = -1 op2(C) = inv(C) The Skeel condition number cond(A) = norminf( |inv(A)||A| ) is computed by computing scaling factors R such that diag(R)*A*op2(C) is row equilibrated and computing the standard infinity-norm condition number
dla_syrcond(l), DLA_SYRCOND(l)
DLA_SYRCOND estimate the Skeel condition number of op(A) * op2(C) where op2 is determined by CMODE as follows CMODE = 1 op2(C) = C CMODE = 0 op2(C) = I CMODE = -1 op2(C) = inv(C) The Skeel condition number cond(A) = norminf( |inv(A)||A| ) is computed by computing scaling factors R such that diag(R)*A*op2(C) is row equilibrated and computing the standard infinity-norm condition number
dlagtf(l), DLAGTF(l)
factorizes the matrix (T - lambda*I), where T is an n by n tridiagonal matrix and lambda is a scalar, as T - lambda*I = PLU,
dlagv2(l), DLAGV2(l)
computes the Generalized Schur factorization of a real 2-by-2 matrix pencil (A,B) where B is upper triangular
dlals0(l), DLALS0(l)
applies back the multiplying factors of either the left or the right singular vector matrix of a diagonal matrix appended by a row to the right hand side matrix B in solving the least squares problem using the divide-and-conquer SVD approach
dlaneg(l), DLANEG(l)
computes the Sturm count, the number of negative pivots encountered while factoring tridiagonal T - sigma I = L D L^T
dlanv2(l), DLANV2(l)
computes the Schur factorization of a real 2-by-2 nonsymmetric matrix in standard form
dlaqgb(l), DLAQGB(l)
equilibrates a general M by N band matrix A with KL subdiagonals and KU superdiagonals using the row and scaling factors in the vectors R and C
dlaqge(l), DLAQGE(l)
equilibrates a general M by N matrix A using the row and column scaling factors in the vectors R and C
dlaqp2(l), DLAQP2(l)
computes a QR factorization with column pivoting of the block A(OFFSET+1:M,1:N)
dlaqps(l), DLAQPS(l)
computes a step of QR factorization with column pivoting of a real M-by-N matrix A by using Blas-3
dlaqsb(l), DLAQSB(l)
equilibrates a symmetric band matrix A using the scaling factors in the vector S
dlaqsp(l), DLAQSP(l)
equilibrates a symmetric matrix A using the scaling factors in the vector S
dlaqsy(l), DLAQSY(l)
equilibrates a symmetric matrix A using the scaling factors in the vector S
dlarft(l), DLARFT(l)
forms the triangular factor T of a real block reflector H of order n, which is defined as a product of k elementary reflectors
dlarzt(l), DLARZT(l)
forms the triangular factor T of a real block reflector H of order > n, which is defined as a product of k elementary reflectors
dlasyf(l), DLASYF(l)
computes a partial factorization of a real symmetric matrix A using the Bunch-Kaufman diagonal pivoting method
dlatdf(l), DLATDF(l)
uses the LU factorization of the n-by-n matrix Z computed by DGETC2 and computes a contribution to the reciprocal Dif-estimate by solving Z * x = b for x, and choosing the r.h.s
dlatrz(l), DLATRZ(l)
factors the M-by-(M+L) real upper trapezoidal matrix [ A1 A2 ] = [ A(1:M,1:M) A(1:M,N-L+1:N) ] as ( R 0 ) * Z, by means of orthogonal transformations
dlauu2(l), DLAUU2(l)
computes the product U * U(aq or L(aq * L, where the triangular factor U or L is stored in the upper or lower triangular part of the array A
dlauum(l), DLAUUM(l)
computes the product U * U(aq or L(aq * L, where the triangular factor U or L is stored in the upper or lower triangular part of the array A
dpbcon(l), DPBCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a real symmetric positive definite band matrix using the Cholesky factorization A = U**T*U or A = L*L**T computed by DPBTRF
dpbstf(l), DPBSTF(l)
computes a split Cholesky factorization of a real symmetric positive definite band matrix A
dpbsvx(l), DPBSVX(l)
uses the Cholesky factorization A = U**T*U or A = L*L**T to compute the solution to a real system of linear equations A * X = B,
dpbtf2(l), DPBTF2(l)
computes the Cholesky factorization of a real symmetric positive definite band matrix A
dpbtrf(l), DPBTRF(l)
computes the Cholesky factorization of a real symmetric positive definite band matrix A
dpbtrs(l), DPBTRS(l)
solves a system of linear equations A*X = B with a symmetric positive definite band matrix A using the Cholesky factorization A = U**T*U or A = L*L**T computed by DPBTRF
dpftrf(l), DPFTRF(l)
computes the Cholesky factorization of a real symmetric positive definite matrix A
dpftri(l), DPFTRI(l)
computes the inverse of a (real) symmetric positive definite matrix A using the Cholesky factorization A = U**T*U or A = L*L**T computed by DPFTRF
dpftrs(l), DPFTRS(l)
solves a system of linear equations A*X = B with a symmetric positive definite matrix A using the Cholesky factorization A = U**T*U or A = L*L**T computed by DPFTRF
dpocon(l), DPOCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a real symmetric positive definite matrix using the Cholesky factorization A = U**T*U or A = L*L**T computed by DPOTRF
dposvx(l), DPOSVX(l)
uses the Cholesky factorization A = U**T*U or A = L*L**T to compute the solution to a real system of linear equations A * X = B,
dposvxx(l), DPOSVXX(l)
DPOSVXX use the Cholesky factorization A = U**T*U or A = L*L**T to compute the solution to a double precision system of linear equations A * X = B, where A is an N-by-N symmetric positive definite matrix and X and B are N-by-NRHS matrices
dpotf2(l), DPOTF2(l)
computes the Cholesky factorization of a real symmetric positive definite matrix A
dpotrf(l), DPOTRF(l)
computes the Cholesky factorization of a real symmetric positive definite matrix A
dpotri(l), DPOTRI(l)
computes the inverse of a real symmetric positive definite matrix A using the Cholesky factorization A = U**T*U or A = L*L**T computed by DPOTRF
dpotrs(l), DPOTRS(l)
solves a system of linear equations A*X = B with a symmetric positive definite matrix A using the Cholesky factorization A = U**T*U or A = L*L**T computed by DPOTRF
dppcon(l), DPPCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a real symmetric positive definite packed matrix using the Cholesky factorization A = U**T*U or A = L*L**T computed by DPPTRF
dppsvx(l), DPPSVX(l)
uses the Cholesky factorization A = U**T*U or A = L*L**T to compute the solution to a real system of linear equations A * X = B,
dpptrf(l), DPPTRF(l)
computes the Cholesky factorization of a real symmetric positive definite matrix A stored in packed format
dpptri(l), DPPTRI(l)
computes the inverse of a real symmetric positive definite matrix A using the Cholesky factorization A = U**T*U or A = L*L**T computed by DPPTRF
dpptrs(l), DPPTRS(l)
solves a system of linear equations A*X = B with a symmetric positive definite matrix A in packed storage using the Cholesky factorization A = U**T*U or A = L*L**T computed by DPPTRF
dpstf2(l), DPSTF2(l)
computes the Cholesky factorization with complete pivoting of a real symmetric positive semidefinite matrix A
dpstrf(l), DPSTRF(l)
computes the Cholesky factorization with complete pivoting of a real symmetric positive semidefinite matrix A
dptcon(l), DPTCON(l)
computes the reciprocal of the condition number (in the 1-norm) of a real symmetric positive definite tridiagonal matrix using the factorization A = L*D*L**T or A = U**T*D*U computed by DPTTRF
dpteqr(l), DPTEQR(l)
computes all eigenvalues and, optionally, eigenvectors of a symmetric positive definite tridiagonal matrix by first factoring the matrix using DPTTRF, and then calling DBDSQR to compute the singular values of the bidiagonal factor
dptsvx(l), DPTSVX(l)
uses the factorization A = L*D*L**T to compute the solution to a real system of linear equations A*X = B, where A is an N-by-N symmetric positive definite tridiagonal matrix and X and B are N-by-NRHS matrices
dpttrf(l), DPTTRF(l)
computes the L*D*L(aq factorization of a real symmetric positive definite tridiagonal matrix A
dpttrs(l), DPTTRS(l)
solves a tridiagonal system of the form A * X = B using the L*D*L(aq factorization of A computed by DPTTRF
dptts2(l), DPTTS2(l)
solves a tridiagonal system of the form A * X = B using the L*D*L(aq factorization of A computed by DPTTRF
dspcon(l), DSPCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a real symmetric packed matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by DSPTRF
dspsvx(l), DSPSVX(l)
uses the diagonal pivoting factorization A = U*D*U**T or A = L*D*L**T to compute the solution to a real system of linear equations A * X = B, where A is an N-by-N symmetric matrix stored in packed format and X and B are N-by-NRHS matrices
dsptrf(l), DSPTRF(l)
computes the factorization of a real symmetric matrix A stored in packed format using the Bunch-Kaufman diagonal pivoting method
dsptri(l), DSPTRI(l)
computes the inverse of a real symmetric indefinite matrix A in packed storage using the factorization A = U*D*U**T or A = L*D*L**T computed by DSPTRF
dsptrs(l), DSPTRS(l)
solves a system of linear equations A*X = B with a real symmetric matrix A stored in packed format using the factorization A = U*D*U**T or A = L*D*L**T computed by DSPTRF
dsycon(l), DSYCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a real symmetric matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by DSYTRF
dsysvx(l), DSYSVX(l)
uses the diagonal pivoting factorization to compute the solution to a real system of linear equations A * X = B,
dsysvxx(l), DSYSVXX(l)
DSYSVXX use the diagonal pivoting factorization to compute the solution to a double precision system of linear equations A * X = B, where A is an N-by-N symmetric matrix and X and B are N-by-NRHS matrices
dsytf2(l), DSYTF2(l)
computes the factorization of a real symmetric matrix A using the Bunch-Kaufman diagonal pivoting method
dsytrf(l), DSYTRF(l)
computes the factorization of a real symmetric matrix A using the Bunch-Kaufman diagonal pivoting method
dsytri(l), DSYTRI(l)
computes the inverse of a real symmetric indefinite matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by DSYTRF
dsytrs(l), DSYTRS(l)
solves a system of linear equations A*X = B with a real symmetric matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by DSYTRF
dtrexc(l), DTREXC(l)
reorders the real Schur factorization of a real matrix A = Q*T*Q**T, so that the diagonal block of T with row index IFST is moved to row ILST
dtrsen(l), DTRSEN(l)
reorders the real Schur factorization of a real matrix A = Q*T*Q**T, so that a selected cluster of eigenvalues appears in the leading diagonal blocks of the upper quasi-triangular matrix T,
ecm(1)
integer factorization using ECM, P-1 or P+1
gfactor(1), factor(1)
factor numbers
glPixelZoom(3), "glPixelZoom(3)
specify the pixel zoom factors
login_duo(8)
second-factor authentication via Duo login service
mouse_setscale(3)
sets a mouse scale factor
pcdbtrf(l), PCDBTRF(l)
compute a LU factorization of an N-by-N complex banded diagonally dominant-like distributed matrix with bandwidth BWL, BWU
pcdttrf(l), PCDTTRF(l)
compute a LU factorization of an N-by-N complex tridiagonal diagonally dominant-like distributed matrix A(1:N, JA:JA+N-1)
pcgbtrf(l), PCGBTRF(l)
compute a LU factorization of an N-by-N complex banded distributed matrix with bandwidth BWL, BWU
pcgecon(l), PCGECON(l)
estimate the reciprocal of the condition number of a general distributed complex matrix A(IA:IA+N-1,JA:JA+N-1), in either the 1-norm or the infinity-norm, using the LU factorization computed by PCGETRF
pcgelq2(l), PCGELQ2(l)
compute a LQ factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = L * Q
pcgelqf(l), PCGELQF(l)
compute a LQ factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = L * Q
pcgeql2(l), PCGEQL2(l)
compute a QL factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * L
pcgeqlf(l), PCGEQLF(l)
compute a QL factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * L
pcgeqpf(l), PCGEQPF(l)
compute a QR factorization with column pivoting of a M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
pcgeqr2(l), PCGEQR2(l)
compute a QR factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * R
pcgeqrf(l), PCGEQRF(l)
compute a QR factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * R
pcgerq2(l), PCGERQ2(l)
compute a RQ factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = R * Q
pcgerqf(l), PCGERQF(l)
compute a RQ factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = R * Q
pcgesvx(l), PCGESVX(l)
use the LU factorization to compute the solution to a complex system of linear equations A(IA:IA+N-1,JA:JA+N-1) * X = B(IB:IB+N-1,JB:JB+NRHS-1),
pcgetf2(l), PCGETF2(l)
compute an LU factorization of a general M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) using partial pivoting with row interchanges
pcgetrf(l), PCGETRF(l)
compute an LU factorization of a general M-by-N distributed matrix sub( A ) = (IA:IA+M-1,JA:JA+N-1) using partial pivoting with row interchanges
pcgetri(l), PCGETRI(l)
compute the inverse of a distributed matrix using the LU factorization computed by PCGETRF
pcgetrs(l), PCGETRS(l)
solve a system of distributed linear equations op( sub( A ) ) * X = sub( B ) with a general N-by-N distributed matrix sub( A ) using the LU factorization computed by PCGETRF
pcggqrf(l), PCGGQRF(l)
compute a generalized QR factorization of an N-by-M matrix sub( A ) = A(IA:IA+N-1,JA:JA+M-1) and an N-by-P matrix sub( B ) = B(IB:IB+N-1,JB:JB+P-1)
pcggrqf(l), PCGGRQF(l)
compute a generalized RQ factorization of an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
pclaqge(l), PCLAQGE(l)
equilibrate a general M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) using the row and scaling factors in the vectors R and C
pclaqsy(l), PCLAQSY(l)
equilibrate a symmetric distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1) using the scaling factors in the vectors SR and SC
pclarft(l), PCLARFT(l)
form the triangular factor T of a complex block reflector H of order n, which is defined as a product of k elementary reflectors
pclarzt(l), PCLARZT(l)
form the triangular factor T of a complex block reflector H of order > n, which is defined as a product of k elementary reflectors as returned by PCTZRZF
pclauu2(l), PCLAUU2(l)
compute the product U * U' or L' * L, where the triangular factor U or L is stored in the upper or lower triangular part of the matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1)
pclauum(l), PCLAUUM(l)
compute the product U * U' or L' * L, where the triangular factor U or L is stored in the upper or lower triangular part of the distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1)
pcpbtrf(l), PCPBTRF(l)
compute a Cholesky factorization of an N-by-N complex banded symmetric positive definite distributed matrix with bandwidth BW
pcpocon(l), PCPOCON(l)
estimate the reciprocal of the condition number (in the 1-norm) of a complex Hermitian positive definite distributed matrix using the Cholesky factorization A = U**H*U or A = L*L**H computed by PCPOTRF
pcposvx(l), PCPOSVX(l)
use the Cholesky factorization A = U**H*U or A = L*L**H to compute the solution to a complex system of linear equations A(IA:IA+N-1,JA:JA+N-1) * X = B(IB:IB+N-1,JB:JB+NRHS-1),
pcpotf2(l), PCPOTF2(l)
compute the Cholesky factorization of a complex hermitian positive definite distributed matrix sub( A )=A(IA:IA+N-1,JA:JA+N-1)
pcpotrf(l), PCPOTRF(l)
compute the Cholesky factorization of an N-by-N complex hermitian positive definite distributed matrix sub( A ) denoting A(IA:IA+N-1, JA:JA+N-1)
pcpotri(l), PCPOTRI(l)
compute the inverse of a complex Hermitian positive definite distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1) using the Cholesky factorization sub( A ) = U**H*U or L*L**H computed by PCPOTRF
pcpttrf(l), PCPTTRF(l)
compute a Cholesky factorization of an N-by-N complex tridiagonal symmetric positive definite distributed matrix A(1:N, JA:JA+N-1)
pddbtrf(l), PDDBTRF(l)
compute a LU factorization of an N-by-N real banded diagonally dominant-like distributed matrix with bandwidth BWL, BWU
pddttrf(l), PDDTTRF(l)
compute a LU factorization of an N-by-N real tridiagonal diagonally dominant-like distributed matrix A(1:N, JA:JA+N-1)
pdgbtrf(l), PDGBTRF(l)
compute a LU factorization of an N-by-N real banded distributed matrix with bandwidth BWL, BWU
pdgecon(l), PDGECON(l)
estimate the reciprocal of the condition number of a general distributed real matrix A(IA:IA+N-1,JA:JA+N-1), in either the 1-norm or the infinity-norm, using the LU factorization computed by PDGETRF
pdgelq2(l), PDGELQ2(l)
compute a LQ factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = L * Q
pdgelqf(l), PDGELQF(l)
compute a LQ factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = L * Q
pdgeql2(l), PDGEQL2(l)
compute a QL factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * L
pdgeqlf(l), PDGEQLF(l)
compute a QL factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * L
pdgeqpf(l), PDGEQPF(l)
compute a QR factorization with column pivoting of a M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
pdgeqr2(l), PDGEQR2(l)
compute a QR factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * R
pdgeqrf(l), PDGEQRF(l)
compute a QR factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * R
pdgerq2(l), PDGERQ2(l)
compute a RQ factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = R * Q
pdgerqf(l), PDGERQF(l)
compute a RQ factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = R * Q
pdgesvx(l), PDGESVX(l)
use the LU factorization to compute the solution to a real system of linear equations A(IA:IA+N-1,JA:JA+N-1) * X = B(IB:IB+N-1,JB:JB+NRHS-1),
pdgetf2(l), PDGETF2(l)
compute an LU factorization of a general M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) using partial pivoting with row interchanges
pdgetrf(l), PDGETRF(l)
compute an LU factorization of a general M-by-N distributed matrix sub( A ) = (IA:IA+M-1,JA:JA+N-1) using partial pivoting with row interchanges
pdgetri(l), PDGETRI(l)
compute the inverse of a distributed matrix using the LU factorization computed by PDGETRF
pdgetrs(l), PDGETRS(l)
solve a system of distributed linear equations op( sub( A ) ) * X = sub( B ) with a general N-by-N distributed matrix sub( A ) using the LU factorization computed by PDGETRF
pdggqrf(l), PDGGQRF(l)
compute a generalized QR factorization of an N-by-M matrix sub( A ) = A(IA:IA+N-1,JA:JA+M-1) and an N-by-P matrix sub( B ) = B(IB:IB+N-1,JB:JB+P-1)
pdggrqf(l), PDGGRQF(l)
compute a generalized RQ factorization of an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
pdlaqge(l), PDLAQGE(l)
equilibrate a general M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) using the row and scaling factors in the vectors R and C
pdlaqsy(l), PDLAQSY(l)
equilibrate a symmetric distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1) using the scaling factors in the vectors SR and SC
pdlarft(l), PDLARFT(l)
form the triangular factor T of a real block reflector H of order n, which is defined as a product of k elementary reflectors
pdlarzt(l), PDLARZT(l)
form the triangular factor T of a real block reflector H of order > n, which is defined as a product of k elementary reflectors as returned by PDTZRZF
pdlauu2(l), PDLAUU2(l)
compute the product U * U' or L' * L, where the triangular factor U or L is stored in the upper or lower triangular part of the matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1)
pdlauum(l), PDLAUUM(l)
compute the product U * U' or L' * L, where the triangular factor U or L is stored in the upper or lower triangular part of the distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1)
pdpbtrf(l), PDPBTRF(l)
compute a Cholesky factorization of an N-by-N real banded symmetric positive definite distributed matrix with bandwidth BW
pdpocon(l), PDPOCON(l)
estimate the reciprocal of the condition number (in the 1-norm) of a real symmetric positive definite distributed matrix using the Cholesky factorization A = U**T*U or A = L*L**T computed by PDPOTRF
pdposvx(l), PDPOSVX(l)
use the Cholesky factorization A = U**T*U or A = L*L**T to compute the solution to a real system of linear equations A(IA:IA+N-1,JA:JA+N-1) * X = B(IB:IB+N-1,JB:JB+NRHS-1),
pdpotf2(l), PDPOTF2(l)
compute the Cholesky factorization of a real symmetric positive definite distributed matrix sub( A )=A(IA:IA+N-1,JA:JA+N-1)
pdpotrf(l), PDPOTRF(l)
compute the Cholesky factorization of an N-by-N real symmetric positive definite distributed matrix sub( A ) denoting A(IA:IA+N-1, JA:JA+N-1)
pdpotri(l), PDPOTRI(l)
compute the inverse of a real symmetric positive definite distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1) using the Cholesky factorization sub( A ) = U**T*U or L*L**T computed by PDPOTRF
pdpttrf(l), PDPTTRF(l)
compute a Cholesky factorization of an N-by-N real tridiagonal symmetric positive definite distributed matrix A(1:N, JA:JA+N-1)
pixilate(1)
parses an input file containing Cisco PIX 6.2x - PIX 6.3x (normal mask) or Cisco IOS (inverted mask) access-list entries and generates the corresponding packets. For information on writing PIX access lists, see http://www.cisco.com/univercd/cc/td/doc/product/iaabu/pix/pix_62/cmdref/ab.htm#xtocid7 and http://www.cisco.com/warp/public/707/confaccesslists.html#intro for Cisco IOS access-lists. is currently capable of generating TCP/UDP/ICMP (various ICMP types), and IGMP utilizing the Libnet 1.1.x library available from http://www.packetfactory.net. NOTE: Libnet 1.0.x is NOT compatible."
psdbtrf(l), PSDBTRF(l)
compute a LU factorization of an N-by-N real banded diagonally dominant-like distributed matrix with bandwidth BWL, BWU
psdttrf(l), PSDTTRF(l)
compute a LU factorization of an N-by-N real tridiagonal diagonally dominant-like distributed matrix A(1:N, JA:JA+N-1)
psgbtrf(l), PSGBTRF(l)
compute a LU factorization of an N-by-N real banded distributed matrix with bandwidth BWL, BWU
psgecon(l), PSGECON(l)
estimate the reciprocal of the condition number of a general distributed real matrix A(IA:IA+N-1,JA:JA+N-1), in either the 1-norm or the infinity-norm, using the LU factorization computed by PSGETRF
psgelq2(l), PSGELQ2(l)
compute a LQ factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = L * Q
psgelqf(l), PSGELQF(l)
compute a LQ factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = L * Q
psgeql2(l), PSGEQL2(l)
compute a QL factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * L
psgeqlf(l), PSGEQLF(l)
compute a QL factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * L
psgeqpf(l), PSGEQPF(l)
compute a QR factorization with column pivoting of a M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
psgeqr2(l), PSGEQR2(l)
compute a QR factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * R
psgeqrf(l), PSGEQRF(l)
compute a QR factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * R
psgerq2(l), PSGERQ2(l)
compute a RQ factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = R * Q
psgerqf(l), PSGERQF(l)
compute a RQ factorization of a real distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = R * Q
psgesvx(l), PSGESVX(l)
use the LU factorization to compute the solution to a real system of linear equations A(IA:IA+N-1,JA:JA+N-1) * X = B(IB:IB+N-1,JB:JB+NRHS-1),
psgetf2(l), PSGETF2(l)
compute an LU factorization of a general M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) using partial pivoting with row interchanges
psgetrf(l), PSGETRF(l)
compute an LU factorization of a general M-by-N distributed matrix sub( A ) = (IA:IA+M-1,JA:JA+N-1) using partial pivoting with row interchanges
psgetri(l), PSGETRI(l)
compute the inverse of a distributed matrix using the LU factorization computed by PSGETRF
psgetrs(l), PSGETRS(l)
solve a system of distributed linear equations op( sub( A ) ) * X = sub( B ) with a general N-by-N distributed matrix sub( A ) using the LU factorization computed by PSGETRF
psggqrf(l), PSGGQRF(l)
compute a generalized QR factorization of an N-by-M matrix sub( A ) = A(IA:IA+N-1,JA:JA+M-1) and an N-by-P matrix sub( B ) = B(IB:IB+N-1,JB:JB+P-1)
psggrqf(l), PSGGRQF(l)
compute a generalized RQ factorization of an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
pslaqge(l), PSLAQGE(l)
equilibrate a general M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) using the row and scaling factors in the vectors R and C
pslaqsy(l), PSLAQSY(l)
equilibrate a symmetric distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1) using the scaling factors in the vectors SR and SC
pslarft(l), PSLARFT(l)
form the triangular factor T of a real block reflector H of order n, which is defined as a product of k elementary reflectors
pslarzt(l), PSLARZT(l)
form the triangular factor T of a real block reflector H of order > n, which is defined as a product of k elementary reflectors as returned by PSTZRZF
pslauu2(l), PSLAUU2(l)
compute the product U * U' or L' * L, where the triangular factor U or L is stored in the upper or lower triangular part of the matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1)
pslauum(l), PSLAUUM(l)
compute the product U * U' or L' * L, where the triangular factor U or L is stored in the upper or lower triangular part of the distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1)
pspbtrf(l), PSPBTRF(l)
compute a Cholesky factorization of an N-by-N real banded symmetric positive definite distributed matrix with bandwidth BW
pspocon(l), PSPOCON(l)
estimate the reciprocal of the condition number (in the 1-norm) of a real symmetric positive definite distributed matrix using the Cholesky factorization A = U**T*U or A = L*L**T computed by PSPOTRF
psposvx(l), PSPOSVX(l)
use the Cholesky factorization A = U**T*U or A = L*L**T to compute the solution to a real system of linear equations A(IA:IA+N-1,JA:JA+N-1) * X = B(IB:IB+N-1,JB:JB+NRHS-1),
pspotf2(l), PSPOTF2(l)
compute the Cholesky factorization of a real symmetric positive definite distributed matrix sub( A )=A(IA:IA+N-1,JA:JA+N-1)
pspotrf(l), PSPOTRF(l)
compute the Cholesky factorization of an N-by-N real symmetric positive definite distributed matrix sub( A ) denoting A(IA:IA+N-1, JA:JA+N-1)
pspotri(l), PSPOTRI(l)
compute the inverse of a real symmetric positive definite distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1) using the Cholesky factorization sub( A ) = U**T*U or L*L**T computed by PSPOTRF
pspttrf(l), PSPTTRF(l)
compute a Cholesky factorization of an N-by-N real tridiagonal symmetric positive definite distributed matrix A(1:N, JA:JA+N-1)
pzdbtrf(l), PZDBTRF(l)
compute a LU factorization of an N-by-N complex banded diagonally dominant-like distributed matrix with bandwidth BWL, BWU
pzdttrf(l), PZDTTRF(l)
compute a LU factorization of an N-by-N complex tridiagonal diagonally dominant-like distributed matrix A(1:N, JA:JA+N-1)
pzgbtrf(l), PZGBTRF(l)
compute a LU factorization of an N-by-N complex banded distributed matrix with bandwidth BWL, BWU
pzgecon(l), PZGECON(l)
estimate the reciprocal of the condition number of a general distributed complex matrix A(IA:IA+N-1,JA:JA+N-1), in either the 1-norm or the infinity-norm, using the LU factorization computed by PZGETRF
pzgelq2(l), PZGELQ2(l)
compute a LQ factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = L * Q
pzgelqf(l), PZGELQF(l)
compute a LQ factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = L * Q
pzgeql2(l), PZGEQL2(l)
compute a QL factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * L
pzgeqlf(l), PZGEQLF(l)
compute a QL factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * L
pzgeqpf(l), PZGEQPF(l)
compute a QR factorization with column pivoting of a M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
pzgeqr2(l), PZGEQR2(l)
compute a QR factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * R
pzgeqrf(l), PZGEQRF(l)
compute a QR factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = Q * R
pzgerq2(l), PZGERQ2(l)
compute a RQ factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = R * Q
pzgerqf(l), PZGERQF(l)
compute a RQ factorization of a complex distributed M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) = R * Q
pzgesvx(l), PZGESVX(l)
use the LU factorization to compute the solution to a complex system of linear equations A(IA:IA+N-1,JA:JA+N-1) * X = B(IB:IB+N-1,JB:JB+NRHS-1),
pzgetf2(l), PZGETF2(l)
compute an LU factorization of a general M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) using partial pivoting with row interchanges
pzgetrf(l), PZGETRF(l)
compute an LU factorization of a general M-by-N distributed matrix sub( A ) = (IA:IA+M-1,JA:JA+N-1) using partial pivoting with row interchanges
pzgetri(l), PZGETRI(l)
compute the inverse of a distributed matrix using the LU factorization computed by PZGETRF
pzgetrs(l), PZGETRS(l)
solve a system of distributed linear equations op( sub( A ) ) * X = sub( B ) with a general N-by-N distributed matrix sub( A ) using the LU factorization computed by PZGETRF
pzggqrf(l), PZGGQRF(l)
compute a generalized QR factorization of an N-by-M matrix sub( A ) = A(IA:IA+N-1,JA:JA+M-1) and an N-by-P matrix sub( B ) = B(IB:IB+N-1,JB:JB+P-1)
pzggrqf(l), PZGGRQF(l)
compute a generalized RQ factorization of an M-by-N matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
pzlaqge(l), PZLAQGE(l)
equilibrate a general M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) using the row and scaling factors in the vectors R and C
pzlaqsy(l), PZLAQSY(l)
equilibrate a symmetric distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1) using the scaling factors in the vectors SR and SC
pzlarft(l), PZLARFT(l)
form the triangular factor T of a complex block reflector H of order n, which is defined as a product of k elementary reflectors
pzlarzt(l), PZLARZT(l)
form the triangular factor T of a complex block reflector H of order > n, which is defined as a product of k elementary reflectors as returned by PZTZRZF
pzlauu2(l), PZLAUU2(l)
compute the product U * U' or L' * L, where the triangular factor U or L is stored in the upper or lower triangular part of the matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1)
pzlauum(l), PZLAUUM(l)
compute the product U * U' or L' * L, where the triangular factor U or L is stored in the upper or lower triangular part of the distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1)
pzpbtrf(l), PZPBTRF(l)
compute a Cholesky factorization of an N-by-N complex banded symmetric positive definite distributed matrix with bandwidth BW
pzpocon(l), PZPOCON(l)
estimate the reciprocal of the condition number (in the 1-norm) of a complex Hermitian positive definite distributed matrix using the Cholesky factorization A = U**H*U or A = L*L**H computed by PZPOTRF
pzposvx(l), PZPOSVX(l)
use the Cholesky factorization A = U**H*U or A = L*L**H to compute the solution to a complex system of linear equations A(IA:IA+N-1,JA:JA+N-1) * X = B(IB:IB+N-1,JB:JB+NRHS-1),
pzpotf2(l), PZPOTF2(l)
compute the Cholesky factorization of a complex hermitian positive definite distributed matrix sub( A )=A(IA:IA+N-1,JA:JA+N-1)
pzpotrf(l), PZPOTRF(l)
compute the Cholesky factorization of an N-by-N complex hermitian positive definite distributed matrix sub( A ) denoting A(IA:IA+N-1, JA:JA+N-1)
pzpotri(l), PZPOTRI(l)
compute the inverse of a complex Hermitian positive definite distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1) using the Cholesky factorization sub( A ) = U**H*U or L*L**H computed by PZPOTRF
pzpttrf(l), PZPTTRF(l)
compute a Cholesky factorization of an N-by-N complex tridiagonal symmetric positive definite distributed matrix A(1:N, JA:JA+N-1)
sc_Integral(3), sc::Integral(3)
The Integral abstract class acts as a factory to provide objects that compute one and two electron integrals'
sc_MOIntsTransformFactory(3), sc::MOIntsTransformFactory(3)
MOIntsTransformFactory is a factory that produces MOIntsTransform objects'
sc_MOPairIterFactory(3), sc::MOPairIterFactory(3)
This class produces MOPairIter objects'
sc_SCMatrixKit(3), sc::SCMatrixKit(3)
The SCMatrixKit abstract class acts as a factory for producing matrices'
sca(nged)
Used to apply a scaling factor
sdbtf2(l), SDBTF2(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting with row interchanges
sdbtrf(l), SDBTRF(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting or row interchanges
sdttrf(l), SDTTRF(l)
compute an LU factorization of a complex tridiagonal matrix A using elimination without partial pivoting
sgbsvx(l), SGBSVX(l)
uses the LU factorization to compute the solution to a real system of linear equations A * X = B, A**T * X = B, or A**H * X = B,
sgbsvxx(l), SGBSVXX(l)
SGBSVXX use the LU factorization to compute the solution to a real system of linear equations A * X = B, where A is an N-by-N matrix and X and B are N-by-NRHS matrices
sgbtf2(l), SGBTF2(l)
computes an LU factorization of a real m-by-n band matrix A using partial pivoting with row interchanges
sgbtrf(l), SGBTRF(l)
computes an LU factorization of a real m-by-n band matrix A using partial pivoting with row interchanges
sgbtrs(l), SGBTRS(l)
solves a system of linear equations A * X = B or A(aq * X = B with a general band matrix A using the LU factorization computed by SGBTRF
sgecon(l), SGECON(l)
estimates the reciprocal of the condition number of a general real matrix A, in either the 1-norm or the infinity-norm, using the LU factorization computed by SGETRF
sgelq2(l), SGELQ2(l)
computes an LQ factorization of a real m by n matrix A
sgelqf(l), SGELQF(l)
computes an LQ factorization of a real M-by-N matrix A
sgels(l), SGELS(l)
solves overdetermined or underdetermined real linear systems involving an M-by-N matrix A, or its transpose, using a QR or LQ factorization of A
sgeql2(l), SGEQL2(l)
computes a QL factorization of a real m by n matrix A
sgeqlf(l), SGEQLF(l)
computes a QL factorization of a real M-by-N matrix A
sgeqp3(l), SGEQP3(l)
computes a QR factorization with column pivoting of a matrix A
sgeqr2(l), SGEQR2(l)
computes a QR factorization of a real m by n matrix A
sgeqrf(l), SGEQRF(l)
computes a QR factorization of a real M-by-N matrix A
sgerq2(l), SGERQ2(l)
computes an RQ factorization of a real m by n matrix A
sgerqf(l), SGERQF(l)
computes an RQ factorization of a real M-by-N matrix A
sgesc2(l), SGESC2(l)
solves a system of linear equations A * X = scale* RHS with a general N-by-N matrix A using the LU factorization with complete pivoting computed by SGETC2
sgesvx(l), SGESVX(l)
uses the LU factorization to compute the solution to a real system of linear equations A * X = B,
sgesvxx(l), SGESVXX(l)
SGESVXX use the LU factorization to compute the solution to a real system of linear equations A * X = B, where A is an N-by-N matrix and X and B are N-by-NRHS matrices
sgetc2(l), SGETC2(l)
computes an LU factorization with complete pivoting of the n-by-n matrix A
sgetf2(l), SGETF2(l)
computes an LU factorization of a general m-by-n matrix A using partial pivoting with row interchanges
sgetrf(l), SGETRF(l)
computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges
sgetri(l), SGETRI(l)
computes the inverse of a matrix using the LU factorization computed by SGETRF
sgetrs(l), SGETRS(l)
solves a system of linear equations A * X = B or A(aq * X = B with a general N-by-N matrix A using the LU factorization computed by SGETRF
sggqrf(l), SGGQRF(l)
computes a generalized QR factorization of an N-by-M matrix A and an N-by-P matrix B
sggrqf(l), SGGRQF(l)
computes a generalized RQ factorization of an M-by-N matrix A and a P-by-N matrix B
sgtcon(l), SGTCON(l)
estimates the reciprocal of the condition number of a real tridiagonal matrix A using the LU factorization as computed by SGTTRF
sgtsvx(l), SGTSVX(l)
uses the LU factorization to compute the solution to a real system of linear equations A * X = B or A**T * X = B,
sgttrf(l), SGTTRF(l)
computes an LU factorization of a real tridiagonal matrix A using elimination with partial pivoting and row interchanges
shapefact(1)
obtain shape factors between named regions of mged database
sla_gbrcond(l), SLA_GBRCOND(l)
SLA_GERCOND Estimate the Skeel condition number of op(A) * op2(C) where op2 is determined by CMODE as follows CMODE = 1 op2(C) = C CMODE = 0 op2(C) = I CMODE = -1 op2(C) = inv(C) The Skeel condition number cond(A) = norminf( |inv(A)||A| ) is computed by computing scaling factors R such that diag(R)*A*op2(C) is row equilibrated and computing the standard infinity-norm condition number
sla_gercond(l), SLA_GERCOND(l)
SLA_GERCOND estimate the Skeel condition number of op(A) * op2(C) where op2 is determined by CMODE as follows CMODE = 1 op2(C) = C CMODE = 0 op2(C) = I CMODE = -1 op2(C) = inv(C) The Skeel condition number cond(A) = norminf( |inv(A)||A| ) is computed by computing scaling factors R such that diag(R)*A*op2(C) is row equilibrated and computing the standard infinity-norm condition number
sla_porcond(l), SLA_PORCOND(l)
SLA_PORCOND Estimate the Skeel condition number of op(A) * op2(C) where op2 is determined by CMODE as follows CMODE = 1 op2(C) = C CMODE = 0 op2(C) = I CMODE = -1 op2(C) = inv(C) The Skeel condition number cond(A) = norminf( |inv(A)||A| ) is computed by computing scaling factors R such that diag(R)*A*op2(C) is row equilibrated and computing the standard infinity-norm condition number
sla_syrcond(l), SLA_SYRCOND(l)
SLA_SYRCOND estimate the Skeel condition number of op(A) * op2(C) where op2 is determined by CMODE as follows CMODE = 1 op2(C) = C CMODE = 0 op2(C) = I CMODE = -1 op2(C) = inv(C) The Skeel condition number cond(A) = norminf( |inv(A)||A| ) is computed by computing scaling factors R such that diag(R)*A*op2(C) is row equilibrated and computing the standard infinity-norm condition number
slagtf(l), SLAGTF(l)
factorizes the matrix (T - lambda*I), where T is an n by n tridiagonal matrix and lambda is a scalar, as T - lambda*I = PLU,
slagv2(l), SLAGV2(l)
computes the Generalized Schur factorization of a real 2-by-2 matrix pencil (A,B) where B is upper triangular
slals0(l), SLALS0(l)
applies back the multiplying factors of either the left or the right singular vector matrix of a diagonal matrix appended by a row to the right hand side matrix B in solving the least squares problem using the divide-and-conquer SVD approach
slaneg(l), SLANEG(l)
computes the Sturm count, the number of negative pivots encountered while factoring tridiagonal T - sigma I = L D L^T
slanv2(l), SLANV2(l)
computes the Schur factorization of a real 2-by-2 nonsymmetric matrix in standard form
slaqgb(l), SLAQGB(l)
equilibrates a general M by N band matrix A with KL subdiagonals and KU superdiagonals using the row and scaling factors in the vectors R and C
slaqge(l), SLAQGE(l)
equilibrates a general M by N matrix A using the row and column scaling factors in the vectors R and C
slaqp2(l), SLAQP2(l)
computes a QR factorization with column pivoting of the block A(OFFSET+1:M,1:N)
slaqps(l), SLAQPS(l)
computes a step of QR factorization with column pivoting of a real M-by-N matrix A by using Blas-3
slaqsb(l), SLAQSB(l)
equilibrates a symmetric band matrix A using the scaling factors in the vector S
slaqsp(l), SLAQSP(l)
equilibrates a symmetric matrix A using the scaling factors in the vector S
slaqsy(l), SLAQSY(l)
equilibrates a symmetric matrix A using the scaling factors in the vector S
slarft(l), SLARFT(l)
forms the triangular factor T of a real block reflector H of order n, which is defined as a product of k elementary reflectors
slarzt(l), SLARZT(l)
forms the triangular factor T of a real block reflector H of order > n, which is defined as a product of k elementary reflectors
slasyf(l), SLASYF(l)
computes a partial factorization of a real symmetric matrix A using the Bunch-Kaufman diagonal pivoting method
slatdf(l), SLATDF(l)
uses the LU factorization of the n-by-n matrix Z computed by SGETC2 and computes a contribution to the reciprocal Dif-estimate by solving Z * x = b for x, and choosing the r.h.s
slatrz(l), SLATRZ(l)
factors the M-by-(M+L) real upper trapezoidal matrix [ A1 A2 ] = [ A(1:M,1:M) A(1:M,N-L+1:N) ] as ( R 0 ) * Z, by means of orthogonal transformations
slauu2(l), SLAUU2(l)
computes the product U * U(aq or L(aq * L, where the triangular factor U or L is stored in the upper or lower triangular part of the array A
slauum(l), SLAUUM(l)
computes the product U * U(aq or L(aq * L, where the triangular factor U or L is stored in the upper or lower triangular part of the array A
spbcon(l), SPBCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a real symmetric positive definite band matrix using the Cholesky factorization A = U**T*U or A = L*L**T computed by SPBTRF
spbstf(l), SPBSTF(l)
computes a split Cholesky factorization of a real symmetric positive definite band matrix A
spbsvx(l), SPBSVX(l)
uses the Cholesky factorization A = U**T*U or A = L*L**T to compute the solution to a real system of linear equations A * X = B,
spbtf2(l), SPBTF2(l)
computes the Cholesky factorization of a real symmetric positive definite band matrix A
spbtrf(l), SPBTRF(l)
computes the Cholesky factorization of a real symmetric positive definite band matrix A
spbtrs(l), SPBTRS(l)
solves a system of linear equations A*X = B with a symmetric positive definite band matrix A using the Cholesky factorization A = U**T*U or A = L*L**T computed by SPBTRF
spftrf(l), SPFTRF(l)
computes the Cholesky factorization of a real symmetric positive definite matrix A
spftri(l), SPFTRI(l)
computes the inverse of a real (symmetric) positive definite matrix A using the Cholesky factorization A = U**T*U or A = L*L**T computed by SPFTRF
spftrs(l), SPFTRS(l)
solves a system of linear equations A*X = B with a symmetric positive definite matrix A using the Cholesky factorization A = U**T*U or A = L*L**T computed by SPFTRF
spocon(l), SPOCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a real symmetric positive definite matrix using the Cholesky factorization A = U**T*U or A = L*L**T computed by SPOTRF
sposvx(l), SPOSVX(l)
uses the Cholesky factorization A = U**T*U or A = L*L**T to compute the solution to a real system of linear equations A * X = B,
sposvxx(l), SPOSVXX(l)
SPOSVXX use the Cholesky factorization A = U**T*U or A = L*L**T to compute the solution to a real system of linear equations A * X = B, where A is an N-by-N symmetric positive definite matrix and X and B are N-by-NRHS matrices
spotf2(l), SPOTF2(l)
computes the Cholesky factorization of a real symmetric positive definite matrix A
spotrf(l), SPOTRF(l)
computes the Cholesky factorization of a real symmetric positive definite matrix A
spotri(l), SPOTRI(l)
computes the inverse of a real symmetric positive definite matrix A using the Cholesky factorization A = U**T*U or A = L*L**T computed by SPOTRF
spotrs(l), SPOTRS(l)
solves a system of linear equations A*X = B with a symmetric positive definite matrix A using the Cholesky factorization A = U**T*U or A = L*L**T computed by SPOTRF
sppcon(l), SPPCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a real symmetric positive definite packed matrix using the Cholesky factorization A = U**T*U or A = L*L**T computed by SPPTRF
sppsvx(l), SPPSVX(l)
uses the Cholesky factorization A = U**T*U or A = L*L**T to compute the solution to a real system of linear equations A * X = B,
spptrf(l), SPPTRF(l)
computes the Cholesky factorization of a real symmetric positive definite matrix A stored in packed format
spptri(l), SPPTRI(l)
computes the inverse of a real symmetric positive definite matrix A using the Cholesky factorization A = U**T*U or A = L*L**T computed by SPPTRF
spptrs(l), SPPTRS(l)
solves a system of linear equations A*X = B with a symmetric positive definite matrix A in packed storage using the Cholesky factorization A = U**T*U or A = L*L**T computed by SPPTRF
spstf2(l), SPSTF2(l)
computes the Cholesky factorization with complete pivoting of a real symmetric positive semidefinite matrix A
spstrf(l), SPSTRF(l)
computes the Cholesky factorization with complete pivoting of a real symmetric positive semidefinite matrix A
sptcon(l), SPTCON(l)
computes the reciprocal of the condition number (in the 1-norm) of a real symmetric positive definite tridiagonal matrix using the factorization A = L*D*L**T or A = U**T*D*U computed by SPTTRF
spteqr(l), SPTEQR(l)
computes all eigenvalues and, optionally, eigenvectors of a symmetric positive definite tridiagonal matrix by first factoring the matrix using SPTTRF, and then calling SBDSQR to compute the singular values of the bidiagonal factor
sptsvx(l), SPTSVX(l)
uses the factorization A = L*D*L**T to compute the solution to a real system of linear equations A*X = B, where A is an N-by-N symmetric positive definite tridiagonal matrix and X and B are N-by-NRHS matrices
spttrf(l), SPTTRF(l)
computes the L*D*L(aq factorization of a real symmetric positive definite tridiagonal matrix A
spttrs(l), SPTTRS(l)
solves a tridiagonal system of the form A * X = B using the L*D*L(aq factorization of A computed by SPTTRF
sptts2(l), SPTTS2(l)
solves a tridiagonal system of the form A * X = B using the L*D*L(aq factorization of A computed by SPTTRF
sspcon(l), SSPCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a real symmetric packed matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by SSPTRF
sspsvx(l), SSPSVX(l)
uses the diagonal pivoting factorization A = U*D*U**T or A = L*D*L**T to compute the solution to a real system of linear equations A * X = B, where A is an N-by-N symmetric matrix stored in packed format and X and B are N-by-NRHS matrices
ssptrf(l), SSPTRF(l)
computes the factorization of a real symmetric matrix A stored in packed format using the Bunch-Kaufman diagonal pivoting method
ssptri(l), SSPTRI(l)
computes the inverse of a real symmetric indefinite matrix A in packed storage using the factorization A = U*D*U**T or A = L*D*L**T computed by SSPTRF
ssptrs(l), SSPTRS(l)
solves a system of linear equations A*X = B with a real symmetric matrix A stored in packed format using the factorization A = U*D*U**T or A = L*D*L**T computed by SSPTRF
ssycon(l), SSYCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a real symmetric matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by SSYTRF
ssysvx(l), SSYSVX(l)
uses the diagonal pivoting factorization to compute the solution to a real system of linear equations A * X = B,
ssysvxx(l), SSYSVXX(l)
SSYSVXX use the diagonal pivoting factorization to compute the solution to a real system of linear equations A * X = B, where A is an N-by-N symmetric matrix and X and B are N-by-NRHS matrices
ssytf2(l), SSYTF2(l)
computes the factorization of a real symmetric matrix A using the Bunch-Kaufman diagonal pivoting method
ssytrf(l), SSYTRF(l)
computes the factorization of a real symmetric matrix A using the Bunch-Kaufman diagonal pivoting method
ssytri(l), SSYTRI(l)
computes the inverse of a real symmetric indefinite matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by SSYTRF
ssytrs(l), SSYTRS(l)
solves a system of linear equations A*X = B with a real symmetric matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by SSYTRF
status(nged)
Without a subcommand, the status command returns the following information: current state, view size of the current display manager, the conversion factor from local model units to the base units (mm) stored in the database, and the view matrices of the current display manager
strexc(l), STREXC(l)
reorders the real Schur factorization of a real matrix A = Q*T*Q**T, so that the diagonal block of T with row index IFST is moved to row ILST
strsen(l), STRSEN(l)
reorders the real Schur factorization of a real matrix A = Q*T*Q**T, so that a selected cluster of eigenvalues appears in the leading diagonal blocks of the upper quasi-triangular matrix T,
zdbtf2(l), ZDBTF2(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting with row interchanges
zdbtrf(l), ZDBTRF(l)
compute an LU factorization of a real m-by-n band matrix A without using partial pivoting or row interchanges
zdttrf(l), ZDTTRF(l)
compute an LU factorization of a complex tridiagonal matrix A using elimination without partial pivoting
zgbsvx(l), ZGBSVX(l)
uses the LU factorization to compute the solution to a complex system of linear equations A * X = B, A**T * X = B, or A**H * X = B,
zgbsvxx(l), ZGBSVXX(l)
ZGBSVXX use the LU factorization to compute the solution to a complex*16 system of linear equations A * X = B, where A is an N-by-N matrix and X and B are N-by-NRHS matrices
zgbtf2(l), ZGBTF2(l)
computes an LU factorization of a complex m-by-n band matrix A using partial pivoting with row interchanges
zgbtrf(l), ZGBTRF(l)
computes an LU factorization of a complex m-by-n band matrix A using partial pivoting with row interchanges
zgbtrs(l), ZGBTRS(l)
solves a system of linear equations A * X = B, A**T * X = B, or A**H * X = B with a general band matrix A using the LU factorization computed by ZGBTRF
zgecon(l), ZGECON(l)
estimates the reciprocal of the condition number of a general complex matrix A, in either the 1-norm or the infinity-norm, using the LU factorization computed by ZGETRF
zgelq2(l), ZGELQ2(l)
computes an LQ factorization of a complex m by n matrix A
zgelqf(l), ZGELQF(l)
computes an LQ factorization of a complex M-by-N matrix A
zgels(l), ZGELS(l)
solves overdetermined or underdetermined complex linear systems involving an M-by-N matrix A, or its conjugate-transpose, using a QR or LQ factorization of A
zgeql2(l), ZGEQL2(l)
computes a QL factorization of a complex m by n matrix A
zgeqlf(l), ZGEQLF(l)
computes a QL factorization of a complex M-by-N matrix A
zgeqp3(l), ZGEQP3(l)
computes a QR factorization with column pivoting of a matrix A
zgeqr2(l), ZGEQR2(l)
computes a QR factorization of a complex m by n matrix A
zgeqrf(l), ZGEQRF(l)
computes a QR factorization of a complex M-by-N matrix A
zgerq2(l), ZGERQ2(l)
computes an RQ factorization of a complex m by n matrix A
zgerqf(l), ZGERQF(l)
computes an RQ factorization of a complex M-by-N matrix A
zgesc2(l), ZGESC2(l)
solves a system of linear equations A * X = scale* RHS with a general N-by-N matrix A using the LU factorization with complete pivoting computed by ZGETC2
zgesvx(l), ZGESVX(l)
uses the LU factorization to compute the solution to a complex system of linear equations A * X = B,
zgesvxx(l), ZGESVXX(l)
ZGESVXX use the LU factorization to compute the solution to a complex*16 system of linear equations A * X = B, where A is an N-by-N matrix and X and B are N-by-NRHS matrices
zgetc2(l), ZGETC2(l)
computes an LU factorization, using complete pivoting, of the n-by-n matrix A
zgetf2(l), ZGETF2(l)
computes an LU factorization of a general m-by-n matrix A using partial pivoting with row interchanges
zgetrf(l), ZGETRF(l)
computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges
zgetri(l), ZGETRI(l)
computes the inverse of a matrix using the LU factorization computed by ZGETRF
zgetrs(l), ZGETRS(l)
solves a system of linear equations A * X = B, A**T * X = B, or A**H * X = B with a general N-by-N matrix A using the LU factorization computed by ZGETRF
zggqrf(l), ZGGQRF(l)
computes a generalized QR factorization of an N-by-M matrix A and an N-by-P matrix B
zggrqf(l), ZGGRQF(l)
computes a generalized RQ factorization of an M-by-N matrix A and a P-by-N matrix B
zgtcon(l), ZGTCON(l)
estimates the reciprocal of the condition number of a complex tridiagonal matrix A using the LU factorization as computed by ZGTTRF
zgtsvx(l), ZGTSVX(l)
uses the LU factorization to compute the solution to a complex system of linear equations A * X = B, A**T * X = B, or A**H * X = B,
zgttrf(l), ZGTTRF(l)
computes an LU factorization of a complex tridiagonal matrix A using elimination with partial pivoting and row interchanges
zhecon(l), ZHECON(l)
estimates the reciprocal of the condition number of a complex Hermitian matrix A using the factorization A = U*D*U**H or A = L*D*L**H computed by ZHETRF
zhesvx(l), ZHESVX(l)
uses the diagonal pivoting factorization to compute the solution to a complex system of linear equations A * X = B,
zhesvxx(l), ZHESVXX(l)
ZHESVXX use the diagonal pivoting factorization to compute the solution to a complex*16 system of linear equations A * X = B, where A is an N-by-N symmetric matrix and X and B are N-by-NRHS matrices
zhetf2(l), ZHETF2(l)
computes the factorization of a complex Hermitian matrix A using the Bunch-Kaufman diagonal pivoting method
zhetrf(l), ZHETRF(l)
computes the factorization of a complex Hermitian matrix A using the Bunch-Kaufman diagonal pivoting method
zhetri(l), ZHETRI(l)
computes the inverse of a complex Hermitian indefinite matrix A using the factorization A = U*D*U**H or A = L*D*L**H computed by ZHETRF
zhetrs(l), ZHETRS(l)
solves a system of linear equations A*X = B with a complex Hermitian matrix A using the factorization A = U*D*U**H or A = L*D*L**H computed by ZHETRF
zhpcon(l), ZHPCON(l)
estimates the reciprocal of the condition number of a complex Hermitian packed matrix A using the factorization A = U*D*U**H or A = L*D*L**H computed by ZHPTRF
zhpsvx(l), ZHPSVX(l)
uses the diagonal pivoting factorization A = U*D*U**H or A = L*D*L**H to compute the solution to a complex system of linear equations A * X = B, where A is an N-by-N Hermitian matrix stored in packed format and X and B are N-by-NRHS matrices
zhptrf(l), ZHPTRF(l)
computes the factorization of a complex Hermitian packed matrix A using the Bunch-Kaufman diagonal pivoting method
zhptri(l), ZHPTRI(l)
computes the inverse of a complex Hermitian indefinite matrix A in packed storage using the factorization A = U*D*U**H or A = L*D*L**H computed by ZHPTRF
zhptrs(l), ZHPTRS(l)
solves a system of linear equations A*X = B with a complex Hermitian matrix A stored in packed format using the factorization A = U*D*U**H or A = L*D*L**H computed by ZHPTRF
zlahef(l), ZLAHEF(l)
computes a partial factorization of a complex Hermitian matrix A using the Bunch-Kaufman diagonal pivoting method
zlals0(l), ZLALS0(l)
applies back the multiplying factors of either the left or the right singular vector matrix of a diagonal matrix appended by a row to the right hand side matrix B in solving the least squares problem using the divide-and-conquer SVD approach
zlanv2(l), ZLANV2(l)
compute the Schur factorization of a complex 2-by-2 nonhermitian matrix in standard form
zlaqgb(l), ZLAQGB(l)
equilibrates a general M by N band matrix A with KL subdiagonals and KU superdiagonals using the row and scaling factors in the vectors R and C
zlaqge(l), ZLAQGE(l)
equilibrates a general M by N matrix A using the row and column scaling factors in the vectors R and C
zlaqhb(l), ZLAQHB(l)
equilibrates a symmetric band matrix A using the scaling factors in the vector S
zlaqhe(l), ZLAQHE(l)
equilibrates a Hermitian matrix A using the scaling factors in the vector S
zlaqhp(l), ZLAQHP(l)
equilibrates a Hermitian matrix A using the scaling factors in the vector S
zlaqp2(l), ZLAQP2(l)
computes a QR factorization with column pivoting of the block A(OFFSET+1:M,1:N)
zlaqps(l), ZLAQPS(l)
computes a step of QR factorization with column pivoting of a complex M-by-N matrix A by using Blas-3
zlaqsb(l), ZLAQSB(l)
equilibrates a symmetric band matrix A using the scaling factors in the vector S
zlaqsp(l), ZLAQSP(l)
equilibrates a symmetric matrix A using the scaling factors in the vector S
zlaqsy(l), ZLAQSY(l)
equilibrates a symmetric matrix A using the scaling factors in the vector S
zlarft(l), ZLARFT(l)
forms the triangular factor T of a complex block reflector H of order n, which is defined as a product of k elementary reflectors
zlarzt(l), ZLARZT(l)
forms the triangular factor T of a complex block reflector H of order > n, which is defined as a product of k elementary reflectors
zlasyf(l), ZLASYF(l)
computes a partial factorization of a complex symmetric matrix A using the Bunch-Kaufman diagonal pivoting method
zlatrz(l), ZLATRZ(l)
factors the M-by-(M+L) complex upper trapezoidal matrix [ A1 A2 ] = [ A(1:M,1:M) A(1:M,N-L+1:N) ] as ( R 0 ) * Z by means of unitary transformations, where Z is an (M+L)-by-(M+L) unitary matrix and, R and A1 are M-by-M upper triangular matrices
zlauu2(l), ZLAUU2(l)
computes the product U * U(aq or L(aq * L, where the triangular factor U or L is stored in the upper or lower triangular part of the array A
zlauum(l), ZLAUUM(l)
computes the product U * U(aq or L(aq * L, where the triangular factor U or L is stored in the upper or lower triangular part of the array A
zpbcon(l), ZPBCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a complex Hermitian positive definite band matrix using the Cholesky factorization A = U**H*U or A = L*L**H computed by ZPBTRF
zpbstf(l), ZPBSTF(l)
computes a split Cholesky factorization of a complex Hermitian positive definite band matrix A
zpbsvx(l), ZPBSVX(l)
uses the Cholesky factorization A = U**H*U or A = L*L**H to compute the solution to a complex system of linear equations A * X = B,
zpbtf2(l), ZPBTF2(l)
computes the Cholesky factorization of a complex Hermitian positive definite band matrix A
zpbtrf(l), ZPBTRF(l)
computes the Cholesky factorization of a complex Hermitian positive definite band matrix A
zpbtrs(l), ZPBTRS(l)
solves a system of linear equations A*X = B with a Hermitian positive definite band matrix A using the Cholesky factorization A = U**H*U or A = L*L**H computed by ZPBTRF
zpftrf(l), ZPFTRF(l)
computes the Cholesky factorization of a complex Hermitian positive definite matrix A
zpftri(l), ZPFTRI(l)
computes the inverse of a complex Hermitian positive definite matrix A using the Cholesky factorization A = U**H*U or A = L*L**H computed by ZPFTRF
zpftrs(l), ZPFTRS(l)
solves a system of linear equations A*X = B with a Hermitian positive definite matrix A using the Cholesky factorization A = U**H*U or A = L*L**H computed by ZPFTRF
zpocon(l), ZPOCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a complex Hermitian positive definite matrix using the Cholesky factorization A = U**H*U or A = L*L**H computed by ZPOTRF
zposvx(l), ZPOSVX(l)
uses the Cholesky factorization A = U**H*U or A = L*L**H to compute the solution to a complex system of linear equations A * X = B,
zposvxx(l), ZPOSVXX(l)
ZPOSVXX use the Cholesky factorization A = U**T*U or A = L*L**T to compute the solution to a complex*16 system of linear equations A * X = B, where A is an N-by-N symmetric positive definite matrix and X and B are N-by-NRHS matrices
zpotf2(l), ZPOTF2(l)
computes the Cholesky factorization of a complex Hermitian positive definite matrix A
zpotrf(l), ZPOTRF(l)
computes the Cholesky factorization of a complex Hermitian positive definite matrix A
zpotri(l), ZPOTRI(l)
computes the inverse of a complex Hermitian positive definite matrix A using the Cholesky factorization A = U**H*U or A = L*L**H computed by ZPOTRF
zpotrs(l), ZPOTRS(l)
solves a system of linear equations A*X = B with a Hermitian positive definite matrix A using the Cholesky factorization A = U**H*U or A = L*L**H computed by ZPOTRF
zppcon(l), ZPPCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a complex Hermitian positive definite packed matrix using the Cholesky factorization A = U**H*U or A = L*L**H computed by ZPPTRF
zppsvx(l), ZPPSVX(l)
uses the Cholesky factorization A = U**H*U or A = L*L**H to compute the solution to a complex system of linear equations A * X = B,
zpptrf(l), ZPPTRF(l)
computes the Cholesky factorization of a complex Hermitian positive definite matrix A stored in packed format
zpptri(l), ZPPTRI(l)
computes the inverse of a complex Hermitian positive definite matrix A using the Cholesky factorization A = U**H*U or A = L*L**H computed by ZPPTRF
zpptrs(l), ZPPTRS(l)
solves a system of linear equations A*X = B with a Hermitian positive definite matrix A in packed storage using the Cholesky factorization A = U**H*U or A = L*L**H computed by ZPPTRF
zpstf2(l), ZPSTF2(l)
computes the Cholesky factorization with complete pivoting of a complex Hermitian positive semidefinite matrix A
zpstrf(l), ZPSTRF(l)
computes the Cholesky factorization with complete pivoting of a complex Hermitian positive semidefinite matrix A
zptcon(l), ZPTCON(l)
computes the reciprocal of the condition number (in the 1-norm) of a complex Hermitian positive definite tridiagonal matrix using the factorization A = L*D*L**H or A = U**H*D*U computed by ZPTTRF
zpteqr(l), ZPTEQR(l)
computes all eigenvalues and, optionally, eigenvectors of a symmetric positive definite tridiagonal matrix by first factoring the matrix using DPTTRF and then calling ZBDSQR to compute the singular values of the bidiagonal factor
zptsvx(l), ZPTSVX(l)
uses the factorization A = L*D*L**H to compute the solution to a complex system of linear equations A*X = B, where A is an N-by-N Hermitian positive definite tridiagonal matrix and X and B are N-by-NRHS matrices
zpttrf(l), ZPTTRF(l)
computes the L*D*L(aq factorization of a complex Hermitian positive definite tridiagonal matrix A
zpttrs(l), ZPTTRS(l)
solves a tridiagonal system of the form A * X = B using the factorization A = U(aq*D*U or A = L*D*L(aq computed by ZPTTRF
zptts2(l), ZPTTS2(l)
solves a tridiagonal system of the form A * X = B using the factorization A = U(aq*D*U or A = L*D*L(aq computed by ZPTTRF
zspcon(l), ZSPCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a complex symmetric packed matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by ZSPTRF
zspsvx(l), ZSPSVX(l)
uses the diagonal pivoting factorization A = U*D*U**T or A = L*D*L**T to compute the solution to a complex system of linear equations A * X = B, where A is an N-by-N symmetric matrix stored in packed format and X and B are N-by-NRHS matrices
zsptrf(l), ZSPTRF(l)
computes the factorization of a complex symmetric matrix A stored in packed format using the Bunch-Kaufman diagonal pivoting method
zsptri(l), ZSPTRI(l)
computes the inverse of a complex symmetric indefinite matrix A in packed storage using the factorization A = U*D*U**T or A = L*D*L**T computed by ZSPTRF
zsptrs(l), ZSPTRS(l)
solves a system of linear equations A*X = B with a complex symmetric matrix A stored in packed format using the factorization A = U*D*U**T or A = L*D*L**T computed by ZSPTRF
zsycon(l), ZSYCON(l)
estimates the reciprocal of the condition number (in the 1-norm) of a complex symmetric matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by ZSYTRF
zsysvx(l), ZSYSVX(l)
uses the diagonal pivoting factorization to compute the solution to a complex system of linear equations A * X = B,
zsysvxx(l), ZSYSVXX(l)
ZSYSVXX use the diagonal pivoting factorization to compute the solution to a complex*16 system of linear equations A * X = B, where A is an N-by-N symmetric matrix and X and B are N-by-NRHS matrices
zsytf2(l), ZSYTF2(l)
computes the factorization of a complex symmetric matrix A using the Bunch-Kaufman diagonal pivoting method
zsytrf(l), ZSYTRF(l)
computes the factorization of a complex symmetric matrix A using the Bunch-Kaufman diagonal pivoting method
zsytri(l), ZSYTRI(l)
computes the inverse of a complex symmetric indefinite matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by ZSYTRF
zsytrs(l), ZSYTRS(l)
solves a system of linear equations A*X = B with a complex symmetric matrix A using the factorization A = U*D*U**T or A = L*D*L**T computed by ZSYTRF
ztrexc(l), ZTREXC(l)
reorders the Schur factorization of a complex matrix A = Q*T*Q**H, so that the diagonal element of T with row index IFST is moved to row ILST
ztrsen(l), ZTRSEN(l)
reorders the Schur factorization of a complex matrix A = Q*T*Q**H, so that a selected cluster of eigenvalues appears in the leading positions on the diagonal of the upper triangular matrix T, and the leading columns of Q form an orthonormal basis of the corresponding right invariant subspace
Ace::Graphics::GlyphFactory(3)
Create Ace::Graphics::Glyphs
Apache2::SiteControl::ManagerFactory(3)
An abstract base class to use as a pattern for custom PermissionManager production
Apache2::SiteControl::UserFactory(3)
User factory/persistence
Badger::Factory(3)
base class factory module
Badger::Factory::Class(3)
class module for Badger::Factory sub-classes
Bio::Annotation::AnnotationFactory(3)
Instantiates a new Bio::AnnotationI (or derived class) through a factory
Bio::Cluster::ClusterFactory(3)
Instantiates a new Bio::ClusterI (or derived class) through a factory
Bio::DB::TFBS(3)
Access to a Transcription Factor Binding Site database
Bio::Factory::AnalysisI(3)
An interface to analysis tool factory
Bio::Factory::ApplicationFactoryI(3)
Interface class for Application Factories
Bio::Factory::DriverFactory(3)
Base class for factory classes loading drivers
Bio::Factory::EMBOSS(3)
EMBOSS application factory class
Bio::Factory::FTLocationFactory(3)
A FeatureTable Location Parser
Bio::Factory::LocationFactoryI(3)
A factory interface for generating locations from a string
Bio::Factory::MapFactoryI(3)
A Factory for getting markers
Bio::Factory::ObjectBuilderI(3)
Interface for an object builder
Bio::Factory::ObjectFactory(3)
Instantiates a new Bio::Root::RootI (or derived class) through a factory
Bio::Factory::ObjectFactoryI(3)
A General object creator factory
Bio::Factory::SeqAnalysisParserFactory(3)
class capable of creating SeqAnalysisParserI compliant parsers
Bio::Factory::SeqAnalysisParserFactoryI(3)
interface describing objects capable of creating SeqAnalysisParserI compliant parsers
Bio::Factory::SequenceFactoryI(3)
This interface allows for generic building of sequences in factories which create sequences (like SeqIO)
Bio::Factory::SequenceProcessorI(3)
Interface for chained sequence processing algorithms
Bio::Factory::SequenceStreamI(3)
Interface describing the basics of a Sequence Stream
Bio::Factory::TreeFactoryI(3)
Factory Interface for getting and writing trees from/to a data stream
Bio::Graphics::Glyph::Factory(3)
Factory for Bio::Graphics::Glyph objects
Bio::MAGETAB::Factor(3)
MAGE-TAB experimental factor class
Bio::MAGETAB::FactorValue(3)
MAGE-TAB experimental factor class
Bio::Map::TranscriptionFactor(3)
A transcription factor modelled as a mappable element
Bio::MapIO(3)
A Map Factory object
Bio::Matrix::IO(3)
A factory for Matrix parsing
Bio::Ontology::RelationshipFactory(3)
Instantiates a new Bio::Ontology::RelationshipI (or derived class) through a factory
Bio::Ontology::TermFactory(3)
Instantiates a new Bio::Ontology::TermI (or derived class) through a factory
Bio::OntologyIO(3)
Parser factory for Ontology formats
Bio::Phylo::Factory(3)
Creator of objects, reduces hardcoded class names in code
Bio::PhyloNetwork::Factory(3)
Module to sequentially generate Phylogenetic Networks
Bio::PhyloNetwork::FactoryX(3)
Module to sequentially generate Phylogenetic Networks
Bio::PhyloNetwork::RandomFactory(3)
Module to generate random Phylogenetic Networks
Bio::PhyloNetwork::TreeFactory(3)
Module to sequentially generate Phylogenetic Trees
Bio::PhyloNetwork::TreeFactoryMulti(3)
Module to sequentially generate Phylogenetic Trees
Bio::PhyloNetwork::TreeFactoryX(3)
Module to sequentially generate Phylogenetic Trees
Bio::PopGen::Simulation::Coalescent(3)
A Coalescent simulation factory
Bio::Search::HSP::HSPFactory(3)
A factory to create Bio::Search::HSP::HSPI objects
Bio::Search::Hit::HitFactory(3)
A factory to create Bio::Search::Hit::HitI objects
Bio::Search::Result::ResultFactory(3)
A factory to create Bio::Search::Result::ResultI objects
Bio::Seq::SeqFactory(3)
Instantiates a new Bio::PrimarySeqI (or derived class) through a factory
Bio::Seq::SeqFastaSpeedFactory(3)
Instantiates a new Bio::PrimarySeqI (or derived class) through a factory
Bio::SeqEvolution::Factory(3)
Factory object to instantiate sequence evolving classes
Bio::Taxonomy::FactoryI(3)
interface to define how to access NCBI Taxonoy
Bio::Tools::AlignFactory(3)
Base object for alignment factories
Bio::Tools::Run::AnalysisFactory(3)
A directory of analysis tools
Bio::Tools::Run::AnalysisFactory::soap(3)
A SOAP-based access to the list of analysis tools
Bio::Tree::DistanceFactory(3)
Construct a tree using distance based methods
Bio::Tree::RandomFactory(3)
TreeFactory for generating Random Trees
CSS::SAC::ConditionFactory(3)
the default ConditionFactory
CSS::SAC::SelectorFactory(3)
the default SelectorFactory
Catalyst::Helper::Model::Factory(3)
helper for the incredibly lazy
Catalyst::Helper::Model::Factory::PerRequest(3)
helper for the incredibly lazy
Catalyst::Model::Factory(3)
use a plain class as a Catalyst model, instantiating it every time it is requested
Catalyst::Model::Factory::PerRequest(3)
use a plain class as a Catalyst model, instantiating it once per Catalyst request
Class::Factory(3)
Base class for dynamic factory classes
Class::Factory::Util(3)
Provide utility methods for factory classes
Class::MixinFactory(3)
Class Factory with Selection of Mixins
Class::MixinFactory::Changes(3)
Revision history for Class::MixinFactory
Class::MixinFactory::Factory(3)
Class Factory with Selection of Mixins
Class::MixinFactory::HasAFactory(3)
Delegates to a Factory
Class::MixinFactory::InsideOutAttr(3)
Method maker for inside out data
Class::MixinFactory::NEXT(3)
Superclass method redispatch for mixins
Class::MixinFactory::ReadMe(3)
About the Mixin Class Factory
Crypt::OpenPGP::Cipher(3)
PGP symmetric cipher factory
Crypt::OpenPGP::Digest(3)
PGP message digest factory
Crypt::OpenPGP::Key(3)
OpenPGP key factory
Crypt::OpenPGP::PacketFactory(3)
Parse and save PGP packet streams
Crypt::Random::Source::Factory(3)
Load and instantiate sources of random data
DBIx::SQLEngine::Record::Class(3)
Factory for Record Classes
Data::FormValidator::ConstraintsFactory(3)
Module to create constraints for HTML::FormValidator
DateTime::TimeZone(3)
Time zone object base class and factory
Devel::Refactor(3)
Perl extension for refactoring Perl code
FCGI::Client::RecordFactory(3)
FCGI record factory
Forest::Tree::Constructor(3)
An abstract role for tree factories
Games::LMSolve(3)
base class for LM-Solve solvers factories
Genezzo::PushHash::hph(3), Genezzo::PushHash::hph.pm(3)
an impure virtual class module that defines a *hierarchical* "push hash", a hash that generates its own unique key for each value. Values are "pushed" into the hash, similar to pushing into an array. Hierarchical pushhashes must be supplied with a factory method which manufactures additional pushhashes as necessary
Gtk2::Ex::FormFactory(3)
Makes building complex GUI's easy
Gtk2::Ex::FormFactory::Button(3)
A Button in a FormFactory framework
Gtk2::Ex::FormFactory::CheckButton(3)
A CheckButton in a FormFactory framework
Gtk2::Ex::FormFactory::CheckButtonGroup(3)
A group of checkbuttons
Gtk2::Ex::FormFactory::Combo(3)
A Combo in a FormFactory framework
Gtk2::Ex::FormFactory::Container(3)
A container in a FormFactory framework
Gtk2::Ex::FormFactory::Context(3)
Context in a FormFactory framework
Gtk2::Ex::FormFactory::DialogButtons(3)
Standard Ok, Apply, Cancel Buttons
Gtk2::Ex::FormFactory::Entry(3)
An Entry in a FormFactory framework
Gtk2::Ex::FormFactory::ExecFlow(3)
Display a Event::ExecFlow job plan
Gtk2::Ex::FormFactory::Expander(3)
An Expander in a FormFactory framework
Gtk2::Ex::FormFactory::Form(3)
A Form in a FormFactory framework
Gtk2::Ex::FormFactory::GtkWidget(3)
Wrap arbitrary Gtk widgets
Gtk2::Ex::FormFactory::HBox(3)
A HBox in a FormFactory framework
Gtk2::Ex::FormFactory::HPaned(3)
A HPaned container in a FormFactory framework
Gtk2::Ex::FormFactory::HSeparator(3)
A HSeparator in a FormFactory framework
Gtk2::Ex::FormFactory::Image(3)
An Image in a FormFactory framework
Gtk2::Ex::FormFactory::Intro(3)
Introduction into the FormFactory framework
Gtk2::Ex::FormFactory::Label(3)
A Label in a FormFactory framework
Gtk2::Ex::FormFactory::Layout(3)
Do layout in a FormFactory framework
Gtk2::Ex::FormFactory::List(3)
A List in a FormFactory framework
Gtk2::Ex::FormFactory::Loader(3)
Dynamic loading of FormFactory modules
Gtk2::Ex::FormFactory::Menu(3)
A Menu in a FormFactory framework
Gtk2::Ex::FormFactory::Notebook(3)
A Notebook in a FormFactory framework
Gtk2::Ex::FormFactory::Popup(3)
A Popup in a FormFactory framework
Gtk2::Ex::FormFactory::ProgressBar(3)
A ProgressBar in a FormFactory framework
Gtk2::Ex::FormFactory::Proxy(3)
Proxy class for application objects
Gtk2::Ex::FormFactory::ProxyBuffered(3)
Buffering object proxy
Gtk2::Ex::FormFactory::RadioButton(3)
A RadioButton in a FormFactory framework
Gtk2::Ex::FormFactory::Rules(3)
Rule checking in a FormFactory framework
Gtk2::Ex::FormFactory::Table(3)
Complex table layouts made easy
Gtk2::Ex::FormFactory::TextView(3)
A TextView in a FormFactory framework
Gtk2::Ex::FormFactory::Timestamp(3)
Enter a valid timestamp
Gtk2::Ex::FormFactory::ToggleButton(3)
A ToggleButton in a FormFactory framework
Gtk2::Ex::FormFactory::VBox(3)
A VBox in a FormFactory framework
Gtk2::Ex::FormFactory::VPaned(3)
A VPaned container in a FormFactory framework
Gtk2::Ex::FormFactory::VSeparator(3)
A VSeparator in a FormFactory framework
Gtk2::Ex::FormFactory::Widget(3)
Base class for all FormFactory Widgets
Gtk2::Ex::FormFactory::Window(3)
A Window in a FormFactory framework
Gtk2::Ex::FormFactory::YesNo(3)
Yes/No radio buttons in a FormFactory framework
Gtk2::ImageView::Zoom(3)
Functions for dealing with zoom factors
Gtk2::SimpleMenu(3)
A simple interface to Gtk2's ItemFactory for creating application menus
Jabber::NodeFactory(3)
Simple XML Node Factory for Jabber
Math::SymbolicX::ParserExtensionFactory(3)
Generate parser extensions
Metabase::Resource(3)
factory class for Metabase resource descriptors
Mobile::UserAgentFactory(3)
Instantiates and caches Mobile::UserAgent objects
Net::Radius::Server::Base(3)
Base definitions and utility methods and factories
OpenXPKI::Workflow::Factory(3), Header "Name" OpenXPKI::Workflow::Factory(3)
OpenXPKI specific workflow factory
POE::Wheel::SocketFactory(3)
non-blocking socket creation
Perl::Critic::Policy::Subroutines::ProhibitExcessComplexity(3)
Minimize complexity by factoring code into smaller subroutines
Perl::Critic::PolicyFactory(3)
Instantiates Policy objects
Plagger::Cookies(3)
cookie_jar factory class
Protocol::XMLRPC::ValueFactory(3)
value objects factory
RDF::Core::NodeFactory(3)
produces literals and resources, generates labels for anonymous resources
RDFStore::NodeFactory(3)
An RDF node factory implementation
RPC::Simple::Factory(3)
Perl extension for creating RPC client
RPC::XML::Parser(3)
Interface for parsers created by RPC::XML::ParserFactory
RPC::XML::ParserFactory(3)
A factory class for RPC::XML::Parser objects
ResourcePool::Factory(3)
A factory to create ResourcePool::Resource objects
ResourcePool::Factory::DBI(3)
A DBI Factory for ResourcePool
ResourcePool::Factory::Net::LDAP(3)
A Net::LDAP Factory for ResourcePool
ResourcePool::Factory::SOAP::Lite(3)
A ResourcePool. Factory for SOAP::Lites
SOAP::WSDL::Client::Base(3)
Factory class for WSDL-based SOAP access
SOAP::WSDL::Factory::Deserializer(3)
Factory for retrieving Deserializer objects
SOAP::WSDL::Factory::Generator(3), SOAP::WSDL::Factory:Generator(3)
Factory for retrieving generator objects
SOAP::WSDL::Factory::Serializer(3)
Factory for retrieving serializer objects
SOAP::WSDL::Factory::Transport(3)
Factory for retrieving transport objects
SPOPS::ClassFactory(3)
Create SPOPS classes from configuration and code
SPOPS::ClassFactory::DBI(3)
Define additional configuration methods
SPOPS::ClassFactory::DefaultBehavior(3)
Default configuration methods called from SPOPS.pm
SPOPS::ClassFactory::LDAP(3)
Create relationships among LDAP objects
SPOPS::Import(3)
Factory and parent for importing SPOPS objects
SPOPS::Import::DBI::TableTransform(3)
Factory class for database-specific transformations
SPOPS::Tool::DBI::DiscoverField(3)
SPOPS::ClassFactory rule implementing autofield discovery
SQL::Statement::TermFactory(3)
Factory for SQL::Statement::Term instances
SRU::Request(3)
Factories for creating SRU request objects
SRU::Response(3)
A factory for creating SRU response objects
TAP::Parser::IteratorFactory(3)
Figures out which SourceHandler objects to use for a given Source
TAP::Parser::ResultFactory(3)
Factory for creating TAP::Parser output objects
Template::Config(3)
Factory module for instantiating other TT2 modules
Test::TempDir::Factory(3)
A factory for creating Test::TempDir::Handle objects
Text::Diff3::Factory(3)
factory for component used by Text::Diff3 modules
Text::Emoticon(3)
Factory class for Yahoo! and MSN emoticons
Tree::Binary::VisitorFactory(3)
A factory object for dispensing Visitor objects
Tree::Simple::VisitorFactory(3)
A factory object for dispensing Visitor objects
WebService::GData::Serialize(3)
Factory class that loads the proper serialize package
Workflow::Factory(3)
Generates new workflow and supporting objects
XML::Grove::Factory(3)
simplify creation of XML::Grove objects
XML::SAX::ParserFactory(3)
Obtain a SAX parser
XML::SAX::PurePerl::Reader(3), XML::Parser::PurePerl::Reader(3)
Abstract Reader factory class
XML::Validate(3)
an XML validator factory
CosEventDomainAdmin_EventDomainFactory(3)
This module implements an Event Domain Factory interface, which is used to create new Event Domain instances
CosNotifyChannelAdmin_EventChannelFactory(3)
This module implements the OMG CosNotifyChannelAdmin::EventChannelFactory interface
CosNotifyFilter_FilterFactory(3)
This module implements the OMG CosNotifyFilter::FilterFactory interface
CosPropertyService_PropertySetDefFactory(3)
This module implements the OMG CosPropertyService::PropertySetDefFactory interface
CosPropertyService_PropertySetFactory(3)
This module implements the OMG CosPropertyService::PropertySetFactory interface
CosTransactions_TransactionFactory(3)
This module implements the OMG CosTransactions::TransactionFactory interface
TAP::Parser::IteratorFactory(3)
Figures out which SourceHandler objects to use for a given Source
TAP::Parser::ResultFactory(3)
Factory for creating TAP::Parser output objects
factor(1)
factor numbers
factor(1), primes(1)
factor a number, generate large primes
mp(3), mpsetminbits(3), mpnew(3), mpfree(3), mpbits(3), mpnorm(3), mpcopy(3), mpassign(3), mprand(3), strtomp(3), mpfmt(3), mptoa(3), betomp(3), mptobe(3), letomp(3), mptole(3), mptoui(3), uitomp(3), mptoi(3), itomp(3), uvtomp(3), mptouv(3), vtomp(3), mptov(3), mpdigdiv(3), mpadd(3), mpsub(3), mpleft(3), mpright(3), mpmul(3), mpexp(3), mpmod(3), mpdiv(3), mpfactorial(3), mpcmp(3), mpextendedgcd(3), mpinvert(3), mpsignif(3), mplowbits0(3), mpvecdigmuladd(3), mpvecdigmulsub(3), mpvecadd(3), mpvecsub(3), mpveccmp(3), mpvecmul(3), mpmagcmp(3), mpmagadd(3), mpmagsub(3), crtpre(3), crtin(3), crtout(3), crtprefree(3), crtresfree(3)
extended precision arithmetic
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