# Pages du manuel Linux : Fonctions des bibliothèques

cheevx
compute selected eigenvalues and, optionally, eigenvectors of a complex Hermitian matrix A
chegs2
reduce a complex Hermitian-definite generalized eigenproblem to standard form
chegst
reduce a complex Hermitian-definite generalized eigenproblem to standard form
chegv
compute all the eigenvalues, and optionally, the eigenvectors of a complex generalized Hermitian-definite eigenproblem, of the form A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x
chegvd
compute all the eigenvalues, and optionally, the eigenvectors of a complex generalized Hermitian-definite eigenproblem, of the form A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x
chegvx
compute selected eigenvalues, and optionally, eigenvectors of a complex generalized Hermitian-definite eigenproblem, of the form A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x
Chemistry::Elements
Perl extension for working with Chemical Elements
chemm
perform one of the matrix-matrix operations C := alpha*A*B + beta*C,
chemv
perform the matrix-vector operation y := alpha*A*x + beta*y,
cher
perform the hermitian rank 1 operation A := alpha*x*conjg( x' ) + A,
cher2
perform the hermitian rank 2 operation A := alpha*x*conjg( y' ) + conjg( alpha )*y*conjg( x' ) + A,
cher2k
perform one of the hermitian rank 2k operations C := alpha*A*conjg( B' ) + conjg( alpha )*B*conjg( A' ) + beta*C,
cherfs
improve the computed solution to a system of linear equations when the coefficient matrix is Hermitian indefinite, and provides error bounds and backward error estimates for the solution
cherk
perform one of the hermitian rank k operations C := alpha*A*conjg( A' ) + beta*C,
chesv
compute the solution to a complex system of linear equations A * X = B,
chesvx
use the diagonal pivoting factorization to compute the solution to a complex system of linear equations A * X = B,
chetd2
reduce a complex Hermitian matrix A to real symmetric tridiagonal form T by a unitary similarity transformation
chetf2
compute the factorization of a complex Hermitian matrix A using the Bunch-Kaufman diagonal pivoting method
chetrd
reduce a complex Hermitian matrix A to real symmetric tridiagonal form T by a unitary similarity transformation
chetrf
compute the factorization of a complex Hermitian matrix A using the Bunch-Kaufman diagonal pivoting method
chetri
compute 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
solve 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
chgeqz
implement a single-shift version of the QZ method for finding the generalized eigenvalues w(i)=ALPHA(i)/BETA(i) of the equation det( A - w(i) B ) = 0 If JOB='S', then the pair (A,B) is simultaneously reduced to Schur form (i.e., A and B are both upper triangular) by applying one unitary tranformation (usually called Q) on the left and another (usually called Z) on the right
Chipcard::PCSC
Chipcard::PCSC::Card
Smarcard communication library
chmod
change mode of a file
ChnlStack
stack an I/O channel on top of another, and undo it
chooseColor
pops up a dialog box for the user to select a color.
chooseDirectory
pops up a dialog box for the user to select a directory.
chown
change owner and group of a file
chpcon
estimate 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
chpev
compute all the eigenvalues and, optionally, eigenvectors of a complex Hermitian matrix in packed storage
chpevd
compute all the eigenvalues and, optionally, eigenvectors of a complex Hermitian matrix A in packed storage
chpevx
compute selected eigenvalues and, optionally, eigenvectors of a complex Hermitian matrix A in packed storage
chpgst
reduce a complex Hermitian-definite generalized eigenproblem to standard form, using packed storage
chpgv
compute all the eigenvalues and, optionally, the eigenvectors of a complex generalized Hermitian-definite eigenproblem, of the form A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x
chpgvd
compute all the eigenvalues and, optionally, the eigenvectors of a complex generalized Hermitian-definite eigenproblem, of the form A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x
chpgvx
compute selected eigenvalues and, optionally, eigenvectors of a complex generalized Hermitian-definite eigenproblem, of the form A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x
chpmv
perform the matrix-vector operation y := alpha*A*x + beta*y,
chpr
perform the hermitian rank 1 operation A := alpha*x*conjg( x' ) + A,
chpr2
perform the hermitian rank 2 operation A := alpha*x*conjg( y' ) + conjg( alpha )*y*conjg( x' ) + A,
chprfs
improve the computed solution to a system of linear equations when the coefficient matrix is Hermitian indefinite and packed, and provides error bounds and backward error estimates for the solution
chpsv
compute the solution to a complex system of linear equations A * X = B,
chpsvx
use 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
chptrd
reduce a complex Hermitian matrix A stored in packed form to real symmetric tridiagonal form T by a unitary similarity transformation
chptrf
compute the factorization of a complex Hermitian packed matrix A using the Bunch-Kaufman diagonal pivoting method
chptri
compute 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
solve 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
chsein
use inverse iteration to find specified right and/or left eigenvectors of a complex upper Hessenberg matrix H
chseqr
compute the eigenvalues of a complex upper Hessenberg matrix H, and, optionally, the matrices T and Z from the Schur decomposition H = Z T Z**H, where T is an upper triangular matrix (the Schur form), and Z is the unitary matrix of Schur vectors