- PDL::Slices
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PDL::Slices -- Indexing, slicing, and dicing
- PDL::State
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A package to keep track of plotting commands
- PDL::Tests
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tests for some PP features
- PDL::Transform
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Coordinate transforms, image warping, and N-D functions
- PDL::Transform::Cartography
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Useful cartographic projections
- PDL::Types
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define fundamental PDL Datatypes
- PDL::Ufunc
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primitive ufunc operations for pdl
- pdlabad
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take as input the values computed by PDLAMCH for underflow and overflow, and returns the square root of each of these values if the log of LARGE is sufficiently large
- pdlabrd
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reduce the first NB rows and columns of a real general M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1) to upper or lower bidiagonal form by an orthogonal transformation Q' * A * P,
- pdlacon
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estimate the 1-norm of a square, real distributed matrix A
- pdlaconsb
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look for two consecutive small subdiagonal elements by seeing the effect of starting a double shift QR iteration given by H44, H33, & H43H34 and see if this would make a subdiagonal negligible
- pdlacp2
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copie all or part of a distributed matrix A to another distributed matrix B
- pdlacp3
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i an auxiliary routine that copies from a global parallel array into a local replicated array or vise versa
- pdlacpy
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copie all or part of a distributed matrix A to another distributed matrix B
- pdlaevswp
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move the eigenvectors (potentially unsorted) from where they are computed, to a ScaLAPACK standard block cyclic array, sorted so that the corresponding eigenvalues are sorted
- pdlahqr
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i an auxiliary routine used to find the Schur decomposition and or eigenvalues of a matrix already in Hessenberg form from cols ILO to IHI
- pdlahrd
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reduce the first NB columns of a real general N-by-(N-K+1) distributed matrix A(IA:IA+N-1,JA:JA+N-K) so that elements below the k-th subdiagonal are zero
- pdlamch
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determine double precision machine parameters
- pdlange
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return the value of the one norm, or the Frobenius norm,
- pdlanhs
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return the value of the one norm, or the Frobenius norm,
- pdlansy
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return the value of the one norm, or the Frobenius norm,
- pdlantr
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return the value of the one norm, or the Frobenius norm,
- pdlapiv
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applie either P (permutation matrix indicated by IPIV) or inv( P ) to a general M-by-N distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1), resulting in row or column pivoting
- pdlapv2
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applie either P (permutation matrix indicated by IPIV) or inv( P ) to a M-by-N distributed matrix sub( A ) denoting A(IA:IA+M-1,JA:JA+N-1), resulting in row or column pivoting
- pdlaqge
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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
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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
- pdlared1d
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redistribute a 1D array It assumes that the input array, BYCOL, is distributed across rows and that all process column contain the same copy of BYCOL
- pdlared2d
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redistribute a 1D array It assumes that the input array, BYROW, is distributed across columns and that all process rows contain the same copy of BYROW
- pdlarf
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applie a real elementary reflector Q (or Q**T) to a real M-by-N distributed matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1), from either the left or the right
- pdlarfb
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applie a real block reflector Q or its transpose Q**T to a real distributed M-by-N matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1)
- pdlarfg
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generate a real elementary reflector H of order n, such that H * sub( X ) = H * ( x(iax,jax) ) = ( alpha ), H' * H = I
- pdlarft
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form the triangular factor T of a real block reflector H of order n, which is defined as a product of k elementary reflectors
- pdlarz
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applie a real elementary reflector Q (or Q**T) to a real M-by-N distributed matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1), from either the left or the right
- pdlarzb
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applie a real block reflector Q or its transpose Q**T to a real distributed M-by-N matrix sub( C ) = C(IC:IC+M-1,JC:JC+N-1)
- pdlarzt
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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
- pdlascl
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multiplie the M-by-N real distributed matrix sub( A ) denoting A(IA:IA+M-1,JA:JA+N-1) by the real scalar CTO/CFROM
- pdlase2
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initialize an M-by-N distributed matrix sub( A ) denoting A(IA:IA+M-1,JA:JA+N-1) to BETA on the diagonal and ALPHA on the offdiagonals
- pdlaset
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initialize an M-by-N distributed matrix sub( A ) denoting A(IA:IA+M-1,JA:JA+N-1) to BETA on the diagonal and ALPHA on the offdiagonals
- pdlasmsub
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look for a small subdiagonal element from the bottom of the matrix that it can safely set to zero
- pdlassq
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return the values scl and smsq such that ( scl**2 )*smsq = x( 1 )**2 +...+ x( n )**2 + ( scale**2 )*sumsq,
- pdlaswp
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perform a series of row or column interchanges on the distributed matrix sub( A ) = A(IA:IA+M-1,JA:JA+N-1)
- pdlatra
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compute the trace of an N-by-N distributed matrix sub( A ) denoting A( IA:IA+N-1, JA:JA+N-1 )
- pdlatrd
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reduce NB rows and columns of a real symmetric distributed matrix sub( A ) = A(IA:IA+N-1,JA:JA+N-1) to symmetric tridiagonal form by an orthogonal similarity transformation Q' * sub( A ) * Q,
- pdlatrs
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solve a triangular system
- pdlatrz
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reduce the M-by-N ( M<=N ) real upper trapezoidal matrix sub( A ) = [ A(IA:IA+M-1,JA:JA+M-1) A(IA:IA+M-1,JA+N-L:JA+N-1) ] to upper triangular form by means of orthogonal transformations
- pdlauu2
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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
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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)
- pdlawil
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get the transform given by H44,H33, & H43H34 into V starting at row M
- Pdlpp
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Write PDL Subroutines inline with PDL::PP
- pdorg2l
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generate an M-by-N real distributed matrix Q denoting A(IA:IA+M-1,JA:JA+N-1) with orthonormal columns, which is defined as the last N columns of a product of K elementary reflectors of order M Q = H(k)