/ 
PDL-LinearAlgebra-0.42
River stage one • 2 direct dependents • 3 total dependents
/ PDL::LinearAlgebra::Trans

NAME

PDL::LinearAlgebra::Trans - Linear Algebra based transcendental functions for PDL

SYNOPSIS

use PDL::LinearAlgebra::Trans;

$a = random (100,100);
$sqrt = msqrt($a);

DESCRIPTION

This module provides some transcendental functions for matrices. Moreover it provides sec, asec, sech, asech, cot, acot, acoth, coth, csc, acsc, csch, acsch. Beware, importing this module will overwrite the hidden PDL routine sec. If you need to call it specify its origin module : PDL::Basic::sec(args)

FUNCTIONS

geexp

Signature: ([io,phys]A(n,n);int deg();scale();[io]trace();int [o]ns();int [o]info(); int [t]ipiv(n); [t]wsp(wspn=CALC(3*$SIZE(n)*$SIZE(n))))

Computes exp(t*A), the matrix exponential of a general matrix, using the irreducible rational Pade approximation to the exponential function exp(x) = r(x) = (+/-)( I + 2*(q(x)/p(x)) ), combined with scaling-and-squaring and optionally normalization of the trace. The algorithm is described in Roger B. Sidje (rbs.uq.edu.au) "EXPOKIT: Software Package for Computing Matrix Exponentials". ACM - Transactions On Mathematical Software, 24(1):130-156, 1998

     A:		On input argument matrix. On output exp(t*A).
		Use Fortran storage type.

     deg:	the degre of the diagonal Pade to be used. 
                a value of 6 is generally satisfactory. 

     scale:	time-scale (can be < 0). 

     trace:	on input, boolean value indicating whether or not perform
		a trace normalization. On output value used.

     ns:	on output number of scaling-squaring used. 

     info:	exit flag.
                      0 - no problem 
                     > 0 - Singularity in LU factorization when solving 
		     Pade approximation
 = random(5,5);
 = pdl(1);
->t->geexp(6,1,, ( = null), ( = null));

geexp does not process bad values. It will set the bad-value flag of all output ndarrays if the flag is set for any of the input ndarrays.

cgeexp

Signature: (complex [io,phys]A(n,n);int deg();scale();int trace();int [o]ns();int [o]info(); int [t] ipiv(n))

Complex version of geexp. The value used for trace normalization is not returned. The algorithm is described in Roger B. Sidje (rbs@maths.uq.edu.au) "EXPOKIT: Software Package for Computing Matrix Exponentials". ACM - Transactions On Mathematical Software, 24(1):130-156, 1998

ctrsqrt

Signature: (complex [io,phys]A(n,n);int uplo();complex [phys,o] B(n,n);int [o]info())

Root square of complex triangular matrix. Uses a recurrence of Bj�rck and Hammarling. (See Nicholas J. Higham. A new sqrtm for MATLAB. Numerical Analysis Report No. 336, Manchester Centre for Computational Mathematics, Manchester, England, January 1999. It's available at http://www.ma.man.ac.uk/~higham/pap-mf.html) If uplo is true, A is lower triangular.

ctrfun

Signature: (complex [io]A(n,n);int uplo();complex [o] B(n,n);int [o]info(); complex [t]diag(n);SV* func)

Apply an arbitrary function to a complex triangular matrix. Uses a recurrence of Parlett. If uplo is true, A is lower triangular.

mlog

Return matrix logarithm of a square matrix.

PDL = mlog(PDL(A))
my $a = random(10,10);
my $log = mlog($a);

msqrt

Return matrix square root (principal) of a square matrix.

PDL = msqrt(PDL(A))
my $a = random(10,10);
my $sqrt = msqrt($a);

mexp

Return matrix exponential of a square matrix.

PDL = mexp(PDL(A))
my $a = random(10,10);
my $exp = mexp($a);

mpow

Return matrix power of a square matrix.

PDL = mpow(PDL(A), SCALAR(exponent))
my $a = random(10,10);
my $powered = mpow($a,2.5);

mcos

Return matrix cosine of a square matrix.

PDL = mcos(PDL(A))
my $a = random(10,10);
my $cos = mcos($a);

macos

Return matrix inverse cosine of a square matrix.

PDL = macos(PDL(A))
my $a = random(10,10);
my $acos = macos($a);

msin

Return matrix sine of a square matrix.

PDL = msin(PDL(A))
my $a = random(10,10);
my $sin = msin($a);

masin

Return matrix inverse sine of a square matrix.

PDL = masin(PDL(A))
my $a = random(10,10);
my $asin = masin($a);

mtan

Return matrix tangent of a square matrix.

PDL = mtan(PDL(A))
my $a = random(10,10);
my $tan = mtan($a);

matan

Return matrix inverse tangent of a square matrix.

PDL = matan(PDL(A))
my $a = random(10,10);
my $atan = matan($a);

mcot

Return matrix cotangent of a square matrix.

PDL = mcot(PDL(A))
my $a = random(10,10);
my $cot = mcot($a);

macot

Return matrix inverse cotangent of a square matrix.

PDL = macot(PDL(A))
my $a = random(10,10);
my $acot = macot($a);

msec

Return matrix secant of a square matrix.

PDL = msec(PDL(A))
my $a = random(10,10);
my $sec = msec($a);

masec

Return matrix inverse secant of a square matrix.

PDL = masec(PDL(A))
my $a = random(10,10);
my $asec = masec($a);

mcsc

Return matrix cosecant of a square matrix.

PDL = mcsc(PDL(A))
my $a = random(10,10);
my $csc = mcsc($a);

macsc

Return matrix inverse cosecant of a square matrix.

PDL = macsc(PDL(A))
my $a = random(10,10);
my $acsc = macsc($a);

mcosh

Return matrix hyperbolic cosine of a square matrix.

PDL = mcosh(PDL(A))
my $a = random(10,10);
my $cos = mcosh($a);

macosh

Return matrix hyperbolic inverse cosine of a square matrix.

PDL = macosh(PDL(A))
my $a = random(10,10);
my $acos = macosh($a);

msinh

Return matrix hyperbolic sine of a square matrix.

PDL = msinh(PDL(A))
my $a = random(10,10);
my $sinh = msinh($a);

masinh

Return matrix hyperbolic inverse sine of a square matrix.

PDL = masinh(PDL(A))
my $a = random(10,10);
my $asinh = masinh($a);

mtanh

Return matrix hyperbolic tangent of a square matrix.

PDL = mtanh(PDL(A))
my $a = random(10,10);
my $tanh = mtanh($a);

matanh

Return matrix hyperbolic inverse tangent of a square matrix.

PDL = matanh(PDL(A))
my $a = random(10,10);
my $atanh = matanh($a);

mcoth

Return matrix hyperbolic cotangent of a square matrix.

PDL = mcoth(PDL(A))
my $a = random(10,10);
my $coth = mcoth($a);

macoth

Return matrix hyperbolic inverse cotangent of a square matrix.

PDL = macoth(PDL(A))
my $a = random(10,10);
my $acoth = macoth($a);

msech

Return matrix hyperbolic secant of a square matrix.

PDL = msech(PDL(A))
my $a = random(10,10);
my $sech = msech($a);

masech

Return matrix hyperbolic inverse secant of a square matrix.

PDL = masech(PDL(A))
my $a = random(10,10);
my $asech = masech($a);

mcsch

Return matrix hyperbolic cosecant of a square matrix.

PDL = mcsch(PDL(A))
my $a = random(10,10);
my $csch = mcsch($a);

macsch

Return matrix hyperbolic inverse cosecant of a square matrix.

PDL = macsch(PDL(A))
my $a = random(10,10);
my $acsch = macsch($a);

mfun

Return matrix function of second argument of a square matrix. Function will be applied on a complex ndarray.

PDL = mfun(PDL(A),'cos')
 my $a = random(10,10);
 my $fun = mfun($a,'cos');
 sub sinbycos2{
	$_[0]->set_inplace(0);
	$_[0] .= $_[0]->Csin/$_[0]->Ccos**2;
 }
 # Try diagonalization
 $fun = mfun($a, \&sinbycos2,1);
 # Now try Schur/Parlett
 $fun = mfun($a, \&sinbycos2);
 # Now with function.
 scalar msolve($a->mcos->mpow(2), $a->msin);

TODO

Improve error return and check singularity. Improve (msqrt,mlog) / r2C

AUTHOR

Copyright (C) Gr�gory Vanuxem 2005-2018.

This library is free software; you can redistribute it and/or modify it under the terms of the Perl Artistic License as in the file Artistic_2 in this distribution.