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NAME
Math::Polynomial::Solve - Find the roots of polynomial equations.
SYNOPSIS
use Math::Complex; # The roots may be complex numbers.
use Math::Polynomial::Solve qw(poly_roots);
my @x = poly_roots(@coefficients);
or
use Math::Complex; # The roots may be complex numbers.
use Math::Polynomial::Solve qw(poly_roots get_hessenberg set_hessenberg);
#
# Force the use of the matrix method.
#
set_hessenberg(1);
my @x = poly_roots(@coefficients);
or
use Math::Complex; # The roots may be complex numbers.
use Math::Polynomial::Solve
qw(linear_roots quadratic_roots cubic_roots quartic_roots);
# Find the roots of ax + b
my @x1 = linear_roots($a, $b);
# Find the roots of ax**2 + bx +c
my @x2 = quadratic_roots($a, $b, $c);
# Find the roots of ax**3 + bx**2 +cx + d
my @x3 = cubic_roots($a, $b, $c, $d);
# Find the roots of ax**4 + bx**3 +cx**2 + dx + e
my @x4 = quartic_roots($a, $b, $c, $d, $e);
DESCRIPTION
This package supplies a set of functions that find the roots of
polynomials. Polynomials up to the quartic may be solved directly by
numerical formulae. Polynomials of fifth and higher powers will be
solved by an iterative method, as there are no general solutions for
fifth and higher powers.
The linear, quadratic, cubic, and quartic *_roots() functions all expect
to have a non-zero value for the $a term.
If the constant term is zero then the first value returned in the list
of answers will always be zero, for all functions.
set_hessenberg()
Sets or removes the condition that forces the use of the Hessenberg
matrix regardless of the polynomial's degree. A non-zero argument forces
the use of the matrix method, a zero removes it.
get_hessenberg()
Returns 1 or 0 depending upon whether the Hessenberg matrix method is
always in use or not.
poly_roots()
A generic function that may call one of the other root-finding
functions, or a polynomial solving method using a Hessenberg matrix,
depending on the degree of the polynomial. You may force it to use the
matrix method regardless of the degree of the polynomial by calling
set_hessenberg(1). Otherwise it will use the specialized root functions
for polynomials of degree 1 to 4.
Unlike the other root-finding functions, it will check for coefficients
of zero for the highest power, and 'step down' the degree of the
polynomial to the appropriate case. Additionally, it will check for
coefficients of zero for the lowest power terms, and add zeros to its
root list before calling one of the root-finding functions. Thus it is
possible to solve a polynomial of degree higher than 4 without using the
matrix method, as long as it meets these rather specialized conditions.
linear_roots()
Here for completeness's sake more than anything else. Returns the
solution for
ax + b = 0
by returning "-b/a". This may be in either a scalar or an array context.
quadratic_roots()
Gives the roots of the quadratic equation
ax**2 + bx + c = 0
using the well-known quadratic formula. Returns a two-element list.
cubic_roots()
Gives the roots of the cubic equation
ax**3 + bx**2 + cx + d = 0
by the method described by R. W. D. Nickalls (see the Acknowledgments
section below). Returns a three-element list. The first element will
always be real. The next two values will either be both real or both
complex numbers.
quartic_roots()
Gives the roots of the quartic equation
ax**4 + bx**3 + cx**2 + dx + e = 0
using Ferrari's method (see the Acknowledgments section below). Returns
a four-element list. The first two elements will be either both real or
both complex. The next two elements will also be alike in type.
EXPORT
There are no default exports. The functions may be named in an export
list.
Acknowledgments
The cubic
The cubic is solved by the method described by R. W. D. Nickalls, "A New
Approach to solving the cubic: Cardan's solution revealed," The
Mathematical Gazette, 77, 354-359, 1993. This article is available on
several different web sites, including
and
. There is also a nice discussion of his paper at
.
Dr. Nickalls was kind enough to send me his article, with notes and
revisions, and directed me to a Matlab script that was based on that
article, written by Herman Bruyninckx, of the Dept. Mechanical Eng.,
Div. PMA, Katholieke Universiteit Leuven, Belgium. This function is an
almost direct translation of that script, and I owe Herman Bruyninckx
for creating it in the first place.
Dick Nickalls, dicknickalls@compuserve.com
Herman Bruyninckx, Herman.Bruyninckx@mech.kuleuven.ac.be, has web page
at . His matlab cubic solver
is at .
Andy Stein has written a version of cubic.m that will work with vectors.
It is included with this package in the eg directory.
The quartic
The method for quartic solution is Ferrari's, as described in the web
page Karl's Calculus Tutor at
. I also made use of some
short cuts mentioned in web page Ask Dr. Math FAQ, at
.
Quintic and higher.
Back when this module could only solve polynomials of degrees 1 through
4, Matz Kindahl, the author of Math::Polynomial, suggested the
poly_roots() function. Later on, Nick Ing-Simmons, who was working on a
perl binding to the GNU Scientific Library, sent a perl translation of
Hiroshi Murakami's Fortran implementation of the QR Hessenberg
algorithm, and it fit very well into the poly_roots() function. Quintics
and higher degree polynomials can now be solved, albeit through numeric
analysis methods.
Hiroshi Murakami's Fortran routines were at
, but do not seem to be available
from that source anymore.
He referenced the following articles:
R. S. Martin, G. Peters and J. H. Wilkinson, "The QR Algorithm for Real
Hessenberg Matrices", Numer. Math. 14, 219-231(1970).
B. N. Parlett and C. Reinsch, "Balancing a Matrix for Calculation of
Eigenvalues and Eigenvectors", Numer. Math. 13, 293-304(1969).
Alan Edelman and H. Murakami, "Polynomial Roots from Companion Matrix
Eigenvalues", Math. Comp., v64,#210, pp.763-776(1995).
For starting out, you may want to read
Numerical Recipes in C, by William Press, Brian P. Flannery, Saul A.
Teukolsky, and William T. Vetterling, Cambridge University Press.
SEE ALSO
Forsythe, George E., Michael A. Malcolm, and Cleve B. Moler (1977),
Computer Methods for Mathematical Computations, Prentice-Hall.
AUTHOR
John M. Gamble may be found at jgamble@ripco.com

NAME
Math::MatrixSparse - Perl extension for sparse matrices.
SYNOPSIS
Math::MatrixSparse is a module implementing naive sparse matrices. Its
syntax is designed to partially overlap with Math::MatrixReal where
possible and reasonable.
Basic matrix operations are present, including addition, subtraction,
scalar multiplication, matrix multiplication, transposition, and
exponentiation.
Three methods of solving systems iteratively are available, including
Jacobi, Gauss-Seidel, and Symmetric Over-Relaxation.
Real-valued matrices can be read from files in the Matrix Market and
Harwell Boeing formats, and written in the Matrix Market format. In
addition, they can be read from a given string.
Certain special types of matrices are understood, but not optimized for,
such as upper and lower triangular, diagonal, symmetric, skew-symmetric,
positive, negative, and pattern. Methods are available to determine the
properties of a given matrix.
Individual rows, columns, and diagonals of matrices can be obtained, as
can the upper and lower triangular, symmetric, skew symmetric, positive
and negative portions.
DESCRIPTION
* "use Math::MatrixSparse;"
Load the module and make its methods and operators available.
CREATION AND INPUT-OUTPUT METHODS
* "Math::MatrixSparse->new($name)"
"new Math::MatrixSparse($name)"
Creates a new empty matrix named $name, which may be undef.
* "Math::MatrixSparse->newfromstring($string,$name)"
Creates a new matrix named $name based on $string. $string is of the
pattern /(\d+)\s+(\d+)\s+(.+)\n/, where ($row, $column, $value) =
($1,$2,$3).
Example:
$matrixspec = <newfromstring($matrixspec,"MS");
$MS has four elements, (1,1), (1,2), (2,1), and (3,3), with the
values 1,2,3, and 4.
* "Math::MatrixSparse->newdiag($arrayref,$name)"
Creates a new square matrix named $name from the elements in
$arrayref. $arrayref[0] will become $matrix(1,1), etc.
* " Math::MatrixSparse->newdiagfromstring($string, $name)"
Similar to "Math::MatrixSparse->newfromstring" except that $string
is of the pattern /(\d+)\s+(.+)\n/, and ($row, $column, $value) =
($1, $1, $2).
Example:
$diagspec = <newdiagfromstring($matrixspec,"MS");
$MD has four elements, (1,1), (2,2), (20,20), and (300,300), with
the values 1, -1, 1, and -1, and is square.
* "Math::MatrixSparse->newrandom($maxrow, $maxcol, $maxentries,
$density,$name)"
Creates a new matrix of the specified size ($maxrow*$maxcol) with at
most $maxentries. If $density is between 0 and 1 (inclusive), the
expected number of entries is $maxentries*$density. If $maxentries
is undef, it is set to $maxrow*$maxcol; if $maxcol is missing, it is
set to $maxrow. If $density is missing, or outside the valid range,
it is set to one.
* "Math::MatrixSparse->newmatrixmarket($filename)"
Creates a new matrix based on data stored in the file $filename, in
Matrix Market format. See http://www.nist.gov/MatrixMarket/ for more
information on this format.
Pattern matrix data has elements set to one. Matrices flagged as
symmetric or skew symmetric have symmetrify() or skewsymmetrify()
applied.
Exits with an error if $filename cannot be read from.
* "Math::MatrixSparse->newharwellboeing($filename)"
Creates a new matrix based on data stored in the file $filename, in
Harwell-Boeing format. See
http://math.nist.gov/MatrixMarket/collections/hb.html for more
information on this format.
Pattern matrix data has elements set to one. Matrices flagged as
symmetric or skew symmetric have symmetrify() or skewsymmetrify()
applied.
Exits with an error if $filename cannot be read from.
* "$matrix->writematrixmarket($filename)"
The contents of $matrix are written, in Matrix Market format, to
$filename. It is assumed that $matrix->{rows} and $matrix->{columns}
are accurate--$matrix->sizetofit() should be called if this is not
the case. No optimizations are performed for symmetric, skew
symmetric, or pattern data, and real values are assumed.
See http://www.nist.gov/MatrixMarket/ for more information on this
format.
Exits with an error if $filename cannot be written to.
* "Math::MatrixSparse->newidentity($n,$m)"
Creates an identity matrix with $n rows and $m columns. If $m is
omitted it is assumed equal to $n.
* "print $matrix"
"$matrix->print($name)"
"$matrix->print()"
Prints the element in the matrix in the format $name($row,$colum) =
$value
Calling this as a method with an argument overrides the value in
$matrix->{name}.
INTERFACE METHODS
* "($i,$j) = &splitkey($key)"
"$key = &makekey($i,$j)"
These two routines convert a position ($i,$j) of the matrix into a
key $key. Programs that use Math::MatrixSparse should not have to
use keys at all, but if they do, they should use these routines.
GENERAL METHODS
* "$matrix2 = $matrix1->copy()"
"$matrix2 = $matrix1->copy($name)"
Returns an exact copy of $matrix1, including dimensions, name, and
special flags. If $name is given, it will be the name of $matrix2.
* "$matrix->name($name)"
Gives a name to $matrix. Useful mostly in printing. Certain methods
attempt to create useful names, but you probably want to set your
own.
* "$matrix->assign($i,$j,$value)"
Puts $value in row $i, column $j of $matrix. Updates $matrix->{row}
and $matrix->{column} if necessary. Removes or modifies special
flags when necessary.
* "$matrix->assignspecial($i,$j,$value)"
As $matrix->assign(), except that it preserves symmetry and
skew-symmetry. That is, if $matrix is marked symmetric, assigning a
value to ($i,$j) also assigns the value to ($j,$i). Also preserves
patterns.
* "$matrix->assignkey($key,$value)"
As $matrix->assign(), except $i and $j have already been combined
into $key.
* "$matrix->element($i,$j)"
Returns the element at row $i column $j of $matrix.
* "$matrix->elementkey($key)"
As $matrix->element(), except $i and $j have already been combined
into $key.
* "$matrix->elements()"
Returns an array consisting of all the elements of $matrix, in key
form, suitable for a loop.
See also SORTING METHODS below if the order of the elements is
important.
Example: foreach my $key ($matrix->elements()) { my ($i,$j) =
&splitkey($key); ... }
* "$matrix->delete($i,$j)"
Deletes the ($i,$j) element of $matrix.
* "$matrix->deletekey($key)"
As $matrix->delete(), except $i and $j have already been combined
into $key.
* "$matrix->cull()"
Returns a copy of $matrix with any zero elements removed. Equivalent
to $matrix->threshold(0).
* "$matrix->threshold($thresh)"
Returns a copy of $matrix with any elements with absolute value less
than $thresh removed.
* "$matrix->sizetofit()"
Returns a copy of $matrix with dimensions sufficient only to cover
its data.
* "$matrix->clearspecials()"
Removes all knowledge of special properties of $matrix. Use
$matrix->diagnose() to put them back.
DECOMPOSITIONAL METHODS
* "$matrix->row($i)"
"$matrix->row($i,$persist)"
Returns a matrix consisting only of the $i th row of $matrix. If
$persist is non-zero, the elements of $matrix are sorted by row, to
speed up future calls to row().
Note that many methods, most notably assign() and delete(), remove
the data necessary to use the fast algorithm. If this data is
present, a binary search is used instead of an exhaustive
term-by-term search. There is an intial cost of O(n log n)
operations (n==$matrix->count()) to use this data, but each search
costs O(log n) operations. This is in comparison to O(n) operations
without the data.
So, in summary, if many separate rows are needed, and the matrix is
unchanging, the first (at least) call to row() should have a
non-zero value of $persist.
* "$matrix->column($j)"
"$matrix->column($j,$persist)"
Returns a matrix consisting only of the $j th column of $matrix. See
also $matrix->row().
* "$matrix->diagpart($offset)"
If $offset is zero or undefined, returns a matrix consisting of the
diagonal elements of $matrix, if any. If $offset is non-zero,
returns a parallel diagonal. For example, if $offset=1, the first
superdiagonal is returned. Posive $offset s return diagonals above
the main diagonal, negative offsets return diagonals below the main
diagonal.
The returned matrix is the same size as $matrix.
* "$matrix->lowerpart()"
Returns a matrix consisting of the strictly lower triangular parts
of $matrix, if any. The returned matrix is the same size as $matrix.
* "$matrix->upperpart()"
Returns a matrix consisting of the strictly upper triangular parts
of $matrix, if any. The returned matrix is the same size as $matrix.
* "$matrix->nondiagpart($offset)" "$matrix->nonlowerpart()"
"$matrix->nonupperpart()"
As before, except that the returned matrix is everything except the
part specified.
Example:
A = D1 U1 U2
L1 D2 U3
L2 L3 D3
$A->lowerpart() == L1 L2 L3
$A->diagpart() == D1 D2 D3
$A->diagpart(1) == U1 U3
$A->diagpart(-1) == L1 L3
$A->upperpart() == U1 U2 U3
$A->nonlowerpart() == D1 U1 U2 D2 U3 D3
$A->nondiagpart(1) == D1 U2 L1 D2 L2 L3 D3
* "$matrix->symmetricpart()"
Returns the symmetric part of $matrix, i.e.
0.5*($matrix+$matrix->transpose()).
* "$matrix->skewsymmetricpart()"
Returns the skewsymmetric part of $matrix, i.e.
0.5*($matrix-$matrix->transpose()).
* "$matrix->positivepart()"
Returns the positive part of $matrix, i.e. those elements of $matrix
larger than zero.
* "$matrix->negativepart()"
Returns the positive part of $matrix, i.e. those elements of $matrix
larger than zero.
* "$matrix->mask($i1,$i2,$j1,$j2)"
Returns a matrix whose only elements are inside ($i1,$j1) ($i1,$j2)
($i2,$j1) ($i2,$j2)
* "$matrix->submatrix($i1,$i2,$j1,$j2)"
Returns that portion of $matrix between ($i1,$j1) ($i1,$j2)
($i2,$j1) ($i2,$j2)
Subscripts are changed, so $matrix($i1,$j1) is $submatrix(1,1).
* "$matrix1->insert($i,$j,$matrix2)"
The values of $matrix2 are assigned to the values of $matrix1,
offset by ($i,$j). That is, $matrix1($i+$k,$j+$l)=$matrix2($j,$l).
* "$A = $matrix->shift($row,$col)"
Creates a new matrix $A, $matrix($i,$j) == $A($i+$row,$j+$col)
INFORMATIONAL METHODS
* "$matrix->dim()"
Returns ($matrix->{rows}, $matrix->{columns})
* "$matrix->exactdim()"
Calculates explicitly the dimension of $matrix. This differs from
$matrix->dim() in that $matrix->{rows} and $matrix->{columns} may
not have been updated properly.
* " $matrix->count()"
Returns the number of defined elements in $matrix, 0 or otherwise.
* "$matrix->width()"
Calculates the bandwidth of $matrix, i.e. the maximum value of
abs($i-$j) for all elements at ($i,$j) in $matrix.
* "$matrix->sum()"
Finds the sum of all elements in $matrix.
* "$matrix->abssum()"
Finds the sum of the absolute values of all elements in $matrix.
* "$matrix->sumeach($coderef)"
Applies &$coderef to each of the elements of $matrix, and sums the
result. See "$matrix->each($coderef)" for more details.
* "$matrix->columnnorm()"
"$matrix->norm_one()"
Finds the maximum column sum of $matrix. That is, for each column of
$matrix, find the sum of absolute values of its elements, then
return the largest such sum. "norm_one" is provided for
compatibility with Math::MatrixReal.
* "$matrix->rownorm()"
"$matrix->norm_max()"
Finds the maximum row sum of $matrix. That is, for each row of
$matrix, find the sum of absolute values of its elements, then
return the largest such sum. "norm_max" is provided for
compatibility with Math::MatrixReal.
* "$matrix->norm_frobenius()"
Finds the Frobenius norm of $matrix. This is just an alias of
sqrt($matrix->sumeach(sub {$_[0]*$_[0]}).
* "$matrix->trace()"
Finds the trace of $matrix, which is the sum of its diagonal
elements. This just is an alias for $matrix->diagpart->sum().
* "$matrix->diagnose()"
Sets the special flags of $matrix.
BOOLEAN INFORMATIONAL METHODS
The following is_xxx() methods use the special flags if they are
present. If more than one will be called for a given matrix, consider
calling $matrix->diagnose() to set the flags.
* "$matrix->is_square()"
"$matrix->is_quadratic()"
Returns the value of the comparison
$matrix->{rows}==$matrix->{columns} That is, it returns 1 if the
matrix is square, 0 otherwise.
* "$matrix->is_diagonal()"
Returns 1 if $matrix is a diagonal matrix, 0 otherwise. $matrix need
not be square.
* "$matrix->is_lowertriangular()"
Returns 1 if $matrix is a lower triangular matrix, 0 otherwise.
$matrix need not be square. Diagonal elements are allowed.
* "$matrix->is_strictlowertriangular()"
Returns 1 if $matrix is a lower triangular matrix, 0 otherwise.
$matrix need not be square. Diagonal elements are not allowed.
* "$matrix->is_uppertriangular()"
Returns 1 if $matrix is an upper triangular matrix, 0 otherwise.
$matrix need not be square. Diagonal elements are allowed.
* "$matrix->is_strictuppertriangular()"
Returns 1 if $matrix is an upper triangular matrix, 0 otherwise.
$matrix need not be square. Diagonal elements are not allowed.
* "$matrix->is_positive()"
Returns 1 if all elements of $matrix are positive, 0 otherwise.
* "$matrix->is_negative()"
Returns 1 if all elements of $matrix are negative, 0 otherwise.
* "$matrix->is_nonpositive()"
Returns 1 if all elements of $matrix are nonpositive (i.e. <=0), 0
otherwise.
* "$matrix->is_nonnegative()"
Returns 1 if all elements of $matrix are nonnegative (i.e. >=0), 0
otherwise.
* "$matrix->is_boolean()"
"$matrix->is_pattern()"
Returns 1 if all elements of $matrix are 0 or 1, 0 otherwise.
* "$matrix->is_symmetric()"
Returns 1 if $matrix is symmetric, i.e.
$matrix==$matrix->transpose(), 0 otherwise. $matrix is assumed to be
square.
* "$matrix->is_skewsymmetric()"
Returns 1 if $matrix is skew-symmetric, i.e.
$matrix==-1*$matrix->transpose(), 0 otherwise. $matrix is assumed to
be square.
ARITHMETIC METHODS
* "$matrix1->add($matrix2)"
Finds and returns $matrix1 + $matrix2. Matrices must be of the same
size.
* "$matrix1->multiply($matrix2)"
Finds and returns $matrix1 * $matrix2. $matrix1->{columns} must
equal $matrix2->{rows}.
* "$matrix1->multiplyfree($matrix2)"
"$matrix1->addfree($matrix2)"
As add() and multiply(), but with no limitations on the dimensions
of the matrices.
* "$matrix1->quickmultiply($matrix2)"
"$matrix1->quickmultiplyfree($matrix2)"
As multiply() and multiplyfree(), but with a different algorithm
that is faster for larger matrices.
* "$matrix->multiplyscalar($scalar)"
Returns the product of $matrix and $scalar.
* "$matrix1->kronecker($matrix2)"
Returns the direct product of $matrix1 and $matrix2. Every element
of $matrix1 is multiplied by the entirely of $matrix2, and those
matrices assembled into a big matrix and returned.
* "$matrix->exponentiate($n)" "$matrix->largeexponentiate($n)"
Finds and returns $matrix raised to the $n th power. $n must be
nonnegative and integral, and $matrix must be square.
For large values of $n, largeexponentiate() is faster.
* "$matrix->terminvert()"
Returns the matrix whose elements are the multiplicative inverses of
$matrix. If $matrix is square diagonal, "$matrix->terminvert()" is
the multiplicative inverse of $matrix.
* "$matrix->transpose()"
Returns the transpose of $matrix.
* "$matrix->each($coderef)"
Applies a subroutine referred to by $coderef to each element of
$matrix. &$coderef should take three arguments ($value, $row,
$column).
* "$matrix->symmetrify()"
Returns a matrix obtained by reflecting $matrix about its main
diagonal. $matrix does not need to be square.
Exits with an error if $matrix(i,j) and $matrix(j,i) both exist and
are not identical.
* "$matrix->skewsymmetrify()"
As symmetrify(), except that the reflected terms are made negative.
Exits with an error if $matrix(i,j) and $matrix(j,i) both exist and
are not negatives of each other.
* "$matrix1->matrixand($matrix2)"
Finds and returns the matrix whose ($i,$j) element is
$matrix1($i,$j) && $matrix2($i,$j). The returned matrix is a pattern
matrix.
* "$matrix1->matrixor($matrix2)"
Finds and returns the matrix whose ($i,$j) element is
$matrix1($i,$j) || $matrix2($i,$j). The returned matrix is a pattern
matrix.
PROBABILISTIC METHODS
* "$matrix->normalize()"
Returns a matrix $matrix2 scaled so that $matrix2->sum()==1.
Exits on error if $matrix is not nonnegative.
* "$matrix->normalizerows()"
As $matrix->normalize(), except that each row is scaled to have a
sum of 1.
Exits on error if $matrix is not nonnegative.
* "$matrix->normalizecolumns()"
As $matrix->normalizerows(), except with columns. Mathematically
equivalent to $matrix->transpose()->normalizerows()->transpose().
Exits on error if $matrix is not nonnegative.
* "$matrix->discretepdf()"
Assuming that $matrix->sum()==1 and $matrix is non-negative, chooses
a random element from $matrix based on the assumption that the entry
at ($i,$j) is the probability of choosing ($i,$j).
SOLUTION OF SYSTEMS METHODS
* "$matrix->jacobi($constant,$guess, $tol, $steps)"
Uses Jacobi iteration to find and return the solution to the system
of equations $matrix * x = $constant, with initial guess $constant,
tolerance $tol, and maximum iterations $steps.
If $steps is undefined, the default value of 100 is used.
Care should be taken to ensure that $matrix is such that the
iteration actually converges.
* "$matrix->gaussseidel($constant,$guess, $tol, $steps)"
Uses Gauss-Seidel iteration to find and return the solution to the
system of equations $matrix * x = $constant, with initial guess
$constant, tolerance $tol, and maximum iterations $steps. This is
equivalent to $matrix->SOR with relaxation parameter 1.
Care should be taken to ensure that $matrix is such that the
iteration actually converges.
* "$matrix->SOR($constant,$guess, $relax, $tol, $steps)"
Uses Successive Over-Relaxation to find and return the solution to
the system of equations $matrix * x = $constant, with initial guess
$constant, relaxation parameter $relax, tolerance $tol, and maximum
iterations $steps.
Care should be taken to ensure that $matrix is such that the
iteration actually converges.
SORTING METHODS
* "$matrix->sortbycolumn()"
"$matrix->sortbyrow()"
Returns an array containing the keys of $matrix, sorted primarily by
either column or row (and secondarily by row or column).
"$matrix->sortbydiagonal()"
Returns an array containing the keys of $matrix, sorted primarily by
their distance from elements on the main diagonal, lower diagonals
first. The row of the key is a secondary criterion.
"$matrix->sortbyvalue()"
Returns an array containing the keys of $matrix, sorted primarily by
the value of the element indexed by the key. Row and column are
secondary and tertiaty criteria.
These methods are suitable for using inside a loop. See also
$matrix->elements() if the order of the elements is not important.
Example:
A 3x3 matrix will be sorted in the following manners:
sortbycolumn()
1 4 7
2 5 8
3 6 9
sortbyrow()
1 2 3
4 5 6
7 8 9
sortbydiagonal()
4 7 9
2 5 8
1 3 6
IN-LINE METHODS
The following are as described above, except that they modify their
calling object instead of a copy thereof.
"_each"
"_mask"
"_insert"
"_cull"
"_threshold"
"_sizetofit"
"_negate"
"_multiplyscalar"
"_terminvert"
"_symmetrify"
"_skewsymmetrify"
"_normalize()"
"_normalizerows()"
"_normalizecolumns()"
"_diagpart()"
"_nondiagpart()"
"_upperpart()"
"_nonupperpart()"
"_lowerpart()"
"_nonlowerpart()"
"_positivepart()"
"_negativepart()"
"_symmetricpart()"
"_skewsymmetricpart()"
In addition to these, the following methods modify the calling object.
"name()"
"assign()"
"assignspecial()"
"assignkey()"
"row()" (if called with the optional second argument)
"column()" (if called with the optional second argument)
"diagnose()"
"delete()"
"deletekey()"
"clearspecials()"
OVERLOADED OPERATORS
"+" add()
"-" subtract()
"*" quickmultiply()
"x" kronecker()
"**" exponential()
"~" transpose()
"&" matrixand()
"|" matrixor()
"" print()
Unary "-" negate()
SPECIAL MATRIX FLAGS
Certain information is stored about the matrix, and is updated when
necessary. See also "$matrix->diagnose()". All flags can also be
"undef". These should not be accessed directly--use the boolean
is_whatever() methods instead.
*structure*
The symmetry of the matrix. Can be "symmetric" or "skewsymmetric".
*shape*
The shape of the matrix. Can be "diagonal", "lower" (triangular),
"upper", "strictlower" or "strictupper".
*sign*
The sign of all the elemetns of a matrix. Can be "positive",
"negative", "nonpostive", "nonnegative", or "zero".
*pattern*
Indicates whether the matrix should be treated as a pattern. Is
non-zero if so.
*bandwidth*
Calculates the bandwidth of $matrix, i.e. the maximum value of
abs($i-$j) for all elements at ($i,$j) in $matrix.
*field*
The underlying field of the elements of the matrix. Currently, can
only be "real".
INTERFACING
The user should not attempt to access the pieces of a Math::MatrixReal
object directly, but instead use the routines provided. Certain methods,
such as the sorters, return keys to the elements of the matrix, and
these should be fed into "splitkey()" to obtain row-column indices.
EXPORT
None.
EXPORT_OK
&splitkey() and &makekey().
BUGS
Horribly, hideously inefficient.
No checks are made to be sure that values are of a proper type, or even
that indices are integers. It is entirely possible to assign() a value
that is, say, another Math::MatrixSparse. However, because of the lack
of these checks, indices can start at zero, or even negative values, if
an algorithm calls for it.
Harwell Boeing support is not robust, and output is not implemented.
Complex matrices in Harwell Boeing and Matrix Market are not supported.
In Matrix Market format, only the real part is read--the imaginary part
is discarded.
Many methods do not modify their calling object, but instead return a
new object. This can be inefficent and a waste of resources, especially
when it will be assigned to the new object anyway. Use the analogous
methods listed in IN-LINE METHODS instead if this is an issue.
AUTHOR
Jacob C. Kesinger,
SEE ALSO
perl, Math::MatrixReal.

NAME
Math::GMatrix - Extension of Math::Matrix for (2D graphics-)vector
manipulation
SYNOPSIS
use Math::GMatrix;
DESCRIPTION
The following methods are available:
new
Constructor arguments are a list of references to arrays of the same
length. The arrays are copied. The method returns undef in case of
error.
$a = new Math::Matrix ([rand,rand,rand],
[rand,rand,rand],
[rand,rand,rand]);
As s special case you can pass a single argument 'I' for getting an
identity matrix.
If you call "new" as method, a zero filled matrix with identical
deminsions is returned.
xform
You can transform one or more vectors by calling:
@V1=(1.5,3.7);
@V2 = $M->xform(@V1);
@L1=( [1.5,3.7], [4.6,6.8], [5.1,-0.7] );
@L2 = $M->xform(@L1);
translate
You can pan (move by x and y offset) your graphics by calling:
$M2 = $M->translate(2.5,10.2);
rotate
You can rotate your graphics by calling:
$M2 = $M->rotate(-90);
scale
You can scale (factor_x and factor_y) your graphics by calling:
$M2 = $M->rotate(2,2);
EXAMPLE
@ListOfVectors = [
[0,1],
[3,5],
[2,7],
[8,-1],
];
$paperwidth = 21; # DIN A4 is 21x29.7 cm
$M = new Math::Matrix('I'); # get an identity matrix
$M = $M->translate(-1,-1)->rotate(90)->translate($paperwidth-1,1);
@Result = $M->xform(@ListOfVectors);
AUTHOR
A. Cester,

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