#
# GENERATED WITH PDL::PP! Don't modify!
#
package PDL::Ufunc;
@EXPORT_OK = qw( PDL::PP sumover PDL::PP dsumover PDL::PP cumusumover PDL::PP dcumusumover PDL::PP prodover PDL::PP dprodover PDL::PP cumuprodover PDL::PP dcumuprodover PDL::PP orover PDL::PP borover PDL::PP zcover PDL::PP andover PDL::PP bandover PDL::PP intover PDL::PP average PDL::PP avgover PDL::PP daverage PDL::PP davgover PDL::PP medover PDL::PP oddmedover PDL::PP modeover PDL::PP pctover PDL::PP oddpctover pct oddpct avg sum prod davg dsum dprod zcheck and band or bor min max median mode oddmedian any all minmax PDL::PP qsort PDL::PP qsorti PDL::PP qsortvec PDL::PP qsortveci PDL::PP minimum PDL::PP minimum_ind PDL::PP minimum_n_ind PDL::PP maximum PDL::PP maximum_ind PDL::PP maximum_n_ind PDL::PP maxover PDL::PP maxover_ind PDL::PP maxover_n_ind PDL::PP minover PDL::PP minover_ind PDL::PP minover_n_ind PDL::PP minmaximum PDL::PP minmaxover );
%EXPORT_TAGS = (Func=>[@EXPORT_OK]);
use PDL::Core;
use PDL::Exporter;
use DynaLoader;
@ISA = ( 'PDL::Exporter','DynaLoader' );
push @PDL::Core::PP, __PACKAGE__;
bootstrap PDL::Ufunc ;
=head1 NAME
PDL::Ufunc - primitive ufunc operations for pdl
=head1 DESCRIPTION
This module provides some primitive and useful functions defined
using PDL::PP based on functionality of what are sometimes called
I<ufuncs> (for example NumPY and Mathematica talk about these).
It collects all the functions generally used to C<reduce> or
C<accumulate> along a dimension. These all do their job across the
first dimension but by using the slicing functions you can do it
on any dimension.
The L<PDL::Reduce|PDL::Reduce> module provides an alternative interface
to many of the functions in this module.
=head1 SYNOPSIS
use PDL::Ufunc;
=cut
use PDL::Slices;
use Carp;
=head1 FUNCTIONS
=cut
=head2 sumover
=for sig
Signature: (a(n); int+ [o]b())
=for ref
Project via sum to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the sum along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = sumover($a);
=for example
$spectrum = sumover $image->xchg(0,1)
=for bad
sumover processes bad values.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*sumover = \&PDL::sumover;
=head2 dsumover
=for sig
Signature: (a(n); double [o]b())
=for ref
Project via sum to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the sum along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = dsumover($a);
=for example
$spectrum = dsumover $image->xchg(0,1)
Unlike L<sumover|/sumover>, the calculations are performed in double
precision.
=for bad
dsumover processes bad values.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*dsumover = \&PDL::dsumover;
=head2 cumusumover
=for sig
Signature: (a(n); int+ [o]b(n))
=for ref
Cumulative sum
This function calculates the cumulative sum
along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
The sum is started so that the first element in the cumulative sum
is the first element of the parameter.
=for usage
$b = cumusumover($a);
=for example
$spectrum = cumusumover $image->xchg(0,1)
=for bad
cumusumover processes bad values.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*cumusumover = \&PDL::cumusumover;
=head2 dcumusumover
=for sig
Signature: (a(n); double [o]b(n))
=for ref
Cumulative sum
This function calculates the cumulative sum
along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
The sum is started so that the first element in the cumulative sum
is the first element of the parameter.
=for usage
$b = cumusumover($a);
=for example
$spectrum = cumusumover $image->xchg(0,1)
Unlike L<cumusumover|/cumusumover>, the calculations are performed in double
precision.
=for bad
dcumusumover processes bad values.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*dcumusumover = \&PDL::dcumusumover;
=head2 prodover
=for sig
Signature: (a(n); int+ [o]b())
=for ref
Project via product to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the product along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = prodover($a);
=for example
$spectrum = prodover $image->xchg(0,1)
=for bad
prodover processes bad values.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*prodover = \&PDL::prodover;
=head2 dprodover
=for sig
Signature: (a(n); double [o]b())
=for ref
Project via product to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the product along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = dprodover($a);
=for example
$spectrum = dprodover $image->xchg(0,1)
Unlike L<prodover|/prodover>, the calculations are performed in double
precision.
=for bad
dprodover processes bad values.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*dprodover = \&PDL::dprodover;
=head2 cumuprodover
=for sig
Signature: (a(n); int+ [o]b(n))
=for ref
Cumulative product
This function calculates the cumulative product
along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
The sum is started so that the first element in the cumulative product
is the first element of the parameter.
=for usage
$b = cumuprodover($a);
=for example
$spectrum = cumuprodover $image->xchg(0,1)
=for bad
cumuprodover processes bad values.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*cumuprodover = \&PDL::cumuprodover;
=head2 dcumuprodover
=for sig
Signature: (a(n); double [o]b(n))
=for ref
Cumulative product
This function calculates the cumulative product
along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
The sum is started so that the first element in the cumulative product
is the first element of the parameter.
=for usage
$b = cumuprodover($a);
=for example
$spectrum = cumuprodover $image->xchg(0,1)
Unlike L<cumuprodover|/cumuprodover>, the calculations are performed in double
precision.
=for bad
dcumuprodover processes bad values.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*dcumuprodover = \&PDL::dcumuprodover;
=head2 orover
=for sig
Signature: (a(n); int+ [o]b())
=for ref
Project via or to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the or along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = orover($a);
=for example
$spectrum = orover $image->xchg(0,1)
=for bad
If C<a()> contains only bad data (and its bad flag is set),
C<b()> is set bad. Otherwise C<b()> will have its bad flag cleared,
as it will not contain any bad values.
=cut
*orover = \&PDL::orover;
=head2 borover
=for sig
Signature: (a(n); [o]b())
=for ref
Project via bitwise or to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the bitwise or along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = borover($a);
=for example
$spectrum = borover $image->xchg(0,1)
=for bad
If C<a()> contains only bad data (and its bad flag is set),
C<b()> is set bad. Otherwise C<b()> will have its bad flag cleared,
as it will not contain any bad values.
=cut
*borover = \&PDL::borover;
=head2 zcover
=for sig
Signature: (a(n); int+ [o]b())
=for ref
Project via == 0 to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the == 0 along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = zcover($a);
=for example
$spectrum = zcover $image->xchg(0,1)
=for bad
If C<a()> contains only bad data (and its bad flag is set),
C<b()> is set bad. Otherwise C<b()> will have its bad flag cleared,
as it will not contain any bad values.
=cut
*zcover = \&PDL::zcover;
=head2 andover
=for sig
Signature: (a(n); int+ [o]b())
=for ref
Project via and to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the and along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = andover($a);
=for example
$spectrum = andover $image->xchg(0,1)
=for bad
If C<a()> contains only bad data (and its bad flag is set),
C<b()> is set bad. Otherwise C<b()> will have its bad flag cleared,
as it will not contain any bad values.
=cut
*andover = \&PDL::andover;
=head2 bandover
=for sig
Signature: (a(n); [o]b())
=for ref
Project via bitwise and to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the bitwise and along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = bandover($a);
=for example
$spectrum = bandover $image->xchg(0,1)
=for bad
If C<a()> contains only bad data (and its bad flag is set),
C<b()> is set bad. Otherwise C<b()> will have its bad flag cleared,
as it will not contain any bad values.
=cut
*bandover = \&PDL::bandover;
=head2 intover
=for sig
Signature: (a(n); float+ [o]b())
=for ref
Project via integral to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the integral along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = intover($a);
=for example
$spectrum = intover $image->xchg(0,1)
Notes:
C<intover> uses a point spacing of one (i.e., delta-h==1). You will
need to scale the result to correct for the true point delta).
For C<n E<gt> 3>, these are all C<O(h^4)> (like Simpson's rule), but are
integrals between the end points assuming the pdl gives values just at
these centres: for such `functions', sumover is correct to C<O(h)>, but
is the natural (and correct) choice for binned data, of course.
=for bad
intover ignores the bad-value flag of the input piddles.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*intover = \&PDL::intover;
=head2 average
=for sig
Signature: (a(n); int+ [o]b())
=for ref
Project via average to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the average along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = average($a);
=for example
$spectrum = average $image->xchg(0,1)
=for bad
average processes bad values.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*average = \&PDL::average;
*PDL::avgover = \&PDL::average;
*avgover = \&PDL::average;
=head2 avgover
=for ref
Synonym for average.
=cut
=head2 daverage
=for sig
Signature: (a(n); double [o]b())
=for ref
Project via average to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the average along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = daverage($a);
=for example
$spectrum = daverage $image->xchg(0,1)
Unlike L<average|/average>, the calculation is performed in double
precision.
=for bad
daverage processes bad values.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*daverage = \&PDL::daverage;
*PDL::davgover = \&PDL::daverage;
*davgover = \&PDL::daverage;
=head2 davgover
=for ref
Synonym for daverage.
=cut
=head2 medover
=for sig
Signature: (a(n); [o]b(); [t]tmp(n))
=for ref
Project via median to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the median along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = medover($a);
=for example
$spectrum = medover $image->xchg(0,1)
=for bad
medover processes bad values.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*medover = \&PDL::medover;
=head2 oddmedover
=for sig
Signature: (a(n); [o]b(); [t]tmp(n))
=for ref
Project via oddmedian to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the oddmedian along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = oddmedover($a);
=for example
$spectrum = oddmedover $image->xchg(0,1)
The median is sometimes not a good choice as if the array has
an even number of elements it lies half-way between the two
middle values - thus it does not always correspond to a data
value. The lower-odd median is just the lower of these two values
and so it ALWAYS sits on an actual data value which is useful in
some circumstances.
=for bad
oddmedover processes bad values.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*oddmedover = \&PDL::oddmedover;
=head2 modeover
=for sig
Signature: (data(n); [o]out(); [t]sorted(n))
=for ref
Project via mode to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the mode along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = modeover($a);
=for example
$spectrum = modeover $image->xchg(0,1)
The mode is the single element most frequently found in a
discrete data set.
It I<only> makes sense for integer data types, since
floating-point types are demoted to integer before the
mode is calculated.
C<modeover> treats BAD the same as any other value: if
BAD is the most common element, the returned value is also BAD.
=for bad
modeover does not process bad values.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*modeover = \&PDL::modeover;
=head2 pctover
=for sig
Signature: (a(n); p(); [o]b(); [t]tmp(n))
=for ref
Project via percentile to N-1 dimensions
This function reduces the dimensionality of a piddle by one by finding
the specified percentile (p) along the 1st dimension. The specified
percentile must be between 0.0 and 1.0. When the specified percentile
falls between data points, the result is interpolated. Values outside
the allowed range are clipped to 0.0 or 1.0 respectively. The algorithm
implemented here is based on the interpolation variant described at
L<http://en.wikipedia.org/wiki/Percentile> as used by Microsoft Excel
and recommended by NIST.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = pctover($a, $p);
=for example
$spectrum = pctover $image->xchg(0,1), $p
=for bad
pctover processes bad values.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*pctover = \&PDL::pctover;
=head2 oddpctover
=for sig
Signature: (a(n); p(); [o]b(); [t]tmp(n))
Project via percentile to N-1 dimensions
This function reduces the dimensionality of a piddle by one by finding
the specified percentile along the 1st dimension. The specified
percentile must be between 0.0 and 1.0. When the specified percentile
falls between two values, the nearest data value is the result.
The algorithm implemented is from the textbook version described
first at L<http://en.wikipedia.org/wiki/Percentile>.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = oddpctover($a, $p);
=for example
$spectrum = oddpctover $image->xchg(0,1), $p
=for bad
oddpctover processes bad values.
It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
=cut
*oddpctover = \&PDL::oddpctover;
=head2 pct
=for ref
Return the specified percentile of all elements in a piddle. The
specified percentile (p) must be between 0.0 and 1.0. When the
specified percentile falls between data points, the result is
interpolated.
=for usage
$x = pct($data, $pct);
=cut
*pct = \&PDL::pct;
sub PDL::pct {
my($x, $p) = @_;
my $tmp;
$x->clump(-1)->pctover($p, $tmp=PDL->nullcreate($x));
return $tmp->at();
}
=head2 oddpct
=for ref
Return the specified percentile of all elements in a piddle. The
specified percentile must be between 0.0 and 1.0. When the specified
percentile falls between two values, the nearest data value is the
result.
=for usage
$x = oddpct($data, $pct);
=cut
*oddpct = \&PDL::oddpct;
sub PDL::oddpct {
my($x, $p) = @_;
my $tmp;
$x->clump(-1)->oddpctover($p, $tmp=PDL->nullcreate($x));
return $tmp->at();
}
=head2 avg
=for ref
Return the average of all elements in a piddle.
See the documentation for L<average|/average> for more information.
=for usage
$x = avg($data);
=cut
=for bad
This routine handles bad values.
=cut
*avg = \&PDL::avg;
sub PDL::avg {
my($x) = @_; my $tmp;
$x->clump(-1)->average( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 sum
=for ref
Return the sum of all elements in a piddle.
See the documentation for L<sumover|/sumover> for more information.
=for usage
$x = sum($data);
=cut
=for bad
This routine handles bad values.
=cut
*sum = \&PDL::sum;
sub PDL::sum {
my($x) = @_; my $tmp;
$x->clump(-1)->sumover( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 prod
=for ref
Return the product of all elements in a piddle.
See the documentation for L<prodover|/prodover> for more information.
=for usage
$x = prod($data);
=cut
=for bad
This routine handles bad values.
=cut
*prod = \&PDL::prod;
sub PDL::prod {
my($x) = @_; my $tmp;
$x->clump(-1)->prodover( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 davg
=for ref
Return the average (in double precision) of all elements in a piddle.
See the documentation for L<daverage|/daverage> for more information.
=for usage
$x = davg($data);
=cut
=for bad
This routine handles bad values.
=cut
*davg = \&PDL::davg;
sub PDL::davg {
my($x) = @_; my $tmp;
$x->clump(-1)->daverage( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 dsum
=for ref
Return the sum (in double precision) of all elements in a piddle.
See the documentation for L<dsumover|/dsumover> for more information.
=for usage
$x = dsum($data);
=cut
=for bad
This routine handles bad values.
=cut
*dsum = \&PDL::dsum;
sub PDL::dsum {
my($x) = @_; my $tmp;
$x->clump(-1)->dsumover( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 dprod
=for ref
Return the product (in double precision) of all elements in a piddle.
See the documentation for L<dprodover|/dprodover> for more information.
=for usage
$x = dprod($data);
=cut
=for bad
This routine handles bad values.
=cut
*dprod = \&PDL::dprod;
sub PDL::dprod {
my($x) = @_; my $tmp;
$x->clump(-1)->dprodover( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 zcheck
=for ref
Return the check for zero of all elements in a piddle.
See the documentation for L<zcover|/zcover> for more information.
=for usage
$x = zcheck($data);
=cut
=for bad
This routine handles bad values.
=cut
*zcheck = \&PDL::zcheck;
sub PDL::zcheck {
my($x) = @_; my $tmp;
$x->clump(-1)->zcover( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 and
=for ref
Return the logical and of all elements in a piddle.
See the documentation for L<andover|/andover> for more information.
=for usage
$x = and($data);
=cut
=for bad
This routine handles bad values.
=cut
*and = \&PDL::and;
sub PDL::and {
my($x) = @_; my $tmp;
$x->clump(-1)->andover( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 band
=for ref
Return the bitwise and of all elements in a piddle.
See the documentation for L<bandover|/bandover> for more information.
=for usage
$x = band($data);
=cut
=for bad
This routine handles bad values.
=cut
*band = \&PDL::band;
sub PDL::band {
my($x) = @_; my $tmp;
$x->clump(-1)->bandover( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 or
=for ref
Return the logical or of all elements in a piddle.
See the documentation for L<orover|/orover> for more information.
=for usage
$x = or($data);
=cut
=for bad
This routine handles bad values.
=cut
*or = \&PDL::or;
sub PDL::or {
my($x) = @_; my $tmp;
$x->clump(-1)->orover( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 bor
=for ref
Return the bitwise or of all elements in a piddle.
See the documentation for L<borover|/borover> for more information.
=for usage
$x = bor($data);
=cut
=for bad
This routine handles bad values.
=cut
*bor = \&PDL::bor;
sub PDL::bor {
my($x) = @_; my $tmp;
$x->clump(-1)->borover( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 min
=for ref
Return the minimum of all elements in a piddle.
See the documentation for L<minimum|/minimum> for more information.
=for usage
$x = min($data);
=cut
=for bad
This routine handles bad values.
=cut
*min = \&PDL::min;
sub PDL::min {
my($x) = @_; my $tmp;
$x->clump(-1)->minimum( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 max
=for ref
Return the maximum of all elements in a piddle.
See the documentation for L<maximum|/maximum> for more information.
=for usage
$x = max($data);
=cut
=for bad
This routine handles bad values.
=cut
*max = \&PDL::max;
sub PDL::max {
my($x) = @_; my $tmp;
$x->clump(-1)->maximum( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 median
=for ref
Return the median of all elements in a piddle.
See the documentation for L<medover|/medover> for more information.
=for usage
$x = median($data);
=cut
=for bad
This routine handles bad values.
=cut
*median = \&PDL::median;
sub PDL::median {
my($x) = @_; my $tmp;
$x->clump(-1)->medover( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 mode
=for ref
Return the mode of all elements in a piddle.
See the documentation for L<modeover|/modeover> for more information.
=for usage
$x = mode($data);
=cut
=for bad
This routine handles bad values.
=cut
*mode = \&PDL::mode;
sub PDL::mode {
my($x) = @_; my $tmp;
$x->clump(-1)->modeover( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 oddmedian
=for ref
Return the oddmedian of all elements in a piddle.
See the documentation for L<oddmedover|/oddmedover> for more information.
=for usage
$x = oddmedian($data);
=cut
=for bad
This routine handles bad values.
=cut
*oddmedian = \&PDL::oddmedian;
sub PDL::oddmedian {
my($x) = @_; my $tmp;
$x->clump(-1)->oddmedover( $tmp=PDL->nullcreate($x) );
return $tmp->at();
}
=head2 any
=for ref
Return true if any element in piddle set
Useful in conditional expressions:
=for example
if (any $a>15) { print "some values are greater than 15\n" }
=cut
=for bad
See L<or|/or> for comments on what happens when all elements
in the check are bad.
=cut
*any = \∨
*PDL::any = \&PDL::or;
=head2 all
=for ref
Return true if all elements in piddle set
Useful in conditional expressions:
=for example
if (all $a>15) { print "all values are greater than 15\n" }
=cut
=for bad
See L<and|/and> for comments on what happens when all elements
in the check are bad.
=cut
*all = \∧
*PDL::all = \&PDL::and;
=head2 minmax
=for ref
Returns an array with minimum and maximum values of a piddle.
=for usage
($mn, $mx) = minmax($pdl);
This routine does I<not> thread over the dimensions of C<$pdl>;
it returns the minimum and maximum values of the whole array.
See L<minmaximum|/minmaximum> if this is not what is required.
The two values are returned as Perl scalars similar to min/max.
=for example
pdl> $x = pdl [1,-2,3,5,0]
pdl> ($min, $max) = minmax($x);
pdl> p "$min $max\n";
-2 5
=cut
*minmax = \&PDL::minmax;
sub PDL::minmax {
my ($x)=@_; my $tmp;
my @arr = $x->clump(-1)->minmaximum;
return map {$_->sclr} @arr[0,1]; # return as scalars !
}
=head2 qsort
=for sig
Signature: (a(n); [o]b(n))
=for ref
Quicksort a vector into ascending order.
=for example
print qsort random(10);
=for bad
Bad values are moved to the end of the array:
pdl> p $b
[42 47 98 BAD 22 96 74 41 79 76 96 BAD 32 76 25 59 BAD 96 32 BAD]
pdl> p qsort($b)
[22 25 32 32 41 42 47 59 74 76 76 79 96 96 96 98 BAD BAD BAD BAD]
=cut
*qsort = \&PDL::qsort;
=head2 qsorti
=for sig
Signature: (a(n); indx [o]indx(n))
=for ref
Quicksort a vector and return index of elements in ascending order.
=for example
$ix = qsorti $a;
print $a->index($ix); # Sorted list
=for bad
Bad elements are moved to the end of the array:
pdl> p $b
[42 47 98 BAD 22 96 74 41 79 76 96 BAD 32 76 25 59 BAD 96 32 BAD]
pdl> p $b->index( qsorti($b) )
[22 25 32 32 41 42 47 59 74 76 76 79 96 96 96 98 BAD BAD BAD BAD]
=cut
*qsorti = \&PDL::qsorti;
=head2 qsortvec
=for sig
Signature: (a(n,m); [o]b(n,m))
=for ref
Sort a list of vectors lexicographically.
The 0th dimension of the source piddle is dimension in the vector;
the 1st dimension is list order. Higher dimensions are threaded over.
=for example
print qsortvec pdl([[1,2],[0,500],[2,3],[4,2],[3,4],[3,5]]);
[
[ 0 500]
[ 1 2]
[ 2 3]
[ 3 4]
[ 3 5]
[ 4 2]
]
=for bad
Vectors with bad components should be moved to the end of the array:
=cut
*qsortvec = \&PDL::qsortvec;
=head2 qsortveci
=for sig
Signature: (a(n,m); indx [o]indx(m))
=for ref
Sort a list of vectors lexicographically, returning the indices of the
sorted vectors rather than the sorted list itself.
As with C<qsortvec>, the input PDL should be an NxM array containing M
separate N-dimensional vectors. The return value is an integer M-PDL
containing the M-indices of original array rows, in sorted order.
As with C<qsortvec>, the zeroth element of the vectors runs slowest in the
sorted list.
Additional dimensions are threaded over: each plane is sorted separately,
so qsortveci may be thought of as a collapse operator of sorts (groan).
=for bad
Vectors with bad components should be moved to the end of the array:
=cut
*qsortveci = \&PDL::qsortveci;
=head2 minimum
=for sig
Signature: (a(n); [o]c())
=for ref
Project via minimum to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the minimum along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = minimum($a);
=for example
$spectrum = minimum $image->xchg(0,1)
=for bad
Output is set bad if all elements of the input are bad,
otherwise the bad flag is cleared for the output piddle.
Note that C<NaNs> are considered to be valid values;
see L<isfinite|PDL::Math/isfinite> and L<badmask|PDL::Math/badmask>
for ways of masking NaNs.
=cut
*minimum = \&PDL::minimum;
=head2 minimum_ind
=for sig
Signature: (a(n); indx [o] c())
=for ref
Like minimum but returns the index rather than the value
=for bad
Output is set bad if all elements of the input are bad,
otherwise the bad flag is cleared for the output piddle.
=cut
*minimum_ind = \&PDL::minimum_ind;
=head2 minimum_n_ind
=for sig
Signature: (a(n); indx [o]c(m))
=for ref
Returns the index of C<m> minimum elements
=for bad
Not yet been converted to ignore bad values
=cut
*minimum_n_ind = \&PDL::minimum_n_ind;
=head2 maximum
=for sig
Signature: (a(n); [o]c())
=for ref
Project via maximum to N-1 dimensions
This function reduces the dimensionality of a piddle
by one by taking the maximum along the 1st dimension.
By using L<xchg|PDL::Slices/xchg> etc. it is possible to use
I<any> dimension.
=for usage
$b = maximum($a);
=for example
$spectrum = maximum $image->xchg(0,1)
=for bad
Output is set bad if all elements of the input are bad,
otherwise the bad flag is cleared for the output piddle.
Note that C<NaNs> are considered to be valid values;
see L<isfinite|PDL::Math/isfinite> and L<badmask|PDL::Math/badmask>
for ways of masking NaNs.
=cut
*maximum = \&PDL::maximum;
=head2 maximum_ind
=for sig
Signature: (a(n); indx [o] c())
=for ref
Like maximum but returns the index rather than the value
=for bad
Output is set bad if all elements of the input are bad,
otherwise the bad flag is cleared for the output piddle.
=cut
*maximum_ind = \&PDL::maximum_ind;
=head2 maximum_n_ind
=for sig
Signature: (a(n); indx [o]c(m))
=for ref
Returns the index of C<m> maximum elements
=for bad
Not yet been converted to ignore bad values
=cut
*maximum_n_ind = \&PDL::maximum_n_ind;
*PDL::maxover = \&PDL::maximum;
*maxover = \&PDL::maximum;
=head2 maxover
=for ref
Synonym for maximum.
=cut
*PDL::maxover_ind = \&PDL::maximum_ind;
*maxover_ind = \&PDL::maximum_ind;
=head2 maxover_ind
=for ref
Synonym for maximum_ind.
=cut
*PDL::maxover_n_ind = \&PDL::maximum_n_ind;
*maxover_n_ind = \&PDL::maximum_n_ind;
=head2 maxover_n_ind
=for ref
Synonym for maximum_n_ind.
=cut
*PDL::minover = \&PDL::minimum;
*minover = \&PDL::minimum;
=head2 minover
=for ref
Synonym for minimum.
=cut
*PDL::minover_ind = \&PDL::minimum_ind;
*minover_ind = \&PDL::minimum_ind;
=head2 minover_ind
=for ref
Synonym for minimum_ind.
=cut
*PDL::minover_n_ind = \&PDL::minimum_n_ind;
*minover_n_ind = \&PDL::minimum_n_ind;
=head2 minover_n_ind
=for ref
Synonym for minimum_n_ind
=cut
=head2 minmaximum
=for sig
Signature: (a(n); [o]cmin(); [o] cmax(); indx [o]cmin_ind(); indx [o]cmax_ind())
=for ref
Find minimum and maximum and their indices for a given piddle;
=for usage
pdl> $a=pdl [[-2,3,4],[1,0,3]]
pdl> ($min, $max, $min_ind, $max_ind)=minmaximum($a)
pdl> p $min, $max, $min_ind, $max_ind
[-2 0] [4 3] [0 1] [2 2]
See also L<minmax|/minmax>, which clumps the piddle together.
=for bad
If C<a()> contains only bad data, then the output piddles will
be set bad, along with their bad flag.
Otherwise they will have their bad flags cleared,
since they will not contain any bad values.
=cut
*minmaximum = \&PDL::minmaximum;
*PDL::minmaxover = \&PDL::minmaximum;
*minmaxover = \&PDL::minmaximum;
=head2 minmaxover
=for ref
Synonym for minmaximum.
=cut
;
=head1 AUTHOR
Copyright (C) Tuomas J. Lukka 1997 (lukka@husc.harvard.edu).
Contributions by Christian Soeller (c.soeller@auckland.ac.nz)
and Karl Glazebrook (kgb@aaoepp.aao.gov.au). All rights
reserved. There is no warranty. You are allowed to redistribute this
software / documentation under certain conditions. For details, see
the file COPYING in the PDL distribution. If this file is separated
from the PDL distribution, the copyright notice should be included in
the file.
=cut
# Exit with OK status
1;