PDL::VectorValued::Utils - Low-level utilities for vector-valued PDLs
use PDL; use PDL::VectorValued::Utils; ##--------------------------------------------------------------------- ## ... stuff happens
Signature: (c(M,N); indx [o]a(N); [o]b(M,N))
Run-length encode a set of vectors.
Higher-order rle(), for use with qsortvec().
Given set of vectors $c, generate a vector $a with the number of occurrences of each element (where an "element" is a vector of length $M ocurring in $c), and a set of vectors $b containing the unique values. As for rle(), only the elements up to the first instance of 0 in $a should be considered.
Can be used together with clump() to run-length encode "values" of arbitrary dimensions. Can be used together with rotate(), cat(), append(), and qsortvec() to count N-grams over a 1d PDL.
See also: PDL::Slices::rle, PDL::Ufunc::qsortvec, PDL::Primitive::uniqvec
rlevec 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.
Signature: (int a(N); b(M,N); [o]c(M,N))
Run-length decode a set of vectors, akin to a higher-order rld().
Given a vector $a() of the number of occurrences of each row, and a set $c() of row-vectors each of length $M, run-length decode to $c().
Can be used together with clump() to run-length decode "values" of arbitrary dimensions.
See also: PDL::Slices::rld.
rldvec 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.
Signature: (v(M,N); int [o]k(N))
Enumerate a list of vectors with locally unique keys.
Given a sorted list of vectors $v, generate a vector $k containing locally unique keys for the elements of $v (where an "element" is a vector of length $M ocurring in $v).
Note that the keys returned in $k are only unique over a run of a single vector in $v, so that each unique vector in $v has at least one 0 (zero) index in $k associated with it. If you need global keys, see enumvecg().
enumvec 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.
Enumerate a list of vectors with globally unique keys.
Given a sorted list of vectors $v, generate a vector $k containing globally unique keys for the elements of $v (where an "element" is a vector of length $M ocurring in $v). Basically does the same thing as:
$k = $v->vsearchvec($v->uniqvec);
... but somewhat more efficiently.
enumvecg 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.
Signature: (c(N); indx [o]a(N); [o]b(N))
Run-length encode a vector of subsequences.
Given a vector of $c() of concatenated variable-length, variable-offset subsequences, generate a vector $a containing the length of each subsequence and a vector $b containing the subsequence offsets. As for rle(), only the elements up to the first instance of 0 in $a should be considered.
See also PDL::Slices::rle.
rleseq 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.
Signature: (int a(N); b(N); [o]c(M))
Run-length decode a subsequence vector.
Given a vector $a() of sequence lengths and a vector $b() of corresponding offsets, decode concatenation of subsequences to $c(), as for:
$c = null; $c = $c->append($b($_)+sequence($a->type,$a($_))) foreach (0..($N-1));
rldseq 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.
Signature: (find(M); which(M,N); int [o]found())
Routine for searching N-dimensional values - akin to vsearch() for vectors.
$found = ccs_vsearchvec($find, $which); $nearest = $which->dice_axis(1,$found);
Returns for each row-vector in $find the index along dimension N of the least row vector of $which greater or equal to it. $which should be sorted in increasing order. If the value of $find is larger than any member of $which, the index to the last element of $which is returned.
$find
$which
See also: PDL::Primitive::vsearch().
vsearchvec 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.
The following functions are provided for lexicographic sorting of vectors, rsp. axis indices. As of PDL::VectorValued v1.0.12, vv_qsortvec() and vv_qsortveci() are just deprecated aliases for the builtin PDL functions of the same names. Older versions of this module used a dedicated implementation as a workaround for a bug in PDL-2.4.3, which has long since been fixed.
Signature: (a(N); b(N); int [o]cmp())
Lexicographically compare a pair of vectors.
cmpvec 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.
Signature: (a(n,m); [o]b(n,m))
Deprecated alias for PDL::Ufunc::qsortvec(), which see for details.
Signature: (a(n,m); indx [o]ix(m))
Deprecated alias for PDL::Ufunc::qsortveci(), which see for details.
The following functions are provided for set operations on sorted vector-valued PDLs.
Signature: (a(M,NA); b(M,NB); [o]c(M,NC); int [o]nc())
Union of two vector-valued PDLs. Input PDLs $a() and $b() MUST be sorted in lexicographic order. On return, $nc() holds the actual number of vector-values in the union.
In scalar context, slices $c() to the actual number of elements in the union and returns the sliced PDL.
vv_union 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.
Intersection of two vector-valued PDLs. Input PDLs $a() and $b() MUST be sorted in lexicographic order. On return, $nc() holds the actual number of vector-values in the intersection.
In scalar context, slices $c() to the actual number of elements in the intersection and returns the sliced PDL.
vv_intersect does not process bad values. It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
Set-difference ($a() \ $b()) of two vector-valued PDLs. Input PDLs $a() and $b() MUST be sorted in lexicographic order. On return, $nc() holds the actual number of vector-values in the computed vector set.
In scalar context, slices $c() to the actual number of elements in the output vector set and returns the sliced PDL.
vv_setdiff 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.
The following functions are provided for set operations on flat sorted PDLs with unique values. They may be more efficient to compute than the corresponding implementations via PDL::Primitive::setops().
Signature: (a(NA); b(NB); [o]c(NC); int [o]nc())
Union of two flat sorted unique-valued PDLs. Input PDLs $a() and $b() MUST be sorted in lexicographic order and contain no duplicates. On return, $nc() holds the actual number of values in the union.
In scalar context, reshapes $c() to the actual number of elements in the union and returns it.
v_union 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.
Intersection of two flat sorted unique-valued PDLs. Input PDLs $a() and $b() MUST be sorted in lexicographic order and contain no duplicates. On return, $nc() holds the actual number of values in the intersection.
In scalar context, reshapes $c() to the actual number of elements in the intersection and returns it.
v_intersect does not process bad values. It will set the bad-value flag of all output piddles if the flag is set for any of the input piddles.
Set-difference ($a() \ $b()) of two flat sorted unique-valued PDLs. Input PDLs $a() and $b() MUST be sorted in lexicographic order and contain no duplicate values. On return, $nc() holds the actual number of values in the computed vector set.
In scalar context, reshapes $c() to the actual number of elements in the difference set and returns it.
v_setdiff 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.
Signature: (a(M,N);b(M);float+ [o]vcos(N))
Computes the vector cosine similarity of a dense vector $b() with respect to each row $a(*,i) of a dense PDL $a(). This is basically the same thing as:
($a * $b)->sumover / ($a->pow(2)->sumover->sqrt * $b->pow(2)->sumover->sqrt)
... but should be must faster to compute, and avoids allocating potentially large temporaries for the vector magnitudes. Output values in $vcos() are cosine similarities in the range [-1,1], except for zero-magnitude vectors which will result in NaN values in $vcos().
You can use PDL threading to batch-compute distances for multiple $b() vectors simultaneously:
$bx = random($M, $NB); ##-- get $NB random vectors of size $N $vcos = vv_vcos($a,$bx); ##-- $vcos(i,j) ~ sim($a(,i),$b(,j))
vv_vcos() will set the bad status flag on the output piddle $vcos() if it is set on either of the input piddles $a() or $b(), but BAD values will otherwise be ignored for computing the cosine similarity.
Perl by Larry Wall
PDL by Karl Glazebrook, Tuomas J. Lukka, Christian Soeller, and others.
Code for rlevec() and rldvec() derived from the PDL builtin functions rle() and rld() in $PDL_SRC_ROOT/Basic/Slices/slices.pd
Probably many.
Bryan Jurish <moocow@cpan.org>
Code for qsortvec() copyright (C) Tuomas J. Lukka 1997. 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.
All other parts copyright (c) 2007-2021, Bryan Jurish. All rights reserved.
This package is free software, and entirely without warranty. You may redistribute it and/or modify it under the same terms as Perl itself.
perl(1), PDL(3perl)
To install PDL::VectorValued, copy and paste the appropriate command in to your terminal.
cpanm
cpanm PDL::VectorValued
CPAN shell
perl -MCPAN -e shell install PDL::VectorValued
For more information on module installation, please visit the detailed CPAN module installation guide.