PDL::CCS::Compat - Backwards-compatibility module for PDL::CCS
use PDL; use PDL::CCS::Compat; ##-- source pdl $a = random($N=8,$M=7); ##--------------------------------------------------------------------- ## Non-missing value counts $nnz = $a->flat->nnz; ##-- "missing" == 0 $nnaz = $a->flat->nnza(1e-6); ##-- "missing" ~= 0 #$ngood = $a->ngood; ##-- "missing" == BAD (see PDL::Bad) ##--------------------------------------------------------------------- ## CCS Encoding ($ptr,$rowids,$vals) = ccsencode_nz ($a); # missing == 0 ($ptr,$rowids,$vals) = ccsencode_naz($a,$eps); # missing ~= 0 ($ptr,$rowids,$vals) = ccsencode_g ($a); # missing == BAD ($ptr,$rowids,$vals) = ccsencode_i ($i,$ivals,$N); # generic flat ($ptr,$rowids,$vals) = ccsencode_i2d($xi,$yi,$ivals); # generic 2d ##--------------------------------------------------------------------- ## CCS Decoding $cols = ccsdecodecols($ptr,$rowids,$nzvals, $xvals $a2 = ccsdecode ($ptr,$rowids,$vals); # missing == 0 $a2 = ccsdecode_g($ptr,$rowids,$vals); # missing == BAD ##--------------------------------------------------------------------- ## CCS Index Conversion $nzi = ccsitonzi ($ptr,$rowids, $ix, $missing); # ix => nzi $nzi = ccsi2dtonzi($ptr,$rowids, $xi,$yi, $missing); # 2d => nzi $ix = ccswhich ($ptr,$rowids,$vals); # CCS => ix ($xi,$yi) = ccswhichND($ptr,$rowids,$vals); # CCS => 2d $xyi = ccswhichND($ptr,$rowids,$vals); # ...as scalar ##--------------------------------------------------------------------- ## CCS Lookup $ixvals = ccsget ($ptr,$rowids,$vals, $ix,$missing); # ix => values $ixvals = ccsget2d($ptr,$rowids,$vals, $xi,$yi,$missing); # 2d => values ##--------------------------------------------------------------------- ## CCS Operations ($ptrT,$rowidsT,$valsT) = ccstranspose($ptr,$rowids,$vals); # CCS<->CRS ##--------------------------------------------------------------------- ## Vector Operations, by column $nzvals_out = ccsadd_cv ($ptr,$rowids,$nzvals, $colvec); $nzvals_out = ccsdiff_cv($ptr,$rowids,$nzvals, $colvec); $nzvals_out = ccsmult_cv($ptr,$rowids,$nzvals, $colvec); $nzvals_out = ccsdiv_cv ($ptr,$rowids,$nzvals, $colvec); ##--------------------------------------------------------------------- ## Vector Operations, by row $nzvals_out = ccsadd_rv ($ptr,$rowids,$nzvals, $rowvec); $nzvals_out = ccsdiff_rv($ptr,$rowids,$nzvals, $rowvec); $nzvals_out = ccsmult_rv($ptr,$rowids,$nzvals, $rowvec); $nzvals_out = ccsdiv_rv ($ptr,$rowids,$nzvals, $rowvec); ##--------------------------------------------------------------------- ## Scalar Operations $nzvals_out = $nzvals * 42; # ... or whatever ##--------------------------------------------------------------------- ## Accumulators $rowsumover = ccssumover ($ptr,$rowids,$nzvals); ##-- like $a->sumover() $colsumovert = ccssumovert($ptr,$rowids,$nzvals); ##-- like $a->xchg(0,1)->sumover
Signature: (indx awhich(2,Nnz); avals(Nnz); indx $N; indx $M; indx [o]ptr(N); indx [o]rowids(Nnz); [o]nzvals(Nnz))
Generic wrapper for backwards-compatible ccsencode() variants.
Signature: (a(N,M); indx [o]ptr(N); indx [o]rowids(Nnz); [o]nzvals(Nnz))
Encodes matrix $a() in compressed column format, interpreting zeroes as "missing" values.
Allocates output vectors if required.
Signature: (a(N,M); eps(); indx [o]ptr(N); indx [o]rowids(Nnz); [o]nzvals(Nnz))
Encodes matrix $a() in CCS format interpreting approximate zeroes as "missing" values. This function is just like ccsencode_nz(), but uses the tolerance parameter $eps() to determine which elements are to be treated as zeroes.
Encodes matrix $a() in CCS format interpreting BAD values as "missing". Requires bad-value support built into PDL.
Signature: (indx ix(Nnz); nzvals(Nnz); indx $N; int [o]ptr(N); indx [o]rowids(Nnz); [o]nzvals_enc(Nnz))
General-purpose CCS encoding method for flat indices. Encodes values $nzvals() from flat-index locations $ix() into a CCS matrix ($ptr(), $rowids(), $nzvals_enc()).
$N (~ $a->dim(0)) must be specified.
Signature: ( indx xvals(Nnz) ; indx yvals(Nnz) ; nzvals(Nnz) ; indx $N ; ##-- optional indx [o]ptr(N) ; indx [o]rowids(Nnz) ; [o]nzvals_enc(Nnz); )
General-purpose encoding method. Encodes values $nzvals() from 2d-index locations ($xvals(), $yvals()) in an $N-by-(whatever) PDL into a CCS matrix $ptr(), $rowids(), $nzvals_enc().
Allocates output vectors if required. If $N is omitted, it defaults to the maximum column index given in $xvals().
Signature: ( indx ptr (N) ; indx rowids (Nnz); nzvals (Nnz); indx xvals (I) ; # default=sequence($N) missing() ; # default=0 M () ; # default=rowids->max+1 [o]cols (I,M); # default=new )
Extract dense columns from a CCS-encoded matrix (no dataflow). Allocates output matrix if required. If $a(N,M) was the dense source matrix for the CCS-encoding, and if missing values are zeros, then the following two calls are equivalent (modulo data flow):
$cols = $a->dice_axis(1,$col_ix); $cols = ccsdecodecols($ptr,$rowids,$nzvals, $col_ix,0);
Signature: (indx ptr(N); indx rowids(Nnz); nzvals(Nnz); $M; [o]dense(N,M))
Decodes compressed column format vectors $ptr(), $rowids(), and $nzvals() into dense output matrix $a(). Allocates the output matrix if required.
Note that if the original matrix (pre-encoding) contained trailing rows with no nonzero elements, such rows will not be allocated by this method (unless you specify either $M or $dense). In such cases, you might prefer to call ccsdecodecols() directly.
Convenience method. Like ccsdecode() but sets "missing" values to BAD.
Signature: (indx ptr(N); indx rowids(Nnz); indx ind(2,I); indx missing(); indx [o]nzix(I))
Convert N-dimensional index values $ind() appropriate for a dense matrix (N,M) into indices $nzix() appropriate for the $rowids() and/or $nzvals() components of the CCS-encoded matrix ($ptr(),$rowids(),$nzvals()). Missing values are returned in $nzix() as $missing().
Signaure: (indx ptr(N); indx rowids(Nnz); indx col_ix(I); indx row_ix(I); indx missing(); indx [o]nzix(I))
Convert 2d index values $col_ix() and $row_ix() appropriate for a dense matrix (N,M) into indices $nzix() appropriate for the $rowids() and/or $nzvals() components of the CCS-encoded matrix ($ptr(),$rowids(),$nzvals()). Missing values are returned in $nzix() as $missing().
Signature: (indx ptr(N); indx rowids(Nnz); indx ix(I); indx missing(); indx [o]nzix(I))
Convert flat index values $ix() appropriate for a dense matrix (N,M) into indices $nzix() appropriate for the $rowids() and/or $nzvals() components of the CCS-encoded matrix ($ptr(),$rowids(),$nzvals()). Missing values are returned in $nzix() as $missing().
Signature: (indx ptr(N); indx rowids(Nnz); nzvals(Nnz); indx [o]which_cols(Nnz); indx [o]which_rows(Nnz)',
In scalar context, returns concatenation of $which_cols() and $which_rows(), similar to the builtin whichND(). Note however that ccswhichND() may return its index PDLs sorted in a different order than the builtin whichND() method for dense matrices. Use the qsort() or qsorti() methods if you need sorted index PDLs.
Signature: (indx ptr(N); indx rowids(Nnz); nzvals(Nnz); indx [o]which(Nnz); indx [t]wcols(Nnz)',
Convenience method. Calls ccswhichfull(), and scales the output PDLs to correspond to a flat enumeration. The output PDL $which() is not guaranteed to be sorted in any meaningful order. Use the qsort() method if you need sorted output.
Signature: (indx ptr(N); indx rowids(Nnz); nzvals(Nnz); indx [o]ptrT(M); indx [o]rowidsT(Nnz); [o]nzvalsT(Nnz)',
Transpose a compressed matrix.
Signature: (indx ptr(N); indx rowids(Nnz); nzvals(Nnz); indx xvals(I); indx yvals(I); missing(); [o]ixvals(I))
Lookup values in a CCS-encoded PDL by 2d source index (no dataflow). Pretty much like ccsi2dtonzi(), but returns values instead of indices. If you know that your index PDLs $xvals() and $yvals() do not refer to any missing values in the CCS-encoded matrix, then the following two calls are equivalent (modulo dataflow):
$ixvals = ccsget2d ($ptr,$rowids,$nzvals, $xvals,$yvals,0); $ixvals = index($nzvals, ccsi2dtonzi($ptr,$rowids, $xvals,$yvals,0));
The difference is that only the second incantation will cause subsequent changes to $ixvals to be propagated back into $nzvals.
Signature: (indx ptr(N); indx rowids(Nnz); nzvals(Nnz); indx ix(I); missing(); [o]ixvals(I))
Lookup values in a CCS-encoded PDL by flat source index (no dataflow). Pretty much like ccsitonzi(), but returns values instead of indices. If you know that your index PDL $ix() does not refer to any missing values in the CCS-encoded matrix, then the following two calls are equivalent (modulo dataflow):
$ixvals = ccsget ($ptr,$rowids,$nzvals, $ix,0); $ixvals = index($nzvals, ccsitonzi($ptr,$rowids, $ix,0))
Signature: (indx ptr(N); indx rowids(Nnz); nzvals_in(Nnz); colvec(M); [o]nzvals_out(Nnz))
Column-vector operation ${OP} on CCS-encoded PDL.
Should do something like the following (without decoding the CCS matrix):
($colvec ${OP} ccsdecode(\$ptr,\$rowids,\$nzvals))->ccsencode;
Missing values in the CCS-encoded PDL are not affected by this operation.
${OP} is one of the following:
plus ##-- addition (alias: 'add') minus ##-- subtraction (alias: 'diff') mult ##-- multiplication (NOT matrix-multiplication) divide ##-- division (alias: 'div') modulo ##-- modulo power ##-- potentiation gt ##-- greater-than ge ##-- greater-than-or-equal lt ##-- less-than le ##-- less-than-or-equal eq ##-- equality ne ##-- inequality spaceship ##-- 3-way comparison and2 ##-- binary AND or2 ##-- binary OR xor ##-- binary XOR shiftleft ##-- left-shift shiftright ##-- right-shift
Signature: (indx ptr(N); indx rowids(Nnz); nzvals_in(Nnz); rowvec(N); [o]nzvals_out(Nnz))
Row-vector operation ${OP} on CCS-encoded PDL. Should do something like the following (without decoding the CCS matrix):
($column->slice("*1,") ${OP} ccsdecode($ptr,$rowids,$nzvals))->ccsencode;
Missing values in the CCS-encoded PDL are not effected by this operation.
See ccs${OP}_cv() above for supported operations.
$a = pdl([ [10, 0, 0, 0,-2, 0], [3, 9, 0, 0, 0, 3], [0, 7, 8, 7, 0, 0], [3, 0, 8, 7, 5, 0], [0, 8, 0, 9, 9, 13], [0, 4, 0, 0, 2, -1] ]); ($ptr,$rowids,$nzvals) = ccsencode($a); print join("\n", "ptr=$ptr", "rowids=$rowids", "nzvals=$nzvals");
... prints something like:
ptr=[0 3 7 9 12 16] rowids=[ 0 1 3 1 2 4 5 2 3 2 3 4 0 3 4 5 1 4 5] nzvals=[10 3 3 9 7 8 4 8 8 7 7 9 -2 5 9 2 3 13 -1]
##-- create a random sparse matrix $a = random(100,100); $a *= ($a>.9); ##-- encode it ($ptr,$rowids,$nzvals) = ccsencode($a); ##-- what did we save? sub pdlsize { return PDL::howbig($_[0]->type)*$_[0]->nelem; } print "Encoding saves us ", ($saved = pdlsize($a) - pdlsize($ptr) - pdlsize($rowids) - pdlsize($nzvals)), " bytes (", (100.0*$saved/pdlsize($a)), "%)\n";
Encoding saves us 71416 bytes (89.27%)
##-- random matrix $a = random(100,100); ##-- make an expensive copy of $a by encoding & decoding ($ptr,$rowids,$nzvals) = ccsencode($a); $a2 = ccsdecode($ptr,$rowids,$nzvals); ##-- ...and make sure it's good print all($a==$a2) ? "Decoding is good!\n" : "Nasty icky bug!\n";
Perl by Larry Wall.
PDL by Karl Glazebrook, Tuomas J. Lukka, Christian Soeller, and others.
Original inspiration and algorithms from the SVDLIBC C library by Douglas Rohde; which is itself based on SVDPACKC by Michael Berry, Theresa Do, Gavin O'Brien, Vijay Krishna and Sowmini Varadhan.
Many.
Bryan Jurish <moocow@cpan.org>
Copyright (C) 2005-2018, 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), PDL::SVDLIBC(3perl), PDL::CCS::Nd(3perl),
SVDLIBC: http://tedlab.mit.edu/~dr/SVDLIBC/
SVDPACKC: http://www.netlib.org/svdpack/
To install PDL::CCS, copy and paste the appropriate command in to your terminal.
cpanm
cpanm PDL::CCS
CPAN shell
perl -MCPAN -e shell install PDL::CCS
For more information on module installation, please visit the detailed CPAN module installation guide.