=head1 NAME Data::Entropy::Algorithms - basic entropy-using algorithms =head1 SYNOPSIS use Data::Entropy::Algorithms qw(rand_bits rand_int rand_prob); $str = rand_bits(17); $i = rand_int(12345); $i = rand_int(Math::BigInt->new("1000000000000")); $j = rand_prob(1, 2, 3); $j = rand_prob([ 1, 2, 3 ]); use Data::Entropy::Algorithms qw(rand_fix rand rand_flt); $x = rand_fix(48); $x = rand(7); $x = rand_flt(0.0, 7.0); use Data::Entropy::Algorithms qw(pick pick_r choose choose_r shuffle shuffle_r); $item = pick($item0, $item1, $item2); $item = pick_r(\@items); @chosen = choose(3, $item0, $item1, $item2, $item3, $item4); $chosen = choose_r(3, \@items); @shuffled = shuffle($item0, $item1, $item2, $item3, $item4); $shuffled = shuffle_r(\@items); =head1 DESCRIPTION This module contains a collection of fundamental algorithms that use entropy. They all use the entropy source mechanism described in L<Data::Entropy>. =cut package Data::Entropy::Algorithms; { use 5.006; } use warnings; use strict; use Carp qw(croak); use Data::Entropy qw(entropy_source); use Data::Float 0.008 qw( have_subnormal min_normal_exp significand_bits float_is_finite float_parts float_sign mult_pow2 copysign ); use Params::Classify 0.000 qw(is_ref); our $VERSION = "0.008"; use parent "Exporter"; our @EXPORT_OK = qw( rand_bits rand_int rand_prob rand_fix rand rand_flt pick_r pick choose_r choose shuffle_r shuffle ); =head1 FUNCTIONS All of these functions use entropy. The entropy source is not an explicit input in any case. All functions use the current entropy source maintained by the C<Data::Entropy> module. To select an entropy source use the C<with_entropy_source> function in that module, or alternatively do nothing to use the default source. =head2 Fundamental entropy extraction =over =item rand_bits(NBITS) Returns NBITS bits of entropy, as a string of octets. If NBITS is not a multiple of eight then the last octet in the string has its most significant bits set to zero. =cut sub rand_bits($) { my($nbits) = @_; croak "need a non-negative number of bits to dispense" unless $nbits >= 0; return entropy_source->get_bits($nbits); } =item rand_int(LIMIT) LIMIT must be a positive integer. Returns a uniformly-distributed random integer in the range [0, LIMIT). LIMIT may be either a native integer, a C<Math::BigInt> object, or an integer-valued C<Math::BigRat> object; the returned number is of the same type. =cut sub rand_int($) { my($limit) = @_; croak "need a positive upper limit for random variable" unless $limit > 0; return entropy_source->get_int($limit); } =item rand_prob(PROB ...) =item rand_prob(PROBS) Returns a random integer selected with non-uniform probability. The relative probabilities are supplied as a list of non-negative integers (multiple PROB arguments) or a reference to an array of integers (the PROBS argument). The relative probabilities may be native integers, C<Math::BigInt> objects, or integer-valued C<Math::BigRat> objects; they must all be of the same type. At least one probability value must be positive. The first relative probability value (the first PROB or the first element of PROBS) is the relative probability of returning 0. The absolute probability of returning 0 is this value divided by the total of all the relative probability values. Similarly the second value controls the probability of returning 1, and so on. =cut sub rand_prob(@) { my $probs = @_ == 1 && is_ref($_[0], "ARRAY") ? $_[0] : \@_; my $total = 0; for(my $i = @$probs; $i--; ) { my $prob = $probs->[$i]; croak "probabilities must be non-negative" unless $prob >= 0; $total += $prob; } croak "can't have nothing possible" if $total == 0; for(my $i = @$probs; $i--; ) { my $prob = $probs->[$i]; $total -= $prob; return $i if entropy_source->get_prob($total, $prob); } } =back =head2 Numbers =over =item rand_fix(NBITS) Returns a uniformly-distributed random NBITS-bit fixed-point fraction in the range [0, 1). That is, the result is a randomly-chosen multiple of 2^-NBITS, the multiplier being a random integer in the range [0, 2^NBITS). The value is returned in the form of a native floating point number, so NBITS can be at most one greater than the number of bits of significand in the floating point format. With NBITS = 48 the range of output values is the same as that of the Unix C<drand48> function. =cut sub rand_fix($) { my($nbits) = @_; croak "need a non-negative number of bits to dispense" unless $nbits >= 0; croak "can't generate more than ".(significand_bits+1). " bits of fixed-point fraction" if $nbits > significand_bits+1; my $frac = 0.0; for(my $pos = 24; $pos <= $nbits; $pos += 24) { $frac += mult_pow2(rand_int(1 << 24), -$pos); } $frac += mult_pow2(rand_int(1 << ($nbits % 24)), -$nbits); return $frac; } =item rand([LIMIT]) Generates a random fixed-point fraction by C<rand_fix> and then multiplies it by LIMIT, returning the result. LIMIT defaults to 1, and if it is 0 then that is also treated as 1. The length of the fixed-point fraction is 48 bits, unless that can't be represented in the native floating point type, in which case the longest possible fraction will be generated instead. This is a drop-in replacement for C<CORE::rand>: it produces exactly the same range of output values, but using the current entropy source instead of a sucky PRNG with linear relationships between successive outputs. (C<CORE::rand> does the type of calculation described, but using the PRNG C<drand48> to generate the fixed-point fraction.) The details of behaviour may change in the future if the behaviour of C<CORE::rand> changes, to maintain the match. Where the source of a module can't be readily modified, it can be made to use this C<rand> by an incantation such as *Foreign::Module::rand = \&Data::Entropy::Algorithms::rand; This must be done before the module is loaded, most likely in a C<BEGIN> block. It is also possible to override C<CORE::rand> for all modules, by performing this similarly early: *CORE::GLOBAL::rand = \&Data::Entropy::Algorithms::rand; This function should not be used in any new code, because the kind of output supplied by C<rand> is hardly ever the right thing to use. The C<int(rand($n))> idiom to generate a random integer has non-uniform probabilities of generating each possible value, except when C<$n> is a power of two. For floating point numbers, C<rand> can't generate most representable numbers in its output range, and the output is biased towards zero. In new code use C<rand_int> to generate integers and C<rand_flt> to generate floating point numbers. =cut use constant RAND_NBITS => 48 > significand_bits+1 ? significand_bits+1 : 48; sub rand(;$) { my($limit) = @_; return rand_fix(RAND_NBITS) * (!defined($limit) || $limit == 0.0 ? 1.0 : $limit); } =item rand_flt(MIN, MAX) Selects a uniformly-distributed real number (with infinite precision) in the range [MIN, MAX] and then rounds this number to the nearest representable floating point value, which it returns. (Actually it is only I<as if> the function worked this way: in fact it never generates the number with infinite precision. It selects between the representable floating point values with the probabilities implied by this process.) This can return absolutely any floating point value in the range [MIN, MAX]; both MIN and MAX themselves are possible return values. All bits of the floating point type are filled randomly, so the range of values that can be returned depends on the details of the floating point format. (See L<Data::Float> for low-level floating point utilities.) The function C<die>s if MIN and MAX are not both finite. If MIN is greater than MAX then their roles are swapped: the order of the limit parameters actually doesn't matter. If the limits are identical then that value is always returned. As a special case, if the limits are positive zero and negative zero then a zero will be returned with a randomly-chosen sign. =cut sub rand_flt($$) { my($a, $b) = @_; croak "bounds for rand_flt() must be finite" unless float_is_finite($a) && float_is_finite($b); if($a == $b) { return $_[rand_int(2)] if $a == 0.0 && float_sign($a) ne float_sign($b); return $_[0]; } ($a, $b) = ($b, $a) if abs($a) < abs($b); my($prm_sign, $prm_max_exp, $prm_max_sgnf) = $a == 0.0 ? ("+", min_normal_exp, 0.0) : float_parts($a); my($b_sign, $b_exp, $b_sgnf) = $b == 0.0 ? ("+", min_normal_exp, 0.0) : float_parts($b); my($min_exp, $min_sgnf); my($opp_max_exp, $opp_max_sgnf); if($b_sign eq $prm_sign) { ($min_exp, $min_sgnf) = ($b_exp, $b_sgnf); ($opp_max_exp, $opp_max_sgnf) = (min_normal_exp, 0.0); } else { ($min_exp, $min_sgnf) = (min_normal_exp, 0.0); ($opp_max_exp, $opp_max_sgnf) = ($b_exp, $b_sgnf); } TRY_AGAIN: my $exp = $prm_max_exp; my $bdone = significand_bits; $bdone = 28 if $bdone > 28; my $prm_frng = $prm_max_sgnf * (1 << $bdone); if($prm_max_sgnf < 1.0) { # subnormal limit my $desired_rng = 1 << $bdone; while($bdone != significand_bits) { $bdone++; $prm_frng += $prm_frng; last if $prm_frng >= $desired_rng; } } my $prm_rng = int($prm_frng); $prm_rng++ if $prm_frng != $prm_rng; my $min_b = $bdone - ($exp - $min_exp); my $min_rng = $min_b >= 0 ? int(mult_pow2($min_sgnf, $min_b)) : 0; my $opp_b = $bdone - ($exp - $opp_max_exp); my $opp_frng = $opp_b >= 0 ? mult_pow2($opp_max_sgnf, $opp_b) : 0; my $opp_rng = int($opp_frng); $opp_rng++ if $opp_frng != $opp_rng; my $n = $min_rng + rand_int($prm_rng - $min_rng + $opp_rng); my($sg, $max_exp, $max_sgnf) = ($a, $prm_max_exp, $prm_max_sgnf); if($n >= $prm_rng) { $n -= $prm_rng; ($sg, $max_exp, $max_sgnf) = ($b, $opp_max_exp, $opp_max_sgnf); } while($n == 0 && $exp - $bdone - 1 >= min_normal_exp) { $exp -= $bdone + 1; $n = rand_int(2 << $bdone); } for(my $bit = 16; $bit; $bit >>= 1) { if($bdone >= $bit && $exp - $bit >= min_normal_exp && $n < (2 << ($bdone - $bit))) { $bdone -= $bit; $exp -= $bit; } } goto TRY_AGAIN if $exp < $min_exp; my $top_sgnf = $exp == $max_exp ? $max_sgnf : 2.0; my $bot_sgnf = $exp == $min_exp ? $min_sgnf : 1.0; my $sgnf = mult_pow2($n, -$bdone); if(!have_subnormal && $exp == min_normal_exp && $sgnf < 1.0) { $top_sgnf = 1.0; $sgnf = 0.0; } else { $bot_sgnf = 1.0 if !have_subnormal && $exp == min_normal_exp && $bot_sgnf < 1.0; while($bdone != significand_bits) { my $bseg = significand_bits - $bdone; $bseg = 28 if $bseg > 28; $bdone += $bseg; $sgnf += mult_pow2(rand_int(1 << $bseg), -$bdone); } } goto TRY_AGAIN if $sgnf < $bot_sgnf || $sgnf >= $top_sgnf; $sgnf = $top_sgnf if $sgnf == $bot_sgnf && rand_int(2); return copysign($sgnf == 0.0 ? 0.0 : mult_pow2($sgnf, $exp), $sg); } =back =head2 Combinatorics =over =item pick(ITEM ...) Randomly selects and returns one of the ITEMs. Each ITEM has equal probability of being selected. =item pick_r(ITEMS) ITEMS must be a reference to an array. Randomly selects and returns one of the elements of the array. Each element has equal probability of being selected. This is the same operation as that performed by C<pick>, but using references to avoid expensive copying of arrays. =cut sub pick_r($) { my($a) = @_; croak "need a non-empty array to pick from" unless is_ref($a, "ARRAY") && @$a; return $a->[rand_int(@$a)]; } sub pick(@) { pick_r(\@_) } =item choose(NCHOOSE, ITEM ...) Randomly selects NCHOOSE of the ITEMs. Each ITEM has equal probability of being selected. The chosen items are returned in a list in the same order in which they appeared in the argument list. =item choose_r(NCHOOSE, ITEMS) ITEMS must be a reference to an array. Randomly selects NCHOOSE of the elements in the array. Each element has equal probability of being selected. Returns a reference to an array containing the chosen items in the same order in which they appeared in the input array. This is the same operation as that performed by C<choose>, but using references to avoid expensive copying of arrays. =cut sub choose_r($$) { my($nchoose, $a) = @_; croak "need a non-negative number of items to choose" unless $nchoose >= 0; croak "need a sufficiently large array to pick from" unless is_ref($a, "ARRAY") && @$a >= $nchoose; my $ntotal = @$a; my $nleave = $ntotal - $nchoose; my @chosen; for(my $i = 0; $i != $ntotal; $i++) { if(entropy_source->get_prob($nleave, $nchoose)) { push @chosen, $a->[$i]; $nchoose--; } else { $nleave--; } } return \@chosen; } sub choose(@) { @{choose_r(shift, \@_)} } =item shuffle(ITEM ...) Reorders the ITEMs randomly, and returns them in a list in random order. Each possible order has equal probability. =item shuffle_r(ITEMS) ITEMS must be a reference to an array. Reorders the elements of the array randomly. Each possible order has equal probability. Returns a reference to an array containing the elements in random order. This is the same operation as that performed by C<shuffle>, but using references to avoid expensive copying of arrays. =cut sub shuffle_r($) { my($a) = @_; croak "need an array to shuffle" unless is_ref($a, "ARRAY"); $a = [ @$a ]; for(my $i = @$a; $i > 1; ) { my $j = rand_int($i--); @{$a}[$i, $j] = @{$a}[$j, $i]; } return $a; } sub shuffle(@) { @{shuffle_r(\@_)} } =back =head1 SEE ALSO L<Data::Entropy>, L<Data::Entropy::Source> =head1 AUTHOR Andrew Main (Zefram) <zefram@fysh.org> Maintained by Robert Rothenberg <rrwo@cpan.org> =head1 COPYRIGHT Copyright (C) 2006, 2007, 2009, 2011, 2025 Andrew Main (Zefram) <zefram@fysh.org> =head1 LICENSE This module is free software; you can redistribute it and/or modify it under the same terms as Perl itself. =cut 1;