Combinations and permutations
Raku can't compute arbitrary large floating point values, thus we will use logarithms, as is often needed when dealing with combinations. We'll also use a Stirling method to approximate ln ( n ! ) {\displaystyle \ln(n!)} :
ln n ! ≈ 1 2 ln ( 2 π n ) + n ln ( n e + 1 12 e n ) {\displaystyle \ln n!\approx {\frac {1}{2}}\ln(2\pi n)+n\ln \left({\frac {n}{e}}+{\frac {1}{12en}}\right)}
Notice that Raku can process arbitrary long integers, though. So it's not clear whether using floating points is useful in this case.
multi P($n, $k) { [*] $n - $k + 1 .. $n }
multi C($n, $k) { P($n, $k) / [*] 1 .. $k }
sub lstirling(\n) {
n < 10 ?? lstirling(n+1) - log(n+1) !!
.5*log(2*pi*n)+ n*log(n/e+1/(12*e*n))
}
role Logarithm {
method gist {
my $e = (self/10.log).Int;
sprintf "%.8fE%+d", exp(self - $e*10.log), $e;
}
}
multi P($n, $k, :$float!) {
(lstirling($n) - lstirling($n -$k))
but Logarithm
}
multi C($n, $k, :$float!) {
(lstirling($n) - lstirling($n -$k) - lstirling($k))
but Logarithm
}
say "Exact results:";
for 1..12 -> $n {
my $p = $n div 3;
say "P($n, $p) = ", P($n, $p);
}
for 10, 20 ... 60 -> $n {
my $p = $n div 3;
say "C($n, $p) = ", C($n, $p);
}
say '';
say "Floating point approximations:";
for 5, 50, 500, 1000, 5000, 15000 -> $n {
my $p = $n div 3;
say "P($n, $p) = ", P($n, $p, :float);
}
for 100, 200 ... 1000 -> $n {
my $p = $n div 3;
say "C($n, $p) = ", C($n, $p, :float);
}Output:
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