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Random::PoissonDisc - distribute points aesthetically in R^n
my $points = Random::PoissonDisc->points(
dimensions => [100,100],
r => $r,
print join( ",", @$_),"\n"
for @$points;
This module allows relatively fast (O(N)) generation of random points in
*n*-dimensional space with a distance of at least `r' between each
other. This distribution results in aesthetic so called "blue noise".
The algorithm was adapted from a sketch by Robert Bridson in
All vectors (or points) are represented as anonymous arrays of numbers.
All have the same dimension as the cardinality of the `dimensions' array
passed in the `->points' method.
`Random::PoissonDisc->points( %options )'
Returns a reference to an array of points.
Acceptable options are:
* `<r'> - minimum distance between points.
Default is 10 units.
* `<dimensions'> - number of dimensions and respective value range as
an arrayref.
Default is
[ 100, 100 ]
meaning all points will be in R^2 , with each coordinate in the
range [0, 100).
* `<candidates'> - Number of candidates to inspect before deciding
that no ew neighbours can be placed around a point.
Default is 30.
This number may or may not need to be tweaked if you go further up
in dimensionality beyond 3 dimensions. The more candidates you
inspect the longer the algorithm will run for generating a number of
In the algorithm description, this constant is named *k*.
These subroutines are used for the algorithm. If you want to port this
module to PDL or any other vector library, you will likely have to
rewrite these.
`rnd( $low, $high )'
print rnd( 0, 1 );
Returns a uniform distributed random number in `[ $low, $high )'.
`grid_coords( $grid_size, $point )'
Returns the string representing the coordinates of the grid cell in
which `$point' falls.
`norm( @vector )'
print norm( 1,1 ); # 1.4142
Returns the Euclidean length of the vector, passed in as array.
`vdist( $l, $r )'
print vdist( [1,0], [0,1] ); # 1.4142
Returns the Euclidean distance between two points (or vectors)
`neighbour_points( $size, $point, $grid )'
my @neighbours = neighbour_points( $size, $p, \%grid )
Returns the points from the grid that have a distance between 0 and 2r
around `$point'. These points are the candidates to check when trying to
insert a new random point into the space.
`random_unit_vector( $dimensions )'
print join ",", @{ random_unit_vector( 2 ) };
Returns a vector of unit lenght poiting in a random uniform distributed
*n*-dimensional direction angle and returns a unit vector pointing in
that direction
The algorithm used is outlined in Knuth, _The Art of Computer
Programming_, vol. 2, 3rd. ed., section 3.4.1.E.6. but has not been
verified formally or mathematically by the module author.
The module does not use PDL or any other vector library.
The public repository of this module is
The public support forum of this module is
Please report bugs in this module via the RT CPAN bug queue at or
via mail to
Max Maischein `'
Copyright 2011 by Max Maischein `'.
This module is released under the same terms as Perl itself.