Re^11: Randomly biased, random numbers.

Your translation looks correct, so I'm a bit surprised by the result. I only tested it in 1-D, but the histogram looked plenty spiky. You could make it spikier by raising the random numbers used to generate @fx to some power, but it sounds like you found another solution.

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Re^12: Randomly biased, random numbers.
by BrowserUk (Patriarch) on Dec 08, 2013 at 07:36 UTC

You could make it spikier by raising the random numbers used to generate @fx to some power

Indeed, adding a power component causes much more clumpiness, and making the power component variable:

my @fx = @{ 
    reduce( sub{ push @$a, $a->[-1]+$b; $a }, [ 0 ], map{ rand()**rand
+(3) } 1..10 ) 
};
[download]

gives a nice variability.

But yes, I am currently much enamoured of my weight-map solution. Some of the grey-scale images it produces are just downright beautiful :)

But thankyou for your input. The vectorising of the 3D weight-map to 1D weight-stick my solution uses. came directly from your example, and I understand a little more about matlab/octave now :)

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