Or if you have thoughts on how to generate same?

You can generate a few triples of random numbers and use them as centers for the new cluster. Then for each center, you can generate a random number of points that are close.

For example you can use a gaussian distribution around the centers. For that you need normally distributed random numbers, which you can generate with the Box–Muller transform out of the uniformly distributed random numbers that perl's rand generates.

Depending on the data you want to emulate, you might also want to add a number of totally random, non-clustered points.

Perl 6 - second systems done right

In reply to Re: 3D test data that exhibits clustering? by moritz
in thread 3D test data that exhibits clustering? by BrowserUk

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