algorithmic modeling for Rhino
I am using the image sampler to produce a 2D representation of the population density around the globe.
Instead of using circle radius to represent differences in density, I would like to have a higher density of points where the population density is higher.
Does anybody know how to do this?
Attached below is the GH file and the image file.
Fraser
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Image sampler returns the brightness of particular pixels inside of assigned picture, related to particular point in Rhino. It can return saturation, RGB colors..., but in this case I chose brightness.
I divided that list of brightnesses for each point in few lists based on their brightness values - for example list1 are only points with brightness value >0.98, list2 two are only points with brightness value >0.95 but <0.98 and so on...
Then I used True, False pattern to cull points from these lists, in a way that, the less value of brightness the list has, the more circles inside of it are culled (more False patterns are).
This means that list with largest values of brightness (closer to 1.0) will have less circles culled, and vice versa - lists with smallest values of brightness (closer to 0.0) will have more circles culled.
This is one way of achieving the density pattern you requested.
How can I make this definition result in only 3 controlled diameter circles.
Thanks in advance.
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