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Rather than binning the area values, they could be mapped to a continuous interval. For example, we could:
'equalise' the value distribution through a non-linear mapping - eg compute (area rank)/(number of areas) to obtain a value between 0 and 1
linearly map the values to the (0,1) interval by computing (y-y_min)/(y_max-y_min). This can be made more robust to data outliers by mapping between the nth and nth last percentiles, rather than the min and max.
apply any other transforms such as truncated logarithm
Rather than binning the area values, they could be mapped to a continuous interval. For example, we could:
We then apply the colour map function to each value to compute a RGB colour. There are many choices of such functions in the literature, but a perceptually linear colour map would be a principled choice - Matplotlib implements a bunch of (often piecewise-linear) functions that could be easily ported to javascript:
http://matplotlib.org/examples/color/colormaps_reference.html
https://github.com/matplotlib/matplotlib/blob/master/lib/matplotlib/_cm.py
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