How to construct a weighed 2D histogram?
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Hey,
I am finding it hard to construct a weighed 2D histogram.
Let us assume that we have two vectors, X and Y, of equal length N such that the entries in each of X and Y are not necessarily unique. Similarly, let's assume that W represents an array of N non-unique, non-integer values weighing each sample point [ X(i), Y(i) ].
To construct a standard 2D histogram, I am aware one can simply use
H = histogram2( X, Y )
to plot (along the z-axis) the sum/count of number of points per bin.
My question: how can I modify this to account for the weight of every sample point within a bin? That is, for the result to be the sum of the weights of all points within a bin.
(Note that this is not equivalent to merely weighing the count per bin by a constant value)
Thanks for any suggestions!
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Answers (2)
John D'Errico
on 12 Jul 2019
Just use accumarray to sum the weights in each bin.
3 Comments
John D'Errico
on 12 Jul 2019
Did you read the help for accumarray? Why not? Note that there are 8 examples of use of accumarray, here:
help accumarray
There will be more complete examples and explanations in
doc accumarray
READ THE HELP!
You will find that you first need to use discretize to bin each sample, so do that twice, once for each dimension. But again, you will find examples in the help. I cannot do better than to re-write the help, and how will that gain you or me?
help discretize
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