Grouping 2d data with different bins for each dimension.

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Dear guys I'm trying to group my 2d data but with poor results.
My input are x and y. At first I divide them into bins with different dimensions as it follows:
a=(min(x):0.2:max(x))'; %17x1
b=(min(y):0.2:max(y))'; %34x1
At this point through I asses the distributions in each bin:
Finally, I subplot my data in order to have at the left side the scatter of points while at the other an heatmap:
subplot(1, 2, 1);
scatter(x, y, 'r.');
subplot(1, 2, 2);
imagesc(a, b, N);
Unfortunately this is my result
The right side is correct but somehow in the wrong side. How can I correct this?

Accepted Answer

Cris LaPierre
Cris LaPierre on 26 Oct 2021
An image axis has the origin and the top left while a cartesian axis has the origin at the bottom left.
Counsider using histogram2 with the 'DisplayStyle' set to 'tile' instead of histcounts2 and imagesc. See this example.
Cris LaPierre
Cris LaPierre on 26 Oct 2021
I'm not sure if that specific option exists, but look into the Normalization options. This is one of the name-value pair arguments for histogram2. Options are
  • 'count' (default)
  • 'probability'
  • 'countdensity'
  • 'pdf'
  • 'cumcount'
  • 'cdf'

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