This example creates a histogram2 object, and then shows how to adjust the properties of the histogram to affect the output display.

Generate 1,000 random numbers in each dimension and create a bivariate histogram.

x = randn(1000,1);
y = randn(1000,1);
h = histogram2(x,y)

h = 

  Histogram2 with properties:

             Data: [1000×2 double]
           Values: [15×15 double]
          NumBins: [15 15]
        XBinEdges: [1×16 double]
        YBinEdges: [1×16 double]
         BinWidth: [0.5000 0.5000]
    Normalization: 'count'
        FaceColor: 'auto'
        EdgeColor: [0.1500 0.1500 0.1500]

  Use GET to show all properties

Change the normalization of the histogram by setting the Normalization property to 'probability'.

h.Normalization = 'probability';

Change the bin limits in each dimension so that and . When you set XBinLimits or YBinLimits, the XBinLimitsMode or YBinLimitsMode property automatically changes to 'manual'.

h.XBinLimits = [-5 5];
h.YBinLimits = [-2 2];

Show the empty bins.

h.ShowEmptyBins = 'on';

Change the display style to show tiles. Switch to a 2-D view.

h.DisplayStyle = 'tile';
view(2)

Use the savefig function to save a histogram2 figure.

y = histogram2(randn(100,1),randn(100,1));
savefig('histogram2.fig');
clear all
close all

Use openfig to load the histogram figure back into MATLAB. openfig also returns a handle to the figure, h.

h = openfig('histogram2.fig');

Use the findobj function to locate the correct object handle from the figure handle. This allows you to continue manipulating the original histogram object used to generate the figure.

y = findobj(h, 'type', 'histogram2')

y = 

  Histogram2 with properties:

             Data: [100×2 double]
           Values: [7×6 double]
          NumBins: [7 6]
        XBinEdges: [-3 -2 -1 0 1 2 3 4]
        YBinEdges: [-3 -2 -1 0 1 2 3]
         BinWidth: [1 1]
    Normalization: 'count'
        FaceColor: 'auto'
        EdgeColor: [0.1500 0.1500 0.1500]

  Use GET to show all properties