hist2d!(counts, M, e1, e2) -> (e1, e2, counts)

Compute a "2d histogram" with respect to the bins delimited by the edges given in e1 and e2. This function writes the results to a pre-allocated array counts.


julia> counts = zeros(Int, 3, 3);
julia> M = [1.2, 2.5, 0.8, 1.7, 2.9];
julia> e1 = [0.0, 1.0, 2.0, 3.0];
julia> e2 = [0.0, 1.5, 3.0, 4.5];

julia> hist2d!(counts, M, e1, e2)
([0.0, 1.0, 2.0, 3.0], [0.0, 1.5, 3.0, 4.5], [0 1 0; 1 1 0; 0 0 0])

julia> counts
3×3 Array{Int64,2}:
 0  1  0
 1  1  0
 0  0  0

This example demonstrates how to use hist2d! to compute a 2D histogram. The counts array is pre-allocated with zeros and has dimensions (3, 3). The M array contains the data points. The e1 and e2 arrays define the bin edges. The function computes the histogram and modifies the counts array in-place. The function returns a tuple containing the bin edges and the modified counts array.

Note: It is important to ensure that the dimensions of the counts array match the number of bins specified by the bin edges. Also, make sure that the data points in M fall within the range defined by the bin edges to obtain accurate results.

See Also

cummax, eigmax, findmax, hist, hist!, hist2d, hist2d!, histrange, indmax, maxabs, maxabs!, maximum!, mean, mean!, median, median!, minabs, minabs!, minimum!, minmax, quantile!, realmax, std, stdm,

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