# hist2d!

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`

.

## Examples

```
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,## User Contributed Notes

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