ds_grid_filter_gaussian

COPY/// @func   ds_grid_filter_gaussian(grid, sigma)
///
/// @desc   Performs a Gaussian convolution on a given grid.
///         If sigma <= 0, no operation is performed.
///
/// @param  {grid}      grid        grid data structure
/// @param  {real}      sigma       standard deviation
///
/// GMLscripts.com/license

function ds_grid_filter_gaussian(grid, sigma)
{
    if (sigma > 0)
    {
        //  Select suitable filter size for sigma
        var size = ceil(6 * sigma);
        var n = 2 * sqr(sigma);
        var d = 1 / (sqrt(2*pi) * sigma);

        //  Compute Gaussian coefficients
        var g;
        for (var i=size; i>=0; i--)
        {
            g[i] = exp(-sqr(i) / n) * d;
        }

        //  Create working grids
        var w = ds_grid_width(grid);
        var h = ds_grid_height(grid);

        var work1 = ds_grid_create(w, h);
        var work2 = ds_grid_create(w, h);

        //  Filter horizontally
        ds_grid_copy(work1, grid);
        ds_grid_multiply_region(work1, 0, 0, w-1, h-1, g[0]);
        for (i=1; i<=size; i++)
        {
            ds_grid_copy(work2, grid);
            ds_grid_multiply_region(work2, 0, 0, w-1, h-1, g[i]);
            ds_grid_add_grid_region(work1, work2, 0, 0, w-1, h-1,  i, 0);
            ds_grid_add_grid_region(work1, work2, 0, 0, w-1, h-1, -i, 0);
        }

        //  Filter vertically
        ds_grid_copy(grid,work1);
        ds_grid_multiply_region(grid, 0, 0, w-1, h-1, g[0]);
        for (i=1; i<=size; i++)
        {
            ds_grid_copy(work2,work1);
            ds_grid_multiply_region(work2, 0, 0, w-1, h-1, g[i]);
            ds_grid_add_grid_region(grid, work2, 0, 0, w-1, h-1, 0,  i);
            ds_grid_add_grid_region(grid, work2, 0, 0, w-1, h-1, 0, -i);
        }

        //  Clean up
        ds_grid_destroy(work1);
        ds_grid_destroy(work2);
    }
}