Joh*_*ohn 8 matlab 2d histogram
我已经为2个matlab向量编写了一个2D直方图算法.不幸的是,我无法弄清楚如何对其进行矢量化,并且它对于我的需求来说太慢了一个数量级.这是我有的:
    function [ result ] = Hist2D( vec0, vec1 )
%Hist2D takes two vectors, and computes the two dimensional histogram
% of those images.  It assumes vectors are non-negative, and bins
% are the integers.
%
%  OUTPUTS
%      result - 
%         size(result) = 1 + [max(vec0) max(vec1)]
%         result(i,j)  = number of pixels that have value 
%                             i-1 in vec0 and value j-1 in vec1.
    result = zeros(max(vec0)+1, max(vec1)+1);
    fvec0 = floor(vec1)+1;
    fvec1 = floor(vec0)+1;
    % UGH, This is gross, there has to be a better way...
    for i = 1 : size(fvec0);
        result(fvec0(i), fvec1(i)) = 1 + result(fvec0(i), fvec1(i));
    end
end
思考?
谢谢!!约翰
Amr*_*mro 19
这是我的2D直方图版本:
%# some random data
X = randn(2500,1);
Y = randn(2500,1)*2;
%# bin centers (integers)
xbins = floor(min(X)):1:ceil(max(X));
ybins = floor(min(Y)):1:ceil(max(Y));
xNumBins = numel(xbins); yNumBins = numel(ybins);
%# map X/Y values to bin indices
Xi = round( interp1(xbins, 1:xNumBins, X, 'linear', 'extrap') );
Yi = round( interp1(ybins, 1:yNumBins, Y, 'linear', 'extrap') );
%# limit indices to the range [1,numBins]
Xi = max( min(Xi,xNumBins), 1);
Yi = max( min(Yi,yNumBins), 1);
%# count number of elements in each bin
H = accumarray([Yi(:) Xi(:)], 1, [yNumBins xNumBins]);
%# plot 2D histogram
imagesc(xbins, ybins, H), axis on %# axis image
colormap hot; colorbar
hold on, plot(X, Y, 'b.', 'MarkerSize',1), hold off

请注意,我删除了"非负"限制,但保留了整数bin中心(这可以很容易地更改为划分范围到相同大小的指定数量的bin而不是"fractions").
这主要是受@SteveEddins 博客文章的启发.