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在我之前的问题的概括中，如何对单元元素（它们本身是并且应该保持数组本身）执行加权平均？

我将首先像这样修改gnovice 的答案：

dim = ndims(c{1});          %# Get the number of dimensions for your arrays
M = cat(dim+1,c{:});        %# Convert to a (dim+1)-dimensional matrix
meanArray = sum(M.*weigth,dim+1)./sum(weigth,dim+1);  %# Get the weighted mean across arrays

在此之前确保weight具有正确的形状。我认为需要处理的三种情况是

  1. weight = 1（或任何常数）=> 返回通常的平均值
  2. numel(weight) == length(c) => weight 是每个单元元素 c{n} （但对于固定 n 的每个数组元素相等）
  3. numel(weight) == numel(cell2mat(c)) => 每个数组元素都有自己的权重...

案例 1 很简单，案例 3 不太可能发生，所以目前我对案例 2 感兴趣：如何将权重转换为一个数组，使得M.*weight上述总和具有正确的维度？当然，也可以理解显示获得加权平均值的另一种方法的答案。

编辑事实上，如果权重与 c 具有相同的结构，则案例 3 甚至比案例 1更微不足道（多么重言式，道歉） 。

这是我对案例 2 的意思的示例：

c = { [1 2 3; 1 2 3], [4 8 3; 4 2 6] };
weight = [ 2, 1 ];

应该返回

meanArray = [ 2 4 3; 2 2 4 ]

（例如对于第一个元素 (2*1 + 1*4)/(2+1) = 2）

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1 回答 1

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在熟悉REPMAT之后，现在这是我的解决方案：

function meanArray = cellMean(c, weight)
% meanArray = cellMean(c, [weight=1])
% mean over the elements of a cell c, keeping matrix structures of cell
% elements etc. Use weight if given.

% based on http://stackoverflow.com/q/5197692/321973, courtesy of gnovice
% (http://stackoverflow.com/users/52738/gnovice)
% extended to weighted averaging by Tobias Kienzler
% (see also http://stackoverflow.com/q/5231406/321973)

dim = ndims(c{1});          %# Get the number of dimensions for your arrays
if ~exist('weight', 'var') || isempty(weight); weight = 1; end;
eins = ones(size(c{1})); % that is german for "one", creative, I know...
if ~iscell(weight)
    % ignore length if all elements are equal, this is case 1
    if isequal(weight./max(weight(:)), ones(size(weight)))
        weight = repmat(eins, [size(eins)>0 length(c)]);
    elseif isequal(numel(weight), length(c)) % case 2: per cell-array weigth
        weight = repmat(shiftdim(weight, -3), [size(eins) 1]);
    else
        error(['Weird weight dimensions: ' num2str(size(weight))]);
    end
else % case 3, insert some dimension check here if you want
    weight = cat(dim+1,weight{:});
end;

M = cat(dim+1,c{:});        %# Convert to a (dim+1)-dimensional matrix
sumc = sum(M.*weight,dim+1);
sumw = sum(weight,dim+1);
meanArray = sumc./sumw;  %# Get the weighted mean across arrays
于 2011-03-09T10:31:03.167 回答