如何计算单元格阵列的加权平均值？

[poster]

在上一个问题的概括中，如何对单元元素（即本身并将保留为数组的元素）进行加权平均？

我将从修改gnovice的答案开始，如下所示：

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，请确保weight具有正确的形状。我认为需要注意的三种情况是

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

第一种情况很简单，第3种情况不太可能发生，所以目前我对第2种情况感兴趣：如何将权重转换为一个数组，以使M.*weight在上述总和中具有正确的维数？当然，也可以理解示出了另一种获得加权平均的方法的答案。

编辑实际上，如果权重与c具有相同的结构，则情况3比情况1更为琐碎（重言，道歉） 。

这是情况2的示例：

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

meanArray = [ 2 4 3; 2 2 4 ] （例如，对于第一个元素（2 * 1 + 1 * 4）/（2 + 1）= 2）



回答：

在熟悉REPMAT之后 ，现在是我的解决方案：

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

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