是否有一种良好的矢量化方法来获取八度(或matlab)稀疏矩阵的每列中所有非零元素的乘积(返回产品的行向量)?
答案 0 :(得分:4)
我将find
与accumarray
合并:
%# create a random sparse array
s = sprand(4,4,0.6);
%# find the nonzero values
[rowIdx,colIdx,values] = find(s);
%# calculate product
product = accumarray(colIdx,values,[],@prod)
一些替代方案(可能效率较低;您可能想要对其进行分析)
%# simply set the zero-elements to 1, then apply prod
%# may lead to memory issues
s(s==0) = 1;
product = prod(s,1);
%# do "manual" accumarray
[rowIdx,colIdx,values] = find(s);
product = zeros(1,size(s,2));
uCols = unique(colIdx);
for col = uCols(:)'
product(col) = prod(values(colIdx==col));
end
答案 1 :(得分:0)
我找到了另一种方法来解决这个问题,但在最坏的情况下,它可能会更慢并且不那么精确:
只需记录所有非零元素,然后对列进行求和。然后取得结果向量的exp:
function [r] = prodnz(m)
nzinds = find(m != 0);
vals = full(m(nzinds));
vals = log(vals);
m(nzinds) = vals;
s = full(sum(m));
r = exp(s);
endfunction