是否有一种很好的向量化方法来获取八度音阶(或matlab)中稀疏矩阵每一列中所有非零元素的乘积(返回乘积的行向量)?
问问题
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2 回答
4
我会find
结合accumarray
:
%# 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;您可能想要对它们进行概要分析)
%# 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
于 2013-04-07T01:28:22.217 回答
0
我找到了解决这个问题的另一种方法,但在最坏的情况下它可能会更慢并且不太精确:
只需记录所有非零元素的对数,然后对列求和。然后取结果向量的 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
于 2013-04-09T20:57:06.100 回答