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I saw in simple testing a ~12% increase in performance just by scaling
functionscale_ls!(A)
s =ones(size(A, 2))
for j =1:size(A, 2)
i = A.colptr[j]
k = A.colptr[j+1] -1
nj = i <= k ?norm(A.nzval[i:k]) :0.0if nj >0.0
A.nzval[i:k] ./= nj
s[j] = nj
endendreturn s # s contains the diagonal elements of the (right) diagonal scalingend
before scaling ~ 1.42s, after scaling 1.23s +0.03s scaling => 12% speedup
the scaling is fast, and can be ignored when multiple channels are fitted
The text was updated successfully, but these errors were encountered:
I saw in simple testing a ~12% increase in performance just by scaling
before scaling ~ 1.42s, after scaling 1.23s +0.03s scaling => 12% speedup
the scaling is fast, and can be ignored when multiple channels are fitted
The text was updated successfully, but these errors were encountered: