# [racket] matrix-solve and approximation errors

I've just been bitten by a bad case of floating-point error with
`matrix-solve` (and a bad CPU that has some floating-point issues):
(let ([n 0.8200000000000001 #;(+ (* .9 .9)(* .1 .1))])
(matrix-solve
(matrix [[ 1 0 .9 1]
[ 0 1 .1 1]
[.9 .1 n 1]
[ 1 1 1 0]])
(col-matrix [0 0 0 1])))
; -> (array #[#[0.0] #[0.5] #[0.0] #[-0.5]])
But clearly here M×X≠B, as is easily seen on the last row.
I've seen other situations where the approximation leads to an approximate
solution (which is okay of course), but this is the first case I see where
the result is completely off.
I have no idea if anything can be done about it, though (apart from
throwing my computer through the window and buy a better one).
Laurent
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