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using NonlinearSolve N = 100_000; levels = 1.5 .* rand(N); out = zeros(N); myfun(x, lv) = x * sin(x) - lv function f(out, levels, u0) for i in 1:N out[i] = solve(NonlinearProblem{false}(NonlinearFunction{false}(myfun), u0, levels[i]), Falsi()).u end end function f2(out, levels, u0) for i in 1:N out[i] = solve(NonlinearProblem{false}(NonlinearFunction{false}(myfun), u0, levels[i]), NewtonRaphson()).u end end @time f(out, levels, (0.0, 2.0)) @time f2(out, levels, 1.0)
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Merge pull request #87 from SciML/matrix_resizing
aa27e6a
Add matrix resizing and fix cases with u0 as a matrix
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The text was updated successfully, but these errors were encountered: