forked from M-Labs/nalgebra
got test to compile
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@ -151,7 +151,7 @@ where
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/// TODO rewrite comment (current version is taken verbatim from eigen)
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/// TODO insures that code is correct for complex numbers, eigen uses abs2 and conj
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/// https://eigen.tuxfamily.org/dox/LLT_8h_source.html
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pub fn rank_one_update<R2: Dim, C2: Dim, S2>(&mut self, x: &Matrix<N, R2, U1, S2>, sigma: N)
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pub fn rank_one_update<R2: Dim, S2>(&mut self, x: &Matrix<N, R2, U1, S2>, sigma: N)
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where
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S2: Storage<N, R2, U1>,
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DefaultAllocator: Allocator<N, R2, U1>,
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@ -79,19 +79,22 @@ macro_rules! gen_tests(
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}
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fn cholesky_rank_one_update(_n: usize) -> bool {
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let m = RandomSDP::new(U4, || random::<$scalar>().0).unwrap();
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let mut m = RandomSDP::new(U4, || random::<$scalar>().0).unwrap();
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let x = Vector4::<$scalar>::new_random().map(|e| e.0);
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let sigma : $scalar = 1.;
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let sigma = random::<$scalar>().0; // random::<$scalar>().0;
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let one = sigma*0. + 1.; // TODO this is dirty but $scalar appears to not be a scalar type
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// updates cholesky decomposition and reconstructs m
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let mut chol = m.clone().cholesky().unwrap();
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chol.rank_one_update(&x, sigma);
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let m_chol_updated = chol.l() * chol.l().adjoint();
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// updates m manually
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let m_updated = m + sigma * x * x.transpose();
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m.syger(sigma, &x, &x, one); // m += sigma * x * x.adjoint()
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// updates cholesky deomposition and reconstruct m
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let mut chol = m.clone().cholesky().unwrap();
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chol.rank_one_update(x, sigma);
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let m_chol_updated = chol.l() * chol.l().transpose();
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println!("m : {:?}", m);
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relative_eq!(m_updated, m_chol_updated, epsilon = 1.0e-7)
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relative_eq!(m, m_chol_updated, epsilon = 1.0e-7)
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}
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}
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}
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