unittest
python
test_LDLT.py
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import
eigenpy
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import
numpy
as
np
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dim = 100
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A = np.random.rand(dim, dim)
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A = (A + A.T) * 0.5 + np.diag(10.0 + np.random.rand(dim))
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ldlt = eigenpy.LDLT(A)
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L = ldlt.matrixL()
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D = ldlt.vectorD()
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P = ldlt.transpositionsP()
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assert
eigenpy.is_approx
(
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np.transpose(P).dot(L.dot(np.diag(D).dot(np.transpose(L).dot(P)))), A
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)
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X = np.random.rand(dim, 20)
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B = A.dot(X)
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X_est = ldlt.solve(B)
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assert
eigenpy.is_approx
(X, X_est)
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assert
eigenpy.is_approx
(A.dot(X_est), B)
eigenpy::is_approx
EIGEN_DONT_INLINE bool is_approx(const Eigen::MatrixBase< MatrixType1 > &mat1, const Eigen::MatrixBase< MatrixType2 > &mat2)
Definition:
is-approx.hpp:20
eigenpy
Author(s): Justin Carpentier, Nicolas Mansard
autogenerated on Tue Jan 23 2024 03:15:01