test_Accelerate.py

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import numpy as np
from scipy.sparse import csc_matrix
 
import eigenpy
 
rng = np.random.default_rng()
 
 
def test(SolverType: type):
    dim = 100
    A = rng.random((dim, dim))
    A = (A + A.T) * 0.5 + np.diag(10.0 + rng.random(dim))
 
    A = csc_matrix(A)
 
    llt = SolverType(A)
 
    assert llt.info() == eigenpy.ComputationInfo.Success
 
    X = rng.random((dim, 20))
    B = A.dot(X)
    X_est = llt.solve(B)
    #    import pdb; pdb.set_trace()
    assert eigenpy.is_approx(X, X_est)
    assert eigenpy.is_approx(A.dot(X_est), B)
 
    llt.analyzePattern(A)
    llt.factorize(A)
 
 
test(eigenpy.AccelerateLLT)
test(eigenpy.AccelerateLDLT)
test(eigenpy.AccelerateLDLTUnpivoted)
test(eigenpy.AccelerateLDLTSBK)
test(eigenpy.AccelerateLDLTTPP)
test(eigenpy.AccelerateQR)
# test(eigenpy.AccelerateCholeskyAtA) # This test is not passing. Seems there is a bug in Eigen with the support of Accelerate.