Ejemplo n.º 1
0
def test_eig_dyn():
    v = 0
    for i in xrange(5):
        n = 1 + int(mp.rand() * 5)
        if mp.rand() > 0.5:
            # real
            A = 2 * mp.randmatrix(n, n) - 1
            if mp.rand() > 0.5:
                A *= 10
                for x in xrange(n):
                    for y in xrange(n):
                        A[x, y] = int(A[x, y])
        else:
            A = (2 * mp.randmatrix(n, n) -
                 1) + 1j * (2 * mp.randmatrix(n, n) - 1)
            if mp.rand() > 0.5:
                A *= 10
                for x in xrange(n):
                    for y in xrange(n):
                        A[x,
                          y] = int(mp.re(A[x, y])) + 1j * int(mp.im(A[x, y]))

        run_hessenberg(A, verbose=v)
        run_schur(A, verbose=v)
        run_eig(A, verbose=v)
Ejemplo n.º 2
0
def test_eighe_randmatrix():
    N = 5

    for a in xrange(10):
        A = (2 * mp.randmatrix(N, N) - 1) + 1j * (2 * mp.randmatrix(N, N) - 1)

        for i in xrange(0, N):
            A[i, i] = mp.re(A[i, i])
            for j in xrange(i + 1, N):
                A[j, i] = mp.conj(A[i, j])

        run_eighe(A)
Ejemplo n.º 3
0
def test_eighe_randmatrix():
    N = 5

    for a in xrange(10):
        A = (2 * mp.randmatrix(N, N) - 1) + 1j * (2 * mp.randmatrix(N, N) - 1)

        for i in xrange(0, N):
            A[i,i] = mp.re(A[i,i])
            for j in xrange(i + 1, N):
                A[j,i] = mp.conj(A[i,j])

        run_eighe(A)
Ejemplo n.º 4
0
def test_svd_c_rand():
    for i in xrange(5):
        full = mp.rand() > 0.5
        m = 1 + int(mp.rand() * 10)
        n = 1 + int(mp.rand() * 10)
        A = (2 * mp.randmatrix(m, n) - 1) + 1j * (2 * mp.randmatrix(m, n) - 1)
        if mp.rand() > 0.5:
            A *= 10
            for x in xrange(m):
                for y in xrange(n):
                    A[x, y] = int(mp.re(A[x, y])) + 1j * int(mp.im(A[x, y]))

        run_svd_c(A, full_matrices=full, verbose=False)
Ejemplo n.º 5
0
def test_eighe_irandmatrix():
    N = 4
    R = 4

    for a in xrange(10):
        A = irandmatrix(N, R) + 1j * irandmatrix(N, R)

        for i in xrange(0, N):
            A[i, i] = mp.re(A[i, i])
            for j in xrange(i + 1, N):
                A[j, i] = mp.conj(A[i, j])

        run_eighe(A)
Ejemplo n.º 6
0
def test_svd_c_rand():
    for i in xrange(5):
        full = mp.rand() > 0.5
        m = 1 + int(mp.rand() * 10)
        n = 1 + int(mp.rand() * 10)
        A = (2 * mp.randmatrix(m, n) - 1) + 1j * (2 * mp.randmatrix(m, n) - 1)
        if mp.rand() > 0.5:
            A *= 10
            for x in xrange(m):
                for y in xrange(n):
                    A[x,y]=int(mp.re(A[x,y])) + 1j * int(mp.im(A[x,y]))

        run_svd_c(A, full_matrices=full, verbose=False)
Ejemplo n.º 7
0
def test_eighe_irandmatrix():
    N = 4
    R = 4

    for a in xrange(10):
        A=irandmatrix(N, R) + 1j * irandmatrix(N, R)

        for i in xrange(0, N):
            A[i,i] = mp.re(A[i,i])
            for j in xrange(i + 1, N):
                A[j,i] = mp.conj(A[i,j])

        run_eighe(A)