Exemple #1
0
def test_lambda2():
  m = 2
  x = np.array([-13324172.755747,
                -10668894.713608,
                -7157225.010770,
                -6149367.974367,
                -7454133.571066,
                -5969200.494550,
                8336734.058423,
                6186974.084502,
                -17549093.883655,
                -13970158.922370])
  sigma = np.matrix([[0.446320, 0.223160, 0.223160, 0.223160, 0.223160, 0.572775, 0.286388, 0.286388, 0.286388, 0.286388],
                     [0.223160, 0.446320, 0.223160, 0.223160, 0.223160, 0.286388, 0.572775, 0.286388, 0.286388, 0.286388],
                     [0.223160, 0.223160, 0.446320, 0.223160, 0.223160, 0.286388, 0.286388, 0.572775, 0.286388, 0.286388],
                     [0.223160, 0.223160, 0.223160, 0.446320, 0.223160, 0.286388, 0.286388, 0.286388, 0.572775, 0.286388],
                     [0.223160, 0.223160, 0.223160, 0.223160, 0.446320, 0.286388, 0.286388, 0.286388, 0.286388, 0.572775],
                     [0.572775, 0.286388, 0.286388, 0.286388, 0.286388, 0.735063, 0.367531, 0.367531, 0.367531, 0.367531],
                     [0.286388, 0.572775, 0.286388, 0.286388, 0.286388, 0.367531, 0.735063, 0.367531, 0.367531, 0.367531],
                     [0.286388, 0.286388, 0.572775, 0.286388, 0.286388, 0.367531, 0.367531, 0.735063, 0.367531, 0.367531],
                     [0.286388, 0.286388, 0.286388, 0.572775, 0.286388, 0.367531, 0.367531, 0.367531, 0.735063, 0.367531],
                     [0.286388, 0.286388, 0.286388, 0.286388, 0.572775, 0.367531, 0.367531, 0.367531, 0.367531, 0.735063]])
  F, s = l.lambda_solution_(x, sigma, m)
  assert np.allclose(F,
                     [[-13324188., -7157236.00000014, -7454143.00000017,
                       8336726.00000008, -17549108.00000054, -13324187.99999997,
                       -7157236.00000013,  -7454143.00000013,   8336717.00000021,
                       -17549108.00000053],
                      [-10668900.99999994,  -6149379.00000041,  -5969220., 6186959.99999982,
                       -13970171.00000022, -10668907.99999984,  -6149379.00000041,
                       -5969219.99999996,   6186959.99999983, -13970171.00000017]])
  assert np.allclose(s, np.array([ 1506.43579559,  1612.81177168]))
def test_lambda1():
    m = 2
    x = np.array([
        1585184.171, -6716599.430, 3915742.905, 7627233.455, 9565990.879,
        989457273.200
    ])
    sigma = np.matrix(
        [[0.227134, 0.112202, 0.112202, 0.112202, 0.112202, 0.103473],
         [0.112202, 0.227134, 0.112202, 0.112202, 0.112202, 0.103473],
         [0.112202, 0.112202, 0.227134, 0.112202, 0.112202, 0.103473],
         [0.112202, 0.112202, 0.112202, 0.227134, 0.112202, 0.103473],
         [0.112202, 0.112202, 0.112202, 0.112202, 0.227134, 0.103473],
         [0.103473, 0.103473, 0.103473, 0.103473, 0.103473, 0.434339]])
    F, s = l.lambda_solution_(x, sigma, m)
    assert np.allclose(
        F,
        np.array([[
            1.58518400e+06, 3.91574300e+06, 9.56599100e+06, 1.58518400e+06,
            3.91574300e+06, 9.56599100e+06
        ],
                  [
                      -6.71659900e+06, 7.62723400e+06, 9.89457273e+08,
                      -6.71660000e+06, 7.62723300e+06, 9.89457273e+08
                  ]]))
    assert np.allclose(s, np.array([3.50798444, 3.70845619]))
def test_lambda4():
    """
  Verify that the relative scale of the covariance matrix doesn't affect
  the solution.
  """
    m = 1
    x = np.array([-22, 22, -55, 55, -33, 33, -66, 66, -44, 44, -77, 77])
    sigma = np.eye(x.size) * 1000
    F, s = l.lambda_solution_(x, np.asfortranarray(sigma), m)
    assert np.allclose(F[0], x)
def test_lambda3():
    """
  Verify that passing in perfectly decorrelated integers results in the
  same integers being identified.
  """
    m = 1
    x = np.array([-22, 22, -55, 55, -33, 33, -66, 66, -44, 44, -77, 77])
    sigma = np.eye(x.size)
    F, s = l.lambda_solution_(x, np.asfortranarray(sigma), m)
    assert np.allclose(F[0], x)
Exemple #5
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def test_lambda4():
  """
  Verify that the relative scale of the covariance matrix doesn't affect
  the solution.
  """
  m = 1
  x = np.array([-22, 22, -55, 55, -33, 33, -66, 66, -44, 44, -77, 77])
  sigma = np.eye(x.size) * 1000
  F, s = l.lambda_solution_(x, np.asfortranarray(sigma), m)
  assert np.allclose(F[0], x)
Exemple #6
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def test_lambda3():
  """
  Verify that passing in perfectly decorrelated integers results in the
  same integers being identified.
  """
  m = 1
  x = np.array([-22, 22, -55, 55, -33, 33, -66, 66, -44, 44, -77, 77])
  sigma = np.eye(x.size)
  F, s = l.lambda_solution_(x, np.asfortranarray(sigma), m)
  assert np.allclose(F[0], x)
Exemple #7
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def test_lambda1():
  m = 2
  x = np.array([1585184.171,
                -6716599.430,
                3915742.905,
                7627233.455,
                9565990.879,
                989457273.200])
  sigma = np.matrix([[0.227134,   0.112202,   0.112202,   0.112202,   0.112202,   0.103473],
                     [0.112202,   0.227134,   0.112202,   0.112202,   0.112202,   0.103473],
                     [0.112202,   0.112202,   0.227134,   0.112202,   0.112202,   0.103473],
                     [0.112202,   0.112202,   0.112202,   0.227134,   0.112202,   0.103473],
                     [0.112202,   0.112202,   0.112202,   0.112202,   0.227134,   0.103473],
                     [0.103473,   0.103473,   0.103473,   0.103473,   0.103473,   0.434339]])
  F, s = l.lambda_solution_(x, sigma, m)
  assert np.allclose(F,
                     np.array([[  1.58518400e+06,   3.91574300e+06,   9.56599100e+06,
                                  1.58518400e+06,   3.91574300e+06,   9.56599100e+06],
                               [ -6.71659900e+06,   7.62723400e+06,   9.89457273e+08,
                                 -6.71660000e+06,   7.62723300e+06,   9.89457273e+08]]))
  assert np.allclose(s, np.array([ 3.50798444,  3.70845619]))
def test_lambda2():
    m = 2
    x = np.array([
        -13324172.755747, -10668894.713608, -7157225.010770, -6149367.974367,
        -7454133.571066, -5969200.494550, 8336734.058423, 6186974.084502,
        -17549093.883655, -13970158.922370
    ])
    sigma = np.matrix([[
        0.446320, 0.223160, 0.223160, 0.223160, 0.223160, 0.572775, 0.286388,
        0.286388, 0.286388, 0.286388
    ],
                       [
                           0.223160, 0.446320, 0.223160, 0.223160, 0.223160,
                           0.286388, 0.572775, 0.286388, 0.286388, 0.286388
                       ],
                       [
                           0.223160, 0.223160, 0.446320, 0.223160, 0.223160,
                           0.286388, 0.286388, 0.572775, 0.286388, 0.286388
                       ],
                       [
                           0.223160, 0.223160, 0.223160, 0.446320, 0.223160,
                           0.286388, 0.286388, 0.286388, 0.572775, 0.286388
                       ],
                       [
                           0.223160, 0.223160, 0.223160, 0.223160, 0.446320,
                           0.286388, 0.286388, 0.286388, 0.286388, 0.572775
                       ],
                       [
                           0.572775, 0.286388, 0.286388, 0.286388, 0.286388,
                           0.735063, 0.367531, 0.367531, 0.367531, 0.367531
                       ],
                       [
                           0.286388, 0.572775, 0.286388, 0.286388, 0.286388,
                           0.367531, 0.735063, 0.367531, 0.367531, 0.367531
                       ],
                       [
                           0.286388, 0.286388, 0.572775, 0.286388, 0.286388,
                           0.367531, 0.367531, 0.735063, 0.367531, 0.367531
                       ],
                       [
                           0.286388, 0.286388, 0.286388, 0.572775, 0.286388,
                           0.367531, 0.367531, 0.367531, 0.735063, 0.367531
                       ],
                       [
                           0.286388, 0.286388, 0.286388, 0.286388, 0.572775,
                           0.367531, 0.367531, 0.367531, 0.367531, 0.735063
                       ]])
    F, s = l.lambda_solution_(x, sigma, m)
    assert np.allclose(
        F, [[
            -13324188., -7157236.00000014, -7454143.00000017, 8336726.00000008,
            -17549108.00000054, -13324187.99999997, -7157236.00000013,
            -7454143.00000013, 8336717.00000021, -17549108.00000053
        ],
            [
                -10668900.99999994, -6149379.00000041, -5969220.,
                6186959.99999982, -13970171.00000022, -10668907.99999984,
                -6149379.00000041, -5969219.99999996, 6186959.99999983,
                -13970171.00000017
            ]])
    assert np.allclose(s, np.array([1506.43579559, 1612.81177168]))