numpy.testing.assert_array_almost_equal

Here are the examples of the python api numpy.testing.assert_array_almost_equal taken from open source projects. By voting up you can indicate which examples are most useful and appropriate.

200 Examples 7

Example 1

Project: RMG-Py
Source File: quantityTest.py
View license
    def test_array_conversion(self):
        """
        ArrayQuantity: test that the value and uncertainty get converted to the proper si value.
        """
        numpy.testing.assert_array_almost_equal(self.v.value_si, self.v.value*1e-2)
        numpy.testing.assert_array_almost_equal(self.v.uncertainty_si, self.v.uncertainty)
        numpy.testing.assert_array_almost_equal(self.v_array.value_si, self.v.value*1e-2)
        numpy.testing.assert_array_almost_equal(self.v_array.uncertainty_si, self.v.uncertainty)

        numpy.testing.assert_array_almost_equal(self.Cp.value_si, self.Cp.value*4.184)
        numpy.testing.assert_array_almost_equal(self.Cp.uncertainty_si, self.Cp.uncertainty*4.184)
        numpy.testing.assert_array_almost_equal(self.Cp_array.value_si, self.Cp.value*4.184)
        numpy.testing.assert_array_almost_equal(self.Cp_array.uncertainty_si, self.Cp.uncertainty*4.184)

Example 2

Project: oq-hazardlib
Source File: gc2_test.py
View license
    def test_downsample_trace(self):
        # Use the simple fault case with a tolerance of 1.0 degree
        downsampled_trace = downsample_trace(SFLT1.mesh, 1.0)
        # Top edge of downsampled mesh should correspond to the five
        # points of the simple fault
        # Check longitudes
        numpy.testing.assert_array_almost_equal(downsampled_trace[:, 0],
                                                AS_ARRAY[:, 0],
                                                5)
        # Check latitude
        numpy.testing.assert_array_almost_equal(downsampled_trace[:, 1],
                                                AS_ARRAY[:, 1],
                                                5)
        # Check depths
        numpy.testing.assert_array_almost_equal(downsampled_trace[:, 2],
                                                AS_ARRAY[:, 2],
                                                5)

Example 3

Project: oq-hazardlib
Source File: gc2_test.py
View license
    def test_downsample_mesh(self):
        # Use the simple fault case with a tolerance of 1.0 degree
        numpy.testing.assert_array_almost_equal(
            downsample_mesh(SFLT1.mesh, 1.0).lons[0, :],
            AS_ARRAY[:, 0],
            5)
        numpy.testing.assert_array_almost_equal(
            downsample_mesh(SFLT1.mesh, 1.0).lats[0, :],
            AS_ARRAY[:, 1],
            5)
        numpy.testing.assert_array_almost_equal(
            downsample_mesh(SFLT1.mesh, 1.0).depths[0, :],
            AS_ARRAY[:, 2],
            5)

Example 4

Project: chainer
Source File: array.py
View license
def assert_array_almost_equal(x, y, decimal=6, err_msg='', verbose=True):
    """Raises an AssertionError if objects are not equal up to desired precision.

    Args:
         x(numpy.ndarray or cupy.ndarray): The actual object to check.
         y(numpy.ndarray or cupy.ndarray): The desired, expected object.
         decimal(int): Desired precision.
         err_msg(str): The error message to be printed in case of failure.
         verbose(bool): If ``True``, the conflicting
             values are appended to the error message.

    .. seealso:: :func:`numpy.testing.assert_array_almost_equal`
    """
    numpy.testing.assert_array_almost_equal(
        cupy.asnumpy(x), cupy.asnumpy(y), decimal=decimal,
        err_msg=err_msg, verbose=verbose)

Example 5

Project: cupy
Source File: array.py
View license
def assert_array_almost_equal(x, y, decimal=6, err_msg='', verbose=True):
    """Raises an AssertionError if objects are not equal up to desired precision.

    Args:
         x(numpy.ndarray or cupy.ndarray): The actual object to check.
         y(numpy.ndarray or cupy.ndarray): The desired, expected object.
         decimal(int): Desired precision.
         err_msg(str): The error message to be printed in case of failure.
         verbose(bool): If ``True``, the conflicting
             values are appended to the error message.

    .. seealso:: :func:`numpy.testing.assert_array_almost_equal`
    """
    numpy.testing.assert_array_almost_equal(
        cupy.asnumpy(x), cupy.asnumpy(y), decimal=decimal,
        err_msg=err_msg, verbose=verbose)

Example 6

Project: pgmpy
Source File: test_ExactInference.py
View license
    def test_query_multiple_variable(self):
        belief_propagation = BeliefPropagation(self.bayesian_model)
        query_result = belief_propagation.query(['Q', 'J'])
        np_test.assert_array_almost_equal(query_result['J'].values,
                                          np.array([0.416, 0.584]))
        np_test.assert_array_almost_equal(query_result['Q'].values,
                                          np.array([0.4912, 0.5088]))

Example 7

Project: pgmpy
Source File: test_ExactInference.py
View license
    def test_query_single_variable_with_evidence(self):
        belief_propagation = BeliefPropagation(self.bayesian_model)
        query_result = belief_propagation.query(variables=['J'],
                                                evidence={'A': 0, 'R': 1})
        np_test.assert_array_almost_equal(query_result['J'].values,
                                          np.array([0.60, 0.40]))

Example 8

Project: poliastro
Source File: test_util.py
View license
def test_transform_unitless_vector():
    vector = [0, 1, 0]
    angle = 45 * u.deg
    axis = 'z'
    expected_vector = [np.sqrt(2) / 2, np.sqrt(2) / 2, 0]
    result = util.transform(vector, angle, axis)
    assert_array_almost_equal(result, expected_vector)

Example 9

Project: numexpr
Source File: test_numexpr.py
View license
        def test_changing_nthreads_00_inc(self):
            a = linspace(-1, 1, 1e6)
            b = ((.25 * a + .75) * a - 1.5) * a - 2
            for nthreads in range(1, 7):
                numexpr.set_num_threads(nthreads)
                c = evaluate("((.25*a + .75)*a - 1.5)*a - 2")
                assert_array_almost_equal(b, c)

Example 10

Project: numexpr
Source File: test_numexpr.py
View license
        def test_changing_nthreads_01_dec(self):
            a = linspace(-1, 1, 1e6)
            b = ((.25 * a + .75) * a - 1.5) * a - 2
            for nthreads in range(6, 1, -1):
                numexpr.set_num_threads(nthreads)
                c = evaluate("((.25*a + .75)*a - 1.5)*a - 2")
                assert_array_almost_equal(b, c)

Example 11

Project: pymanopt
Source File: test_manifold_euclidean.py
View license
    def test_exp_log_inverse(self):
        s = self.man
        X = s.rand()
        Y = s.rand()
        Yexplog = s.exp(X, s.log(X, Y))
        np_testing.assert_array_almost_equal(Y, Yexplog)

Example 12

Project: pymanopt
Source File: test_manifold_oblique.py
View license
    def test_pairmean(self):
        s = self.man
        X = s.rand()
        Y = s.rand()
        Z = s.pairmean(X, Y)
        np_testing.assert_array_almost_equal(s.dist(X, Z), s.dist(Y, Z))

Example 13

Project: python-acoustics
Source File: test_building.py
View license
def test_stc_curve():
    tl = np.array([18, 18, 17, 17, 20, 21, 22, 23, 25, 26, 26, 25, 25, 26,
                   30, 31])
    calculated = stc_curve(tl)
    real = np.array([9, 12, 15, 18, 21, 24, 25, 26, 27, 28, 29, 29, 29, 29,
                     29, 29])
    assert_array_almost_equal(calculated, real)

Example 14

Project: python-control
Source File: matlab_test.py
View license
    def testMargin(self):
        #! TODO: check results to make sure they are OK
        gm, pm, wg, wp = margin(self.siso_tf1);
        gm, pm, wg, wp = margin(self.siso_tf2);
        gm, pm, wg, wp = margin(self.siso_ss1);
        gm, pm, wg, wp = margin(self.siso_ss2);
        gm, pm, wg, wp = margin(self.siso_ss2*self.siso_ss2*2);
        np.testing.assert_array_almost_equal(
            [gm, pm, wg, wp], [1.5451, 75.9933, 1.2720, 0.6559], decimal=3)

Example 15

Project: qutip
Source File: test_mkl.py
View license
@unittest.skipIf(qset.has_mkl == False, 'MKL extensions not found.')
def test_mkl_spsolve1():
    """
    MKL spsolve : Single RHS vector (Real)
    """
    Adense = np.array([[0., 1., 1.],
                    [1., 0., 1.],
                    [0., 0., 1.]])
    As = sp.csr_matrix(Adense)
    np.random.seed(1234)
    x = np.random.randn(3)
    b = As * x
    x2 = mkl_spsolve(As, b)
    assert_array_almost_equal(x, x2)

Example 16

Project: Axelrod
Source File: test_eigen.py
View license
    def test_eigen_4(self):
        # Test a 4x4 matrix
        mat = [[2, 0, 0, 0], [1, 2, 0, 0], [0, 1, 3, 0], [0, 0, 1, 3]]
        evector, evalue = principal_eigenvector(mat, maximum_iterations=None,
                                                max_error=1e-10)
        self.assertAlmostEqual(evalue, 3, places=3)
        assert_array_almost_equal(evector, numpy.dot(mat, evector) / evalue)
        assert_array_almost_equal(evector, normalise([0, 0, 0, 1]), decimal=4)

Example 17

Project: attention-lvcsr
Source File: test_rng_mrg.py
View license
def test_random_state_transfer():
    """
    Test that random state can be transferred from one theano graph to another.

    """
    class Graph:
        def __init__(self, seed=123):
            self.rng = MRG_RandomStreams(seed)
            self.y = self.rng.uniform(size=(1,))
    g1 = Graph(seed=123)
    f1 = theano.function([], g1.y)
    g2 = Graph(seed=987)
    f2 = theano.function([], g2.y)

    g2.rng.rstate = g1.rng.rstate
    for (su1, su2) in zip(g1.rng.state_updates, g2.rng.state_updates):
        su2[0].set_value(su1[0].get_value())

    numpy.testing.assert_array_almost_equal(f1(), f2(), decimal=6)

Example 18

View license
    def test_random_state_transfer(self):
        """
        Test that random state can be transferred from one theano graph to another.
        """
        class Graph:
            def __init__(self, seed=123):
                self.rng = RandomStreams(seed)
                self.y = self.rng.uniform(size=(1,))
        g1 = Graph(seed=123)
        f1 = function([], g1.y)
        g2 = Graph(seed=987)
        f2 = function([], g2.y)

        for (su1, su2) in zip(g1.rng.state_updates, g2.rng.state_updates):
            su2[0].set_value(su1[0].get_value())

        numpy.testing.assert_array_almost_equal(f1(), f2(), decimal=6)

Example 19

Project: spykeutils
Source File: test_scipy_quantities.py
View license
    def test_works_with_multidimensional_arrays(self):
        a = sp.array([[0.0, 1.0], [2.0, 3.0]]) * pq.s
        b = sp.array([[2.0, 2.0], [3.0, 4.0]]) * pq.s
        expected = sp.array([[2.0, 4.0], [10.0, 18.0]]) * pq.s
        actual = spq.inner(a, b)
        assert_array_almost_equal(expected, actual.rescale(expected.units))

Example 20

Project: scikit-image
Source File: test_colorconv.py
View license
    def test_yuv(self):
        rgb = np.array([[[1.0, 1.0, 1.0]]])
        assert_array_almost_equal(rgb2yuv(rgb), np.array([[[1, 0, 0]]]))
        assert_array_almost_equal(rgb2yiq(rgb), np.array([[[1, 0, 0]]]))
        assert_array_almost_equal(rgb2ypbpr(rgb), np.array([[[1, 0, 0]]]))
        assert_array_almost_equal(rgb2ycbcr(rgb), np.array([[[235, 128, 128]]]))
        rgb = np.array([[[0.0, 1.0, 0.0]]])
        assert_array_almost_equal(rgb2yuv(rgb), np.array([[[0.587, -0.28886916, -0.51496512]]]))
        assert_array_almost_equal(rgb2yiq(rgb), np.array([[[0.587, -0.27455667, -0.52273617]]]))
        assert_array_almost_equal(rgb2ypbpr(rgb), np.array([[[0.587, -0.331264, -0.418688]]]))
        assert_array_almost_equal(rgb2ycbcr(rgb), np.array([[[144.553,   53.797,   34.214]]]))

Example 21

Project: scikit-image
Source File: test_colorconv.py
View license
    def test_yuv_roundtrip(self):
        img_rgb = img_as_float(self.img_rgb)[::16, ::16]
        assert_array_almost_equal(yuv2rgb(rgb2yuv(img_rgb)), img_rgb)
        assert_array_almost_equal(yiq2rgb(rgb2yiq(img_rgb)), img_rgb)
        assert_array_almost_equal(ypbpr2rgb(rgb2ypbpr(img_rgb)), img_rgb)
        assert_array_almost_equal(ycbcr2rgb(rgb2ycbcr(img_rgb)), img_rgb)

Example 22

Project: cartopy
Source File: test_lambert_conformal.py
View license
    def test_single_spole(self):
        s_pole_crs = ccrs.LambertConformal(standard_parallels=[-1.])
        assert_array_almost_equal(s_pole_crs.x_limits,
                                  (-19840440, 19840440.),
                                  decimal=0)
        assert_array_almost_equal(s_pole_crs.y_limits,
                                  (-370239953, -8191953),
                                  decimal=0)

Example 23

Project: iris
Source File: test_mapping.py
View license
    def test_default_projection_and_extent(self):
        self.assertEqual(iplt.default_projection(self.cube),
                         ccrs.PlateCarree())
        np_testing.assert_array_almost_equal(
            iplt.default_projection_extent(self.cube),
            [0., 360., -89.99995422, 89.99998474])
        np_testing.assert_array_almost_equal(
            iplt.default_projection_extent(
                self.cube, mode=iris.coords.BOUND_MODE),
            [-1.875046, 358.124954, -91.24995422, 91.24998474])

Example 24

Project: GPy
Source File: inference_tests.py
View license
    def test_inferenceX_GPLVM_RBF(self):
        Ys = self.genData()
        m = GPy.models.GPLVM(Ys,3,kernel=GPy.kern.RBF(3,ARD=True))
        m.optimize()
        x, mi = m.infer_newX(m.Y, optimize=True)
        np.testing.assert_array_almost_equal(m.X, mi.X, decimal=2)

Example 25

Project: pyvolve
Source File: parameters_sanity_test.py
View license
    def test_sanity_state_freqs_aminoacid(self):
        wag_freqs = [0.08662799999999994, 0.0193078, 0.0570451, 0.0580589, 0.0384319, 0.0832518, 0.0244313, 0.048466, 0.0620286, 0.086209, 0.0195027, 0.0390894, 0.0457631, 0.0367281, 0.043972, 0.0695179, 0.0610127, 0.0708956, 0.0143859, 0.0352742]
        params = {}    
        pm = ECM_Sanity("wag", params, size = 20)
        pm._sanity_state_freqs(empirical = True)
        np.testing.assert_array_almost_equal(pm.params["state_freqs"], wag_freqs, decimal = DECIMAL, err_msg = "WAG (aa model) default state_freqs not set up properly.")

Example 26

Project: pyvolve
Source File: parameters_sanity_test.py
View license
    def test_sanity_state_freqs_MG_provided_codon(self):
        mg_nuc = [ 0.23577944,  0.2426595,   0.28132983,  0.24023122]
        mg_codon = [6.48685834e-03, 2.56846182e-02, 3.62821504e-02, 1.78992022e-02, 3.78995203e-03, 1.27376858e-02, 1.11733512e-02, 2.77350952e-03, 3.21357920e-02, 1.15713167e-02, 1.35629025e-03, 2.18752127e-02, 2.50168300e-05, 3.10876439e-02, 3.37328837e-02, 1.65327942e-02, 8.21428969e-03, 1.55572812e-02, 1.76293820e-02, 2.29747386e-02, 1.73289159e-03, 1.13379531e-02, 1.59673812e-02, 2.97921605e-02, 3.52280293e-02, 9.42724910e-03, 2.48052302e-02, 1.47583962e-02, 1.96410901e-02, 9.33795423e-03, 6.06200346e-05, 1.11892264e-02, 1.18844724e-02, 1.75173640e-02, 2.77504624e-02, 1.90563757e-02, 3.16335607e-02, 1.45931598e-02, 1.42666011e-02, 2.96971714e-02, 1.90421569e-02, 3.33563400e-03, 2.94568624e-03, 3.40917454e-02, 1.32157035e-02, 1.94067362e-02, 1.83063743e-02, 1.03705727e-02, 1.09380931e-02, 6.07488829e-03, 1.17862027e-02, 4.53122192e-03, 2.49775815e-02, 8.96308703e-03, 3.10326855e-02, 2.94072089e-02, 1.93306945e-02, 3.42785939e-03, 2.24745563e-02, 7.87119137e-03, 1.92728016e-02]
        params = {"state_freqs": mg_codon}
        pm = MechCodon_Sanity("mg", params, size=61)
        pm._sanity_state_freqs_MG()
        np.testing.assert_array_almost_equal(pm.params["nuc_freqs"], mg_nuc, decimal = DECIMAL, err_msg = "Nucleotide frequencies not properly calc'd from codon frequencies for an MG model.")

Example 27

Project: sklearn-theano
Source File: test_base.py
View license
def test_relu():

    arr = np.arange(-12, 13).reshape(5, 5).astype(np.float32)

    expressions, input_variable = fuse([Relu()])
    relu_func = theano.function([input_variable], expressions)
    arr = arr[np.newaxis, np.newaxis]

    arr2 = arr.copy()
    arr2[arr2 <= 0] = 0

    thresholded = relu_func(arr)[0]

    assert_array_almost_equal(thresholded, arr2)

Example 28

Project: spinn
Source File: test_cuda_util.py
View license
def _test_masked_careduce_inner(f, X, Y, mask, expected):
    print X
    print Y
    print mask

    ret = f(X, Y, mask)
    print ret
    print expected
    np.testing.assert_array_almost_equal(ret, expected)

Example 29

Project: statsmodels
Source File: test_multivariate.py
View license
    def test_mvn_pdf(self):
        cov3 = self.cov3
        mvn3 = self.mvn3
        mvn3c = self.mvn3c

        r_val = [-7.667977543898155, -6.917977543898155, -5.167977543898155]
        assert_array_almost_equal( mvn3.logpdf(cov3), r_val, decimal = 14)
        #decimal 18
        r_val = [0.000467562492721686, 0.000989829804859273, 0.005696077243833402]
        assert_array_almost_equal( mvn3.pdf(cov3), r_val, decimal = 17)
        #cheating new mean, same cov, too dangerous, got wrong instance in tests
        #mvn3.mean = np.array([0,0,0])
        mvn3b = MVNormal(np.array([0,0,0]), cov3)
        r_val = [0.02914269740502042, 0.02269635555984291, 0.01767593948287269]
        assert_array_almost_equal( mvn3b.pdf(cov3), r_val, decimal = 16)

Example 30

Project: python-pcl
Source File: test.py
View license
    def test_asarray(self):
        p = pcl.PointCloud(self.p)      # copy
        # old0 = p[0]
        a = np.asarray(p)               # view
        a[:] += 6
        assert_array_almost_equal(p[0], a[0])

        # Regression test: deleting a second view would previously
        # reset the view count to zero.
        b = np.asarray(p)
        del b

        self.assertRaises(ValueError, p.resize, 2 * len(p))

Example 31

Project: bdot
Source File: test_carray.py
View license
def test_dot_matrix_chunklen_greater_than_length_m2_numpy_out():

	matrix = np.random.random_sample(size=(1000, 100))
	bcarray1 = bdot.carray(matrix, chunklen=2**9, cparams=bdot.cparams(clevel=2))
	bcarray2 = bdot.carray(matrix, chunklen=2**11, cparams=bdot.cparams(clevel=2))


	result = np.empty((1000, 1000), dtype=np.float64)
	bcarray1.dot(bcarray2, out=result)
	expected = matrix.dot(matrix.T)

	assert_array_almost_equal(expected, result, decimal=5)

Example 32

Project: tensorlib
Source File: test_mathutils.py
View license
def test_matricize():
    """
    Test implementation of matricize.
    """
    X = np.arange(1, 9).reshape(2, 2, 2)
    matricize(X, 0)
    assert_array_almost_equal(matricize(X, 2), matricize(X, -1))
    assert_array_almost_equal(matricize(X, 1), matricize(X, -2))

Example 33

Project: tensorlib
Source File: test_mathutils.py
View license
def test_unmatricize():
    """
    Test implementation of unmatricize.
    """
    X = np.arange(2 * 3 * 4 * 5).reshape(3, 2, 4, 5)
    for i in range(X.ndim):
        X2 = matricize(X, i)
        assert_array_almost_equal(unmatricize(X2, i, X.shape), X)

    X2 = matricize(X, -2)
    assert_array_almost_equal(unmatricize(X2, -2, X.shape), X)

    X = np.arange(1, 9).reshape(2, 2, 2)
    for i in range(X.ndim):
        X2 = matricize(X, i)
        assert_array_almost_equal(unmatricize(X2, i, X.shape), X)

Example 34

View license
    def test_2region_1color(self):
        self.setup_method(self, w = 1, h = 2)
        for y in range(self.h):
            self.f.label[y, :] = y

        hist = self.f._Features__init_color(2)
        assert len(hist) == 2
        assert hist[0].shape == (75,)
        r1_expected = ([1.0/3] + [0] * 24) + ([1.0/3] + [0] * 24) + ([1.0/3] + [0] * 24)
        r2_expected = ([1.0/3] + [0] * 24) + ([1.0/3] + [0] * 24) + ([1.0/3] + [0] * 24)
        numpy.testing.assert_array_almost_equal(hist[0].ravel(), r1_expected)
        numpy.testing.assert_array_almost_equal(hist[1].ravel(), r2_expected)

Example 35

Project: gplearn
Source File: test_fixes.py
View license
def test_expit():
    # Check numerical stability of expit (logistic function).

    # Simulate our previous Cython implementation, based on
    #http://fa.bianp.net/blog/2013/numerical-optimizers-for-logistic-regression
    assert_almost_equal(expit(1000.), 1. / (1. + np.exp(-1000.)), decimal=16)
    assert_almost_equal(expit(-1000.), np.exp(-1000.) / (1. + np.exp(-1000.)),
                        decimal=16)

    x = np.arange(10)
    out = np.zeros_like(x, dtype=np.float32)
    assert_array_almost_equal(expit(x), expit(x, out=out))

Example 36

Project: siphon
Source File: test_dataset.py
View license
@recorder.use_cassette('nc4_compound_ref')
def test_struct():
    "Test reading a structured variable"
    ds = Dataset('http://localhost:8080/thredds/cdmremote/nc4/compound/ref_tst_compounds.nc4')
    var = ds.variables['obs'][:]
    assert var.shape == (3,)
    assert var.dtype == np.dtype([('day', 'b'), ('elev', '<i2'), ('count', '<i4'),
                                  ('relhum', '<f4'), ('time', '<f8')])
    assert_array_equal(var['day'], np.array([15, -99, 20]))
    assert_array_equal(var['elev'], np.array([2, -99, 6]))
    assert_array_equal(var['count'], np.array([1, -99, 3]))
    assert_array_almost_equal(var['relhum'], np.array([0.5, -99.0, 0.75]))
    assert_array_almost_equal(var['time'],
                              np.array([3600.01, -99.0, 5000.01], dtype=np.double))

Example 37

Project: tracer
Source File: test_flat_surface.py
View license
    def test_register_incoming(self):
        """Flat mirror: a simple bundle is registered correctly"""
        correct_params = r_[[math.sqrt(3)]*4]
        params = self._surf.register_incoming(self._bund)
        
        N.testing.assert_array_almost_equal(params, correct_params)

Example 38

Project: tifffile
Source File: test_tifffile.py
View license
@skipif(si is None)
def test_imread_uint16_big_endian():
    expected = np.load(os.path.join(si.data_dir, 'chessboard_GRAY_U8.npy'))
    img = imread(os.path.join(si.data_dir, 'chessboard_GRAY_U16B.tif'))
    assert img.dtype == np.uint16
    assert_array_almost_equal(img, expected)

Example 39

Project: tsfresh
Source File: test_ts_features.py
View license
    def test_calculate_ts_features_after_randomisation(self):
        df = self.create_test_data_sample()
        df_random = df.copy().sample(frac=1)

        extracted_features = extract_features(df, self.settings, "id", "sort", "kind", "val").sort_index()
        extracted_features_from_random = extract_features(df_random, self.settings,
                                                          "id", "sort", "kind", "val").sort_index()


        six.assertCountEqual(self, extracted_features.columns, extracted_features_from_random.columns)

        for col in extracted_features:
            self.assertIsNone(np.testing.assert_array_almost_equal(extracted_features[col],
                                                                   extracted_features_from_random[col]))

Example 40

Project: ldsc
Source File: test_jackknife.py
View license
    def test_jknife_2d(self):
        pseudovalues = np.vstack([np.arange(10), np.arange(10)]).T
        (est, var, se, cov) = jk.Jackknife.jknife(pseudovalues)
        assert_array_almost_equal(var, np.array([[0.91666667, 0.91666667]]))
        assert_array_almost_equal(est, np.array([[4.5, 4.5]]))
        assert_array_almost_equal(
            cov, np.matrix([[0.91666667, 0.91666667], [0.91666667, 0.91666667]]))
        assert_array_almost_equal(se ** 2, var)
        assert_array_equal(cov.shape, (2, 2))
        assert_array_equal(var.shape, (1, 2))
        assert_array_equal(est.shape, (1, 2))
        assert_array_equal(se.shape, (1, 2))

Example 41

Project: lifelines
Source File: test_estimation.py
View license
    def test_output_against_R(self, rossi):
        # from http://cran.r-project.org/doc/contrib/Fox-Companion/appendix-cox-regression.pdf
        # Link is now broken, but this is the code:
        #
        # rossi <- read.csv('.../lifelines/datasets/rossi.csv')
        # mod.allison <- coxph(Surv(week, arrest) ~ fin + age + race + wexp + mar + paro + prio,
        #     data=rossi)
        # cat(round(mod.allison$coefficients, 4), sep=", ")
        expected = np.array([[-0.3794, -0.0574, 0.3139, -0.1498, -0.4337, -0.0849,  0.0915]])
        cf = CoxPHFitter(normalize=False)
        cf.fit(rossi, duration_col='week', event_col='arrest')
        npt.assert_array_almost_equal(cf.hazards_.values, expected, decimal=3)

Example 42

Project: lifelines
Source File: test_estimation.py
View license
    def test_penalized_output_against_R(self, rossi):
        # R code:
        #
        # rossi <- read.csv('.../lifelines/datasets/rossi.csv')
        # mod.allison <- coxph(Surv(week, arrest) ~ ridge(fin, age, race, wexp, mar, paro, prio,
        #                                                 theta=1.0, scale=FALSE), data=rossi)
        # cat(round(mod.allison$coefficients, 4), sep=", ")
        expected = np.array([[-0.3641, -0.0580, 0.2894, -0.1496, -0.3837, -0.0822, 0.0913]])
        cf = CoxPHFitter(normalize=False, penalizer=1.0)
        cf.fit(rossi, duration_col='week', event_col='arrest')
        npt.assert_array_almost_equal(cf.hazards_.values, expected, decimal=3)

Example 43

Project: lifetimes
Source File: test_estimation.py
View license
    def test_expectation_returns_same_value_Hardie_excel_sheet(self):
        bfg = estimation.BetaGeoFitter()
        bfg.fit(cdnow_customers['frequency'], cdnow_customers['recency'], cdnow_customers['T'], tol=1e-6)

        times = np.array([0.1429, 1.0, 3.00, 31.8571, 32.00, 78.00])
        expected = np.array([0.0078 ,0.0532 ,0.1506 ,1.0405,1.0437, 1.8576])
        actual = bfg.expected_number_of_purchases_up_to_time(times)
        npt.assert_array_almost_equal(actual, expected, decimal=3)

Example 44

Project: lifetimes
Source File: test_estimation.py
View license
    def test_params_out_is_close_to_BTYDplus(self):
        """ See https://github.com/mplatzer/BTYDplus """
        mbfg = estimation.ModifiedBetaGeoFitter()
        mbfg.fit(cdnow_customers['frequency'], cdnow_customers['recency'], cdnow_customers['T'], iterative_fitting=3)
        expected = np.array([0.525, 6.183, 0.891, 1.614])
        npt.assert_array_almost_equal(expected, np.array(mbfg._unload_params('r', 'alpha', 'a', 'b')), decimal=3)

Example 45

Project: APGL
Source File: UtilTest.py
View license
    def testPowerEigs(self): 
        n = 10 
        numRuns = 10 
        
        for i in range(numRuns): 
            A = numpy.random.rand(n, n)
            
            l, v = Util.powerEigs(A, 0.001)
            nptst.assert_array_almost_equal(v*l, A.dot(v), 2)
            
            u, V = numpy.linalg.eig(A)
            self.assertAlmostEquals(numpy.max(u), l, 2)
            
            try: 
                nptst.assert_array_almost_equal(V[:, 0], v, 2)
            except AssertionError: 
                nptst.assert_array_almost_equal(V[:, 0], -v, 2)

Example 46

Project: pymbar
Source File: utils_for_testing.py
View license
def assert_sparse_matrix_equal(m1, m2, decimal=6):
    """Assert two scipy.sparse matrices are equal."""
    # both are sparse matricies
    assert isspmatrix(m1)
    assert isspmatrix(m1)

    # make sure they have the same format
    eq_(m1.format, m2.format)

    # even though its called assert_array_almost_equal, it will
    # work for scalars
    assert_array_almost_equal((m1 - m2).sum(), 0, decimal=decimal)

Example 47

Project: PyFME
Source File: test_cessna_310.py
View license
def test_calculate_aero_forces_moments_alpha_beta_zero():
    aircraft = Cessna310()
    aircraft.q_inf = 0.5 * 1.225 * 100 ** 2
    aircraft.alpha = 0
    aircraft.beta = 0

    aircraft.controls = {'delta_elevator': 0,
                         'hor_tail_incidence': 0,
                         'delta_aileron': 0,
                         'delta_rudder': 0,
                         'delta_t': 0}

    L, D, Y, l, m, n = aircraft._calculate_aero_forces_moments()
    assert_array_almost_equal([L, D, Y],
                              [28679.16845, 2887.832934, 0.],
                              decimal=4)
    assert_array_almost_equal([l, m, n],
                              [0, 10177.065816, 0],
                              decimal=4)

Example 48

Project: scikit-aero
Source File: test_coesa.py
View license
def test_under_1000m():
    """Tests for altitude values under 1000.0 m

    """
    z = np.array([50.0, 550.0, 850.0])
    h = util.geometric_to_geopotential(z)
    expected_h = np.array([50.0, 550.0, 850.0])
    expected_T = np.array([287.825, 284.575, 282.626])
    expected_p = np.array([100720.0, 94890.0, 91523.0])
    expected_rho = np.array([1.2191, 1.1616, 1.1281])

    h, T, p, rho = coesa.table(h)

    assert_array_almost_equal(h, expected_h, decimal=0)
    assert_array_almost_equal(T, expected_T, decimal=3)
    assert_array_almost_equal(p, expected_p, decimal=-1)
    assert_array_almost_equal(rho, expected_rho, decimal=4)

Example 49

Project: dask
Source File: test_ghost.py
View license
def test_nearest_ghost():
    a = np.arange(144).reshape(12, 12).astype(float)

    darr = da.from_array(a, chunks=(6, 6))
    garr = ghost(darr, depth={0: 5, 1: 5},
                 boundary={0: 'nearest', 1: 'nearest'})
    tarr = trim_internal(garr, {0: 5, 1: 5})
    assert_array_almost_equal(tarr, a)

Example 50

View license
def test_fractional_anisotropy(N=10, random=numpy.random.RandomState(0)):
    tensors = random.randn(N, 3, 3)
    fa = numpy.empty(N)
    for i, t in enumerate(tensors):
        tt = numpy.dot(t, t.T)
        tensors[i] = tt
        ev = numpy.linalg.eigvalsh(tt)
        mn = ev.mean()
        fa[i] = numpy.sqrt(1.5 * ((ev - mn) ** 2).sum() / (ev ** 2).sum())

    assert_array_almost_equal(fa, scalar_measures.fractional_anisotropy(tensors))