numpy.array.T

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

166 Examples 7

Example 1

Project: lifelines Source File: test_estimation.py
    def test_kmf_survival_curve_output_against_R(self):
        df = load_g3()
        ix = df['group'] == 'RIT'
        kmf = KaplanMeierFitter()

        expected = np.array([[0.909, 0.779]]).T
        kmf.fit(df.ix[ix]['time'], df.ix[ix]['event'], timeline=[25, 53])
        npt.assert_array_almost_equal(kmf.survival_function_.values, expected, decimal=3)

        expected = np.array([[0.833, 0.667, 0.5, 0.333]]).T
        kmf.fit(df.ix[~ix]['time'], df.ix[~ix]['event'], timeline=[9, 19, 32, 34])
        npt.assert_array_almost_equal(kmf.survival_function_.values, expected, decimal=3)

Example 2

Project: datasketch Source File: similarity_benchmark.py
Function: run_test
def _run_test(A, B, data, n, p, num_perm, b):
    logging.info("Running MinHash with num_perm = %d" % num_perm)
    minhash_runs, bbit_runs = np.array([_run_minhash(A, B, data,
            i, num_perm, b)
        for i in xrange(n)]).T
    logging.info("Running HyperLogLog with p = %d" % p)
    hll_runs = [_run_hyperloglog(A, B, data, i, p) for i in xrange(n)]
    return (minhash_runs, bbit_runs, hll_runs)

Example 3

Project: stingray Source File: test_io.py
    def test_save_ascii_with_format(self):
        time = ["bla", 1, 2, 3]
        counts = [2,3,41,4]
        write(np.array([time, counts]).T,
              filename="ascii_test.txt", format_="ascii",
              fmt=["%s", "%s"])

Example 4

Project: 2013-Sep-HR-ML-sprint Source File: nightmaremode.py
Function: group_data
def group_data(data, degree=2, hash=hash):
    """
    numpy.array -> numpy.array

    Groups all columns of data into all combinations of triples
    """
    new_data = []
    m,n = data.shape
    for indices in combinations(range(n), degree):
        new_data.append([hash(tuple(v)) for v in data[:,indices]])
    return array(new_data).T

Example 5

Project: DataSciencePython Source File: logistic_regression_updated.py
Function: group_data
def group_data(data, degree=3, hash=hash):
    """ 
    numpy.array -> numpy.array
    
    Groups all columns of data into all combinations of triples
    """
    new_data = []
    m,n = data.shape
    for indicies in combinations(range(n), degree):
        new_data.append([hash(tuple(v)) for v in data[:,indicies]])
    return array(new_data).T

Example 6

Project: rdfspace Source File: rdf_space_tests.py
def test_centrality():
    rdf_space = Space('tests/example.n3')
    # Overriding _ut
    rdf_space._ut = np.array([[-1,1,0,0],[1,0,0,0],[2,1,0,0],[3,1,1,1]], dtype=float).T
    # Overriding uri_index
    rdf_space._uri_index = {'http://0': 0, 'http://1': 1, 'http://2': 2, 'http://3': 3}

    assert_equal(rdf_space.centrality('http://0'), 1)
    assert_equal(rdf_space.centrality('http://1'), 1)
    assert_equal(rdf_space.centrality('http://2'), 2)
    assert_equal(rdf_space.centrality('http://3'), 3)

Example 7

Project: mindpark Source File: reader.py
    def _collect_columns(self, engine, table):
        result = engine.execute(sql.select([table]))
        columns = np.array([x for x in result]).T
        if not len(columns) or not columns.shape[1]:
            return None
        columns = Metric(
            id=np.array([int(x, 16) for x in columns[0]]),
            timestamp=columns[1],
            step=columns[2].astype(int),
            epoch=columns[3].astype(int),
            training=columns[4].astype(bool),
            episode=columns[5].astype(int),
            data=columns[6:].T.astype(float))
        columns = self._sort_columns(columns)
        return columns

Example 8

Project: scikit-image Source File: adapt_rgb.py
def each_channel(image_filter, image, *args, **kwargs):
    """Return color image by applying `image_filter` on channels of `image`.

    Note that this function is intended for use with `adapt_rgb`.

    Parameters
    ----------
    image_filter : function
        Function that filters a gray-scale image.
    image : array
        Input image.
    """
    c_new = [image_filter(c, *args, **kwargs) for c in image.T]
    return np.array(c_new).T

Example 9

Project: deepTools Source File: test_countReadsPerBin.py
    def test_countReadsInRegions_min_mapping_quality(self):
        # Test min mapping quality.
        self.c.minMappingQuality = 40
        self.c.skipZeros = False

        resp, _ = self.c.count_reads_in_region(self. chrom, 0, 200)
        nt.assert_equal(resp, np.array([[0, 0, 0, 1.],
                                        [0, 0, 0, 1.]]).T)

Example 10

Project: scikit-image Source File: test_colorconv.py
    def test_rgb2luv_brucelindbloom(self):
        """
        Test the RGB->Lab conversion by comparing to the calculator on the
        authoritative Bruce Lindbloom
        [website](http://brucelindbloom.com/index.html?ColorCalculator.html).
        """
        # Obtained with D65 white point, sRGB model and gamma
        gt_for_colbars = np.array([
            [100, 0, 0],
            [97.1393, 7.7056, 106.7866],
            [91.1132, -70.4773, -15.2042],
            [87.7347, -83.0776, 107.3985],
            [60.3242, 84.0714, -108.6834],
            [53.2408, 175.0151, 37.7564],
            [32.2970, -9.4054, -130.3423],
            [0, 0, 0]]).T
        gt_array = np.swapaxes(gt_for_colbars.reshape(3, 4, 2), 0, 2)
        assert_array_almost_equal(rgb2luv(self.colbars_array),
                                  gt_array, decimal=2)

Example 11

Project: tracer Source File: test_tracer_engine.py
    def setUp(self):
        dir = N.array([[1,1,-1],[-1,1,-1],[-1,-1,-1],[1,-1,-1]]).T/math.sqrt(3)
        position = N.c_[[0,0,1],[1,-1,1],[1,1,1],[-1,1,1]]
        self._bund = RayBundle(position, dir, energy=N.ones(4))
        
        self.assembly = Assembly()
        object = AssembledObject()
        object.add_surface(Surface(FlatGeometryManager(), opt.perfect_mirror))
        self.assembly.add_object(object)
        self.engine = TracerEngine(self.assembly)

Example 12

Project: PyFR Source File: polys.py
    @clean
    def ortho_basis_at(self, pts):
        if len(pts) and not isinstance(pts[0], Iterable):
            pts = [(p,) for p in pts]

        return np.array([self.ortho_basis_at_py(*p) for p in pts]).T

Example 13

Project: Chimp Source File: dqn_learner.py
    def save_training_history(self, path='.'):
        ''' save training history '''
        train_hist = np.array([range(len(self.train_rewards)),self.train_losses,self.train_rewards, self.train_qval_avgs, self.train_episodes, self.train_times]).T
        eval_hist = np.array([range(len(self.val_rewards)),self.val_losses,self.val_rewards, self.val_qval_avgs, self.val_episodes, self.val_times]).T
        # TODO: why is this here and not in agent?
        np.savetxt(path + '/training_hist.csv', train_hist, delimiter=',')
        np.savetxt(path + '/evaluation_hist.csv', eval_hist, delimiter=',')

Example 14

Project: acoular Source File: trajectory.py
    @property_depends_on('points[]')
    def _get_tck( self ):
        t = sort(self.points.keys())
        xp = array([self.points[i] for i in t]).T
        k = min(3, len(self.points)-1)
        tcku = splprep(xp, u=t, s=0, k=k)
        return tcku[0]

Example 15

Project: PRST Source File: test_utils.py
    def test_mul_ad_ad(self):
        # Answers computed using MRST's initVariablesADI
        x, y = initVariablesADI(np.array([[1,2]]).T, np.array([[4,5]]).T)
        z = x*y
        assert np.array_equal(z.val, np.array([[4, 10]]).T)
        assert np.array_equal(np.array([[4,0],[0,5]]), z.jac[0].toarray())
        assert np.array_equal(np.array([[1,0],[0,2]]), z.jac[1].toarray())

        f = x*x*y
        g = x*y*z
        h = f*g
        assert np.array_equal(h.val, np.array([[64, 2000]]).T)
        assert np.array_equal(np.array([[256,0],[0,4000]]), h.jac[0].toarray())
        assert np.array_equal(np.array([[48,0],[0,1200]]), h.jac[1].toarray())

        w = f*g + f + g*x*y
        assert np.array_equal(w.val, np.array([[132, 3020]]).T)
        assert np.array_equal(np.array([[456,0],[0,5520]]), w.jac[0].toarray())
        assert np.array_equal(np.array([[97,0],[0,1804]]), w.jac[1].toarray())

Example 16

Project: gala Source File: test_composite.py
    def test_shit(self):
        potential = self.Cls(one=self.p1, two=self.p2)

        q = np.ascontiguousarray(np.array([[1.1,0,0]]).T)
        print("val", potential.value(q))

        q = np.ascontiguousarray(np.array([[1.1,0,0]]).T)
        print("grad", potential.gradient(q))

Example 17

Project: statsmodels Source File: gam.py
Function: smoothed
    def smoothed(self, exog):
        '''get smoothed prediction for each component

        '''
        #bug: with exog in predict I get a shape error
        #print 'smoothed', exog.shape, self.smoothers[0].predict(exog).shape
        #there was a mistake exog didn't have column index i
        return np.array([self.smoothers[i].predict(exog[:,i]) + self.offset[i]
        #shouldn't be a mistake because exog[:,i] is attached to smoother, but
        #it is for different exog
        #return np.array([self.smoothers[i].predict() + self.offset[i]
                         for i in range(exog.shape[1])]).T

Example 18

Project: RITSAR Source File: signal.py
def sph2cart(sph):
    azimuth     = np.array([sph[:,0]]).T
    elevation   = np.array([sph[:,1]]).T
    r           = np.array([sph[:,2]]).T
    x = r * np.cos(elevation) * np.cos(azimuth)
    y = r * np.cos(elevation) * np.sin(azimuth)
    z = r * np.sin(elevation)
    cart = np.hstack([x,y,z])
    return cart

Example 19

Project: amazonaccess Source File: greedy.py
Function: group_data
def group_data(data, degree=3, hash=hash):
    new_data = []
    m, n = data.shape
    for indices in combinations(range(n), degree):
        new_data.append([hash(tuple(v)) for v in data[:, indices]])
    return np.array(new_data).T

Example 20

Project: chaco Source File: speedups_test_case.py
Function: test_masked
    def test_masked(self):
        index = linspace(0.0, 10.0, 11)
        value = linspace(0.0, 1.0, 11)
        index_mask = zeros(11, dtype=bool)
        index_mask[2:6] = 1
        value_mask = zeros(11, dtype=bool)
        value_mask[4:8] = 1

        points, selection = self.func(index, 0, 10, value, 0, 1,
                                index_mask = index_mask)
        desired = array([[2, 3, 4, 5], [0.2, 0.3, 0.4, 0.5]]).T
        assert_close(desired, points)

        points, selection = self.func(index, 0, 10, value, 0, 1,
                                index_mask = index_mask,
                                value_mask = value_mask)
        desired = array([[4, 0.4], [5, 0.5]])
        assert_close(desired, points)

Example 21

Project: properscoring Source File: test_crps.py
    def test_grad(self):
        from scipy import optimize
        f = lambda z: crps_gaussian(self.obs[0, 0], z[0], z[1], grad=False)
        g = lambda z: crps_gaussian(self.obs[0, 0], z[0], z[1], grad=True)[1]
        x0 = np.array([self.mu.reshape(-1),
                       self.sig.reshape(-1)]).T
        for x in x0:
            self.assertLessEqual(optimize.check_grad(f, g, x), 1e-6)

Example 22

Project: thunder Source File: test_series.py
def test_stat_by_index_multi(eng):
    index = [
        [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1],
        [0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1],
        [0, 1, 0, 1, 2, 3, 0, 1, 0, 1, 2, 3]
    ]
    data = fromlist([arange(12)], index=array(index).T, engine=eng)
    result = data.stat_by_index('sum', level=[0, 1])
    assert allclose(result.toarray(), array([1, 14, 13, 38]))
    assert allclose(result.index, array([[0, 0], [0, 1], [1, 0], [1, 1]]))
    result = data.sum_by_index(level=[0, 1])
    assert allclose(result.toarray(), array([1, 14, 13, 38]))
    assert allclose(result.index, array([[0, 0], [0, 1], [1, 0], [1, 1]]))

Example 23

Project: pykalman Source File: test_unscented.py
def test_qr():
    A = np.array([[1, 0.2, 1], [0.2, 0.8, 2]]).T
    R = qr(A)
    assert R.shape == (2, 2)

    assert_array_almost_equal(R.T.dot(R), A.T.dot(A))

Example 24

Project: mystic Source File: search.py
Function: samples
    def Samples(self):
        import numpy as np
        xy,xy,z = self.Trajectories()
        xy = np.vstack((np.array(xy).T,z))
        if self._inv: xy[-1,:] = -xy[-1]
        return xy #NOTE: actually xyz

Example 25

Project: scikit-learn Source File: multiclass.py
Function: predict
    def predict(self, X):
        """Predict multi-class targets using underlying estimators.

        Parameters
        ----------
        X : (sparse) array-like, shape = [n_samples, n_features]
            Data.

        Returns
        -------
        y : numpy array of shape [n_samples]
            Predicted multi-class targets.
        """
        check_is_fitted(self, 'estimators_')
        Y = np.array([_predict_binary(e, X) for e in self.estimators_]).T
        pred = euclidean_distances(Y, self.code_book_).argmin(axis=1)
        return self.classes_[pred]

Example 26

Project: tracer Source File: test_flat_surface.py
    def setUp(self):
        self._surf = Surface(FlatGeometryManager(), perfect_mirror)
        
        dir = N.array([[1, 1, -1], [-1, 1, -1], [-1, -1, -1], [1, -1, -1]]).T / math.sqrt(3)
        position = c_[[0,0,1], [1,-1,1], [1,1,1], [-1,1,1]]
        self._bund = RayBundle(position, dir, energy=N.ones(4)*100)

Example 27

Project: vispy Source File: cube.py
Function: rotate
def rotate(M, angle, x, y, z, point=None):
    angle = math.pi * angle / 180
    c, s = math.cos(angle), math.sin(angle)
    n = math.sqrt(x * x + y * y + z * z)
    x /= n
    y /= n
    z /= n
    cx, cy, cz = (1 - c) * x, (1 - c) * y, (1 - c) * z
    R = np.array([[cx * x + c, cy * x - z * s, cz * x + y * s, 0],
                  [cx * y + z * s, cy * y + c, cz * y - x * s, 0],
                  [cx * z - y * s, cy * z + x * s, cz * z + c, 0],
                  [0, 0, 0, 1]], dtype=M.dtype).T
    M[...] = np.dot(M, R)
    return M

Example 28

Project: iris Source File: test_rotate_winds.py
    def test_transposed(self):
        # Test case where the coordinates are not ordered yx in the cube.
        u, v = self._uv_cubes_limited_extent()
        # Slice out 4 points that lie in and outside OSGB extent.
        u = u[1:3, 3:5]
        v = v[1:3, 3:5]
        # Transpose cubes (in-place)
        u.transpose()
        v.transpose()
        ut, vt = rotate_winds(u, v, iris.coord_systems.OSGB())
        # Values precalculated and checked.
        expected_ut_data = np.array([[0.16285514,  0.35323639],
                                     [1.82650698,  2.62455840]]).T
        expected_vt_data = np.array([[19.88979966,  19.01921346],
                                     [19.88018847,  19.01424281]]).T
        # Compare u and v data values against previously calculated values.
        self.assertArrayAllClose(ut.data, expected_ut_data, rtol=1e-5)
        self.assertArrayAllClose(vt.data, expected_vt_data, rtol=1e-5)

Example 29

Project: tracer Source File: sphere_surface.py
Function: select_coords
    def _select_coords(self, coords, prm):
        """
        Select from dual intersections by checking which of the  impact points
        is contained in a volume defined at object creation time.
        """
        select = SphericalGM._select_coords(self, coords, prm)
        if self._bound is None:
            return select
        
        #in_bd = self._bound.in_bounds(coords) & (prm > 0)
        in_bd = N.array([self._bound.in_bounds(coords[...,c]) for c in xrange(prm.shape[1])]).T
        in_bd &= prm > 0
        select[~N.logical_or(*in_bd)] = N.nan
        one_hit = N.logical_xor(*in_bd)
        select[one_hit] = N.nonzero(in_bd[:,one_hit])[0]
        
        return select

Example 30

Project: PRST Source File: test_utils.py
Function: test_rsub
    def test_rsub(self):
        x, y = initVariablesADI(np.array([[1,2]]).T, np.array([[4]]).T)
        z = 5 - x
        assert np.array_equal(z.val, 5-x.val)
        assert (x+z).jac[0].nnz == 0
        assert (x+z).jac[1].nnz == 0

Example 31

Project: NeuroM Source File: transform.py
Function: call
    def __call__(self, points):
        '''Apply a 3D pivoted rotation to a set of points'''
        points = points - self._origin
        points = np.dot(self._dcm, np.array(points).T).T
        points += self._origin
        return points

Example 32

Project: rdfspace Source File: rdf_space_tests.py
def test_similarity():
    rdf_space = Space('tests/example.n3')
    # Overriding _ut
    rdf_space._ut = np.array([[0,1,0,0],[1,0,0,0],[0,1,0,0],[1,1,1,1]], dtype=float).T
    # Overriding uri_index
    rdf_space._uri_index = {'http://0': 0, 'http://1': 1, 'http://2': 2, 'http://3': 3}

    assert_equal(rdf_space.similarity('http://0', 'http://0'), 1.0)
    assert_equal(rdf_space.similarity('http://0', 'http://1'), 0)
    assert_equal(rdf_space.similarity('http://0', 'http://2'), 1.0)
    assert_equal(rdf_space.similarity('http://0', 'http://3'), 0.5)

Example 33

Project: ldsc Source File: jackknife.py
Function: init
    def __init__(self, x, y, n_blocks=None, nn=False, separators=None):
        Jackknife.__init__(self, x, y, n_blocks, separators)
        if nn:  # non-negative least squares
            func = lambda x, y: np.atleast_2d(nnls(x, np.array(y).T[0])[0])
        else:
            func = lambda x, y: np.atleast_2d(
                np.linalg.lstsq(x, np.array(y).T[0])[0])

        self.est = func(x, y)
        self.delete_values = self.delete_values(x, y, func, self.separators)
        self.pseudovalues = self.delete_values_to_pseudovalues(
            self.delete_values, self.est)
        (self.jknife_est, self.jknife_var, self.jknife_se, self.jknife_cov) =\
            self.jknife(self.pseudovalues)

Example 34

Project: amazonaccess Source File: logistic.py
Function: group_data
def group_data(data, degree=3, hash=hash):
    """ 
    numpy.array -> numpy.array
    
    Groups all columns of data into all combinations of triples
    """
    new_data = []
    m,n = data.shape
    for indicies in combinations(range(n), degree):
	if 5 in indicies and 7 in indicies:
	    print "feature Xd"
	elif 2 in indicies and 3 in indicies:
	    print "feature Xd"
	else:
            new_data.append([hash(tuple(v)) for v in data[:,indicies]])
    return array(new_data).T

Example 35

Project: gala Source File: test_nonlinear.py
@pytest.mark.skipif(True, reason="too slow")
def test_surface_of_section(tmpdir):
    # TODO: needs overhaul
    # from mpl_toolkits.mplot3d import Axes3D
    from ...potential import LogarithmicPotential
    from ...units import galactic

    pot = LogarithmicPotential(v_c=1., r_h=1., q1=1., q2=0.9, q3=0.8, units=galactic)

    w0 = np.array([[0.,0.8,0.,1.,0.,0.],
                   [0.,0.9,0.,1.,0.,0.]]).T
    orbit = pot.integrate_orbit(w0, dt=0.02, n_steps=100000)
    sos = surface_of_section(orbit, plane_ix=1)

Example 36

Project: rdfspace Source File: rdf_space_tests.py
def test_centroid():
    rdf_space = Space('tests/example.n3')
    # Overriding _ut
    rdf_space._ut = np.array([[0,1,0,0],[1,0,0,0],[0,1,0,0],[1,1,1,1]], dtype=float).T
    # Overriding uri_index
    rdf_space._uri_index = {'http://0': 0, 'http://1': 1, 'http://2': 2, 'http://3': 3}

    centroid = rdf_space.centroid(['http://0', 'http://1', 'http://2', 'http://3'])
    assert_array_equal(centroid, np.array([0.5, 0.75, 0.25, 0.25]))
    centroid = rdf_space.centroid(['http://0', 'http://3'])
    assert_array_equal(centroid, np.array([0.5, 1, 0.5, 0.5]))
    centroid = rdf_space.centroid(['http://0', 'http://1'])
    assert_array_equal(centroid, np.array([0.5, 0.5, 0, 0]))
    centroid = rdf_space.centroid(['http://0', 'http://6'])
    assert_array_equal(centroid, np.array([0, 1, 0, 0]))
    centroid = rdf_space.centroid([])
    assert_array_equal(centroid, None)

Example 37

Project: mindpark Source File: figure.py
Function: create_subplots
    def _create_subplots(self, rows, cols, **kwargs):
        size = [4 * cols, 3 * rows]
        fig, ax = plt.subplots(ncols=cols, nrows=rows, figsize=size, **kwargs)
        if cols == 1:
            ax = np.array([ax]).T
        return fig, ax

Example 38

Project: PRST Source File: test_utils.py
    def test_mul_ad_vector(self):
        x, y = initVariablesADI(np.array([[1,2,3]]).T, np.array([[4,5,6]]).T)
        w = x*x*y*np.array([[3],[3],[3]]) + x*y*y*np.array([[5],[5],[5]])
        assert np.array_equal(np.array([[92, 310, 702]]).T, w.val)
        assert np.array_equal(np.array([[104,0,0],[0,185,0], [0,0,288]]), w.jac[0].toarray())
        assert np.array_equal(np.array([[43,0,0],[0,112,0], [0,0,207]]), w.jac[1].toarray())
        z = np.array([[2]])
        f = x*z
        assert np.array_equal(np.array([[2, 4, 6]]).T, f.val)
        assert np.array_equal(np.array([[2,0,0],[0,2,0], [0,0,2]]), f.jac[0].toarray())
        assert np.array_equal(np.array([[0,0,0],[0,0,0], [0,0,0]]), f.jac[1].toarray())
        with pytest.raises(ValueError):
            x*np.array([[1,2]]).T

Example 39

Project: RITSAR Source File: signal.py
Function: cart2sph
def cart2sph(cart):
    x = np.array([cart[:,0]]).T
    y = np.array([cart[:,1]]).T
    z = np.array([cart[:,2]]).T
    azimuth = np.arctan2(y,x)
    elevation = np.arctan2(z,np.sqrt(x**2 + y**2))
    r = np.sqrt(x**2 + y**2 + z**2)
    sph = np.hstack([azimuth, elevation, r])
    return sph

Example 40

Project: stingray Source File: test_io.py
    def test_save_ascii_with_mixed_types(self):
        time = ["bla", 1, 2, 3]
        counts = [2,3,41,4]
        with pytest.raises(Exception):
             write(np.array([time, counts]).T,
                   "ascii_test.txt", "ascii")

Example 41

Project: datasketch Source File: b_bit_minhash_benchmark.py
Function: run_test
def _run_test(A, B, data, n, bs, num_perm):
    logging.info("Run tests with A = (%d, %d), B = (%d, %d), n = %d"
            % (A[0], A[1], B[0], B[1], n))
    runs = np.array([_run_minhash(A, B, data, i, bs, num_perm)
        for i in xrange(n)]).T
    return runs

Example 42

Project: pvlib-python Source File: test_spa.py
    def test_solar_position(self):
        assert_almost_equal(
            np.array([[theta, theta0, e, e0, Phi]]).T, self.spa.solar_position(
                unixtimes, lat, lon, elev, pressure, temp, delta_t,
                atmos_refract)[:-1], 5)
        assert_almost_equal(
            np.array([[v, alpha, delta]]).T, self.spa.solar_position(
                unixtimes, lat, lon, elev, pressure, temp, delta_t,
                atmos_refract, sst=True)[:3], 5)

Example 43

Project: chaco Source File: speedups_test_case.py
Function: test_basic
    def test_basic(self):
        index = linspace(0.0, 20.0, 21)
        value = linspace(0.0, 1.0, 21)
        points, selection = self.func(index, 4.5, 14.5, value, -1.0, 2.4)
        desired = array([[5, 6, 7, 8, 9, 10, 11, 12, 13, 14],
            [0.25, 0.3, 0.35, 0.4, 0.45, 0.5, 0.55, 0.6, 0.65, 0.8]]).T
        self.assert_(selection == None)
        assert_close(desired, points)

Example 44

Project: stingray Source File: test_io.py
Function: test_read_ascii
    def test_read_ascii(self):
        time = [1,2,3,4,5]
        counts = [5,7,8,2,3]
        np.savetxt("ascii_test.txt", np.array([time, counts]).T)
        read("ascii_test.txt", "ascii")
        os.remove("ascii_test.txt")

Example 45

Project: scikit-image Source File: test_colorconv.py
    def test_rgb2lab_brucelindbloom(self):
        """
        Test the RGB->Lab conversion by comparing to the calculator on the
        authoritative Bruce Lindbloom
        [website](http://brucelindbloom.com/index.html?ColorCalculator.html).
        """
        # Obtained with D65 white point, sRGB model and gamma
        gt_for_colbars = np.array([
            [100,0,0],
            [97.1393, -21.5537, 94.4780],
            [91.1132, -48.0875, -14.1312],
            [87.7347, -86.1827, 83.1793],
            [60.3242, 98.2343, -60.8249],
            [53.2408, 80.0925, 67.2032],
            [32.2970, 79.1875, -107.8602],
            [0,0,0]]).T
        gt_array = np.swapaxes(gt_for_colbars.reshape(3, 4, 2), 0, 2)
        assert_array_almost_equal(rgb2lab(self.colbars_array), gt_array, decimal=2)

Example 46

Project: popupcad Source File: solidworksimport.py
    @staticmethod
    def transform_loop(loop, R1, b1, R2, b2, scalefactor):
        looparray = numpy.array(loop).T

        v2 = R1.T.dot(R2.T.dot(looparray) + b2)
        v2 = v2[0:2, :].T
        v2 = v2 * scalefactor * popupcad.solidworks_mm_conversion
        return v2.tolist()

Example 47

Project: pvlib-python Source File: test_spa.py
    def test_solar_position_singlethreaded(self):
        assert_almost_equal(
            np.array([[theta, theta0, e, e0, Phi]]).T, self.spa.solar_position(
                unixtimes, lat, lon, elev, pressure, temp, delta_t,
                atmos_refract, numthreads=1)[:-1], 5)
        assert_almost_equal(
            np.array([[v, alpha, delta]]).T, self.spa.solar_position(
                unixtimes, lat, lon, elev, pressure, temp, delta_t,
                atmos_refract, numthreads=1, sst=True)[:3], 5)

Example 48

Project: msCentipede Source File: mscentipedepy.py
Function: transform
    def transform(self, profile):
        """Transform a vector of read counts or parameter values
        into a multiscale representation.
        
        .. note::
            See msCentipede manual for more details.   

        """

        for j in xrange(self.J):
            size = self.L/(2**(j+1))
            self.total[j] = np.array([profile[:,k*size:(k+2)*size,:].sum(1) for k in xrange(0,2**(j+1),2)]).T
            self.value[j] = np.array([profile[:,k*size:(k+1)*size,:].sum(1) for k in xrange(0,2**(j+1),2)]).T

Example 49

Project: scipy Source File: test_savitzky_golay.py
Function: test_polyder
def test_polyder():
    cases = [
        ([5], 0, [5]),
        ([5], 1, [0]),
        ([3, 2, 1], 0, [3, 2, 1]),
        ([3, 2, 1], 1, [6, 2]),
        ([3, 2, 1], 2, [6]),
        ([3, 2, 1], 3, [0]),
        ([[3, 2, 1], [5, 6, 7]], 0, [[3, 2, 1], [5, 6, 7]]),
        ([[3, 2, 1], [5, 6, 7]], 1, [[6, 2], [10, 6]]),
        ([[3, 2, 1], [5, 6, 7]], 2, [[6], [10]]),
        ([[3, 2, 1], [5, 6, 7]], 3, [[0], [0]]),
    ]
    for p, m, expected in cases:
        yield check_polyder, np.array(p).T, m, np.array(expected).T

Example 50

Project: vispy Source File: cube.py
Function: translate
def translate(M, x, y=None, z=None):
    y = x if y is None else y
    z = x if z is None else z
    T = np.array([[1.0, 0.0, 0.0, x],
                  [0.0, 1.0, 0.0, y],
                  [0.0, 0.0, 1.0, z],
                  [0.0, 0.0, 0.0, 1.0]], dtype=M.dtype).T
    M[...] = np.dot(M, T)
    return M
See More Examples - Go to Next Page
Page 1 Selected Page 2 Page 3 Page 4