Python matplotlib._tri.Triangulation() Examples

def set_mask(self, mask):
        """
        Set or clear the mask array.  This is either None, or a boolean
        array of shape (ntri).
        """
        if mask is None:
            self.mask = None
        else:
            self.mask = np.asarray(mask, dtype=np.bool)
            if len(self.mask.shape) != 1 or \
                    self.mask.shape[0] != self.triangles.shape[0]:
                raise ValueError('mask array must have same length as '
                                 'triangles array')

        # Set mask in C++ Triangulation.
        if self._cpp_triangulation is not None:
            self._cpp_triangulation.set_mask(self.mask)

        # Clear derived fields so they are recalculated when needed.
        self._edges = None
        self._neighbors = None

        # Recalculate TriFinder if it exists.
        if self._trifinder is not None:
            self._trifinder._initialize() 

def set_mask(self, mask):
        """
        Set or clear the mask array.  This is either None, or a boolean
        array of shape (ntri).
        """
        if mask is None:
            self.mask = None
        else:
            self.mask = np.asarray(mask, dtype=bool)
            if self.mask.shape != (self.triangles.shape[0],):
                raise ValueError('mask array must have same length as '
                                 'triangles array')

        # Set mask in C++ Triangulation.
        if self._cpp_triangulation is not None:
            self._cpp_triangulation.set_mask(self.mask)

        # Clear derived fields so they are recalculated when needed.
        self._edges = None
        self._neighbors = None

        # Recalculate TriFinder if it exists.
        if self._trifinder is not None:
            self._trifinder._initialize() 

def test_trirefiner_fortran_contiguous_triangles():
    # github issue 4180.  Test requires two arrays of triangles that are
    # identical except that one is C-contiguous and one is fortran-contiguous.
    triangles1 = np.array([[2, 0, 3], [2, 1, 0]])
    assert not np.isfortran(triangles1)

    triangles2 = np.array(triangles1, copy=True, order='F')
    assert np.isfortran(triangles2)

    x = np.array([0.39, 0.59, 0.43, 0.32])
    y = np.array([33.99, 34.01, 34.19, 34.18])
    triang1 = mtri.Triangulation(x, y, triangles1)
    triang2 = mtri.Triangulation(x, y, triangles2)

    refiner1 = mtri.UniformTriRefiner(triang1)
    refiner2 = mtri.UniformTriRefiner(triang2)

    fine_triang1 = refiner1.refine_triangulation(subdiv=1)
    fine_triang2 = refiner2.refine_triangulation(subdiv=1)

    assert_array_equal(fine_triang1.triangles, fine_triang2.triangles) 

def test_qhull_triangle_orientation():
    # github issue 4437.
    xi = np.linspace(-2, 2, 100)
    x, y = map(np.ravel, np.meshgrid(xi, xi))
    w = np.logical_and(x > y - 1, np.logical_and(x < -1.95, y > -1.2))
    x, y = x[w], y[w]
    theta = np.radians(25)
    x1 = x*np.cos(theta) - y*np.sin(theta)
    y1 = x*np.sin(theta) + y*np.cos(theta)

    # Calculate Delaunay triangulation using Qhull.
    triang = mtri.Triangulation(x1, y1)

    # Neighbors returned by Qhull.
    qhull_neighbors = triang.neighbors

    # Obtain neighbors using own C++ calculation.
    triang._neighbors = None
    own_neighbors = triang.neighbors

    assert_array_equal(qhull_neighbors, own_neighbors) 

def set_mask(self, mask):
        """
        Set or clear the mask array.  This is either None, or a boolean
        array of shape (ntri).
        """
        if mask is None:
            self.mask = None
        else:
            self.mask = np.asarray(mask, dtype=bool)
            if self.mask.shape != (self.triangles.shape[0],):
                raise ValueError('mask array must have same length as '
                                 'triangles array')

        # Set mask in C++ Triangulation.
        if self._cpp_triangulation is not None:
            self._cpp_triangulation.set_mask(self.mask)

        # Clear derived fields so they are recalculated when needed.
        self._edges = None
        self._neighbors = None

        # Recalculate TriFinder if it exists.
        if self._trifinder is not None:
            self._trifinder._initialize() 

def test_tripcolor():
    x = np.asarray([0, 0.5, 1, 0,   0.5, 1,   0, 0.5, 1, 0.75])
    y = np.asarray([0, 0,   0, 0.5, 0.5, 0.5, 1, 1,   1, 0.75])
    triangles = np.asarray([
        [0, 1, 3], [1, 4, 3],
        [1, 2, 4], [2, 5, 4],
        [3, 4, 6], [4, 7, 6],
        [4, 5, 9], [7, 4, 9], [8, 7, 9], [5, 8, 9]])

    # Triangulation with same number of points and triangles.
    triang = mtri.Triangulation(x, y, triangles)

    Cpoints = x + 0.5*y

    xmid = x[triang.triangles].mean(axis=1)
    ymid = y[triang.triangles].mean(axis=1)
    Cfaces = 0.5*xmid + ymid

    plt.subplot(121)
    plt.tripcolor(triang, Cpoints, edgecolors='k')
    plt.title('point colors')

    plt.subplot(122)
    plt.tripcolor(triang, facecolors=Cfaces, edgecolors='k')
    plt.title('facecolors') 

def test_tripcolor():
    x = np.asarray([0, 0.5, 1, 0,   0.5, 1,   0, 0.5, 1, 0.75])
    y = np.asarray([0, 0,   0, 0.5, 0.5, 0.5, 1, 1,   1, 0.75])
    triangles = np.asarray([
        [0, 1, 3], [1, 4, 3],
        [1, 2, 4], [2, 5, 4],
        [3, 4, 6], [4, 7, 6],
        [4, 5, 9], [7, 4, 9], [8, 7, 9], [5, 8, 9]])

    # Triangulation with same number of points and triangles.
    triang = mtri.Triangulation(x, y, triangles)

    Cpoints = x + 0.5*y

    xmid = x[triang.triangles].mean(axis=1)
    ymid = y[triang.triangles].mean(axis=1)
    Cfaces = 0.5*xmid + ymid

    plt.subplot(121)
    plt.tripcolor(triang, Cpoints, edgecolors='k')
    plt.title('point colors')

    plt.subplot(122)
    plt.tripcolor(triang, facecolors=Cfaces, edgecolors='k')
    plt.title('facecolors') 

def set_mask(self, mask):
        """
        Set or clear the mask array.  This is either None, or a boolean
        array of shape (ntri).
        """
        if mask is None:
            self.mask = None
        else:
            self.mask = np.asarray(mask, dtype=np.bool)
            if (len(self.mask.shape) != 1 or
                    self.mask.shape[0] != self.triangles.shape[0]):
                raise ValueError('mask array must have same length as '
                                 'triangles array')

        # Set mask in C++ Triangulation.
        if self._cpp_triangulation is not None:
            self._cpp_triangulation.set_mask(self.mask)

        # Clear derived fields so they are recalculated when needed.
        self._edges = None
        self._neighbors = None

        # Recalculate TriFinder if it exists.
        if self._trifinder is not None:
            self._trifinder._initialize() 

def set_mask(self, mask):
        """
        Set or clear the mask array.  This is either None, or a boolean
        array of shape (ntri).
        """
        if mask is None:
            self.mask = None
        else:
            self.mask = np.asarray(mask, dtype=bool)
            if self.mask.shape != (self.triangles.shape[0],):
                raise ValueError('mask array must have same length as '
                                 'triangles array')

        # Set mask in C++ Triangulation.
        if self._cpp_triangulation is not None:
            self._cpp_triangulation.set_mask(self.mask)

        # Clear derived fields so they are recalculated when needed.
        self._edges = None
        self._neighbors = None

        # Recalculate TriFinder if it exists.
        if self._trifinder is not None:
            self._trifinder._initialize() 

def set_mask(self, mask):
        """
        Set or clear the mask array.  This is either None, or a boolean
        array of shape (ntri).
        """
        if mask is None:
            self.mask = None
        else:
            self.mask = np.asarray(mask, dtype=bool)
            if self.mask.shape != (self.triangles.shape[0],):
                raise ValueError('mask array must have same length as '
                                 'triangles array')

        # Set mask in C++ Triangulation.
        if self._cpp_triangulation is not None:
            self._cpp_triangulation.set_mask(self.mask)

        # Clear derived fields so they are recalculated when needed.
        self._edges = None
        self._neighbors = None

        # Recalculate TriFinder if it exists.
        if self._trifinder is not None:
            self._trifinder._initialize() 

def set_mask(self, mask):
        """
        Set or clear the mask array.  This is either None, or a boolean
        array of shape (ntri).
        """
        if mask is None:
            self.mask = None
        else:
            self.mask = np.asarray(mask, dtype=bool)
            if self.mask.shape != (self.triangles.shape[0],):
                raise ValueError('mask array must have same length as '
                                 'triangles array')

        # Set mask in C++ Triangulation.
        if self._cpp_triangulation is not None:
            self._cpp_triangulation.set_mask(self.mask)

        # Clear derived fields so they are recalculated when needed.
        self._edges = None
        self._neighbors = None

        # Recalculate TriFinder if it exists.
        if self._trifinder is not None:
            self._trifinder._initialize() 

def set_mask(self, mask):
        """
        Set or clear the mask array.  This is either None, or a boolean
        array of shape (ntri).
        """
        if mask is None:
            self.mask = None
        else:
            self.mask = np.asarray(mask, dtype=np.bool)
            if (len(self.mask.shape) != 1 or
                    self.mask.shape[0] != self.triangles.shape[0]):
                raise ValueError('mask array must have same length as '
                                 'triangles array')

        # Set mask in C++ Triangulation.
        if self._cpp_triangulation is not None:
            self._cpp_triangulation.set_mask(self.mask)

        # Clear derived fields so they are recalculated when needed.
        self._edges = None
        self._neighbors = None

        # Recalculate TriFinder if it exists.
        if self._trifinder is not None:
            self._trifinder._initialize() 

def set_mask(self, mask):
        """
        Set or clear the mask array.  This is either None, or a boolean
        array of shape (ntri).
        """
        if mask is None:
            self.mask = None
        else:
            self.mask = np.asarray(mask, dtype=bool)
            if self.mask.shape != (self.triangles.shape[0],):
                raise ValueError('mask array must have same length as '
                                 'triangles array')

        # Set mask in C++ Triangulation.
        if self._cpp_triangulation is not None:
            self._cpp_triangulation.set_mask(self.mask)

        # Clear derived fields so they are recalculated when needed.
        self._edges = None
        self._neighbors = None

        # Recalculate TriFinder if it exists.
        if self._trifinder is not None:
            self._trifinder._initialize() 

def test_trirefiner_fortran_contiguous_triangles():
    # github issue 4180.  Test requires two arrays of triangles that are
    # identical except that one is C-contiguous and one is fortran-contiguous.
    triangles1 = np.array([[2, 0, 3], [2, 1, 0]])
    assert not np.isfortran(triangles1)

    triangles2 = np.array(triangles1, copy=True, order='F')
    assert np.isfortran(triangles2)

    x = np.array([0.39, 0.59, 0.43, 0.32])
    y = np.array([33.99, 34.01, 34.19, 34.18])
    triang1 = mtri.Triangulation(x, y, triangles1)
    triang2 = mtri.Triangulation(x, y, triangles2)

    refiner1 = mtri.UniformTriRefiner(triang1)
    refiner2 = mtri.UniformTriRefiner(triang2)

    fine_triang1 = refiner1.refine_triangulation(subdiv=1)
    fine_triang2 = refiner2.refine_triangulation(subdiv=1)

    assert_array_equal(fine_triang1.triangles, fine_triang2.triangles) 

def test_tripcolor():
    x = np.asarray([0, 0.5, 1, 0,   0.5, 1,   0, 0.5, 1, 0.75])
    y = np.asarray([0, 0,   0, 0.5, 0.5, 0.5, 1, 1,   1, 0.75])
    triangles = np.asarray([
        [0, 1, 3], [1, 4, 3],
        [1, 2, 4], [2, 5, 4],
        [3, 4, 6], [4, 7, 6],
        [4, 5, 9], [7, 4, 9], [8, 7, 9], [5, 8, 9]])

    # Triangulation with same number of points and triangles.
    triang = mtri.Triangulation(x, y, triangles)

    Cpoints = x + 0.5*y

    xmid = x[triang.triangles].mean(axis=1)
    ymid = y[triang.triangles].mean(axis=1)
    Cfaces = 0.5*xmid + ymid

    plt.subplot(121)
    plt.tripcolor(triang, Cpoints, edgecolors='k')
    plt.title('point colors')

    plt.subplot(122)
    plt.tripcolor(triang, facecolors=Cfaces, edgecolors='k')
    plt.title('facecolors') 

def set_mask(self, mask):
        """
        Set or clear the mask array.  This is either None, or a boolean
        array of shape (ntri).
        """
        if mask is None:
            self.mask = None
        else:
            self.mask = np.asarray(mask, dtype=np.bool)
            if len(self.mask.shape) != 1 or \
                    self.mask.shape[0] != self.triangles.shape[0]:
                raise ValueError('mask array must have same length as '
                                 'triangles array')

        # Set mask in C++ Triangulation.
        if self._cpp_triangulation is not None:
            self._cpp_triangulation.set_mask(self.mask)

        # Clear derived fields so they are recalculated when needed.
        self._edges = None
        self._neighbors = None

        # Recalculate TriFinder if it exists.
        if self._trifinder is not None:
            self._trifinder._initialize() 

def test_qhull_triangle_orientation():
    # github issue 4437.
    xi = np.linspace(-2, 2, 100)
    x, y = map(np.ravel, np.meshgrid(xi, xi))
    w = np.logical_and(x > y - 1, np.logical_and(x < -1.95, y > -1.2))
    x, y = x[w], y[w]
    theta = np.radians(25)
    x1 = x*np.cos(theta) - y*np.sin(theta)
    y1 = x*np.sin(theta) + y*np.cos(theta)

    # Calculate Delaunay triangulation using Qhull.
    triang = mtri.Triangulation(x1, y1)

    # Neighbors returned by Qhull.
    qhull_neighbors = triang.neighbors

    # Obtain neighbors using own C++ calculation.
    triang._neighbors = None
    own_neighbors = triang.neighbors

    assert_array_equal(qhull_neighbors, own_neighbors) 

def test_delaunay():
    # No duplicate points, regular grid.
    nx = 5
    ny = 4
    x, y = np.meshgrid(np.linspace(0.0, 1.0, nx), np.linspace(0.0, 1.0, ny))
    x = x.ravel()
    y = y.ravel()
    npoints = nx*ny
    ntriangles = 2 * (nx-1) * (ny-1)
    nedges = 3*nx*ny - 2*nx - 2*ny + 1

    # Create delaunay triangulation.
    triang = mtri.Triangulation(x, y)

    # The tests in the remainder of this function should be passed by any
    # triangulation that does not contain duplicate points.

    # Points - floating point.
    assert_array_almost_equal(triang.x, x)
    assert_array_almost_equal(triang.y, y)

    # Triangles - integers.
    assert len(triang.triangles) == ntriangles
    assert np.min(triang.triangles) == 0
    assert np.max(triang.triangles) == npoints-1

    # Edges - integers.
    assert len(triang.edges) == nedges
    assert np.min(triang.edges) == 0
    assert np.max(triang.edges) == npoints-1

    # Neighbors - integers.
    # Check that neighbors calculated by C++ triangulation class are the same
    # as those returned from delaunay routine.
    neighbors = triang.neighbors
    triang._neighbors = None
    assert_array_equal(triang.neighbors, neighbors)

    # Is each point used in at least one triangle?
    assert_array_equal(np.unique(triang.triangles), np.arange(npoints)) 

def __init__(self, x, y, triangles=None, mask=None):
        self.x = np.asarray(x, dtype=np.float64)
        self.y = np.asarray(y, dtype=np.float64)
        if self.x.shape != self.y.shape or self.x.ndim != 1:
            raise ValueError("x and y must be equal-length 1-D arrays")

        self.mask = None
        self._edges = None
        self._neighbors = None
        self.is_delaunay = False

        if triangles is None:
            # No triangulation specified, so use matplotlib._qhull to obtain
            # Delaunay triangulation.
            self.triangles, self._neighbors = _qhull.delaunay(x, y)
            self.is_delaunay = True
        else:
            # Triangulation specified. Copy, since we may correct triangle
            # orientation.
            self.triangles = np.array(triangles, dtype=np.int32, order='C')
            if self.triangles.ndim != 2 or self.triangles.shape[1] != 3:
                raise ValueError('triangles must be a (?,3) array')
            if self.triangles.max() >= len(self.x):
                raise ValueError('triangles max element is out of bounds')
            if self.triangles.min() < 0:
                raise ValueError('triangles min element is out of bounds')

        if mask is not None:
            self.mask = np.asarray(mask, dtype=bool)
            if self.mask.shape != (self.triangles.shape[0],):
                raise ValueError('mask array must have same length as '
                                 'triangles array')

        # Underlying C++ object is not created until first needed.
        self._cpp_triangulation = None

        # Default TriFinder not created until needed.
        self._trifinder = None 

def get_cpp_triangulation(self):
        # Return the underlying C++ Triangulation object, creating it
        # if necessary.
        if self._cpp_triangulation is None:
            self._cpp_triangulation = _tri.Triangulation(
                self.x, self.y, self.triangles, self.mask, self._edges,
                self._neighbors, not self.is_delaunay)
        return self._cpp_triangulation 

def test_delaunay_insufficient_points(x, y):
    with pytest.raises(ValueError):
        mtri.Triangulation(x, y) 

def test_delaunay_points_in_line():
    # Cannot triangulate points that are all in a straight line, but check
    # that delaunay code fails gracefully.
    x = np.linspace(0.0, 10.0, 11)
    y = np.linspace(0.0, 10.0, 11)
    with pytest.raises(RuntimeError):
        mtri.Triangulation(x, y)

    # Add an extra point not on the line and the triangulation is OK.
    x = np.append(x, 2.0)
    y = np.append(y, 8.0)
    triang = mtri.Triangulation(x, y) 

def __init__(self, x, y, triangles=None, mask=None):
        self.x = np.asarray(x, dtype=np.float64)
        self.y = np.asarray(y, dtype=np.float64)
        if self.x.shape != self.y.shape or len(self.x.shape) != 1:
            raise ValueError("x and y must be equal-length 1-D arrays")

        self.mask = None
        self._edges = None
        self._neighbors = None
        self.is_delaunay = False

        if triangles is None:
            # No triangulation specified, so use matplotlib._qhull to obtain
            # Delaunay triangulation.
            self.triangles, self._neighbors = _qhull.delaunay(x, y)
            self.is_delaunay = True
        else:
            # Triangulation specified. Copy, since we may correct triangle
            # orientation.
            self.triangles = np.array(triangles, dtype=np.int32)
            if self.triangles.ndim != 2 or self.triangles.shape[1] != 3:
                raise ValueError('triangles must be a (?,3) array')
            if self.triangles.max() >= len(self.x):
                raise ValueError('triangles max element is out of bounds')
            if self.triangles.min() < 0:
                raise ValueError('triangles min element is out of bounds')

        if mask is not None:
            self.mask = np.asarray(mask, dtype=np.bool)
            if (len(self.mask.shape) != 1 or
                    self.mask.shape[0] != self.triangles.shape[0]):
                raise ValueError('mask array must have same length as '
                                 'triangles array')

        # Underlying C++ object is not created until first needed.
        self._cpp_triangulation = None

        # Default TriFinder not created until needed.
        self._trifinder = None 

def test_delaunay_insufficient_points(x, y):
    with pytest.raises(ValueError):
        mtri.Triangulation(x, y) 

def test_delaunay_points_in_line():
    # Cannot triangulate points that are all in a straight line, but check
    # that delaunay code fails gracefully.
    x = np.linspace(0.0, 10.0, 11)
    y = np.linspace(0.0, 10.0, 11)
    with pytest.raises(RuntimeError):
        mtri.Triangulation(x, y)

    # Add an extra point not on the line and the triangulation is OK.
    x = np.append(x, 2.0)
    y = np.append(y, 8.0)
    triang = mtri.Triangulation(x, y) 

def test_delaunay():
    # No duplicate points, regular grid.
    nx = 5
    ny = 4
    x, y = np.meshgrid(np.linspace(0.0, 1.0, nx), np.linspace(0.0, 1.0, ny))
    x = x.ravel()
    y = y.ravel()
    npoints = nx*ny
    ntriangles = 2 * (nx-1) * (ny-1)
    nedges = 3*nx*ny - 2*nx - 2*ny + 1

    # Create delaunay triangulation.
    triang = mtri.Triangulation(x, y)

    # The tests in the remainder of this function should be passed by any
    # triangulation that does not contain duplicate points.

    # Points - floating point.
    assert_array_almost_equal(triang.x, x)
    assert_array_almost_equal(triang.y, y)

    # Triangles - integers.
    assert len(triang.triangles) == ntriangles
    assert np.min(triang.triangles) == 0
    assert np.max(triang.triangles) == npoints-1

    # Edges - integers.
    assert len(triang.edges) == nedges
    assert np.min(triang.edges) == 0
    assert np.max(triang.edges) == npoints-1

    # Neighbors - integers.
    # Check that neighbors calculated by C++ triangulation class are the same
    # as those returned from delaunay routine.
    neighbors = triang.neighbors
    triang._neighbors = None
    assert_array_equal(triang.neighbors, neighbors)

    # Is each point used in at least one triangle?
    assert_array_equal(np.unique(triang.triangles), np.arange(npoints)) 

def get_cpp_triangulation(self):
        """
        Return the underlying C++ Triangulation object, creating it
        if necessary.
        """
        if self._cpp_triangulation is None:
            self._cpp_triangulation = _tri.Triangulation(
                self.x, self.y, self.triangles, self.mask, self._edges,
                self._neighbors, not self.is_delaunay)
        return self._cpp_triangulation 

def __init__(self, x, y, triangles=None, mask=None):
        self.x = np.asarray(x, dtype=np.float64)
        self.y = np.asarray(y, dtype=np.float64)
        if self.x.shape != self.y.shape or self.x.ndim != 1:
            raise ValueError("x and y must be equal-length 1-D arrays")

        self.mask = None
        self._edges = None
        self._neighbors = None
        self.is_delaunay = False

        if triangles is None:
            # No triangulation specified, so use matplotlib._qhull to obtain
            # Delaunay triangulation.
            self.triangles, self._neighbors = _qhull.delaunay(x, y)
            self.is_delaunay = True
        else:
            # Triangulation specified. Copy, since we may correct triangle
            # orientation.
            self.triangles = np.array(triangles, dtype=np.int32, order='C')
            if self.triangles.ndim != 2 or self.triangles.shape[1] != 3:
                raise ValueError('triangles must be a (?,3) array')
            if self.triangles.max() >= len(self.x):
                raise ValueError('triangles max element is out of bounds')
            if self.triangles.min() < 0:
                raise ValueError('triangles min element is out of bounds')

        if mask is not None:
            self.mask = np.asarray(mask, dtype=bool)
            if self.mask.shape != (self.triangles.shape[0],):
                raise ValueError('mask array must have same length as '
                                 'triangles array')

        # Underlying C++ object is not created until first needed.
        self._cpp_triangulation = None

        # Default TriFinder not created until needed.
        self._trifinder = None 

def get_cpp_triangulation(self):
        # Return the underlying C++ Triangulation object, creating it
        # if necessary.
        if self._cpp_triangulation is None:
            self._cpp_triangulation = _tri.Triangulation(
                self.x, self.y, self.triangles, self.mask, self._edges,
                self._neighbors)
        return self._cpp_triangulation 

def get_cpp_triangulation(self):
        # Return the underlying C++ Triangulation object, creating it
        # if necessary.
        if self._cpp_triangulation is None:
            self._cpp_triangulation = _tri.Triangulation(
                self.x, self.y, self.triangles, self.mask, self._edges,
                self._neighbors)
        return self._cpp_triangulation