Esempio n. 1
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def test_flip1_cgal():
    plot = False
    g = unstructured_grid.UnstructuredGrid()
    cdt = shadow_cdt.ShadowCGALCDT(g)

    pnts = [[0, 0], [8, 0], [10, 5], [5, 5], [3, 0]]

    [g.add_node(x=pnt) for pnt in pnts]
Esempio n. 2
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def test_constraints_dim1_cgal():
    g = unstructured_grid.UnstructuredGrid()
    cdt = shadow_cdt.ShadowCGALCDT(g)
    pnts = [[0, 0], [5, 0], [10, 0]]
    nodes = [g.add_node(x=pnt) for pnt in pnts]

    j0 = g.add_edge(nodes=[nodes[0], nodes[1]])
    j1 = g.add_edge(nodes=[nodes[1], nodes[2]])
    g.delete_edge(j0)
    g.delete_edge(j1)
    try:
        g.add_edge(nodes=[nodes[0], nodes[2]])
        assert False
    except cdt.ConstraintCollinearNode:
        pass  #
Esempio n. 3
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def test_remove_constraint_cgal():
    g = unstructured_grid.UnstructuredGrid()
    cdt = shadow_cdt.ShadowCGALCDT(g)

    # inserting a constraint
    pnts = [[0, 0], [5, 0], [10, 0], [5, 5], [3, 0], [6, 2], [12, 4]]
    nodes = [g.add_node(x=pnt) for pnt in pnts]

    j0 = g.add_edge(nodes=[nodes[4], nodes[6]])
    nodes.append(g.add_node(x=[7, 0.5]))

    g.delete_edge(j0)
    j1 = g.add_edge(nodes=[nodes[2], nodes[3]])
    j2 = g.add_edge(nodes=[nodes[4], nodes[7]])
    g.delete_edge(j1)
    g.delete_edge(j2)
Esempio n. 4
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def test_fuzz1_cgal():
    plot = False
    # Fuzzing, regular
    x = np.arange(5)
    y = np.arange(5)

    X, Y = np.meshgrid(x, y)
    xys = np.array([X.ravel(), Y.ravel()]).T

    if plot:
        plt.figure(1).clf()
        fig, ax = plt.subplots(num=1)

        ax.plot(xys[:, 0], xys[:, 1], 'go', alpha=0.4)
        ax.axis([-1, 5, -1, 5])

    idxs = np.zeros(len(xys), 'i8') - 1

    g = unstructured_grid.UnstructuredGrid()
    cdt = shadow_cdt.ShadowCGALCDT(g)

    # definitely slows down as the number of nodes gets larger.
    # starting off with <1s per 100 operations, later more like 2s
    for repeat in range(1):
        print "Repeat: ", repeat
        for step in range(1000):
            if step % 200 == 0:
                print "  step: ", step
            toggle = np.random.randint(len(idxs))
            if idxs[toggle] < 0:
                idxs[toggle] = g.add_node(x=xys[toggle])
            else:
                g.delete_node(idxs[toggle])
                idxs[toggle] = -1

            if plot:
                del ax.lines[1:]
                ax.texts = []
                ax.collections = []
                dt.plot_nodes(labeler=lambda n, nrec: str(n))
                dt.plot_edges(alpha=0.5, lw=2)
                dt.plot_cells(lw=7,
                              facecolor='#ddddff',
                              edgecolor='w',
                              zorder=-5)
                plt.draw()
Esempio n. 5
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def test_atomic_move_cgal():
    """ Make sure that when a modify_node call tries an
    illegal move of a node with a constraint, the DT state
    is restored to the original state before raising the exception
    """
    # inserting a constraint
    g = unstructured_grid.UnstructuredGrid()
    cdt = shadow_cdt.ShadowCGALCDT(g)

    pnts = [[0, 0], [5, 0], [10, 0], [5, 5], [3, 0], [6, 2], [12, 4]]
    nodes = [g.add_node(x=pnt) for pnt in pnts]

    j0 = g.add_edge(nodes=[nodes[0], nodes[5]])
    j1 = g.add_edge(nodes=[nodes[3], nodes[2]])

    assert np.all(g.nodes['x'][5] == [6, 2])

    try:
        g.modify_node(nodes[5], x=[8, 3])
        assert False  # it should raise the exception
    except cdt.IntersectingConstraints:
        # And the nodes/constraints should be where they started.
        assert np.all(g.nodes['x'][5] == [6, 2])
Esempio n. 6
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def test_basic1_cgal():
    g = unstructured_grid.UnstructuredGrid()
    cdt = shadow_cdt.ShadowCGALCDT(g)

    pnts = [[0, 0], [5, 0], [10, 0], [5, 5], [3, 0], [6, 2]]
    nodes = [g.add_node(x=pnt) for pnt in pnts]
Esempio n. 7
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def test_collinear():
    g = unstructured_grid.UnstructuredGrid()
    cdt = shadow_cdt.ShadowCGALCDT(g)

    xys = [[0, 0], [1, 0], [1, 1], [0, -1], [2, 0], [2, 1]]

    for xy in xys:
        g.add_node(x=xy)

    g.add_edge(nodes=[0, 1])
    g.add_edge(nodes=[0, 3])
    g.add_edge(nodes=[1, 2])
    g.add_edge(nodes=[1, 4])

    # this is problematic -
    #  in one case, it goes through a node, and the successive faces
    #  don't share an edge.  not sure if this is guaranteed behavior.
    #  even if it is, there could be a collinear node, but without
    #  extra adjacent faces, so we wouldn't know...
    # print segment_is_free(DT,vh[3], vh[5])

    # Want to detect that this failed:
    ##
    fig = plt.figure(1)
    fig.clf()
    g.plot_edges(lw=7, color='0.5')
    g.plot_nodes(labeler=lambda n, rec: str(n))

    plot_dt(cdt.DT, ax=fig.gca())

    ##

    a = 3
    b = 5

    # actions in the cdt before allowing the grid to add the edge:

    cdt.DT.insert_constraint(g.nodes['vh'][a], g.nodes['vh'][b])

    ##

    # traverse constrained edges from vh[3], trying to get
    # to vh[5]. Anonymous vertices mean we had intersecting constraints,
    # any other vertices mean collinear nodes.
    # the trick is figuring out how to traverse

    ##

    # stepping along from vh_trav
    def traverse_fresh_edge(self, a, b):
        """
        invoke after adding a constraint a--b, but before
        it has been added to self.g.

        steps from node a to node b, finding out what constrained
        edges actually were added.
        returns a list of tuples, each tuple is (node, vertex_handle)
        """

        vh_trav = self.g.nodes['vh'][a]
        vh_list = [(vh_trav, a)]

        while 1:
            # fetch list of constraints for traversal vertex handle
            constraints = []
            self.DT.incident_constraints(vh_trav, constraints)

            n_trav = self.vh_info[vh_trav]
            # which neighbors are already constrained
            trav_nbrs_to_ignore = list(self.g.node_to_nodes(n_trav))

            maybe_next = []  # potential vh for next step

            for edge in constraints:
                face = edge[0]  # work around missing API
                idx = edge[1]

                v1 = face.vertex((idx + 1) % 3)
                v2 = face.vertex((idx + 2) % 3)

                if v1 == vh_trav:
                    vh_other = v2
                else:
                    vh_other = v1

                n_me = self.vh_info[vh_trav]
                n_other = self.vh_info[vh_other]

                print "Checking constrained edge %s -- %s." % (n_me, n_other)

                # If this is an existing neighbor in some other direction, ignore.

                if n_other != b and n_other in trav_nbrs_to_ignore:
                    print "   [skip]"
                    continue
                if len(vh_list) > 1 and vh_other == vh_list[-2][0]:
                    print "   [backwards - skip]"
                    continue

                maybe_next.append((vh_other, n_other))
            assert len(maybe_next) == 1

            vh_trav, n_trav = maybe_next[0]
            vh_list.append(maybe_next[0])

            print "Stepped to node: %s" % (n_trav)

            if n_trav == b:
                print "Done with traversal"
                break
        return vh_list

    # This works okay..
    elts = traverse_fresh_edge(cdt, a, b)
Esempio n. 8
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    # This works okay..
    elts = traverse_fresh_edge(cdt, a, b)

    # what are the options?
    #   a. bring in the big guns like in live_dt.py
    #   b. ignore this, and move on to quad algorithm
    #   c. insert the edge, and if it doesn't come back
    #      looking right, rewind manually
    #      This seems best, assuming we can do that.


##

# def test_intersection():
g = unstructured_grid.UnstructuredGrid()
cdt = shadow_cdt.ShadowCGALCDT(g)

xys = [[0, 0], [1, 0], [1, 1], [0, -1], [2, 0], [2, 2]]

for xy in xys:
    g.add_node(x=xy)

g.add_edge(nodes=[0, 1])
g.add_edge(nodes=[0, 3])
g.add_edge(nodes=[1, 2])
g.add_edge(nodes=[1, 4])

# this is problematic -
#  in one case, it goes through a node, and the successive faces
#  don't share an edge.  not sure if this is guaranteed behavior.
#  even if it is, there could be a collinear node, but without