def test_slices_are_associated_single_index():
dataset = examples.load_structured()
points = pyvista_ndarray(dataset.GetPoints().GetData(), dataset=dataset)
assert points[1, 1].VTKObject == points.VTKObject
assert points[1, 1].dataset.Get() == points.dataset.Get()
assert points[1, 1].association == points.association
def datasets():
return [
examples.load_uniform(), # UniformGrid
examples.load_rectilinear(), # RectilinearGrid
examples.load_hexbeam(), # UnstructuredGrid
examples.load_airplane(), # PolyData
examples.load_structured(), # StructuredGrid
]
def test_slices_are_associated():
dataset = examples.load_structured()
points = pyvista_ndarray(dataset.GetPoints().GetData(), dataset=dataset)
# check that slices of pyvista_ndarray are associated correctly
assert points[1, :].VTKObject == points.VTKObject
assert points[1, :].dataset.Get() == points.dataset.Get()
assert points[1, :].association == points.association
def test_struct_example():
# create and plot structured grid
grid = examples.load_structured()
cpos = grid.plot(off_screen=True) # basic plot
assert isinstance(cpos, list)
# Plot mean curvature
cpos_curv = grid.plot_curvature(off_screen=True)
assert isinstance(cpos_curv, list)
def test_copies_are_not_associated():
dataset = examples.load_structured()
points = pyvista_ndarray(dataset.GetPoints().GetData(), dataset=dataset)
points_2 = points.copy()
# check that copies of pyvista_ndarray are dissociated from the original dataset
assert points_2.VTKObject is None
assert points_2.dataset is None
assert points_2.association.name == 'NONE'
assert not np.shares_memory(points, points_2)
def structured_grids_split_disconnected():
"""Two structured grids which are disconnected."""
structured = examples.load_structured()
point_data = (np.ones((80, 80)) * np.arange(0, 80)).ravel(order='F')
cell_data = (np.ones((79, 79)) * np.arange(0, 79)).T.ravel(order='F')
structured.point_arrays['point_data'] = point_data
structured.cell_arrays['cell_data'] = cell_data
voi_1 = structured.extract_subset([0, 80, 0, 40, 0, 1])
voi_2 = structured.extract_subset([0, 80, 45, 80, 0, 1])
return voi_1, voi_2
def structured_grids_split_coincident():
"""Two structured grids which are coincident along second axis (axis=1), and
the grid from which they were extracted."""
structured = examples.load_structured()
point_data = (np.ones((80, 80)) * np.arange(0, 80)).ravel(order='F')
cell_data = (np.ones((79, 79)) * np.arange(0, 79)).T.ravel(order='F')
structured.point_arrays['point_data'] = point_data
structured.cell_arrays['cell_data'] = cell_data
voi_1 = structured.extract_subset([0, 80, 0, 40, 0, 1])
voi_2 = structured.extract_subset([0, 80, 40, 80, 0, 1])
return voi_1, voi_2, structured
def test_modifying_modifies_dataset():
dataset = examples.load_structured()
points = pyvista_ndarray(dataset.GetPoints().GetData(), dataset=dataset)
dataset_modified = mock.Mock()
array_modified = mock.Mock()
dataset.AddObserver(_vtk.vtkCommand.ModifiedEvent, dataset_modified)
points.AddObserver(_vtk.vtkCommand.ModifiedEvent, array_modified)
# __setitem__ calls dataset.Modified() and points.Modified()
points[:] *= 0.5
assert dataset_modified.call_count == 1
assert array_modified.call_count == 1
# __setitem__ with single-indices works does same
points[0, 0] = 0.5
assert dataset_modified.call_count == 2
assert array_modified.call_count == 2
# setting all new points calls dataset.Modified()
dataset.points = points.copy()
assert dataset_modified.call_count == 3
assert array_modified.call_count == 2
import os
import sys
import platform
import numpy as np
import pytest
import pyvista
from pyvista import examples
DATASETS = [
examples.load_uniform(), # UniformGrid
examples.load_rectilinear(), # RectilinearGrid
examples.load_hexbeam(), # UnstructuredGrid
examples.load_airplane(), # PolyData
examples.load_structured(), # StructuredGrid
]
normals = ['x', 'y', '-z', (1, 1, 1), (3.3, 5.4, 0.8)]
COMPOSITE = pyvista.MultiBlock(DATASETS, deep=True)
skip_py2_nobind = pytest.mark.skipif(
int(sys.version[0]) < 3, reason="Python 2 doesn't support binding methods")
skip_windows = pytest.mark.skipif(os.name == 'nt',
reason="Flaky Windows tests")
skip_mac = pytest.mark.skipif(platform.system() == 'Darwin',
reason="Flaky Mac tests")
@pytest.fixture(scope='module')
mesh.dimensions = [29, 32, 1] # and then inspect it! mesh.plot(show_edges=True, show_grid=True, cpos="xy") ############################################################################### # Extending a 2D StructuredGrid to 3D # +++++++++++++++++++++++++++++++++++ # # A 2D :class:`pyvista.StructuredGrid` mesh can be extended into a 3D mesh. # This is highly applicable when wanting to create a terrain following mesh # in earth science research applications. # # For example, we could have a :class:`pyvista.StructuredGrid` of a topography # surface and extend that surface to a few different levels and connect each # "level" to create the 3D terrain following mesh. # # Let's start with a simple example by extending the wave mesh to 3D struct = examples.load_structured() struct.plot(show_edges=True) ############################################################################### top = struct.points.copy() bottom = struct.points.copy() bottom[:, -1] = -10.0 # Wherever you want the plane vol = pv.StructuredGrid() vol.points = np.vstack((top, bottom)) vol.dimensions = [*struct.dimensions[0:2], 2] vol.plot(show_edges=True)
def test_structured_add_non_grid():
grid = examples.load_structured()
merged = grid + examples.load_hexbeam()
assert isinstance(merged, pyvista.UnstructuredGrid)
def test_extract_subset_structured():
structured = examples.load_structured()
voi = structured.extract_subset([0, 3, 1, 4, 0, 1])
assert isinstance(voi, pyvista.StructuredGrid)
assert voi.dimensions == [4, 4, 1]
def test_struct_example():
# create and plot structured grid
grid = examples.load_structured()
grid.plot(off_screen=True) # basic plot
grid.plot_curvature(off_screen=True)