def test_multi_block_data_range():
volume = pyvista.Wavelet()
a = volume.slice_along_axis(5, 'x')
with pytest.raises(ValueError):
a.get_data_range('foo')
mi, ma = a.get_data_range(volume.active_scalars_name)
assert mi is not None
assert ma is not None
# Test on a nested MultiBlock
b = volume.slice_along_axis(5, 'y')
slices = pyvista.MultiBlock([a, b])
with pytest.raises(ValueError):
slices.get_data_range('foo')
mi, ma = slices.get_data_range(volume.active_scalars_name)
assert mi is not None
assert ma is not None
def test_find_closest_cell():
mesh = pyvista.Wavelet()
node = np.array([0, 0.2, 0.2])
with pytest.raises(ValueError):
mesh.find_closest_cell([1, 2])
with pytest.raises(TypeError):
# allow Sequence but not Iterable
mesh.find_closest_cell({1, 2, 3})
# array but bad size
with pytest.raises(ValueError):
mesh.find_closest_cell(np.empty(4))
index = mesh.find_closest_cell(node)
assert isinstance(index, int)
def test_wavelet():
mesh = pyvista.Wavelet()
assert mesh.n_points
assert mesh.n_cells
stitle='Elevation - interpolated',
**dargs)
p.link_views()
p.camera_position = [(-1.67, -5.10, 2.06), (0.0, 0.0, 0.0), (0.00, 0.37, 0.93)]
p.show()
###############################################################################
# The cylider mesh above is a great example dataset for this as it has a wide
# spread between the vertices (points are only at the top and bottom of the
# cylinder) which means high surface are of the mesh has to be interpolated.
#
# However, most meshes don't have such a wide spread and the effects of
# color interpolating are harder to notice. Let's take a look at a wavelet
# example and try to figure out how the ``interpolate_before_map`` option
# affects its rendering.
wavelet = pv.Wavelet().clip('x')
# Common display argument to make sure all else is constant
dargs = dict(scalars='RTData', cmap='rainbow', show_edges=True)
p = pv.Plotter(shape=(1, 2))
p.add_mesh(wavelet,
interpolate_before_map=False,
stitle='RTData - not interpolated',
**dargs)
p.subplot(0, 1)
p.add_mesh(wavelet,
interpolate_before_map=True,
stitle='RTData - interpolated',
**dargs)
p.link_views()
A spline widget can be enabled and disabled by the
:func:`pyvista.WidgetHelper.add_spline_widget` and
:func:`pyvista.WidgetHelper.clear_spline_widgets` methods respectively.
This widget allows users to interactively create a poly line (spline) through
a scene and use that spline.
A common task with splines is to slice a volumetric dataset using an irregular
path. To do this, we have added a convenient helper method which leverages the
:func:`pyvista.DataSetFilters.slice_along_line` filter named
:func:`pyvista.WidgetHelper.add_mesh_slice_spline`.
"""
import pyvista as pv
import numpy as np
##############################################################################
mesh = pv.Wavelet()
# initial spline to seed the example
points = np.array([[-8.64208925, -7.34294559, -9.13803458],
[-8.25601497, -2.54814702, 0.93860914],
[-0.30179377, -3.21555997, -4.19999019],
[3.24099167, 2.05814768, 3.39041509],
[4.39935227, 4.18804542, 8.96391132]])
p = pv.Plotter()
p.add_mesh(mesh.outline(), color='black')
p.add_mesh_slice_spline(mesh, initial_points=points, n_handles=5)
p.camera_position = [(30, -42, 30), (0.0, 0.0, 0.0), (-0.09, 0.53, 0.84)]
p.show()
