def simple_cow(self, fbo):
from pyvista import examples
# download mesh
mesh = examples.download_cow()
decimated = mesh.decimate_boundary(target_reduction=0.75)
fbo.set_subplots((1, 2))
fbo.subplot(0, 0)
fbo.add_text("Original mesh", font_size=24, color='black')
fbo.add_mesh(mesh, show_edges=True, color='brown')
fbo.subplot(0, 1)
fbo.add_text("Decimated version", font_size=24, color='black')
fbo.add_mesh(decimated, show_edges=True, color=True)
fbo.link_views() # link all the views
# Set a camera position to all linked views
fbo.camera_position = [(15, 5, 0), (0, 0, 0), (0, 1, 0)]
fbo.set_background('red')
fbo.update()
style = MouseInteractorHighLightActor(ren_win=fbo.ren_win,
ren=fbo.renderers)
# style.SetDefaultRenderer(fbo.renderer)
fbo._style_class = style
fbo.update_style()
image_data = fbo.image
print(image_data)
def test_box_grid():
grid = np.zeros((30, 30, 30))
grid[13:18, 5:25, 13:18] = 1
elements, vertices, vert_manager = grid_to_tets(grid, 0.1)
mesh = examples.download_cow()
distances = mesh_select(vertices, mesh)
print("distances: ", distances)
print(elements, vertices)
constraints = [[0, [1, 1, 1]], [1, [1, 1, 1]], [2, [1, 1, 1]],
[3, [1, 1, 1]]]
loads = [[32, -10000., 0.0, 0]]
# [20, 1000., 0.0, 0],
#[34, 1000., 0.0, 0],
# [31, 10000., 0.0, 0]]
poisson = 0.3
youngs = 2000
displacements = solve_full(elements, vertices, poisson, youngs,
constraints, loads)
magnitudes = get_displacement_magnitudes(displacements)
print("magnitudes", magnitudes)
plotter = pv.Plotter()
#add_tets_to_display(vertices, elements, plotter, magnitudes)
surface = generate_unstructured_grid(elements, vertices)
voxels = pv.voxelize(surface, density=surface.length / 200)
plotter.add_mesh(voxels)
plotter.show()
def cow(self, fbo):
from pyvista import examples
# download mesh
mesh = examples.download_cow()
decimated = mesh.decimate_boundary(target_reduction=0.75)
fbo.set_subplots((1, 2))
fbo.subplot(0, 0)
fbo.add_text("Original mesh", font_size=24, color='black')
fbo.add_mesh(mesh, show_edges=True, color='brown')
fbo.subplot(0, 1)
fbo.add_text("Decimated version", font_size=24, color='black')
fbo.add_mesh(decimated, show_edges=True, color=True)
fbo.link_views() # link all the views
# Set a camera position to all linked views
fbo.camera_position = [(15, 5, 0), (0, 0, 0), (0, 1, 0)]
fbo.set_background('red')
fbo.update()
style = MouseInteractorHighLightActor(ren_win=fbo.ren_win,
ren=fbo.renderers)
# style.SetDefaultRenderer(fbo.renderer)
fbo._style_class = style
fbo.update_style()
fbo.open_gif("linked.gif")
# Update camera and write a frame for each updated position
nframe = 15
for i in range(nframe):
fbo.camera_position = [
(15 * np.cos(i * np.pi / 45.0), 5.0,
15 * np.sin(i * np.pi / 45.0)),
(0, 0, 0),
(0, 1, 0),
]
# fbo.update()
fbo.write_frame()
def test_download_cow():
data = examples.download_cow()
assert data.n_points
~~~~~~~~~~~~
Positional lights in PyVista have customizable beam shapes, see the
:ref:`ref_light_beam_shape_example` example. Spotlights are special in
the sense that they are unidirectional lights with a finite position,
so they can be visualized using a cone.
This is exactly the purpose of a ``vtk.vtkLightActor``, the
functionality of which can be enabled for spotlights:
"""
# sphinx_gallery_thumbnail_number = 1
import numpy as np
import pyvista as pv
from pyvista import examples
cow = examples.download_cow()
cow.rotate_x(90)
plotter = pv.Plotter(lighting='none', window_size=(1000, 1000))
plotter.add_mesh(cow, color='white')
floor = pv.Plane(center=(*cow.center[:2], cow.bounds[-2]),
i_size=30, j_size=25)
plotter.add_mesh(floor, color='green')
UFO = pv.Light(position=(0, 0, 10), focal_point=(0, 0, 0), color='white')
UFO.positional = True
UFO.cone_angle = 40
UFO.exponent = 10
UFO.intensity = 3
UFO.show_actor()
plotter.add_light(UFO)
""" Cow ~~~ Tetrahedralize a cow mesh """ # sphinx_gallery_thumbnail_number = 3 import numpy as np import pyvista as pv from pyvista import examples import tetgen import pymeshfix ############################################################################### cow_mesh = examples.download_cow().triangulate() cpos = [(13., 7.6, -13.85), (0.44, -0.4, -0.37), (-0.28, 0.9, 0.3)] cpos=[(15.87144235049248, 4.879216382405231, -12.14248864876951), (1.1623113035352375, -0.7609060338348953, 0.3192320579894903), (-0.19477922834083672, 0.9593375398915212, 0.20428542963665386)] cow_mesh.plot(cpos=cpos) ############################################################################### tet = tetgen.TetGen(cow_mesh) tet.make_manifold()
# Extract the edges above a 12 degree feature angle edges = mesh.extract_feature_edges(12) # Render the edge lines on top of the original mesh p = pv.Plotter() p.add_mesh(mesh, color=True) p.add_mesh(edges, color="red", line_width=5) # Define a camera position that will zoom to her eye p.camera_position = [(96.0, -197.0, 45.0), (7.0, -109.0, 22.0), (0, 0, 1)] p.show() ############################################################################### # We can do this analysis for any :class:`pyvista.PolyData` object. Let's try # the cow mesh example: mesh = examples.download_cow() edges = mesh.extract_feature_edges(20) p = pv.Plotter() p.add_mesh(mesh, color=True) p.add_mesh(edges, color="red", line_width=5) p.camera_position = [(9.5, 3.0, 5.5), (2.5, 1, 0), (0, 1, 0)] p.show() ############################################################################### # We can leverage the :any:`pyvista.PolyData.n_open_edges` property and # :func:`pyvista.PolyDataFilters.extract_feature_edges` filter to count and extract the # open edges on a :class:`pyvista.PolyData` mesh. # Download a sample surface mesh with visible open edges
"""
.. _mesh_quality_example:
Computing Mesh Quality
~~~~~~~~~~~~~~~~~~~~~~
Leverage powerful VTK algorithms for computing mesh quality.
Here we will use the :func:`pyvista.DataSetFilters.compute_cell_quality` filter
to compute the cell qualities. For a full list of the various quality metrics
available, please refer to the documentation for that filter.
"""
import pyvista as pv
from pyvista import examples
import numpy as np
mesh = examples.download_cow().triangulate().decimate(0.7)
cpos = [(10.10963531890468, 4.61130688407898, -4.503884867626516),
(1.2896420468715433, -0.055387528972708225, 1.1228250502811408),
(-0.2970769821136617, 0.9100381451936025, 0.2890948650371137)]
###############################################################################
# Compute the cell quality. Note that there are many different quality measures
qual = mesh.compute_cell_quality(quality_measure='scaled_jacobian')
qual
###############################################################################
qual.plot(cpos=cpos, scalars='CellQuality')
def __init__(self):
self._example_data = examples.download_cow()
_ExampleLoader.__init__(self)
""" Cow ~~~ Tetrahedralize a cow mesh """ # sphinx_gallery_thumbnail_number = 3 import numpy as np import pyvista as pv from pyvista import examples import tetgen import pymeshfix ############################################################################### cow_mesh = examples.download_cow().tri_filter() cpos = [(13., 7.6, -13.85), (0.44, -0.4, -0.37), (-0.28, 0.9, 0.3)] cpos=[(15.87144235049248, 4.879216382405231, -12.14248864876951), (1.1623113035352375, -0.7609060338348953, 0.3192320579894903), (-0.19477922834083672, 0.9593375398915212, 0.20428542963665386)] cow_mesh.plot(cpos=cpos) ############################################################################### tet = tetgen.TetGen(cow_mesh) tet.make_manifold()
