12.2. VTK Output for 3D (and 2D) Visualization

Besides the convenient visualizations of the Netgen GUI and the NGSolve webgui, we can also use the VTK output for 3D visualization.

This is particularly useful for polished visualizations of 3D simulations where you want to apply several filters to the visualization, e.g. to show the solution on a slice of the domain, or to show the solution as a surface plot and possibly combine these things.

12.2.1. Setup dependencies

In this unit we will use pyvista to visualize the VTK output and we will need vtk as well. You can install these packages via pip in your terminal (or a virtual env.):

pip3 install pyvista vtk ipywidgets trame trame-vtk trame-vuetify --break-system-packages --upgrade

or execute the following cell:

!PIP_BREAK_SYSTEM_PACKAGES=1 pip3 install pyvista vtk ipywidgets trame trame-vtk trame-vuetify --upgrade

WARNING: Ignoring invalid distribution ~etgen-mesher (/home/jschoebe/ngs24/lib/python3.11/site-packages)

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WARNING: Ignoring invalid distribution ~etgen-mesher (/home/jschoebe/ngs24/lib/python3.11/site-packages)

12.2.2. Functionality on dummy data

If you want to, you can skip to the next section for the visualization of a flow field.

12.2.2.1. Generating the VTK output

from ngsolve import *
from netgen.occ import unit_cube

#VTKOutput?

mesh = Mesh (unit_cube.GenerateMesh(maxh=0.4))
gfu = GridFunction (L2(mesh=mesh, order=3))
gfu.Set(sin(4*pi*x*y*z))
gfv = GridFunction (L2(mesh=mesh, order=3))
gfv.Set(cos(x**2+y**2-z**2))

#define VTK output for visualization:
vtk = VTKOutput(mesh,coefs=[gfu,gfv],names=["gfu","gfv"],filename="vtkout",subdivision=3, floatsize="single",legacy=False)
#execute the VTK output:
vtk.Do()

'vtkout'

12.2.2.2. Reading the VTK data to pyvista

import pyvista
pyvista.set_jupyter_backend('html')
visobj = pyvista.read('vtkout.vtu')

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[5], line 3
      1 import pyvista
      2 pyvista.set_jupyter_backend('html')
----> 3 visobj = pyvista.read('vtkout.vtu')

File ~/ngs24/lib/python3.11/site-packages/pyvista/core/utilities/fileio.py:201, in read(filename, force_ext, file_format, progress_bar)
    199 if progress_bar:
    200     reader.show_progress()
--> 201 mesh = reader.read()
    202 if observer.has_event_occurred():
    203     warnings.warn(
    204         f"The VTK reader `{reader.reader.GetClassName()}` in pyvista reader `{reader}` raised an error"
    205         "while reading the file.\n"
    206         f'\t"{observer.get_message()}"'
    207     )

File ~/ngs24/lib/python3.11/site-packages/pyvista/core/utilities/reader.py:387, in BaseReader.read(self)
    384 data._post_file_load_processing()
    386 # check for any pyvista metadata
--> 387 data._restore_metadata()
    388 return data

File ~/ngs24/lib/python3.11/site-packages/pyvista/core/dataobject.py:192, in DataObject._restore_metadata(self)
    190 for assoc_type in ('POINT', 'CELL'):
    191     key = f'_PYVISTA_{assoc_name}_{assoc_type}_'.upper()
--> 192     if key in fdata:
    193         assoc_data = getattr(self, f'_association_{assoc_name}_names')
    194         assoc_data[assoc_type] = set(fdata[key])

TypeError: argument of type 'vtkmodules.vtkCommonDataModel.vtkFieldData' is not iterable

12.2.2.3. Simple plotting

Option 1: Call plot: (will give no result for jupyter book)

visobj.plot(scalars="gfu")

Option 1b: Call plot with several options: (will give no result for jupyter book)

visobj.plot(scalars="gfu", show_scalar_bar=True, show_edges=False, 
            edge_color='black', cmap='jet', lighting=True, 
            n_colors=16, clim=[-1,1], 
            scalar_bar_args={'title':'u', 'height':1.5, 'width':0.5, 
                             'position_x':0.1, 'position_y':0.1})

Option 2: Use a visualization object (pyvista.Plotter) and add the data (possibly step by step) to it:

plot = pyvista.Plotter()
plot.add_mesh(visobj, scalars="gfu", cmap="terrain")
plot.show()
plot.export_html("plot1.html")

For jupyter book take a look here

12.2.2.4. Some filters

Slices: (will give no result for jupyter book)

orthoslices = visobj.slice_orthogonal()
orthoslices.plot(scalars="gfu")

Iso-surfaces: (will give no result for jupyter book)

contour = visobj.contour([0.25], scalars="gfu", rng=[-1,1])
print(contour)
contour.plot(color="lightblue", smooth_shading=False)

Combining stuff: (will give no result for jupyter book)

import numpy as np
def translation_matrix(x, y, z):
    return np.array([
        [1, 0, 0, x],
        [0, 1, 0, 0],
        [0, 0, 1, 0],
        [0, 0, 0, 1]])
box_moved_left = visobj.copy().transform(translation_matrix(-1,0,0))
orthoslices_moved_right = orthoslices.combine().transform(translation_matrix(1,0,0))

plot = pyvista.Plotter(shape=(1,2))
plot.subplot(0,0)
plot.add_text("subplot1", font_size=24)
plot.add_mesh(box_moved_left, scalars="gfu", cmap="jet")
plot.add_mesh(contour, color="lightblue", opacity=0.7)
plot.add_mesh(orthoslices_moved_right, scalars="gfu", cmap="jet")
plot.subplot(0,1)
plot.add_text("subplot2", font_size=24)
plot.add_mesh(visobj, scalars="gfv")

plot.show()
plot.export_html("plot2.html")

For jupyter book take a look here

12.2.3. Visualizing for the flow problem

We assume that you ran the navierstokes_hdg_chorin.ipynb example successfully (in parallel) and have the VTK output files available.

import pyvista
pyvista.set_jupyter_backend('html')
visobj = pyvista.read('parstokes.pvd')

visobj = visobj.combine()

(next cell generates no output in jupyter book)

orthoslices = visobj.slice_orthogonal().combine()
orthoslices.plot(scalars="velocity",cmap="jet",clim=[0,2.25])
orthoslices.plot(scalars="pressure",cmap="coolwarm",clim=[-0.06,0])

plot = pyvista.Plotter()
arrows = orthoslices.glyph(scale="velocity", orient="velocity", tolerance=0.03)

seed = pyvista.Box(bounds=(-2,1,-1,1,-1,1), level=5)

strl = visobj.streamlines_from_source(
    seed,
    vectors="velocity",
    max_step_length=1,
    min_step_length=0.1,
    max_time=500,
    max_steps=5000,
    max_error=1e-6,
    integration_direction="forward",
)

plot.add_mesh(orthoslices, scalars="velocity", cmap="jet")
#plot.add_mesh(arrows, color="black")
plot.add_mesh(strl, color="black")
#plot.add_mesh(pyvista.Cylinder(center=(0.5,0.2,0.2), direction=(0,0,1), height=0.41, radius=0.05), color="white")
plot.show()
plot.export_html("plot5.html")

When considered in html export (jupyter book), take a look here