Note

Click here to download the full example code

# Table of Glyphs¶

`vtk`

supports tables of glyphs from which glyphs are looked
up. This example demonstrates this functionality.

```
import pyvista as pv
import numpy as np
```

We can allow tables of glyphs in a backward-compatible way by
allowing a sequence of geometries as well as single (scalar)
geometries to be passed as the `geom`

kwarg of `pyvista.DataSetFilters.glyph()`

.
An `indices`

optional keyword specifies the index of each glyph geometry in
the table, and it has to be the same length as `geom`

if specified. If it is
absent a default value of `range(len(geom))`

is assumed.

```
# get dataset for the glyphs: supertoroids in xy plane
# use N random kinds of toroids over a mesh with 27 points
N = 5
values = np.arange(N) # values for scalars to look up glyphs by
# taken from:
# rng = np.random.default_rng()
# params = rng.uniform(0.5, 2, size=(N, 2)) # (n1, n2) parameters for the toroids
params = np.array([[1.56821334, 0.99649769],
[1.08247844, 1.83758874],
[1.49598881, 0.83495047],
[1.52442129, 0.89600688],
[1.92212387, 0.78096621]])
geoms = [pv.ParametricSuperToroid(n1=n1, n2=n2) for n1, n2 in params]
# get dataset where to put glyphs
x,y,z = np.mgrid[:3, :3, :3]
mesh = pv.StructuredGrid(x, y, z)
# add random scalars
# rng_int = rng.integers(0, N, size=x.size)
rng_int = np.array([4, 1, 2, 0, 4, 0, 1, 4, 3, 1, 1, 3, 3, 4, 3, 4, 4,
3, 3, 2, 2, 1, 1, 1, 2, 0, 3])
mesh.point_arrays['scalars'] = rng_int
# construct the glyphs on top of the mesh; don't scale by scalars now
glyphs = mesh.glyph(geom=geoms, indices=values, scale=False, factor=0.3, rng=(0, N-1))
# create plotter and add our glyphs with some nontrivial lighting
plotter = pv.Plotter()
plotter.add_mesh(glyphs, specular=1, specular_power=15,
smooth_shading=True, show_scalar_bar=False)
plotter.show()
```

Out:

```
[(6.244271937741485, 6.244394544495788, 6.244271446003165),
(1.0000000298023224, 1.0001226365566254, 0.999999538064003),
(0.0, 0.0, 1.0)]
```

**Total running time of the script:** ( 0 minutes 1.668 seconds)