Creating a Uniform Grid

Create a simple uniform grid from a 3D NumPy array of values.

import numpy as np
import pyvista as pv

Take a 3D NumPy array of data values that holds some spatial data where each axis corresponds to the XYZ cartesian axes. This example will create a pyvista.ImageData that will hold the spatial reference for a 3D grid by which a 3D NumPy array of values can be plotted against.

Create the 3D NumPy array of spatially referenced data. This is spatially referenced such that the grid is (20, 5, 10), (nx, ny, nz).

values = np.linspace(0, 10, 1000).reshape((20, 5, 10))
values.shape

Create the ImageData

grid = pv.ImageData()

Set the grid dimensions to shape + 1 because we want to inject our values on the CELL data.

grid.dimensions = np.array(values.shape) + 1

Edit the spatial reference.

grid.origin = (100, 33, 55.6)  # The bottom left corner of the data set
grid.spacing = (1, 5, 2)  # These are the cell sizes along each axis

Assign the data to the cell data. Be sure to flatten the data for ImageData objects using Fortran ordering.

grid.cell_data["values"] = values.flatten(order="F")
grid

Now plot the grid!

grid.plot(show_edges=True)

Don’t like cell data? You could also add the NumPy array to the point data of a pyvista.ImageData. Take note of the subtle difference when setting the grid dimensions upon initialization.

# Create the 3D NumPy array of spatially referenced data again.
values = np.linspace(0, 10, 1000).reshape((20, 5, 10))
values.shape

Create the PyVista object and set the same attributes as earlier.

grid = pv.ImageData()

# Set the grid dimensions to ``shape`` because we want to inject our values on
# the POINT data
grid.dimensions = values.shape

# Edit the spatial reference
grid.origin = (100, 33, 55.6)  # The bottom left corner of the data set
grid.spacing = (1, 5, 2)  # These are the cell sizes along each axis

Add the data values to the cell data

grid.point_data["values"] = values.flatten(order="F")  # Flatten the array!
grid

Now plot the grid!

grid.plot(show_edges=True)

Exercise

Now create your own pyvista.ImageData from a 3D NumPy array!

help(pv.ImageData)

Generate example 3D data using numpy.random.random(). Feel free to use your own 3D numpy array here.

arr = np.random.random((100, 100, 100))
arr.shape

Create the pyvista.ImageData.

Note

You will likely need to ravel the array with Fortran-ordering: arr.ravel(order="F")

vol = pv.ImageData()
# Set attributes and data
...

Plot the ImageData

vol.plot()

Example

PyVista has several examples that use ImageData.

See the PyVista documentation for further details on Volume Rendering

Here’s one of these example datasets:

from pyvista import examples

vol = examples.download_knee_full()

p = pv.Plotter()
p.add_volume(vol, cmap="bone", opacity="sigmoid")
p.show()

vol = pv.Wavelet()
vol.plot(volume=True)