3D Box Surface Plot

Introduction

This lab will guide you through creating a 3D box surface plot using Python and Matplotlib. We will define dimensions, create fake data, and plot contour surfaces. We will set limits of the plot, plot edges, set labels and zticks, set zoom and angle view, and add a colorbar.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

Skills Graph

Define Dimensions

Define the dimensions of the box by creating three variables for the length of each side: Nx, Ny, and Nz. Then create three meshgrids for X, Y, and Z using numpy's arange method. Finally, set the negative value for Z to create a box instead of a plane.

import matplotlib.pyplot as plt
import numpy as np

## Define dimensions
Nx, Ny, Nz = 100, 300, 500
X, Y, Z = np.meshgrid(np.arange(Nx), np.arange(Ny), -np.arange(Nz))

Create Fake Data

Create fake data to plot by using a formula to calculate data based on the values of X, Y, and Z. We will add one to the result to ensure that the minimum value is greater than zero.

## Create fake data
data = (((X+100)**2 + (Y-20)**2 + 2*Z)/1000+1)

Plot Contour Surfaces

Plot contour surfaces for the box using the contourf method for each surface. Use appropriate parameters for zdir and offset.

kw = {
    'vmin': data.min(),
    'vmax': data.max(),
    'levels': np.linspace(data.min(), data.max(), 10),
}

## Create a figure with 3D ax
fig = plt.figure(figsize=(5, 4))
ax = fig.add_subplot(111, projection='3d')

## Plot contour surfaces
_ = ax.contourf(
    X[:, :, 0], Y[:, :, 0], data[:, :, 0],
    zdir='z', offset=0, **kw
)
_ = ax.contourf(
    X[0, :, :], data[0, :, :], Z[0, :, :],
    zdir='y', offset=0, **kw
)
C = ax.contourf(
    data[:, -1, :], Y[:, -1, :], Z[:, -1, :],
    zdir='x', offset=X.max(), **kw
)

Set Limits of the Plot

Set limits of the plot using the set method and passing in the limits of the X, Y, and Z coordinates.

## Set limits of the plot from coord limits
xmin, xmax = X.min(), X.max()
ymin, ymax = Y.min(), Y.max()
zmin, zmax = Z.min(), Z.max()
ax.set(xlim=[xmin, xmax], ylim=[ymin, ymax], zlim=[zmin, zmax])

Plot Edges

Plot edges using the plot method. We will plot three lines along the X and Y coordinates, and one line along the X and Z coordinates.

## Plot edges
edges_kw = dict(color='0.4', linewidth=1, zorder=1e3)
ax.plot([xmax, xmax], [ymin, ymax], 0, **edges_kw)
ax.plot([xmin, xmax], [ymin, ymin], 0, **edges_kw)
ax.plot([xmax, xmax], [ymin, ymin], [zmin, zmax], **edges_kw)

Set Labels and Zticks

Set labels and zticks using the set method. We will set the labels for X, Y, and Z coordinates, and set the zticks to show the depth of the box.

## Set labels and zticks
ax.set(
    xlabel='X [km]',
    ylabel='Y [km]',
    zlabel='Z [m]',
    zticks=[0, -150, -300, -450],
)

Set Zoom and Angle View

Set zoom and angle view using the view_init and set_box_aspect methods. We will set the angle view to 40 degrees in the X direction and -30 degrees in the Y direction, and the zoom to 0.9.

## Set zoom and angle view
ax.view_init(40, -30, 0)
ax.set_box_aspect(None, zoom=0.9)

Add a Colorbar

Add a colorbar using the colorbar method. We will set the fraction and pad parameters to adjust the location of the colorbar, and set the label to show the name and units of the data.

## Colorbar
fig.colorbar(C, ax=ax, fraction=0.02, pad=0.1, label='Name [units]')

Summary

In this lab, we created a 3D box surface plot using Python and Matplotlib. We defined dimensions, created fake data, and plotted contour surfaces. We set limits of the plot, plotted edges, set labels and zticks, set zoom and angle view, and added a colorbar. This plot can be used to visualize 3D data and explore relationships between variables.