Visualization with show()

magpylib_jax ships a lightweight matplotlib 3D renderer for inspecting source, sensor, and collection geometry. It is available both as a free function, mpj.show(...), and as a .show() method on every object.

Note

The renderer is for geometry inspection, not field visualization. Use the field API (getB/getH) together with your own plotting code for field maps.

Basic usage

Pass any number of sources, sensors, or collections to mpj.show:

import magpylib_jax as mpj

coil = mpj.current.Circle(current=1.2, diameter=0.6)
magnet = mpj.magnet.Cuboid(
    dimension=(0.4, 0.3, 0.2),
    polarization=(0.0, 0.0, 0.7),
    position=(0.0, 0.0, 0.5),
)
sensor = mpj.Sensor(pixel=[(0.0, 0.0, 0.2), (0.0, 0.1, 0.2)])

mpj.show(coil, magnet, sensor)

Every object also carries a .show() method that renders it on its own:

magnet.show()

A Collection renders all of its children in one scene:

system = mpj.Collection(coil, magnet)
system.show()

A coil, cuboid magnet, and sensor rendered together by mpj.show.

Composing with your own axes

Pass an existing 3D axes through ax= to draw into a subplot you control — useful for side-by-side layouts or for overlaying show() output with other matplotlib content:

import matplotlib.pyplot as plt

fig = plt.figure(figsize=(11, 5))
ax_left = fig.add_subplot(1, 2, 1, projection="3d")
ax_right = fig.add_subplot(1, 2, 2, projection="3d")

mpj.show(magnet, ax=ax_left)
mpj.show(coil, sensor, ax=ax_right)
fig.tight_layout()

When you supply ax, show() draws into it and does not create or display a new figure.

Returning the figure

Set return_fig=True to get the matplotlib.figure.Figure back instead of showing it. This is the right choice for headless rendering, saving to disk, or tests, and it never calls plt.show():

fig = mpj.show(coil, magnet, sensor, return_fig=True)
fig.savefig("system.png", dpi=150)

Titles and styling

A title can be set through either title= or a style mapping:

mpj.show(coil, magnet, title="Coil and magnet")
mpj.show(coil, magnet, style={"title": "Coil and magnet"})

Objects can also carry a style_label, which is used to annotate the object marker in the scene.

What each object renders

The renderer color-codes objects by physical category (magnets red, currents blue, dipoles purple, sensors teal, custom sources grey) and draws a legend for the categories present.

Magnet sources (red)

Cuboid, Cylinder, CylinderSegment, and Sphere render as their solid bodies; Tetrahedron, TriangularMesh, and Triangle render as their oriented faces.

Current sources (blue)

Circle and Polyline render as their conductor path; TriangleStrip and TriangleSheet render as their triangle faces.

Dipole sources (purple)

Dipole renders as a moment arrow through its position.

Sensors (teal)

Sensor renders as a square marker with its pixel points and local axis arrows.

Custom sources (grey)

CustomSource renders as a labeled position marker.

Multi-point motion paths are drawn as a dashed trailing line, and the body itself is drawn at the final pose on the path.

Backends

Only the matplotlib backend is provided. Requesting another backend raises a ValueError:

mpj.show(magnet, backend="matplotlib")  # the only supported value

Interactive backends such as plotly and pyvista, which upstream Magpylib offers, are not (yet) implemented here. matplotlib must be installed; it is included in the docs and test extras.

See also