Scientific Visualisations with Python

import numpy as np
import pyvista as pv
#
# ---------------------------------------------------------
# Load scalar field: expected columns = x y z value
# ---------------------------------------------------------
data = np.loadtxt("./scalar_field.txt")
#
x, y, z, s = data.T
#
# Create point cloud
points = np.vstack((x, y, z)).T
cloud = pv.PolyData(points)
# Add scalar array
cloud["scalar"] = s
#
# Create sphere glyphs
#
sphere = pv.Sphere(radius=0.02)   # adjust radius
#
glyphs = cloud.glyph(
    geom=sphere,
    scale=False,                  # True or False
    orient=False,
)
#
# Plot
#
plotter = pv.Plotter()
#
plotter.add_mesh(
    glyphs,
    scalars="scalar",
    cmap="viridis",
    show_scalar_bar=True,
    scalar_bar_args={"title": "Scalar Value"},
)
#
plotter.set_background("white")
plotter.add_axes()
plotter.show()

import numpy as np
import pyvista as pv
#
data = np.loadtxt("./vector_field.txt")
#
x, y, z, vx, vy, vz = data.T
#
# Compute magnitude for coloring
magnitude = np.linalg.norm(np.vstack((vx, vy, vz)), axis=0)
#
# Create PyVista point cloud
points = np.vstack((x, y, z)).T
cloud = pv.PolyData(points)
#
# Add vector & magnitude arrays
cloud["vectors"] = np.vstack((vx, vy, vz)).T
cloud["magnitude"] = magnitude
#
# Create arrow glyphs
# scale="magnitude" → scale arrows by vector magnitude
# orient="vectors" → orient arrows by direction
glyphs = cloud.glyph(
    orient="vectors",
    scale="magnitude",
    factor=0.1,       # global scaling factor for arrow size
    geom=pv.Arrow(),  # arrow shape
)
#
# Plot
plotter = pv.Plotter()
#
plotter.add_mesh(
    glyphs,
    scalars="magnitude",
    cmap="viridis",
    show_scalar_bar=True,
    scalar_bar_args={"title": "Vector Magnitude"},
)
#
plotter.set_background("white")
plotter.add_axes()
plotter.show()

# Example

# Example