Color scatter plots

This example shows different ways to color vectors and (mis)orientations in scatter plots.

import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np

from orix.plot import register_projections
from orix.quaternion import Orientation
from orix.quaternion.symmetry import Oh
from orix.vector import Vector3d

register_projections()  # Register our custom Matplotlib projections
np.random.seed(2319)  # Create reproducible random data

Create some random vectors and plot them in the stereographic projection, coloring by:

• Scalar values mapped to a Matplotlib color map

• Pre-computed RGBA colormapping from a Matplotlib color map

• RGB values

• A single color

v = Vector3d.random(50)

c_scalar = np.linspace(0, 1, v.size)
c_rgba = mpl.colormaps["viridis"](c_scalar)
c_rgb = np.random.random(v.size * 3).reshape(v.size, 3)
c_color = "xkcd:salmon"

n = 4
fig = plt.figure(figsize=(n * 3, n), layout="constrained")

ax0 = fig.add_subplot(1, n, 1, projection="stereographic")
ax0.scatter(v, c=c_scalar, cmap="inferno")
ax0.set_title("Scalars mapped to colormap")

ax1 = fig.add_subplot(1, n, 2, projection="stereographic")
ax1.scatter(v, c=c_rgba)
ax1.set_title("Pre-computed RGBA colormap")

ax2 = fig.add_subplot(1, n, 3, projection="stereographic")
ax2.scatter(v, c=c_rgb)
ax2.set_title("Pre-computed RGB values")

ax3 = fig.add_subplot(1, n, 4, projection="stereographic")
ax3.scatter(v, c=c_color)
_ = ax3.set_title("A single color")

This also works nicely when coloring (mis)orientations

ori = Orientation.random(50)
ori.symmetry = Oh

n = 4
fig = plt.figure(figsize=(n * 3, n), layout="tight")
scatter_kwargs = {"projection": "axangle", "figure": fig}

ori.scatter(c=c_scalar, cmap="inferno", position=(1, n, 1), **scatter_kwargs)
fig.axes[0].set_title("Scalars mapped to colormap")

ori.scatter(c=c_rgba, position=(1, n, 2), **scatter_kwargs)
fig.axes[1].set_title("Pre-computed RGBA colormap")

ori.scatter(c=c_rgb, position=(1, n, 3), **scatter_kwargs)
fig.axes[2].set_title("Pre-computed RGB values")

ori.scatter(c=c_color, position=(1, n, 4), **scatter_kwargs)
_ = fig.axes[3].set_title("A single color")

plt.show()

Estimated memory usage: 583 MB