TickedStroke patheffect

Matplotlib's patheffects can be used to alter the way paths are drawn at a low enough level that they can affect almost anything.

The patheffects guide details the use of patheffects.

The TickedStroke patheffect illustrated here draws a path with a ticked style. The spacing, length, and angle of ticks can be controlled.

See also the Lines with a ticked patheffect example.

See also the Contouring the solution space of optimizations example.

import matplotlib.pyplot as plt
import numpy as np

Applying TickedStroke to paths

import matplotlib.patches as patches
from matplotlib.path import Path
import matplotlib.patheffects as patheffects

fig, ax = plt.subplots(figsize=(6, 6))
path = Path.unit_circle()
patch = patches.PathPatch(path, facecolor='none', lw=2, path_effects=[
    patheffects.withTickedStroke(angle=-90, spacing=10, length=1)])

ax.add_patch(patch)
ax.axis('equal')
ax.set_xlim(-2, 2)
ax.set_ylim(-2, 2)

plt.show()

Applying TickedStroke to lines

fig, ax = plt.subplots(figsize=(6, 6))
ax.plot([0, 1], [0, 1], label="Line",
        path_effects=[patheffects.withTickedStroke(spacing=7, angle=135)])

nx = 101
x = np.linspace(0.0, 1.0, nx)
y = 0.3*np.sin(x*8) + 0.4
ax.plot(x, y, label="Curve", path_effects=[patheffects.withTickedStroke()])

ax.legend()

plt.show()

Applying TickedStroke to contour plots

Contour plot with objective and constraints. Curves generated by contour to represent a typical constraint in an optimization problem should be plotted with angles between zero and 180 degrees.

fig, ax = plt.subplots(figsize=(6, 6))

nx = 101
ny = 105

# Set up survey vectors
xvec = np.linspace(0.001, 4.0, nx)
yvec = np.linspace(0.001, 4.0, ny)

# Set up survey matrices.  Design disk loading and gear ratio.
x1, x2 = np.meshgrid(xvec, yvec)

# Evaluate some stuff to plot
obj = x1**2 + x2**2 - 2*x1 - 2*x2 + 2
g1 = -(3*x1 + x2 - 5.5)
g2 = -(x1 + 2*x2 - 4.5)
g3 = 0.8 + x1**-3 - x2

cntr = ax.contour(x1, x2, obj, [0.01, 0.1, 0.5, 1, 2, 4, 8, 16],
                  colors='black')
ax.clabel(cntr, fmt="%2.1f", use_clabeltext=True)

cg1 = ax.contour(x1, x2, g1, [0], colors='sandybrown')
cg1.set(path_effects=[patheffects.withTickedStroke(angle=135)])

cg2 = ax.contour(x1, x2, g2, [0], colors='orangered')
cg2.set(path_effects=[patheffects.withTickedStroke(angle=60, length=2)])

cg3 = ax.contour(x1, x2, g3, [0], colors='mediumblue')
cg3.set(path_effects=[patheffects.withTickedStroke(spacing=7)])

ax.set_xlim(0, 4)
ax.set_ylim(0, 4)

plt.show()

Direction/side of the ticks

To change which side of the line the ticks are drawn, change the sign of the angle.

fig, ax = plt.subplots(figsize=(6, 6))
line_x = line_y = [0, 1]
ax.plot(line_x, line_y, label="Line",
        path_effects=[patheffects.withTickedStroke(spacing=7, angle=135)])

ax.plot(line_x, line_y, label="Opposite side",
        path_effects=[patheffects.withTickedStroke(spacing=7, angle=-135)])

ax.legend()
plt.show()