Matplotlib Triangular Mesh and Polar Coordinate Functions

Matplotlib 参考文档Matplotlib Reference Documentation

Triangular mesh functions are used to plot and visualize data on unstructured grids, while polar coordinate functions plot in the polar coordinate system.

Function Overview

FunctionDescription
triplot()Draw a wireframe of an unstructured triangular mesh
tripcolor()Draw a pseudocolor plot on a triangular mesh
tricontour()Draw contour lines on a triangular mesh
tricontourf()Draw filled contour lines on a triangular mesh
polar()Plot in the polar coordinate system (equivalent to subplot_kw projection='polar')

Triangular Mesh Functions

triplot() - Mesh Wireframe

matplotlib.pyplot.triplot(*args, **kwargs)
Axes.triplot(triangulation, **kwargs)
# triangulation: Triangulation 对象（由 x, y 坐标创建）

tripcolor() - Triangular Pseudocolor

matplotlib.pyplot.tripcolor(*args, **kwargs)
Axes.tripcolor(triangulation, C=None, **kwargs)

tricontour() / tricontourf() - Triangular Contour

matplotlib.pyplot.tricontour(*args, **kwargs)
matplotlib.pyplot.tricontourf(*args, **kwargs)
Axes.tricontour(triangulation, C=None, levels=None, **kwargs)
Axes.tricontourf(triangulation, C=None, levels=None, **kwargs)

Example

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

np.random.seed(42)

# Generate random scatter points
n = 200
x = np.random.rand(n) * 4 - 2
y = np.random.rand(n) * 4 - 2
# Function value at each point
z = x * np.exp(-x**2 - y**2)

# Create Delaunay triangulation
triang = tri.Triangulation(x, y)

fig, axes = plt.subplots(2, 2, figsize=(10, 8),
                          layout='constrained')

# Triangular mesh wireframe
axes[0, 0].triplot(triang, 'k-', linewidth=0.5, alpha=0.5)
axes[0, 0].scatter(x, y, c=z, s=8, cmap='viridis')
axes[0, 0].set_title('triplot() - Mesh + Scatter')

# Triangular pseudocolor
tc1 = axes[0, 1].tripcolor(triang, z, cmap='viridis',
                            shading='gouraud')  # Smooth shading
fig.colorbar(tc1, ax=axes[0, 1], label='z value')
axes[0, 1].set_title('tripcolor()')

# Triangular contour
tc2 = axes[1, 0].tricontourf(triang, z, levels=12,
                              cmap='RdYlBu')
axes[1, 0].tricontour(triang, z, levels=12,
                       colors='black', linewidths=0.3)
fig.colorbar(tc2, ax=axes[1, 0], label='z value')
axes[1, 0].set_title('tricontourf()')

# Contour lines only
axes[1, 1].tricontour(triang, z, levels=15,
                       cmap='viridis', linewidths=1.5)
axes[1, 1].set_title('tricontour()')

plt.show()

polar() - Polar Plot

matplotlib.pyplot.polar(*args, **kwargs)
# 等同于:
# plt.subplot(projection='polar')
# ax.plot(theta, r)
ParameterDescription
thetaAngle array (radians)
rRadial distance array

Example

import matplotlib.pyplot as plt
import numpy as np

theta = np.linspace(0, 2*np.pi, 100)

fig, axes = plt.subplots(2, 2, figsize=(10, 10),
    subplot_kw={'projection': 'polar'},
    layout='constrained')

# Rose curve r = sin(3θ)
r1 = np.abs(np.sin(3 * theta))
axes[0, 0].plot(theta, r1, 'blue', linewidth=2)
axes[0, 0].set_title('Rose Curve: r=|sin(3θ)|')

# Archimedean spiral r = θ
r2 = theta
axes[0, 1].plot(theta, r2, 'red', linewidth=2)
axes[0, 1].set_title('Archimedean Spiral: r=θ')

# Cardioid r = 1 + cos(θ)
r3 = 1 + np.cos(theta)
axes[1, 0].fill(theta, r3, alpha=0.5, color='coral')
axes[1, 0].plot(theta, r3, 'red', linewidth=2)
axes[1, 0].set_title('Cardioid: r=1+cos(θ)')

# Multiple petals
r4 = np.sin(4 * theta)
axes[1, 1].fill(theta, np.abs(r4), alpha=0.5, color='purple')
axes[1, 1].plot(theta, np.abs(r4), 'purple', linewidth=2)
axes[1, 1].set_rticks([0.5, 1.0])
axes[1, 1].set_title('4-petal Rose: r=|sin(4θ)|')

plt.show()

rgrids() / thetagrids() - Polar Grid

matplotlib.pyplot.rgrids(radii=None, labels=None, angle=None,
    fmt=None, **kwargs)
matplotlib.pyplot.thetagrids(angles=None, labels=None, fmt=None,
    **kwargs)

Example

import matplotlib.pyplot as plt
import numpy as np

fig, ax = plt.subplots(subplot_kw={'projection': 'polar'},
                        figsize=(6, 6), layout='constrained')

theta = np.linspace(0, 2*np.pi, 100)
ax.plot(theta, theta/3, linewidth=2)

# Custom radial grid
ax.set_rticks([1, 3, 5, 7, 9])      # Radial tick positions
ax.set_rlabel_position(-22.5)         # Radial label positions

# Custom angle grid
ax.set_thetagrids(np.arange(0, 360, 45),  # Every 45 degrees
                  labels=['0°','45°','90°','135°','180°',
                          '225°','270°','315°'])

ax.set_title('Custom Polar Grid')
plt.show()

Matplotlib 参考文档Matplotlib Reference Documentation

Other Extensions