轮廓演示#

说明简单的等高线绘图、图像上的等高线以及等高线的颜色条和标记的等高线。

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


delta = 0.025
x = np.arange(-3.0, 3.0, delta)
y = np.arange(-2.0, 2.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = np.exp(-X**2 - Y**2)
Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
Z = (Z1 - Z2) * 2

使用默认颜色创建带有标签的简单等高线图。clabel 的 inline 参数将控制标签是否绘制在轮廓的线段上，删除标签下方的线。

fig, ax = plt.subplots()
CS = ax.contour(X, Y, Z)
ax.clabel(CS, inline=True, fontsize=10)
ax.set_title('Simplest default with labels')

Text(0.5, 1.0, 'Simplest default with labels')

通过提供位置列表（在数据坐标中），可以手动放置轮廓标签。有关交互式放置，请参阅交互式功能。

fig, ax = plt.subplots()
CS = ax.contour(X, Y, Z)
manual_locations = [
    (-1, -1.4), (-0.62, -0.7), (-2, 0.5), (1.7, 1.2), (2.0, 1.4), (2.4, 1.7)]
ax.clabel(CS, inline=True, fontsize=10, manual=manual_locations)
ax.set_title('labels at selected locations')

Text(0.5, 1.0, 'labels at selected locations')

您可以强制所有轮廓为相同颜色。

fig, ax = plt.subplots()
CS = ax.contour(X, Y, Z, 6, colors='k')  # Negative contours default to dashed.
ax.clabel(CS, fontsize=9, inline=True)
ax.set_title('Single color - negative contours dashed')

Text(0.5, 1.0, 'Single color - negative contours dashed')

您可以将负轮廓设置为实心而不是虚线：

plt.rcParams['contour.negative_linestyle'] = 'solid'
fig, ax = plt.subplots()
CS = ax.contour(X, Y, Z, 6, colors='k')  # Negative contours default to dashed.
ax.clabel(CS, fontsize=9, inline=True)
ax.set_title('Single color - negative contours solid')

Text(0.5, 1.0, 'Single color - negative contours solid')

您可以手动指定轮廓的颜色

fig, ax = plt.subplots()
CS = ax.contour(X, Y, Z, 6,
                linewidths=np.arange(.5, 4, .5),
                colors=('r', 'green', 'blue', (1, 1, 0), '#afeeee', '0.5'),
                )
ax.clabel(CS, fontsize=9, inline=True)
ax.set_title('Crazy lines')

Text(0.5, 1.0, 'Crazy lines')

或者您可以使用颜色图来指定颜色；默认颜色图将用于等高线

fig, ax = plt.subplots()
im = ax.imshow(Z, interpolation='bilinear', origin='lower',
               cmap=cm.gray, extent=(-3, 3, -2, 2))
levels = np.arange(-1.2, 1.6, 0.2)
CS = ax.contour(Z, levels, origin='lower', cmap='flag', extend='both',
                linewidths=2, extent=(-3, 3, -2, 2))

# Thicken the zero contour.
CS.collections[6].set_linewidth(4)

ax.clabel(CS, levels[1::2],  # label every second level
          inline=True, fmt='%1.1f', fontsize=14)

# make a colorbar for the contour lines
CB = fig.colorbar(CS, shrink=0.8)

ax.set_title('Lines with colorbar')

# We can still add a colorbar for the image, too.
CBI = fig.colorbar(im, orientation='horizontal', shrink=0.8)

# This makes the original colorbar look a bit out of place,
# so let's improve its position.

l, b, w, h = ax.get_position().bounds
ll, bb, ww, hh = CB.ax.get_position().bounds
CB.ax.set_position([ll, b + 0.1*h, ww, h*0.8])

plt.show()

参考

此示例中显示了以下函数、方法、类和模块的使用：

脚本总运行时间：（0分2.685秒）

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