向matplotlib颜色图例添加垂直标签 [英] Add a vertical label to matplotlib colormap legend

问题描述

此代码使我能够绘制"3d"数组[X，Y，Z]的颜色图(它们是3个简单的元素np.array).但是我无法在颜色栏图例的右侧添加垂直的书面标签.

import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure("Color MAP 2D+")

contour = plt.tricontourf(X, Y, Z, 100, cmap="bwr")

plt.xlabel("X")
plt.ylabel("Y")
plt.title("Color MAP 2D+")

#Legend
def fmt(x, pos):
    a, b = '{:.2e}'.format(x).split('e')
    b = int(b)
    return r'${} \times 10^{{{}}}$'.format(a, b)
import matplotlib.ticker as ticker
plt.colorbar(contour, format=ticker.FuncFormatter(fmt))

plt.show()

不能从Google那里得到一个简单的答案很烦人...有人可以帮助我吗?

解决方案

您要向colorbar对象添加label.幸运的是，colorbar具有 set_label 函数. /p>

简而言之:

cbar = plt.colorbar(contour, format=ticker.FuncFormatter(fmt))
cbar.set_label('your label here')

在最小的脚本中:

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

X = np.random.uniform(-2, 2, 200)
Y = np.random.uniform(-2, 2, 200)
Z = X*np.exp(-X**2 - Y**2)

contour = plt.tricontourf(X, Y, Z, 100, cmap="bwr")

def fmt(x, pos):
    a, b = '{:.2e}'.format(x).split('e')
    b = int(b)
    return r'${} \times 10^{{{}}}$'.format(a, b)

cbar = plt.colorbar(contour, format=ticker.FuncFormatter(fmt))
cbar.set_label('your label here')

plt.show()

This code enables me to plot a colormap of a "3d" array [X,Y,Z] (they are 3 simple np.array of elements). But I can't succeed in adding a vertical written label at the right of the colorbar legend.

import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure("Color MAP 2D+")

contour = plt.tricontourf(X, Y, Z, 100, cmap="bwr")

plt.xlabel("X")
plt.ylabel("Y")
plt.title("Color MAP 2D+")

#Legend
def fmt(x, pos):
    a, b = '{:.2e}'.format(x).split('e')
    b = int(b)
    return r'${} \times 10^{{{}}}$'.format(a, b)
import matplotlib.ticker as ticker
plt.colorbar(contour, format=ticker.FuncFormatter(fmt))

plt.show()

It's anoying to not get an easy answer from google... can someone help me ?

解决方案

You are looking to add a label to the colorbar object. Thankfully, colorbar has a set_label function.

in short:

cbar = plt.colorbar(contour, format=ticker.FuncFormatter(fmt))
cbar.set_label('your label here')

In a minimal script:

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

X = np.random.uniform(-2, 2, 200)
Y = np.random.uniform(-2, 2, 200)
Z = X*np.exp(-X**2 - Y**2)

contour = plt.tricontourf(X, Y, Z, 100, cmap="bwr")

def fmt(x, pos):
    a, b = '{:.2e}'.format(x).split('e')
    b = int(b)
    return r'${} \times 10^{{{}}}$'.format(a, b)

cbar = plt.colorbar(contour, format=ticker.FuncFormatter(fmt))
cbar.set_label('your label here')

plt.show()

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