matplotlib:colorbars及其文本标签

时间:2013-04-09 17:20:07

标签: python matplotlib label legend colorbar

我想为colorbar创建一个heatmap图例,以便标签位于每个离散颜色的中心。 Example borrowed from here

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import ListedColormap

#discrete color scheme
cMap = ListedColormap(['white', 'green', 'blue','red'])

#data
np.random.seed(42)
data = np.random.rand(4, 4)
fig, ax = plt.subplots()
heatmap = ax.pcolor(data, cmap=cMap)

#legend
cbar = plt.colorbar(heatmap)
cbar.ax.set_yticklabels(['0','1','2','>3'])
cbar.set_label('# of contacts', rotation=270)

# put the major ticks at the middle of each cell
ax.set_xticks(np.arange(data.shape[1]) + 0.5, minor=False)
ax.set_yticks(np.arange(data.shape[0]) + 0.5, minor=False)
ax.invert_yaxis()

#labels
column_labels = list('ABCD')
row_labels = list('WXYZ')
ax.set_xticklabels(column_labels, minor=False)
ax.set_yticklabels(row_labels, minor=False)

plt.show()

这会生成以下图表:

pmesh plot

理想情况下,我想生成一个带有四种颜色的图例条,每种颜色的标签位于其中心:0,1,2,>3。如何实现这一目标?

3 个答案:

答案 0 :(得分:77)

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import ListedColormap

#discrete color scheme
cMap = ListedColormap(['white', 'green', 'blue','red'])

#data
np.random.seed(42)
data = np.random.rand(4, 4)
fig, ax = plt.subplots()
heatmap = ax.pcolor(data, cmap=cMap)

#legend
cbar = plt.colorbar(heatmap)

cbar.ax.get_yaxis().set_ticks([])
for j, lab in enumerate(['$0$','$1$','$2$','$>3$']):
    cbar.ax.text(.5, (2 * j + 1) / 8.0, lab, ha='center', va='center')
cbar.ax.get_yaxis().labelpad = 15
cbar.ax.set_ylabel('# of contacts', rotation=270)


# put the major ticks at the middle of each cell
ax.set_xticks(np.arange(data.shape[1]) + 0.5, minor=False)
ax.set_yticks(np.arange(data.shape[0]) + 0.5, minor=False)
ax.invert_yaxis()

#labels
column_labels = list('ABCD')
row_labels = list('WXYZ')
ax.set_xticklabels(column_labels, minor=False)
ax.set_yticklabels(row_labels, minor=False)

plt.show()

你非常接近。一旦你有了颜色条轴的参考,你可以做任何你想做的事情,包括在中间放置文本标签。您可能希望使用格式化以使其更加可见。

demo

答案 1 :(得分:1)

这将使您添加标签并更改颜色条的刻度和标签大小:

clb=plt.colorbar()
clb.ax.tick_params(labelsize=8) 
clb.ax.set_title('Your Label',fontsize=8)

如果您有子批次,也可以使用此方法:

plt.tight_layout()
plt.subplots_adjust(bottom=0.05)
cax = plt.axes([0.1, 0, 0.8, 0.01]) #Left,bottom, length, width
clb=plt.colorbar(cax=cax,orientation="horizontal")
clb.ax.tick_params(labelsize=8) 
clb.ax.set_title('Your Label',fontsize=8)

答案 2 :(得分:0)

要添加到tacaswell's answercolorbar()函数具有可选的cax输入,您可以使用该输入来传递应在其上绘制颜色条的轴。如果使用该输入,则可以使用该轴直接设置标签。

import matplotlib.pyplot as plt
from mpl_toolkits.axes.grid1 import make_axes_locatable

fig, ax = plt.subplots()
heatmap = ax.imshow(data)
divider = make_axes_locatable(ax)
cax = divider.append_axes('bottom', size='10%', pad=0.6)
cb = fig.colorbar(heatmap, cax=cax, orientation='horizontal')

cax.set_xlabel('data label')  # cax == cb.ax