在matplotlib中标准化后修剪颜色条

如何解决在matplotlib中标准化后修剪颜色条

我已将颜色条与水平箱线图的 x 轴对齐。

如下图所示，x轴上有一片空白区域。

所以我想将 x 轴与颜色条一起修剪，颜色条由 vmin 和 vmax 标准化

知道如何做到这一点吗？

非常感谢！

test_data = [np.random.normal(mean,1,10) for mean in range(400,500,10)]

### set sns style
sns.set_style('white')

### set fig,ax
fig = plt.figure(figsize=(4,2))
ax1 = fig.add_axes([0.10,0.10,1.2,2])

### Define color bar
# choose color map
cmap = plt.get_cmap('nipy_spectral')
# normalize min and max
norm = mpl.colors.Normalize(vmin=380,vmax=780)
# assign cmap and norm
sm = plt.cm.ScalarMappable(cmap=cmap,norm=norm)
sm.set_array([])

### Plot color bar (change "pad" to adjust distance of color bar to x-axis)
plt.colorbar(sm,ticks=np.linspace(380,780,11),location="bottom",pad=0)

### Plot boxplot
bplot = ax1.boxplot(test_data,vert=False,patch_artist=True)

### Set axis
ax1.set_yticklabels(["a","b","c","d","e","f","g","h","i","j"])
ax1.get_xaxis().set_visible(False)
ax1.set_xlim(380,780)   

plt.show()

解决方法

将颜色条与主 ax 完全对齐的最简单方法是使用与主 ax 相同的 x 和宽度并调整 y 和高度将其 ax 创建为 cax = fig.add_axes([...])。然后可以将颜色条创建为 plt.colorbar(sm,ticks=np.linspace(380,780,11),orientation='horizontal',cax=cax)。

由于您想缩小颜色条的一部分，使用将其与 x 轴对齐的范围通过 imshow() 绘制它可能更容易。

import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import matplotlib as mpl

test_data = [np.random.normal(mean,1,10) for mean in range(400,500,10)]

sns.set_style('white')

fig = plt.figure(figsize=(10,3))
ax1 = fig.add_axes([0.10,0.17,0.88,0.80])  # x0,y0,width,height in figure coordinates
cax = fig.add_axes([0.10,0.12,0.05],sharex=ax1)  # use same x0 and width

### Define color bar
cmap = plt.get_cmap('nipy_spectral')
norm = mpl.colors.Normalize(vmin=380,vmax=780)
xmin,xmax = 380,500
cax.imshow(np.linspace(xmin,xmax,100).reshape(1,-1),extent=[xmin,1],cmap=cmap,norm=norm,aspect='auto')
cax.set_yticks([])

bplot = ax1.boxplot(test_data,vert=False,patch_artist=True)

ax1.set_yticklabels(["a","b","c","d","e","f","g","h","i","j"])
ax1.set_xlim(xmin,xmax)
ax1.tick_params(axis='x',labelbottom=False)
cax.set_xticks(np.arange(xmin,xmax + 1,20))

plt.show()

imshow() 也可用于以类似方式为箱线图矩形着色。下面的示例使用改编的示例数据来更好地说明该概念。请注意，imshow 会重置 xlims 和 ylims，因此需要先保存它们，然后再重置。

test_data = [np.random.uniform(mean - 20,mean + 20,510
cax.imshow(np.linspace(xmin,200).reshape(1,patch_artist=True,medianprops={'color': 'white'})

ax1.set_yticklabels(["a","j"])
ax1.tick_params(axis='x',20))
ymin,ymax = ax1.get_ylim()

for art in ax1.artists:
    art.set_facecolor('none')  # make transparent
    x0,x1,y1 = art.get_path().get_extents().extents
    ax1.imshow(np.linspace(x0,extent=[x0,y1],aspect='auto',zorder=0)
ax1.set_xlim(xmin,xmax)
ax1.set_ylim(ymin,ymax)