将子批次与颜色B对齐

2024-09-30 03:24:21 发布

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我试着分享一个imshow的x轴,它必须是正方形和一个经典的绘图:

  1. 图像必须是方形的
  2. 用颜色条
  3. 下面的绘图应该共享同一个轴(或者至少看起来与imshow对齐)

我花了两天时间,现在我疯了。有人知道如何排列它们吗?在

square imshow on the top, with a color bar, and bellow a plot, that should share the same axis

用于生成图像的代码如下所示。在

def myplot( Nbin=20 ):

X = np.random.rand(1000)
Y = np.random.rand(1000)
h2, yh2, xh2 = np.histogram2d( Y, X, bins=[Nbin,Nbin] )
h1, xh1 = np.histogram( X, bins=Nbin )
######################################
######################################
fig = plt.figure(  )
gs = gridspec.GridSpec( 3, 2 )
######################################
######################################
ax1 = plt.subplot( gs[:-1,:] )
im = plt.imshow( h2, interpolation='nearest', origin='lower',
                 extent=[xh2[0],xh2[-1],yh2[0],yh2[-1]] )
cb = plt.colorbar( im, ax=ax1 )
plt.xlim( xh1[0], xh1[-1] )
plt.ylim( xh1[0], xh1[-1] )
ax1.tick_params( axis='x', which='both', bottom='on', top='on', labelbottom='off' )
######################################
######################################
ax2 = plt.subplot( gs[-1,:] )
plt.plot( xh1[:-1] + np.diff(xh1)/2., h1 )
plt.xlim( xh1[0], xh1[-1] )
cm = plt.cm.Blues
cb2 = plt.colorbar( ax=ax2 )
ax2.tick_params( axis='x', which='both', bottom='on', top='on', labelbottom='on' )
######################################
######################################
fig.tight_layout()
fig.subplots_adjust(hspace=0.05)
cb2.ax.set_visible(False)

Tags: 图像gs绘图onnpfigpltax
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1楼 · 发布于 2024-09-30 03:24:21

我可以想象,让第二个轴直接位于图像下方的最简单方法是使用mpl_toolkits.axes_grid1.make_axes_locatable。这允许以新创建的子图为代价来缩小图像,并且可以同样地用于定位colorbar。在

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable

Nbin=20

X = np.random.rand(1000)
Y = np.random.rand(1000)
h2, yh2, xh2 = np.histogram2d( Y, X, bins=[Nbin,Nbin] )
h1, xh1 = np.histogram( X, bins=Nbin )

fig = plt.figure(  )


ax1 = plt.subplot(111)
im = ax1.imshow( h2, interpolation='nearest', origin='lower',
                 extent=[xh2[0],xh2[-1],yh2[0],yh2[-1]] )

plt.xlim( xh1[0], xh1[-1] )
plt.ylim( xh1[0], xh1[-1] )
ax1.tick_params( axis='x', which='both', bottom='on', top='on', labelbottom='off' )


divider = make_axes_locatable(ax1)
ax2 = divider.append_axes("bottom", size="50%", pad=0.08)
cax = divider.append_axes("right", size="5%", pad=0.08)
cb = plt.colorbar( im, ax=ax1, cax=cax )

#ax2 = plt.subplot( gs[-1,:] )  # , sharex=ax1
ax2.plot( xh1[:-1] + np.diff(xh1)/2., h1 )
ax2.set_xlim( xh1[0], xh1[-1] )
cm = plt.cm.Blues

ax2.tick_params( axis='x', which='both', bottom='on', top='on', labelbottom='on' )

plt.show()

enter image description here

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