Matplotlib奇数子图

Question

我必须绘制一个包含11个子点的图形，如下所示。但由于它是一个奇数，我不知道如何处理子图（4,3,12）去除它...并将最后2个图放在中心 此外，我想增加子图大小，因为空间太重要了。代码如下。

代码是：

plt.close()

fig, axes = plt.subplots(nrows=4, ncols=3)

plt.tight_layout(pad=0.05, w_pad=0.001, h_pad=2.0)
ax1 = plt.subplot(431) # creates first axis
ax1.set_xticks([])
ax1.set_yticks([])
ax1.tick_params(labelsize=8) 
i1 = ax1.imshow(IIIm,cmap='hot',extent=(0,2000,0,2000),vmin=-0.2,vmax=-0.1)
i11 = ax1.plot((0,600),(1000,1000),'k-',linewidth=3)
cb1=plt.colorbar(i1,ax=ax1,ticks=[-0.2,-0.15,-0.1],fraction=0.046, pad=0.04,format='%.3f')
cb1.ax.tick_params(labelsize=8)
ax1.set_title("$n = -3$", y=1.05, fontsize=12)


ax2 = plt.subplot(432) # creates second axis
ax2.set_xticks([])
ax2.set_yticks([])
i2=ax2.imshow(IIm,cmap='hot',extent=(0,2000,0,2000),vmin=-0.1,vmax=0.1)
i22 = ax2.plot((0,600),(1000,1000),'k-',linewidth=3)
ax2.set_title("$n = -2$", y=1.05, fontsize=12)
ax2.set_xticklabels([])
ax2.set_yticklabels([])
cb2=plt.colorbar(i2,ax=ax2,ticks=[-0.1,0.0,0.1],fraction=0.046, pad=0.04,format='%.3f')
cb2.ax.tick_params(labelsize=8)

ax3 = plt.subplot(433) # creates first axis
ax3.set_xticks([])
ax3.set_yticks([])
i3 = ax3.imshow(Im,cmap='hot',extent=(0,2000,0,2000),vmin=-1,vmax=-0.2)
i33 = ax3.plot((0,600),(1000,1000),'k-',linewidth=3)
ax3.set_title("$n = -1$ ", y=1.05, fontsize=12)
cb3=plt.colorbar(i3,ax=ax3,ticks=[-1,-0.6,-0.2],fraction=0.046, pad=0.04,format='%.3f')
ax3.set_xticklabels([])
ax3.set_yticklabels([])
cb3.ax.tick_params(labelsize=8)
#plt.gcf().tight_layout()





#plt.tight_layout(pad=0.05, w_pad=0.001, h_pad=2.0)
ax1 = plt.subplot(434) # creates first axis
ax1.set_xticks([])
ax1.set_yticks([])
ax1.tick_params(labelsize=8) 
i1 = ax1.imshow(ZV_0_modeI,extent=(0,2000,0,2000),cmap=plt.cm.hot,origin="lower", vmin=-1, vmax=1)
i11 = ax1.plot((0,600),(1000,1000),'k-',linewidth=3)
cb1=plt.colorbar(i1,ax=ax1,ticks=[-1,0, 1],fraction=0.046, pad=0.04,format='%.2f')
cb1.ax.tick_params(labelsize=8)
ax1.set_title("$ n = 0$", y=1.05, fontsize=12)


ax2 = plt.subplot(435) # creates second axis
ax2.set_xticks([])
ax2.set_yticks([])
i2=ax2.imshow(I,cmap='hot',extent=(0,2000,0,2000), vmin=-1, vmax=1)
i22 = ax2.plot((0,600),(1000,1000),'k-',linewidth=3)
ax2.set_title("$n = 1$", y=1.05, fontsize=12)
ax2.set_xticklabels([])
ax2.set_yticklabels([])
cb2=plt.colorbar(i2,ax=ax2,fraction=0.046, pad=0.04,ticks=[-1,0,1],format='%.2f')
cb2.ax.tick_params(labelsize=8)

ax3 = plt.subplot(436) # creates first axis
ax3.set_xticks([])
ax3.set_yticks([])
i3 = ax3.imshow(II,cmap='hot',extent=(0,2000,0,2000),vmin=-1,vmax=1)
i33 = ax3.plot((0,600),(1000,1000),'k-',linewidth=3)
ax3.set_title("$n = 2$ ", y=1.05, fontsize=12)
cb3=plt.colorbar(i3,ax=ax3,fraction=0.046, pad=0.04,ticks=[-1.,0,1.],format='%.2f')
ax3.set_xticklabels([])
ax3.set_yticklabels([])
cb3.ax.tick_params(labelsize=8)
plt.gcf().tight_layout()




plt.tight_layout(pad=0.05, w_pad=0.001, h_pad=2.0)
ax1 = plt.subplot(437) # creates first axis
ax1.set_xticks([])
ax1.set_yticks([])
ax1.tick_params(labelsize=8) 
i1 = ax1.imshow(III,cmap=plt.cm.hot,origin="lower",extent=(0,2000,0,2000),vmin=-1, vmax=1)
i11 = ax1.plot((0,600),(1000,1000),'k-',linewidth=3)
cb1=plt.colorbar(i1,ax=ax1,ticks=[-1,0, 1],fraction=0.046, pad=0.04,format='%.2f')
cb1.ax.tick_params(labelsize=8)
ax1.set_title("$ n = 3$", y=1.05, fontsize=12)

ax2 = plt.subplot(438) # creates second axis
ax2.set_xticks([])
ax2.set_yticks([])
i2=ax2.imshow(IV,cmap='hot',extent=(0,2000,0,2000), vmin=-1, vmax=1)
i22 = ax2.plot((0,600),(1000,1000),'k-',linewidth=3)
ax2.set_title("$n = 4$", y=1.05, fontsize=12)
ax2.set_xticklabels([])
ax2.set_yticklabels([])
cb2=plt.colorbar(i2,ax=ax2,fraction=0.046, pad=0.04,ticks=[-1,0,1],format='%.2f')
cb2.ax.tick_params(labelsize=8)

ax3 = plt.subplot(439) # creates first axis
ax3.set_xticks([])
ax3.set_yticks([])
i3 = ax3.imshow(V,cmap='hot',extent=(0,2000,0,2000),vmin=-1,vmax=1)
i33 = ax3.plot((0,600),(1000,1000),'k-',linewidth=3)
ax3.set_title("$n = 5$ ", y=1.05, fontsize=12)
cb3=plt.colorbar(i3,ax=ax3,fraction=0.046, pad=0.04,ticks=[-1.,0,1.],format='%.2f')
ax3.set_xticklabels([])
ax3.set_yticklabels([])
cb3.ax.tick_params(labelsize=8)
plt.gcf().tight_layout()




plt.tight_layout(pad=0.05, w_pad=0.001, h_pad=2.0)
ax1 = plt.subplot(4,3,10) # creates first axis
ax1.set_xticks([])
ax1.set_yticks([])
ax1.tick_params(labelsize=8) 
i1 = ax1.imshow(VI,cmap=plt.cm.hot,origin="lower",extent=(0,2000,0,2000),vmin=-1, vmax=1)
i11 = ax1.plot((0,600),(1000,1000),'k-',linewidth=3)
cb1=plt.colorbar(i1,ax=ax1,ticks=[-1,0, 1],fraction=0.046, pad=0.04,format='%.2f')
cb1.ax.tick_params(labelsize=8)
ax1.set_title("$ n = 6$", y=1.05, fontsize=12)

ax2 = plt.subplot(4,3,11) # creates second axis
ax2.set_xticks([0])
ax2.set_yticks([])
i2=ax2.imshow(VII,cmap='hot',extent=(0,2000,0,2000), vmin=-1, vmax=1)
i22 = ax2.plot((0,600),(1000,1000),'k-',linewidth=3)
ax2.set_title("$n = 7$", y=1.05, fontsize=12)
ax2.set_xticklabels([])
ax2.set_yticklabels([])
cb2=plt.colorbar(i2,ax=ax2,fraction=0.046, pad=0.04,ticks=[-1,0,1],format='%.2f')
cb2.ax.tick_params(labelsize=8)


plt.savefig('filtre.png', dpi=250,bbox_inches='tight', pad_inches=0.1)

plt.show()

Answer 1

实现所需要的一种方法是使用matplotlibs subplot2grid功能。使用此选项可以设置网格的总大小（在您的情况下为4,3），并选择仅绘制此网格中某些子图中的数据。以下是一个简化示例：

import matplotlib.pyplot as plt

x = [1,2]
y = [3,4]

ax1 = plt.subplot2grid((4, 3), (0, 0))
ax2 = plt.subplot2grid((4, 3), (0, 1))
ax3 = plt.subplot2grid((4, 3), (0, 2))
ax4 = plt.subplot2grid((4, 3), (1, 0))
ax5 = plt.subplot2grid((4, 3), (1, 1))
ax6 = plt.subplot2grid((4, 3), (1, 2))
ax7 = plt.subplot2grid((4, 3), (2, 0))
ax8 = plt.subplot2grid((4, 3), (2, 1))
ax9 = plt.subplot2grid((4, 3), (2, 2))
ax10 = plt.subplot2grid((4, 3), (3, 0))
ax11 = plt.subplot2grid((4, 3), (3, 1))

plt.subplots_adjust(wspace = 0.3, hspace = 0.3) #make the figure look better

ax1.plot(x,y)
ax2.plot(x,y)
ax3.plot(x,y)
ax4.plot(x,y)
ax5.plot(x,y)
ax6.plot(x,y)
ax7.plot(x,y)
ax8.plot(x,y)
ax9.plot(x,y)
ax10.plot(x,y)
ax11.plot(x,y)

plt.show()

这产生了数字：

Answer 2

什么也没画，但是关闭轴

ax = plt.subplot(4,3,12)
ax.axis('off')

如有必要，您可以使用循环

images = [rgb, depth, depth, rgb, rgb]
fig, axes = plt.subplots(rows, columns)
    for index, axis in enumerate(axes.reshape(-1)):
        if index < no_of_images:
            axis.imshow(images[index])
        axis.axis('off')