pythonmatplotlib坐标轴打断
想要绘制出如下类型坐标轴断开的图，matplotlib中并没有直接可⽤的API，但是官⽅给出了⼀个demo:
⼤概说下思路：画出两个共享X轴，完全相同的图，下图取消上边界，下图取消下边界，然后再使⽤plot画两组平⾏线就⼤功告成。
参照官⽹例⼦画的堆积图代码
def respond_mode_bar(self):
labels =['Braking','Right','Left','R&B','L&B']
# color_list = ['silver', 'red', 'blue', 'orange', 'deepskyblue']
# color_list = ['blue', 'orange', 'green', 'red', 'olive']
x =list(self.sub_list)
y = np.zeros((len(self.sub_list),len(labels)), dtype=np.float)
y0 = np.zeros(len(self.sub_list), dtype=np.float)
# fig, (ax1, ax2) = plt.subplots(2, 1, sharex=True)
gs = gridspec.GridSpec(2,1, height_ratios=[3,1], hspace=0.15)
fig = plt.figure(figsize=(8,4.5))
ax1 = fig.add_subplot(gs[0,:])
ax2 = fig.add_subplot(gs[1,:], sharex=ax1)
ax1.set_ylim(70,100)
ax2.set_ylim(0,10)
ax1.spines['bottom'].set_visible(False)
ax2.spines['top'].set_visible(False)
ax1.xaxis.tick_top()
ax1.tick_params(labeltop='off')
ax2.xaxis.tick_bottom()
for idx, sub in enumerate(self.sub_list):
sub =str(sub).zfill(4)
y[idx,:]= np.array(self.data_dict[sub]['respond_mode'])
for ii in range(len(labels)):
if ii==0: ax1.bar(x, y[:,ii], align='center', \
label = labels[ii], width=0.6)
if ii==0: ax2.bar(x, y[:,ii], align='center', \
label = labels[ii], width=0.6)
else:
matplotlib中subploty0 = y0 +y[:, ii-1]
ax1.bar(x, y[:,ii], bottom=y0, align='center', \
label = labels[ii], width=0.6)
ax2.bar(x, y[:,ii], bottom=y0, align='center', \
label = labels[ii], width=0.6)
d =.01# how big to mak
e the diagonal lines in axes coordinates
kwargs =dict(ansAxes, color='k', clip_on=False)
ax1.plot((-d,+d),(-d,+d),**kwargs)# top-left diagonal
ax1.plot((1- d,1+ d),(-d,+d),**kwargs)# top-right diagonal
kwargs.update(ansAxes)# switch to the bottom axes
ax2.plot((-d,+d),(1- d*3,1+ d*3),**kwargs)# bottom-left diagonal
ax2.plot((1- d,1+ d),(1- d*3,1+ d*3),**kwargs)# bottom-right diagonal
plt.xlabel('Subject index')
ax1.set_ylabel('Percentage (%)')
plt.legend(loc=(0.65,0.1), title='Evasive Maneuvers', \
facecolor='w', framealpha=1)
plt.savefig(self.fig_path+sub+'_respond_mode.png', dpi=300, transparent=True)        plt.show()

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