我已经在图表的x-ticks上丢失了数字，我该如何回复它们？

Z时代
2024-01-10
分类：问答

这是我绘制残差图的代码;然而，我已经失去了我的X轴刻度数字，我不知道如何让他们回来......任何帮助将不胜感激。对不起，如果这个线程的格式不对，这是我的第一个。我已经在图表的x-ticks上丢失了数字，我该如何回复它们？

代码：

pyplot.figure() 
fig1 = plt.figure(1) 
frame1=fig1.add_axes((.1,.3,.8,.6)) 
pyplot.errorbar(xval, yval, yerr=yerr, xerr=xerr, marker='o',markersize = 2, linestyle='None', color = 'black') 
# Axis labels 
pyplot.xlabel(' Height (m)') 
pyplot.ylabel('Mass per second (kg.s-1)') 
# Generate best fit line using model function and best fit parameters, and add to plot 
fit_line=model_funct(xval, [a_soln, b_soln]) 
# Theoretical line 
x = np.array(arange(0.07,0.15, 0.001)) 
y = (-2.61049E-05) + (0.005815772)*x 
plt.plot(x, y, linestyle = '--', color ='r',linewidth = 0.7, label = 'Theoretical') 
# Experimental line 
s = (-4.43329E-05) + (0.006008837)*x 
pyplot.plot(x, s,linewidth = 0.7, color = 'black', label = 'Experimental Chi Squared Fit') 
# Set suitable axis limits: you will probably need to change these... 
pyplot.xlim(0.08, 0.14) 
pyplot.ylim(0.0004, 0.0008) 
pyplot.legend(loc = 'upper left',prop={'size':10}) 
frame2=fig1.add_axes((.1,.1,.8,.2)) 
difference = y - s 
pyplot.plot(x, difference, color = 'black') 
frame2.set_ylabel('Residual') 
plt.xlabel('Height (m)') 
plt.yticks(numpy.arange(-0.000010, 0.000010, 0.00001)) 
plt.xticks(numpy.arange(0.08, 0.14, 0.01)) 
pyplot.ylim(-0.000010, 0.000010) 
pyplot.xlim(0.08,0.14) 
pyplot.grid() 
pyplot.show()

回答：

相反牵伸装置中，可以考虑使用次要情节代替。正如我从代码中看到的那样，您试图使用不同高度比例的子图。有更好的方法来做到这一点，例如与gridspec：

import numpy as np 
import matplotlib.pyplot as plt 
import matplotlib.gridspec as gridspec 
fig = plt.figure() 
gs = gridspec.GridSpec(2, 1, height_ratios=[4, 1]) 
ax1 = plt.subplot(gs[0, 0]) 
plt.errorbar(xval, yval, yerr=yerr, xerr=xerr, marker='o', markersize = 2, linestyle='None', color='black') 
#Axis labels 
ax1.set_xlabel(' Height (m)') 
ax1.set_ylabel(r'Mass per second (kg$\cdot$s$^{-1}$)') 
#Generate best fit line using model function and best fit parameters, and add to plot 
fit_line=model_funct(xval, [a_soln, b_soln]) 
#Theoretical line 
x = np.arange(0.07, 0.15, 0.001) 
y = (-2.61049E-05) + (0.005815772)*x 
ax1.plot(x, y, linestyle = '--', color ='r',linewidth = 0.7, label = 'Theoretical') 
#Experimental line 
s = (-4.43329E-05) + (0.006008837)*x 
ax1.plot(x, s,linewidth = 0.7, color = 'black', label = 'Experimental Chi Squared Fit') 
#Set suitable axis limits: you will probably need to change these... 
ax1.set_xlim(0.08, 0.14) #redundant by adding "sharex=ax1" 4 lines blelow 
ax1.set_ylim(0.0004, 0.0008) 
ax1.legend(loc = 'upper left',prop={'size':10}) 
ax2 = plt.subplot(gs[1, 0], sharex=ax1) 
difference = y - s 
plt.plot(x, difference, color = 'black') 
ax2.set_ylabel('Residual') 
ax2.set_xlabel('Height (m)') 
ax2.set_yticks(np.arange(-0.000010, 0.000010, 0.00001)) 
ax2.set_xticks(np.arange(0.08, 0.14, 0.01)) 
ax2.set_ylim(-0.000010, 0.000010) 
ax2.set_xlim(0.08,0.14) 
ax2.grid() 
plt.tight_layout() 
plt.show()