问题描述
我在尝试将绘图的直线部分拟合为线性部分时遇到问题。 为了完成我的绘图，我必须将红线像直线一样延伸，以便可以观察到它与至少 x 轴的交点。
我的代码是：
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
#data = pd.read_csv("LPPII_cw_2_1.csv")
#f = data["f [kHz]"]
f = (1,10,20,30,40,50,60,70,80,90,100,200,500)
#h21e = data["h21e [A/A]"]
h21e = (218.,215.,210.,200.,189.,175.,165.,150.,140.,129.,120.,69.,30.)
linearf = f[-3:]
linearh = h21e[-3:]
logA = np.log(linearf)
logB = np.log(linearh)
m,c = np.polyfit(logA,logB,1,w=np.sqrt(linearh))
y_fit = np.exp(m*logA + c)
fig,ax = plt.subplots()
ax.set_xscale('log')
ax.set_yscale('log')
ax.set_xlabel('f [kHz]')
ax.set_ylabel('h$_{21e}$ [A/A]')
ax.scatter(f,h21e,marker='.',color='k')
ax.plot(linearf,y_fit,color='r',linestyle='-')
plt.show()
我的情节是这样的：
解决方法
您可以添加 x 轴的最大值并将其附加到 linearf 的末尾。然后计算曲线，并绘制它。需要保存和重置旧的 y 限制，以防止 matplotlib 自动扩展这些限制。请注意，只有在绘制散点图后才能提取 x-lims。
import matplotlib.pyplot as plt
import numpy as np
f = (1,10,20,30,40,50,60,70,80,90,100,200,500)
h21e = (218.,215.,210.,200.,189.,175.,165.,150.,140.,129.,120.,69.,30.)
linearf = f[-3:]
linearh = h21e[-3:]
logA = np.log(linearf)
logB = np.log(linearh)
m,c = np.polyfit(logA,logB,1,w=np.sqrt(linearh))
fig,ax = plt.subplots()
ax.set_xscale('log')
ax.set_yscale('log')
ax.set_xlabel('f [kHz]')
ax.set_ylabel('h$_{21e}$ [A/A]')
ax.scatter(f,h21e,marker='.',color='k')
linearf_ext = list(linearf) + [ax.get_xlim()[1]]
logA = np.log(linearf_ext)
y_fit = np.exp(m * logA + c)
ymin,ymax = ax.get_ylim()
ax.plot(linearf_ext,y_fit,color='r',linestyle='-')
ax.set_ylim(ymin,ymax)
plt.tight_layout()
plt.show()
