import numpy as np
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif']=['Microsoft YaHei'] #用来正常显示中文标签
plt.rcParams['axes.unicode_minus']=False #用来正常显示负号
#数据准备
X= np.loadtxt("E:/20230914/data/2017124.txt", delimiter=",", usecols=(0),dtype=float)
Y= np.loadtxt("E:/20230914/data/2017124.txt", delimiter=",", usecols=(1),dtype=float)
new_x=np.arange(0.001,2,0.001) #定义差值点
#进行样条差值
import scipy.interpolate as spi
#进行三次样条拟合
ipo3=spi.splrep(X,Y,k=3) #样本点导入,生成参数
iy3=spi.splev(new_x,ipo3) #根据观测点和样条参数,生成插值
##作图
fig, ax = plt.subplots(figsize=(8,8),dpi=300)
#fig.canvas.draw()
#fig.canvas.flush_events()
ax.set_xscale('log')
ax.plot(X,Y,'o',label='实测点')
ax.plot(new_x,iy3,label='插值点')
ax.set_ylim(Y.min()-1,Y.max()+1)
plt.tick_params(labelsize=14) #刻度值字体大小设置(x轴和y轴同时设置)
ax.set_ylabel('沙重百分数',fontsize=14)
ax.set_xlabel('泥沙粒径',fontsize=14)
ax.set_title('泥沙级配曲线图三次样条插值',fontsize=14)
#设置主网格线
ax.grid(color ="black")
#设置次网格线
ax.minorticks_on()
ax.grid(which='minor', linestyle=':', linewidth='0.5', color='gray')
ax.legend(fontsize=14)\
#保存图片至指定路径
fig = plt.gcf()
fig.savefig('E:/20230914/figure/2017124.jpg',dpi=300,bbox_inches='tight')
plt.show()
图1

图2
