焊道塌陷识别-Halcon编程实现

#-*- codeing = utf-8 -*- #@Time : 2022/1/11 21:24 #@Author : HRoss717 #@File ： test.py #@Software : PyCharm import numpy as np import matplotlib.pyplot as plt from scipy.optimize import leastsq import csv import pandas as pd filename ='test.csv' with open(filename) as f: reader =csv.reader(f) first_row =next(reader) second_row =next(reader) # 分别删除最后一个空的元素 del first_row[len(first_row)-1] del second_row[len(second_row)-1] # 分别从str类型，转换为float类型 first_row=np.array(first_row).astype(np.float64) second_row = np.array(second_row).astype(np.float64) # //也可以通过这种方式进行数据转换 # first_row=list(map(float,first_row)) # second_row = list(map(float, second_row)) # # 待拟合的数据 # X = np.array([1,2,3,4,5,6]) # Y=np.array([9.1,18.3,32,47,69.5,94.8]) # x = np.array(second_row) # y = np.array(first_row) # X = np.array(first_row) Y = np.array(second_row) # x=np.array(first_row) # y=np.array(second_row) # 用7次多项式拟合 f1 = np.polyfit(X, Y,7) print('f1 is :\n', f1) p1 = np.poly1d(f1) print('p1 is :\n', p1) print("-----------------------") from sympy import * x = symbols('x') # ds=f1[0]*x**7+f1[1]*x+f1[2]*x+f[3]*x+f1[4]*x+f1[5]*x+f1[6]*x+f1[7] ds=f1[0]*(x**7)+f1[1]*(x**6)+f1[2]*(x**5)+f1[3]*(x**4)+f1[4]*(x**3)+f1[5]*(x**2)+f1[6]*(x**1)+f1[7]*(x**0) diff=diff(ds,x) print(diff) degreeMy=[] for lena in range(0,382): degreeMy.append( diff.evalf(subs={'x': lena})) print(degreeMy) degreeMy=np.array(degreeMy) # 也可使用yvals=np.polyval(f1, x) yvals = p1(X) # 拟合y值 print('yvals is :\n', yvals) # 绘图 plot1 = plt.plot(X, -Y, 's', marker="o",label='original values') plot2 = plt.plot(X,-yvals, 'r', label='polyfit values') plt.xlabel('x') plt.ylabel('y') plt.legend(loc=3) # 指定legend的位置右下角---根据象限来设定1,2,3,4 plt.twinx() plot3 = plt.plot(X, degreeMy, 'g', label='deri values') plt.xlabel('x') plt.ylabel('y') plt.legend(loc=4) # 指定legend的位置右下角---根据象限来设定1,2,3,4 plt.title('polyfitting') plt.show()