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distance_accuracy_repeatability.py
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from tkinter import *
import os
import math
import csv
import data_read
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import pyplot as plt
from matplotlib.ticker import FuncFormatter
class distance_ar():
def __init__(self, cycle, pose, angle):
self.cycle = int(cycle)
self.pose = int(pose)
self.angle = angle
self.dataPath = r'.\fileSelect.txt'
self.refreshPath = r'.\refreshd.txt'
self.pathResult = r'.\result.txt'
def calculate(self):
#读取待处理数据目录
with open(self.dataPath, 'r') as ff:
path = ff.read()
#判断是否有姿态
if self.angle == True: #有姿态
#确定子图的布局
figColumn = 4
figRows = 1
#画图
fig = plt.figure(figsize=(12,3))
fig.subplots_adjust(hspace=0.5, wspace=0.5)
fig.suptitle('距离准确度重复性(带姿态)', fontsize=16)
#读取数据
dataTest = data_read.dataRead(path)
dataTest.csvread()
points = dataTest.data['pose']
aa = dataTest.data['a']
ba = dataTest.data['b']
ca = dataTest.data['c']
#按照点位将测量结果分开
posePoint = {}
a = {}
b = {}
c = {}
for i in range(2):
posePoint[i] = np.array([points[m] for m in range(len(points)) if m%self.pose==i ])
a[i] = np.array([aa[m] for m in range(len(aa)) if m%self.pose==i ])
b[i] = np.array([ba[m] for m in range(len(ba)) if m%self.pose==i ])
c[i] = np.array([ca[m] for m in range(len(ca)) if m%self.pose==i ])
#读取指令点
filePath = os.path.split(path)
insPath = filePath[-2] + '\指令点.txt'
dataIns = data_read.dataRead(insPath)
dataIns.txtRead()
insPoints = dataIns.data[:,0:3]
insA = dataIns.data[:,3]
insB = dataIns.data[:,4]
insC = dataIns.data[:,5]
#计算指令距离
Dcxyz = np.linalg.norm(insPoints[0]-insPoints[1])
Dca = abs(insA[0]-insA[1])
Dcb = abs(insB[0]-insB[1])
Dcc = abs(insC[0]-insC[1])
#计算每次测量的距离
D = [np.linalg.norm(posePoint[0][m]-posePoint[1][m]) for m in range(self.cycle)]
Da = [np.linalg.norm(a[0][m]-a[1][m]) for m in range(self.cycle)]
Db = [np.linalg.norm(b[0][m]-b[1][m]) for m in range(self.cycle)]
Dc = [np.linalg.norm(c[0][m]-c[1][m]) for m in range(self.cycle)]
#计算平均值
DAve = sum(D) / self.cycle
DA = sum(Da) / self.cycle
DB = sum(Db) / self.cycle
DC = sum(Dc) / self.cycle
#准确度
ADp = DAve - Dcxyz
Aa = DA - Dca
Ab = DB - Dcb
Ac = DC - Dcc
#重复性
RD = 3*math.sqrt(sum((D-DAve)**2)/(self.cycle-1))
RDa = 3*math.sqrt(sum((Da-DA)**2)/(self.cycle-1))
RDb = 3*math.sqrt(sum((Db-DB)**2)/(self.cycle-1))
RDc = 3*math.sqrt(sum((Dc-DC)**2)/(self.cycle-1))
#输出结果
r = open(self.pathResult, 'a+')
r.truncate(0)
r.write('***距离准确度和距离重复性(有姿态)***\n')
r.write('距离准确度为%.4fmm，%.4f°，%.4f°，%.4f°；\n'
'距离重复性为：±%.4fmm，±%.4f°，±%.4f°，±%.4f°；'
% (ADp, Aa, Ab, Ac,
RD, RDa, RDb, RDc))
r.flush()
r.close()
ref = open(self.refreshPath, 'a+')
ref.truncate(0)
ref.write('1')
ref.flush()
ref.close()
#xyz
ax = fig.add_subplot(figRows, figColumn, 1)
ax.plot([m for m in range(1,31)], D, c='blue')
ax.hlines(DAve, 0, 30, colors='red', linestyle="--")
ax.set_xlabel('测量次数')
ax.set_ylabel('距离(mm)')
titlePlot = '点位距离'
ax.set_title(titlePlot)
#A
ax = fig.add_subplot(figRows, figColumn, 2)
ax.plot([m for m in range(1,31)], Da, c='blue')
ax.hlines(DA, 0, 30, colors='red', linestyle="--")
titlePlot = 'A'
ax.set_title(titlePlot)
#B
ax = fig.add_subplot(figRows, figColumn, 3)
ax.plot([m for m in range(1,31)], Db, c='blue')
ax.hlines(DB, 0, 30, colors='red', linestyle="--")
titlePlot = 'B'
ax.set_title(titlePlot)
#C
ax = fig.add_subplot(figRows, figColumn, 4)
ax.plot([m for m in range(1,31)], Dc, c='blue')
ax.hlines(DC, 0, 30, colors='red', linestyle="--")
titlePlot = 'C'
ax.set_title(titlePlot)
elif self.angle == False:
#读取测试数据
dataTest = data_read.dataRead(path)
dataTest.txtRead()
points = dataTest.data
#按照点位将测量结果分开
posePoint = {}
for i in range(self.pose):
posePoint[i] = np.array([points[m] for m in range(len(points)) if m%self.pose==i ])
#读取指令点
filePath = os.path.split(path)
insPath = filePath[-2] + '\指令点.txt'
dataIns = data_read.dataRead(insPath)
dataIns.txtRead()
insPoints = dataIns.data
#计算指令距离
Dcxyz = np.linalg.norm(insPoints[0]-insPoints[1])
#计算每次测量的距离
D = [np.linalg.norm(posePoint[0][m]-posePoint[1][m]) for m in range(self.cycle)]
#计算平均值
DAve = sum(D) / self.cycle
#准确度
ADp = DAve - Dcxyz
#重复性
RD = 3*math.sqrt(sum((D-DAve)**2)/(self.cycle-1))
# 输出结果
r = open(self.pathResult, 'a+')
r.truncate(0)
r.write('***距离准确度和距离重复性***\n')
r.write('距离准确度为%.4fmm；\n'
'距离重复性为：±%.4fmm；'
% (ADp, RD))
r.flush()
r.close()
ref = open(self.refreshPath, 'a+')
ref.truncate(0)
ref.write('1')
ref.flush()
ref.close()
#确定子图的布局
#画图
plt.figure()
plt.title('距离准确度重复性', fontsize=16)
plt.plot([m for m in range(1,31)], D, c='blue')
plt.hlines(DAve, 0, 30, colors='red', linestyle="--")
plt.xlabel('测量次数')
plt.ylabel('距离(mm)')
plt.axis()
plt.grid()
plt.show()