实现检测数据分析,上下限自动填充,一键导出方案
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andy
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import json
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import csv
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#coding:utf-8
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# 导入matplotlib模块并使用Qt5Agg
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import typing
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from PyQt5.QtCore import QObject
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import matplotlib
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matplotlib.use('Qt5Agg')
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# 使用 matplotlib中的FigureCanvas (在使用 Qt5 Backends中 FigureCanvas继承自QtWidgets.QWidget)
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from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
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from PyQt5.QtCore import *
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from PyQt5.QtGui import *
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from PyQt5.QtWidgets import *
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import matplotlib.pyplot as plt
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import sys
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import scheme_data
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import numpy as np
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import threading
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# 生成一个任务的参数
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def scheme_task_to_retinfo(j:json):
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texts=[]
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length=len(j["TestStandard"])
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for i in j["ReturnInfo"]:
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texts.append(i)
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return texts
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# 生成任务参数序列
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def scheme_tasks_to_retinfo(j:json):
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# texts=[]
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# for i in j["TaskArray"]:
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# texts+=scheme_task_to_retinfo(i)
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texts=j["CheckerRtvName"]
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print(texts)
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return texts
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plt.rcParams['font.sans-serif']=['SimHei']
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plt.rcParams['axes.unicode_minus']=False
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def json_extract_retinfo(name:str):
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with open(name,"rb") as f:
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json_obj=json.loads(f.read())
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return scheme_tasks_to_retinfo(json_obj)
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return None
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# 定义一个可以嵌入到qt的figure
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class QFigure(QObject):
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def __init__(self,title:str) -> None:
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QObject.__init__(self)
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self.__figure = plt.figure(figsize=(14,7))
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self.__canvas = FigureCanvas(self.__figure)
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self.__ax = self.__figure.add_axes([0.1,0.1,0.8,0.8])
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self.__ax.set_title(title)
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def draw(self,x,y,lable:str=None,limit_max:int=None,limit_min:int=None):
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line,=self.__ax.plot(x,y,)
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if(lable!=None):
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line.set_label(lable)
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self.__ax.legend()
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if(limit_max!=None):
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self.__ax.axhline(y=limit_max,color='g',linestyle='--')
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if(limit_min!=None):
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self.__ax.axhline(y=limit_min,color='r',linestyle='--')
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# start, end = self.__ax.get_ylim()
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# self.__ax.yaxis.set_ticks(np.arange(start, end,(end-start)/20),minor=True)
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# ticks=self.__ax.yaxis.get_ticklocs()
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# self.__ax.yaxis.set_ticks(minor=True)
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# self.__ax.yaxis.set_ticks(ticks)
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self.__ax.grid(visible=True,which="major",axis="y")
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self.__canvas.draw()
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def lable(self,lablex,labley):
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self.__ax.set_ylabel(labley)
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self.__ax.set_xlabel(lablex)
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def canvas(self):
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return self.__canvas
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# 定义一个任务需要的参数布局
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class TParamLayout(QObject):
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def __init__(self) -> None:
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QObject.__init__(self)
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self.__layout=QFormLayout()
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self.__items=[]
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def add_item(self,name:str,value:str="",tooltip:str=None):
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line_edit = QLineEdit()
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line_edit.setObjectName(value)
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line_edit.setText(value)
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line_edit_label = QLabel()
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line_edit_label.setObjectName(name)
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line_edit_label.setText(name)
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line_edit_label.setAlignment(Qt.AlignmentFlag.AlignCenter)
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if(tooltip!=None):
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line_edit_label.setToolTip(tooltip)
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line_edit.setToolTip(tooltip)
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self.__layout.addRow(line_edit_label,line_edit)
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self.__items.append((line_edit_label,line_edit))
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def item_value(self,name:str):
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for i in self.__items:
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if(i[0].text()==name):
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return i[1].text()
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return None
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def values(self):
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vals=[]
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for i in self.__items:
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vals.append((i[0].text(),i[1].text()))
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return vals
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def layout(self):
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return self.__layout
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class Analysis(QWidget):
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def __init__(self,parent=None):
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super(Analysis,self).__init__(parent)
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self.setWindowTitle("检测数据分析")
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self.__import_but = QPushButton("导入方案",self)
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self.__import_but.clicked.connect(self.import_but_clicked)
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self.__import_but.setGeometry(QRect(0,0,100,27))
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self.__export_but = QPushButton("导出方案")
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self.__export_but.clicked.connect(self.export_but_clicked)
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self.__scroll=QScrollArea(self)
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self.__scroll.setGeometry(0,30,1230,700)
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# 设置布局
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self.__layout = QFormLayout()
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self.__layout.addRow(' ',self.__export_but)
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self.__items=[]
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def main():
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save_name="check_data.csv"
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title=json_extract_retinfo("代工厂数据采集EJ旧68uF22um08211.json")
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save_f=open(save_name,'+w')
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save_f.write(','.join(title)+'\n')
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err_num=0
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with open("EJ09C测试数据.csv",newline="") as f:
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data=csv.reader(f)
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for row in data:
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if(row[3]=='0'):
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save_f.write(row[4]+'\n')
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else:
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err_num+=1
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print(row)
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print("检测异常数量为：",err_num)
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if __name__ == "__main__":
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main()
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def addItem(self,data,name:str,params:list()):
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length=len(data)
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if(length<1000):
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print("data length too less.")
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return
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# 排序,从小到大
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sort_list=np.sort(data)
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dat_count=np.bincount(data)
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avg=round(np.average(data))
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max=sort_list[-1]
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min=sort_list[0]
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mid=sort_list[len(sort_list)//2]
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std=round(np.std(data))
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# 把众数和原始值对齐
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dat_count=dat_count[min:]
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dat_count_max=np.max(dat_count)
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dat_zoom=length//dat_count_max
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dat_count=np.multiply(dat_count,dat_zoom)
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# 去掉极大值,去掉极小值,使用99.8%的数据来统计区间
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limit_max_t=sort_list[-(length//1000)]
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limit_min_t=sort_list[(length//1000)]
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limit_max=limit_max_t+(limit_max_t-limit_min_t)//5
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limit_min=limit_min_t-(limit_max_t-limit_min_t)//5
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# 使用3倍标准差来统计区间
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# limit_max=avg+3*std
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# limit_min=avg-3*std
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if(limit_min<0):
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limit_min=0
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figure = QFigure(name)
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figure.lable("序号","数值")
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tplayout=TParamLayout()
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for i in params:
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tplayout.add_item(i+":Max",str(max))
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tplayout.add_item(i+":Min",str(min))
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tplayout.add_item(i+":Avg",str(avg))
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tplayout.add_item(i+":Mid",str(mid))
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tplayout.add_item(i+":Std",str(std))
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tplayout.add_item(i+":LimitMax",str(limit_max))
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tplayout.add_item(i+":LimitMin",str(limit_min))
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self.__layout.addRow(figure.canvas(),tplayout.layout())
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figure.draw(range(len(data)),data,lable="原始值",limit_max=limit_max,limit_min=limit_min)
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y=np.add(range(len(dat_count)),min)
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figure.draw(dat_count,y,lable="权重")
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self.__items.append((figure,tplayout))
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# 连接的绘制的方法
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def import_but_clicked(self):
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# t = threading.Thread(target=self.__anslysis, args=())
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# t.start()
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# def __anslysis(self):
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self.__import_but.setEnabled(False)
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widget=QWidget()
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widget.setGeometry(QRect(0,0,1200,20000))
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self.titles,datas=scheme_data.datas()
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for i in range(len(self.titles)):
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self.addItem(datas[i],self.titles[i],[self.titles[i]])
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widget.setLayout(self.__layout)
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self.__scroll.setWidget(widget)
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def export_but_clicked(self):
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ret_limit=[]
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for i,t in zip(self.__items,self.titles):
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max=i[1].item_value(t+":LimitMax")
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min=i[1].item_value(t+":LimitMin")
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ret_limit.append((max,min))
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scheme_data.export_scheme(ret_limit)
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# 运行程序
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if __name__ == '__main__':
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app = QApplication(sys.argv)
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main_window = Analysis()
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main_window.show()
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app.exec()
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