def twoLocalTDCDataProcess(dataFile1,dataFile2,fineTimeFile1,fineTimeFile2,order,tau): channel1=int(fineTimeFile1[-8]) channel2=int(fineTimeFile2[-8]) saveFile1 = dataFile1[:-4] + '_channel%s.txt'%channel1 dataList1 = TDCDataConvert.TDCDataParse(dataFile1, fineTimeFile1, 8, str(40+channel1-1)) saveFile2 = dataFile2[:-4] + '_channel%s.txt' % channel2 dataList2 = TDCDataConvert.TDCDataParse(dataFile2, fineTimeFile2, 8, str(40+channel2-1)) fileToList.listToFile(dataList1, saveFile1) fileToList.listToFile(dataList2, saveFile2) num1=len(dataList1) num2=len(dataList2) if num1!=num2: print 'data lenght is not equal!' return 0 xa=[] xb=[] ya=[] for i in range(num1): xa.append(dataList1[i][0]) xb.append([dataList1[i][0]]) ya.append(dataList1[i][0]-dataList2[i][0]) xa, ya, fitList, residual =fitting.polyFitSegment(xa, ya, order, 10000) del xa[:] del fitList[:] xOneSec, residualOneSec = filter.normalByTime(xb, residual, 1000000000000) fileToList.listToFileLong(residualOneSec, saveFile1[:-4] + '-%s_residual-%s-1s-ps.txt'%(channel2,order)) xTau,residualTau=filter.normalByTime(xb, residual, tau) residualFile=saveFile1[:-4] + '-%s_residual-%s-%.3fs-ps.txt' % (channel2, order,tau/1000000000000.0) fileToList.listToFileLong(residualTau, residualFile) fig = plt.figure() ax1 = fig.add_subplot(111) for i,item in enumerate(xOneSec): xOneSec[i]=item/1000000000000.0 residualOneSec[i][0]=residualOneSec[i][0]*1000000000000 ax1.plot(xOneSec,residualOneSec, color='g', linestyle='-', marker='*') ax1.xaxis.grid(True, which='major') # x坐标轴的网格使用主刻度 ax1.yaxis.grid(True, which='major') # y坐标轴的网格使用次刻度show() plt.show() tdevFile = residualFile[:-4] + '_TDEV.txt' tdev = varianceStatistics.TDEV(residualTau, tau/1000000000000.0) fileToList.listToFileFloat(tdev, tdevFile) print 'TDEV calculation finished!' fig = plt.figure() dataPlot.logPlotAx(tdev, fig, 'r','--','s', '11.25 tdev') dataFile1 = unicode( 'C:\Users\Levit\Experiment Data\Rakon晶振测试数据\两TDC测试\\20171114200130-tdc2-13-2k-500s-3_residual-1-0.01s-ps_TDEV.txt', 'utf8') List1 = fileToList.fileToList(dataFile1) dataPlot.logPlotAx(List1, fig, 'g', '--', 'o', '11.14') plt.show()
def polyFitSegmentTest(date): order = 2 timeNormal = 100000000000 # timeFile = unicode('C:\Users\Levit\Experiment Data\德令哈测试\\20171226\零基线实验\\20171227015305-tdc2_4_filterN_coindence_filtered_250-350s.txt' , 'utf8') timeFile = unicode( 'C:\Users\Levit\Experiment Data\双站数据\\20180121\\result\\synCoincidence-124-216--17-1-Coin-紫台WGS84-atm-factor-haiji_laser改正_filtered.txt', 'utf8') timeList = fileToList.fileToList(timeFile) xa = [] ya = [] # for i in range(len(timeList)): # xa.append(timeList[i][0]-timeList[i][4]) # # ya.append((timeList[i][0] - timeList[i][1])) # ya.append([(timeList[i][2])/1000000000000.0]) # xa, ya, timeList, fitList, residual = filter.fitFilter( timeList, 2500 / 1000000000000.0, 1, 2) # fileToList.listToFile(timeList,timeFile[:-4] + '_filtered.txt') # xa,ya,fitList, residual = polyFitSegment(xa, ya, 1, 0.1) # xa, ya, filteredList, residual=filter.thresholdFilter(xa,ya,residual,timeList,0,0.000000002) xa, ya, fitList, residual = polyFitSegment(xa, ya, order, 1000) # xa, ya, filteredList, residual = filter.thresholdFilter(xa, ya, residual, timeList, 0, 0.0000001) # residual=[] # for item in timeList: # # residual.append([(item[0]-item[1])/1000000000000.0]) # residual.append([(item[2] ) / 1000000000000.0]) print numpy.std(residual, ddof=1) xa, residual = filter.normalByTime(timeList, residual, timeNormal) fileToList.listToFileLong( residual, timeFile[:-4] + '_residual-%s-0.1s-ps.txt' % order) # fileToList.listToFile(filteredList,timeFile[:-4]+'_filtered.txt') fig = plt.figure() ax1 = fig.add_subplot(111) # ax2= fig.add_subplot(212) for i, item in enumerate(xa): xa[i] = item / 1000000000000.0 # fitList[i][0]=fitList[i][0]*1000000000000.0 # ya[i]=[timeList[i][3]] residual[i][0] = residual[i][0] * 1000000000000 # print '%s\t%s'%(xa[i],residual[i][0]) ax1.plot(xa, residual, color='g', linestyle='-', marker='*') # xa, ya = filter.normalByTime(timeList, ya, timeNormal) # ax1.plot(xa, ya, color='g', linestyle='-', marker='') ax1.xaxis.grid(True, which='major') #x坐标轴的网格使用主刻度 ax1.yaxis.grid(True, which='major') #y坐标轴的网格使用次刻度show() ax1.set_ylabel('Difference(Residual after %s order fitting) (ps)' % order, fontsize=20) ax1.set_xlabel('Time (s)', fontsize=20) ax1.set_title('Time Compare', fontsize=24) # ax2.plot(xa,ya,color='m',linestyle='',marker='.') # ax2.plot(xa, fitList, color='g', linestyle='-', marker='') # ax.legend() plt.show()
def fitting_segment(startTime,endTime,coindenceFile): coindenceList=fileToList.fileToList(coindenceFile) second=1000000000000.0 tau=100000000000 order=2 num = len(coindenceList) xa = [] xb = [] ya = [] for i in range(num): if coindenceList[i][0]/second>=startTime and coindenceList[i][0]/second<endTime: xa.append(coindenceList[i][0]) ya.append(coindenceList[i][2]) # xa, ya, coindenceList, fitList, residual = filter.fitFilter(coindenceList, 2000 / 1000000000000.0, 2, 1) xa, ya, fitList, residual = fitting.polyFitSegment(xa, ya, order, 10000) for i in range(len(xa)): xb.append([xa[i]]) xOneSec, residualOneSec = filter.normalByTime(xb, residual, second) del xa[:] del fitList[:] del coindenceList[:] fileToList.listToFileLong(residualOneSec, coindenceFile[:-4] + '_%s-%s-1s-ps.txt' % (startTime, endTime)) xTau, residualTau = filter.normalByTime(xb, residual, tau) residualFile = coindenceFile[:-4] + '_%s-%s-%.3fs-ps.txt' % (startTime, endTime, tau / 1000000000000.0) fileToList.listToFileLong(residualTau, residualFile) fig = plt.figure() ax1 = fig.add_subplot(111) for i, item in enumerate(xOneSec): xOneSec[i] = item / 1000000000000.0 residualOneSec[i][0] = residualOneSec[i][0] * 1000000000000 ax1.plot(xOneSec, residualOneSec, color='g', linestyle='-', marker='*') ax1.xaxis.grid(True, which='major') # x坐标轴的网格使用主刻度 ax1.yaxis.grid(True, which='major') # y坐标轴的网格使用次刻度show() plt.show() tdevFile = residualFile[:-4] + '_TDEV.txt' tdev = varianceStatistics.TDEV(residualTau, tau / 1000000000000.0) fileToList.listToFileFloat(tdev, tdevFile) print 'TDEV calculation finished!' tdevName='TDEV %s-%s second'%(startTime,endTime) fig = plt.figure() dataPlot.logPlotAx(tdev, fig, 'r', '--', 's', tdevName) plt.show()
def test1(): dataFile = unicode( 'E:\Experiment Data\时频传输数据处理\本地光路系统测试\\5.17\\5.17-850-2路-1_coinDiff_segment_search.txt', 'utf8') timeList = fileToList.fileToList(dataFile) xa = [] ya = [] timeNormal = 250000000000 for i in range(len(timeList)): if timeList[i][1] > -700 and timeList[i][1] < 600: xa.append([timeList[i][0]]) ya.append([timeList[i][1]]) xa, ya = filter.normalByTime(xa, ya, timeNormal) fig = plt.figure() ax1 = fig.add_subplot(111) ax1.xaxis.grid(True, which='major') #x坐标轴的网格使用主刻度 ax1.yaxis.grid(True, which='major') #y坐标轴的网格使用次刻度show() ax1.plot(xa, ya, color='g', linestyle='-', marker='') plt.show()
def polyLeastFitSegmentTest(date): order = 50 timeNormal = 50000000000 timeFile = unicode( 'E:\Experiment Data\时频传输数据处理\双站数据处理\\%s\\Result\\synCoincidenceEM_0530-85-250-EM--18.txt' % date, 'utf8') # timeFile=unicode('E:\Experiment Data\时频传输数据处理\丽江测试\\4.14\\4.14-lzx-lj-400s_coinDiff_segment_search.txt','utf8') timeList = fileToList.fileToList(timeFile) xa = [] ya = [] x = [] for i in range(len(timeList)): xa.append(timeList[i][1]) ya.append(timeList[i][0] - timeList[i][1]) xa.append(timeList[i][0]) ya.append(timeList[i][1]) # xa = xa[50000:70000] ya = ya[50000:70000] # print len(xa), len(ya) xa, ya = filter.preFilter(timeList, 2, 100000) print len(xa), len(ya) fitList, residual = polyLeastFitSegment(xa, ya, 10, 1000) filter.dotFilter(residual, 0, 10000.0, 3) xa, ya, residual = filter.thresholdFilter(xa, ya, residual, 0, 4000) fitList, residual = polyLeastFitSegment(xa, ya, order, 100) xa, ya, residual = filter.thresholdFilter(xa, ya, residual, 0, 2500) # xa,ya,timeList,fitList,residual=filter.fitFilter(timeList,3000,2,order) # # print len(xa),len(timeList),len(residual) residualNormal = filter.normalByTime(timeList, residual, timeNormal) # residualSecUnit=filter.timeUnitConvert(residual,1000000000000) # fileToList.listToFileLong(residualSecUnit, timeFile[:-4] + '_%s_residual-0531-10-20000-ps.txt' % date) fileToList.listToFile(timeList, timeFile[:-4] + '_filtered.txt') # fig = plt.figure() # ax = fig.add_subplot(111) # ax.plot(xa, residual, color='g', linestyle='-', marker='') ax.plot(xa, ya, color='m', linestyle='', marker='.ux')
def twoLightTDCDataProcess(channel1,channel2,delay,window,dataFile1,dataFile2,fineTimeFile1,fineTimeFile2,order,tau,tdevName,tdevComp,tdevCompFile): saveFile1 = dataFile1[:-4] + '_channel_%s.txt'%channel1 dataList1 = TDCDataConvert.TDCDataParse(dataFile1, fineTimeFile1, 8, str(40+channel1-1)) fileToList.listToFile(dataList1, saveFile1) dataList1_filter=filter.freqFilter(dataList1,10000200,6,300000) dataList1_filterN=filter.reflectNoiseFilter(dataList1_filter,1000000,0) fileToList.listToFile(dataList1_filterN, saveFile1[:-4]+'_filterN.txt') saveFile2 = dataFile2[:-4] + '_channel_%s.txt' % channel2 dataList2 = TDCDataConvert.TDCDataParse(dataFile2, fineTimeFile2, 8, str(40+channel2 - 1)) fileToList.listToFile(dataList2, saveFile2) dataList2_filter = filter.freqFilter(dataList2, 10000200, 6, 300000) dataList2_filterN = filter.reflectNoiseFilter(dataList2_filter, 1000000, 0) TDCTest.countBySec(dataList2) TDCTest.countBySec(dataList1) TDCTest.countBySec(dataList2_filterN) TDCTest.countBySec(dataList1_filterN) fileToList.listToFile(dataList2_filterN, saveFile2[:-4] + '_filterN.txt') saveCoinFile = dataFile1[:-4] + '_%s_filterN_coindence.txt'%channel1 coindenceList,averSecCount=TDCTest.coindenceTest(dataList1_filterN, dataList2_filterN, delay, window, saveCoinFile) tdevName=tdevName+' %s'%averSecCount del dataList1,dataList1_filter,dataList1_filterN del dataList2,dataList2_filter,dataList2_filterN num=len(coindenceList) xa = [] xb = [] ya = [] for i in range(num): xa.append(coindenceList[i][0]) ya.append(coindenceList[i][2]) xa, ya, coindenceList, fitList, residual = filter.fitFilter(coindenceList, 2000 / 1000000000000.0, 2, 1) xa, ya, fitList, residual = fitting.polyFitSegment(xa, ya, order, 10000) fileToList.listToFile(coindenceList,saveCoinFile[:-4]+'_filtered.txt') for i in range(len(xa)): xb.append([xa[i]]) xOneSec, residualOneSec = filter.normalByTime(xb, residual, 1000000000000) del xa[:] del fitList[:] del coindenceList[:] fileToList.listToFileLong(residualOneSec, saveFile1[:-4] + '-%s_residual-%s-1s-ps.txt' % (channel2, order)) xTau, residualTau = filter.normalByTime(xb, residual, tau) residualFile = saveFile1[:-4] + '-%s_residual-%s-%.3fs-ps.txt' % (channel2, order, tau / 1000000000000.0) fileToList.listToFileLong(residualTau, residualFile) fig = plt.figure() ax1 = fig.add_subplot(111) for i, item in enumerate(xOneSec): xOneSec[i] = item / 1000000000000.0 residualOneSec[i][0] = residualOneSec[i][0] * 1000000000000 ax1.plot(xOneSec, residualOneSec, color='g', linestyle='-', marker='*') ax1.xaxis.grid(True, which='major') # x坐标轴的网格使用主刻度 ax1.yaxis.grid(True, which='major') # y坐标轴的网格使用次刻度show() plt.show() tdevFile = residualFile[:-4] + '_TDEV.txt' tdev = varianceStatistics.TDEV(residualTau, tau / 1000000000000.0) fileToList.listToFileFloat(tdev, tdevFile) print 'TDEV calculation finished!' fig = plt.figure() dataPlot.logPlotAx(tdev, fig, 'r', '--', 's', tdevName) List1 = fileToList.fileToList(tdevCompFile) dataPlot.logPlotAx(List1, fig, 'g', '--', 'o', tdevComp) plt.show()