import scipy import random cwd = os.getcwd() if os.path.exists('./result'): os.system('rm -rf result') os.makedirs("result") #How many beacons and best reference points? howmanybestreferencepoints = 5 howmanybeacons = 2 #Generate test point coordinates test_coordinate = lib.generateTest() #Generate training point coordinates training_coordinate = lib.generateRef() #Import data distance estimation fn = "%s/data/data-master-1.7-validation.xlsx" % (cwd) dataAll = lib.importData(fn) #Import RSI data test points fnRSITest = "%s/data/AverageTesting.csv" % (cwd) rsiDataTest = lib.genRSIData(fnRSITest) #Import RSI data training points fnRSITrain = "%s/data/AverageTraining.csv" % (cwd) rsiDataTrain = lib.genRSIData(fnRSITrain)
cwd = os.getcwd() #File name for summary sumfile = "summary.csv" f = open(sumfile, 'w') f.write('Titik,MAEX,MAEY\n') f.close() #xtrue,ytrue,xpred,ypred,x1,y1,r1,x2,y2,r2,x3,y3,r3 XTRUE = [] YTRUE = [] XPRED = [] YPRED = [] test_point = lib.generateTest() points = np.arange(0, 156, 1) for point in points: XTRUE.append(test_point[point][0]) YTRUE.append(test_point[point][1]) f = open("./result/res_titik_%s.csv" % (point), "r") next(f) deltaX = [] deltaY = [] print("Start processing the data for test point ", point) iterator = 1