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