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gazesim/code/Visualization/3CalibrationDepths.py

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migrated code to public repository
2016-03-09 19:52:35 +01:00
import os, sys
import seaborn
from pylab import rcParams
import cv2
import numpy as np
from numpy import linalg as LA
from time import time
from itertools import combinations
import matplotlib.pyplot as plt
from matplotlib.pyplot import *
import matplotlib.patches as mpatches
# activate latex text rendering
#rc('text', usetex=True)
def main(argv):
# path = str(argv[0])
#/home/Julian/3D_Pupil_Project/work/results/2D2D/3_calibration_depths/p5.csv
path ="/home/mmbrian/3D_Gaze_Tracking/work/results/2D3D/3_calibration_depths/"
Data1 = np.load(path + "p5.npy")
Data2 = np.load(path + "p7.npy")
Data3 = np.load(path + "p10.npy")
Data4 = np.load(path + "p11.npy")
Data5 = np.load(path + "p12.npy")
Data6 = np.load(path + "p13.npy")
Data7 = np.load(path + "p14.npy")
Data8 = np.load(path + "p15.npy")
Data9 = np.load(path + "p16.npy")
Data10 = np.load(path + "p20.npy")
Data11 = np.load(path + "p21.npy")
Data12 = np.load(path + "p24.npy")
Data13 = np.load(path + "p25.npy")
Data14 = np.load(path + "p26.npy")
Data = [Data1,Data2,Data3,Data4,Data5,Data6,Data7,Data8,Data9,Data10,Data11,Data12,Data13,Data14]
AngularerrorC1 = []
for i in xrange(5):
AngularerrorC1.append([])
for j in xrange(14):
AngularerrorC1[i].append(float(0))
AngularerrorC2 = []
for i in xrange(5):
AngularerrorC2.append([])
for j in xrange(14):
AngularerrorC2[i].append(float(0))
AngularerrorC3 = []
for i in xrange(5):
AngularerrorC3.append([])
for j in xrange(14):
AngularerrorC3[i].append(float(0))
AngularerrorC4 = []
for i in xrange(5):
AngularerrorC4.append([])
for j in xrange(14):
AngularerrorC4[i].append(float(0))
AngularerrorC5 = []
for i in xrange(5):
AngularerrorC5.append([])
for j in xrange(14):
AngularerrorC5[i].append(float(0))
AngularerrorC6 = []
for i in xrange(5):
AngularerrorC6.append([])
for j in xrange(14):
AngularerrorC6[i].append(float(0))
AngularerrorC7 = []
for i in xrange(5):
AngularerrorC7.append([])
for j in xrange(14):
AngularerrorC7[i].append(float(0))
AngularerrorC8 = []
for i in xrange(5):
AngularerrorC8.append([])
for j in xrange(14):
AngularerrorC8[i].append(float(0))
AngularerrorC9 = []
for i in xrange(5):
AngularerrorC9.append([])
for j in xrange(14):
AngularerrorC9[i].append(float(0))
AngularerrorC10 = []
for i in xrange(5):
AngularerrorC10.append([])
for j in xrange(14):
AngularerrorC10[i].append(float(0))
# Combi1 1,1.25,1.5
distance1 = 1.0
distance2 = 1.25
distance3 = 1.5
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Data[i][j][1], Data[i][j][1]
if Data[i][j][3] == 1.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3:
AngularerrorC1[0][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Data[i][j][3] == 1.25 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3:
AngularerrorC1[1][i] = Data[i][j][4]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.5 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3:
AngularerrorC1[2][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.75 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3:
AngularerrorC1[3][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 2.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3:
AngularerrorC1[4][i] = Data[i][j][4]
break
else:
j += 1
i += 1
print "AngularerrorC1: ", AngularerrorC1[0]
print "AngularerrorC2: ", AngularerrorC1[1]
print "AngularerrorC3: ", AngularerrorC1[2]
print "AngularerrorC4: ", AngularerrorC1[3]
print "AngularerrorC5: ", AngularerrorC1[4]
meanC1D1 = np.mean(AngularerrorC1[0])
meanC1D2 = np.mean(AngularerrorC1[1])
meanC1D3 = np.mean(AngularerrorC1[2])
meanC1D4 = np.mean(AngularerrorC1[3])
meanC1D5 = np.mean(AngularerrorC1[4])
stdC1D1 = np.std(AngularerrorC1[0])
stdC1D2 = np.std(AngularerrorC1[1])
stdC1D3 = np.std(AngularerrorC1[2])
stdC1D4 = np.std(AngularerrorC1[3])
stdC1D5 = np.std(AngularerrorC1[4])
meanC1 = [meanC1D1,meanC1D2,meanC1D3,meanC1D4,meanC1D5]
stdC1 = [stdC1D1,stdC1D2,stdC1D3,stdC1D4,stdC1D5]
# Combi2 1,1.25,1.75
distance1 = 1.0
distance2 = 1.25
distance3 = 1.75
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Data[i][j][1], Data[i][j][1]
if Data[i][j][3] == 1.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC2[0][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Data[i][j][3] == 1.25 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC2[1][i] = Data[i][j][4]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.5 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC2[2][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.75 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC2[3][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 2.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC2[4][i] = Data[i][j][4]
break
else:
j += 1
i += 1
print "AngularerrorC1: ", AngularerrorC2[0]
print "AngularerrorC2: ", AngularerrorC2[1]
print "AngularerrorC3: ", AngularerrorC2[2]
print "AngularerrorC4: ", AngularerrorC2[3]
print "AngularerrorC5: ", AngularerrorC2[4]
meanC2D1 = np.mean(AngularerrorC2[0])
meanC2D2 = np.mean(AngularerrorC2[1])
meanC2D3 = np.mean(AngularerrorC2[2])
meanC2D4 = np.mean(AngularerrorC2[3])
meanC2D5 = np.mean(AngularerrorC2[4])
stdC2D1 = np.std(AngularerrorC2[0])
stdC2D2 = np.std(AngularerrorC2[1])
stdC2D3 = np.std(AngularerrorC2[2])
stdC2D4 = np.std(AngularerrorC2[3])
stdC2D5 = np.std(AngularerrorC2[4])
meanC2 = [meanC2D1,meanC2D2,meanC2D3,meanC2D4,meanC2D5]
stdC2 = [stdC2D1,stdC2D2,stdC2D3,stdC2D4,stdC2D5]
# Combi3 1,1.25,2.0
distance1 = 1.0
distance2 = 1.25
distance3 = 2.0
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Data[i][j][1], Data[i][j][1]
if Data[i][j][3] == 1.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC3[0][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Data[i][j][3] == 1.25 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC3[1][i] = Data[i][j][4]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.5 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC3[2][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.75 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC3[3][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 2.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC3[4][i] = Data[i][j][4]
break
else:
j += 1
i += 1
print "AngularerrorC1: ", AngularerrorC3[0]
print "AngularerrorC2: ", AngularerrorC3[1]
print "AngularerrorC3: ", AngularerrorC3[2]
print "AngularerrorC4: ", AngularerrorC3[3]
print "AngularerrorC5: ", AngularerrorC3[4]
meanC3D1 = np.mean(AngularerrorC3[0])
meanC3D2 = np.mean(AngularerrorC3[1])
meanC3D3 = np.mean(AngularerrorC3[2])
meanC3D4 = np.mean(AngularerrorC3[3])
meanC3D5 = np.mean(AngularerrorC3[4])
stdC3D1 = np.std(AngularerrorC3[0])
stdC3D2 = np.std(AngularerrorC3[1])
stdC3D3 = np.std(AngularerrorC3[2])
stdC3D4 = np.std(AngularerrorC3[3])
stdC3D5 = np.std(AngularerrorC3[4])
meanC3 = [meanC3D1,meanC3D2,meanC3D3,meanC3D4,meanC3D5]
stdC3 = [stdC3D1,stdC3D2,stdC3D3,stdC3D4,stdC3D5]
# Combi4 1,1.5,1.75
distance1 = 1.0
distance2 = 1.5
distance3 = 1.75
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Data[i][j][1], Data[i][j][1]
if Data[i][j][3] == 1.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC4[0][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Data[i][j][3] == 1.25 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC4[1][i] = Data[i][j][4]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.5 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC4[2][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.75 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC4[3][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 2.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC4[4][i] = Data[i][j][4]
break
else:
j += 1
i += 1
print "AngularerrorC4: ", AngularerrorC4[0]
print "AngularerrorC2: ", AngularerrorC4[1]
print "AngularerrorC3: ", AngularerrorC4[2]
print "AngularerrorC4: ", AngularerrorC4[3]
print "AngularerrorC5: ", AngularerrorC4[4]
meanC4D1 = np.mean(AngularerrorC4[0])
meanC4D2 = np.mean(AngularerrorC4[1])
meanC4D3 = np.mean(AngularerrorC4[2])
meanC4D4 = np.mean(AngularerrorC4[3])
meanC4D5 = np.mean(AngularerrorC4[4])
stdC4D1 = np.std(AngularerrorC4[0])
stdC4D2 = np.std(AngularerrorC4[1])
stdC4D3 = np.std(AngularerrorC4[2])
stdC4D4 = np.std(AngularerrorC4[3])
stdC4D5 = np.std(AngularerrorC4[4])
meanC4 = [meanC4D1,meanC4D2,meanC4D3,meanC4D4,meanC4D5]
stdC4 = [stdC4D1,stdC4D2,stdC4D3,stdC4D4,stdC4D5]
# Combi5 1.0,1.5,2.0
distance1 = 1.0
distance2 = 1.5
distance3 = 2.0
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Data[i][j][1], Data[i][j][1]
if Data[i][j][3] == 1.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC5[0][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Data[i][j][3] == 1.25 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC5[1][i] = Data[i][j][4]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.5 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC5[2][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.75 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC5[3][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 2.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC5[4][i] = Data[i][j][4]
break
else:
j += 1
i += 1
print "AngularerrorC5: ", AngularerrorC5[0]
print "AngularerrorC2: ", AngularerrorC5[1]
print "AngularerrorC3: ", AngularerrorC5[2]
print "AngularerrorC4: ", AngularerrorC5[3]
print "AngularerrorC5: ", AngularerrorC5[4]
meanC5D1 = np.mean(AngularerrorC5[0])
meanC5D2 = np.mean(AngularerrorC5[1])
meanC5D3 = np.mean(AngularerrorC5[2])
meanC5D4 = np.mean(AngularerrorC5[3])
meanC5D5 = np.mean(AngularerrorC5[4])
stdC5D1 = np.std(AngularerrorC5[0])
stdC5D2 = np.std(AngularerrorC5[1])
stdC5D3 = np.std(AngularerrorC5[2])
stdC5D4 = np.std(AngularerrorC5[3])
stdC5D5 = np.std(AngularerrorC5[4])
meanC5 = [meanC5D1,meanC5D2,meanC5D3,meanC5D4,meanC5D5]
stdC5 = [stdC5D1,stdC5D2,stdC5D3,stdC5D4,stdC5D5]
# Combi6 1.0,1.75,2.0
distance1 = 1.0
distance2 = 1.75
distance3 = 2.0
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Data[i][j][1], Data[i][j][1]
if Data[i][j][3] == 1.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC6[0][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Data[i][j][3] == 1.25 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC6[1][i] = Data[i][j][4]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.5 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC6[2][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.75 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC6[3][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 2.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC6[4][i] = Data[i][j][4]
break
else:
j += 1
i += 1
print "AngularerrorC6: ", AngularerrorC6[0]
print "AngularerrorC2: ", AngularerrorC6[1]
print "AngularerrorC3: ", AngularerrorC6[2]
print "AngularerrorC4: ", AngularerrorC6[3]
print "AngularerrorC5: ", AngularerrorC6[4]
meanC6D1 = np.mean(AngularerrorC6[0])
meanC6D2 = np.mean(AngularerrorC6[1])
meanC6D3 = np.mean(AngularerrorC6[2])
meanC6D4 = np.mean(AngularerrorC6[3])
meanC6D5 = np.mean(AngularerrorC6[4])
stdC6D1 = np.std(AngularerrorC6[0])
stdC6D2 = np.std(AngularerrorC6[1])
stdC6D3 = np.std(AngularerrorC6[2])
stdC6D4 = np.std(AngularerrorC6[3])
stdC6D5 = np.std(AngularerrorC6[4])
meanC6 = [meanC6D1,meanC6D2,meanC6D3,meanC6D4,meanC6D5]
stdC6 = [stdC6D1,stdC6D2,stdC6D3,stdC6D4,stdC6D5]
# Combi7 1.25,1.5,1,75
distance1 = 1.25
distance2 = 1.5
distance3 = 1.75
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Data[i][j][1], Data[i][j][1]
if Data[i][j][3] == 1.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC7[0][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Data[i][j][3] == 1.25 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC7[1][i] = Data[i][j][4]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.5 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC7[2][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.75 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC7[3][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 2.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC7[4][i] = Data[i][j][4]
break
else:
j += 1
i += 1
print "AngularerrorC7: ", AngularerrorC7[0]
print "AngularerrorC2: ", AngularerrorC7[1]
print "AngularerrorC3: ", AngularerrorC7[2]
print "AngularerrorC4: ", AngularerrorC7[3]
print "AngularerrorC5: ", AngularerrorC7[4]
meanC7D1 = np.mean(AngularerrorC7[0])
meanC7D2 = np.mean(AngularerrorC7[1])
meanC7D3 = np.mean(AngularerrorC7[2])
meanC7D4 = np.mean(AngularerrorC7[3])
meanC7D5 = np.mean(AngularerrorC7[4])
stdC7D1 = np.std(AngularerrorC7[0])
stdC7D2 = np.std(AngularerrorC7[1])
stdC7D3 = np.std(AngularerrorC7[2])
stdC7D4 = np.std(AngularerrorC7[3])
stdC7D5 = np.std(AngularerrorC7[4])
meanC7 = [meanC7D1,meanC7D2,meanC7D3,meanC7D4,meanC7D5]
stdC7 = [stdC7D1,stdC7D2,stdC7D3,stdC7D4,stdC7D5]
# Combi8 1.25,1.5,2.0
distance1 = 1.25
distance2 = 1.5
distance3 = 2.0
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Data[i][j][1], Data[i][j][1]
if Data[i][j][3] == 1.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC8[0][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Data[i][j][3] == 1.25 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC8[1][i] = Data[i][j][4]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.5 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC8[2][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.75 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC8[3][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 2.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC8[4][i] = Data[i][j][4]
break
else:
j += 1
i += 1
print "AngularerrorC8: ", AngularerrorC8[0]
print "AngularerrorC2: ", AngularerrorC8[1]
print "AngularerrorC3: ", AngularerrorC8[2]
print "AngularerrorC4: ", AngularerrorC8[3]
print "AngularerrorC5: ", AngularerrorC8[4]
meanC8D1 = np.mean(AngularerrorC8[0])
meanC8D2 = np.mean(AngularerrorC8[1])
meanC8D3 = np.mean(AngularerrorC8[2])
meanC8D4 = np.mean(AngularerrorC8[3])
meanC8D5 = np.mean(AngularerrorC8[4])
stdC8D1 = np.std(AngularerrorC8[0])
stdC8D2 = np.std(AngularerrorC8[1])
stdC8D3 = np.std(AngularerrorC8[2])
stdC8D4 = np.std(AngularerrorC8[3])
stdC8D5 = np.std(AngularerrorC8[4])
meanC8 = [meanC8D1,meanC8D2,meanC8D3,meanC8D4,meanC8D5]
stdC8 = [stdC8D1,stdC8D2,stdC8D3,stdC8D4,stdC8D5]
# Combi9 1.25,1.75,2.0
distance1 = 1.25
distance2 = 1.75
distance3 = 2.0
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Data[i][j][1], Data[i][j][1]
if Data[i][j][3] == 1.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC9[0][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Data[i][j][3] == 1.25 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC9[1][i] = Data[i][j][4]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.5 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC9[2][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.75 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC9[3][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 2.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC9[4][i] = Data[i][j][4]
break
else:
j += 1
i += 1
print "AngularerrorC9: ", AngularerrorC9[0]
print "AngularerrorC2: ", AngularerrorC9[1]
print "AngularerrorC3: ", AngularerrorC9[2]
print "AngularerrorC4: ", AngularerrorC9[3]
print "AngularerrorC5: ", AngularerrorC9[4]
meanC9D1 = np.mean(AngularerrorC9[0])
meanC9D2 = np.mean(AngularerrorC9[1])
meanC9D3 = np.mean(AngularerrorC9[2])
meanC9D4 = np.mean(AngularerrorC9[3])
meanC9D5 = np.mean(AngularerrorC9[4])
stdC9D1 = np.std(AngularerrorC9[0])
stdC9D2 = np.std(AngularerrorC9[1])
stdC9D3 = np.std(AngularerrorC9[2])
stdC9D4 = np.std(AngularerrorC9[3])
stdC9D5 = np.std(AngularerrorC9[4])
meanC9 = [meanC9D1,meanC9D2,meanC9D3,meanC9D4,meanC9D5]
stdC9 = [stdC9D1,stdC9D2,stdC9D3,stdC9D4,stdC9D5]
# Combi10 1.5,1.75,2.0
distance1 = 1.5
distance2 = 1.75
distance3 = 2.0
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Data[i][j][1], Data[i][j][1]
if Data[i][j][3] == 1.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC10[0][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Data[i][j][3] == 1.25 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC10[1][i] = Data[i][j][4]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.5 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC10[2][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 1.75 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC10[3][i] = Data[i][j][4]
break
else:
j += 1
j = 0
while j < 50:
if Data[i][j][3] == 2.0 and Data[i][j][0] == distance1 and Data[i][j][1] == distance2 and Data[i][j][2] == distance3 :
AngularerrorC10[4][i] = Data[i][j][4]
break
else:
j += 1
i += 1
print "AngularerrorC10: ", AngularerrorC10[0]
print "AngularerrorC2: ", AngularerrorC10[1]
print "AngularerrorC3: ", AngularerrorC10[2]
print "AngularerrorC4: ", AngularerrorC10[3]
print "AngularerrorC5: ", AngularerrorC10[4]
meanC10D1 = np.mean(AngularerrorC10[0])
meanC10D2 = np.mean(AngularerrorC10[1])
meanC10D3 = np.mean(AngularerrorC10[2])
meanC10D4 = np.mean(AngularerrorC10[3])
meanC10D5 = np.mean(AngularerrorC10[4])
stdC10D1 = np.std(AngularerrorC10[0])
stdC10D2 = np.std(AngularerrorC10[1])
stdC10D3 = np.std(AngularerrorC10[2])
stdC10D4 = np.std(AngularerrorC10[3])
stdC10D5 = np.std(AngularerrorC10[4])
meanC10 = [meanC10D1,meanC10D2,meanC10D3,meanC10D4,meanC10D5]
stdC10 = [stdC10D1,stdC10D2,stdC10D3,stdC10D4,stdC10D5]
#####################################################################################
path ="/home/mmbrian/3D_Gaze_Tracking/work/results/2D2D/3_calibration_depths/"
Datatwo1 = np.load(path + "p5.npy")
Datatwo2 = np.load(path + "p7.npy")
Datatwo3 = np.load(path + "p10.npy")
Datatwo4 = np.load(path + "p11.npy")
Datatwo5 = np.load(path + "p12.npy")
Datatwo6 = np.load(path + "p13.npy")
Datatwo7 = np.load(path + "p14.npy")
Datatwo8 = np.load(path + "p15.npy")
Datatwo9 = np.load(path + "p16.npy")
Datatwo10 = np.load(path + "p20.npy")
Datatwo11 = np.load(path + "p21.npy")
Datatwo12 = np.load(path + "p24.npy")
Datatwo13 = np.load(path + "p25.npy")
Datatwo14 = np.load(path + "p26.npy")
Datatwo = [Datatwo1,Datatwo2,Datatwo3,Datatwo4,Datatwo5,Datatwo6,Datatwo7,Datatwo8,Datatwo9,Datatwo10,Datatwo11,Datatwo12,Datatwo13,Datatwo14]
AngularerrorCtwo1 = []
for i in xrange(5):
AngularerrorCtwo1.append([])
for j in xrange(14):
AngularerrorCtwo1[i].append(float(0))
AngularerrorCtwo2 = []
for i in xrange(5):
AngularerrorCtwo2.append([])
for j in xrange(14):
AngularerrorCtwo2[i].append(float(0))
AngularerrorCtwo3 = []
for i in xrange(5):
AngularerrorCtwo3.append([])
for j in xrange(14):
AngularerrorCtwo3[i].append(float(0))
AngularerrorCtwo4 = []
for i in xrange(5):
AngularerrorCtwo4.append([])
for j in xrange(14):
AngularerrorCtwo4[i].append(float(0))
AngularerrorCtwo5 = []
for i in xrange(5):
AngularerrorCtwo5.append([])
for j in xrange(14):
AngularerrorCtwo5[i].append(float(0))
AngularerrorCtwo6 = []
for i in xrange(5):
AngularerrorCtwo6.append([])
for j in xrange(14):
AngularerrorCtwo6[i].append(float(0))
AngularerrorCtwo7 = []
for i in xrange(5):
AngularerrorCtwo7.append([])
for j in xrange(14):
AngularerrorCtwo7[i].append(float(0))
AngularerrorCtwo8 = []
for i in xrange(5):
AngularerrorCtwo8.append([])
for j in xrange(14):
AngularerrorCtwo8[i].append(float(0))
AngularerrorCtwo9 = []
for i in xrange(5):
AngularerrorCtwo9.append([])
for j in xrange(14):
AngularerrorCtwo9[i].append(float(0))
AngularerrorCtwo10 = []
for i in xrange(5):
AngularerrorCtwo10.append([])
for j in xrange(14):
AngularerrorCtwo10[i].append(float(0))
# Combi1 1,1.25,1.5
distance1 = 1.0
distance2 = 1.25
distance3 = 1.5
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Datatwo[i][j][1], Datatwo[i][j][1]
if Datatwo[i][j][3] == 1.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3:
AngularerrorCtwo1[0][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Datatwo[i][j][3] == 1.25 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3:
AngularerrorCtwo1[1][i] = Datatwo[i][j][9]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.5 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3:
AngularerrorCtwo1[2][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.75 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3:
AngularerrorCtwo1[3][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 2.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3:
AngularerrorCtwo1[4][i] = Datatwo[i][j][9]
break
else:
j += 1
i += 1
print "AngularerrorCtwo1: ", AngularerrorCtwo1[0]
print "AngularerrorCtwo2: ", AngularerrorCtwo1[1]
print "AngularerrorCtwo3: ", AngularerrorCtwo1[2]
print "AngularerrorCtwo4: ", AngularerrorCtwo1[3]
print "AngularerrorCtwo5: ", AngularerrorCtwo1[4]
meantwoC1D1 = np.mean(AngularerrorCtwo1[0])
meantwoC1D2 = np.mean(AngularerrorCtwo1[1])
meantwoC1D3 = np.mean(AngularerrorCtwo1[2])
meantwoC1D4 = np.mean(AngularerrorCtwo1[3])
meantwoC1D5 = np.mean(AngularerrorCtwo1[4])
stdtwoC1D1 = np.std(AngularerrorCtwo1[0])
stdtwoC1D2 = np.std(AngularerrorCtwo1[1])
stdtwoC1D3 = np.std(AngularerrorCtwo1[2])
stdtwoC1D4 = np.std(AngularerrorCtwo1[3])
stdtwoC1D5 = np.std(AngularerrorCtwo1[4])
meantwoC1 = [meantwoC1D1,meantwoC1D2,meantwoC1D3,meantwoC1D4,meantwoC1D5]
stdtwoC1 = [stdtwoC1D1,stdtwoC1D2,stdtwoC1D3,stdtwoC1D4,stdtwoC1D5]
# Combi2 1,1.25,1.75
distance1 = 1.0
distance2 = 1.25
distance3 = 1.75
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Datatwo[i][j][1], Datatwo[i][j][1]
if Datatwo[i][j][3] == 1.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo2[0][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Datatwo[i][j][3] == 1.25 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo2[1][i] = Datatwo[i][j][9]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.5 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo2[2][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.75 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo2[3][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 2.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo2[4][i] = Datatwo[i][j][9]
break
else:
j += 1
i += 1
print "AngularerrorCtwo1: ", AngularerrorCtwo2[0]
print "AngularerrorCtwo2: ", AngularerrorCtwo2[1]
print "AngularerrorCtwo3: ", AngularerrorCtwo2[2]
print "AngularerrorCtwo4: ", AngularerrorCtwo2[3]
print "AngularerrorCtwo5: ", AngularerrorCtwo2[4]
meantwoC2D1 = np.mean(AngularerrorCtwo2[0])
meantwoC2D2 = np.mean(AngularerrorCtwo2[1])
meantwoC2D3 = np.mean(AngularerrorCtwo2[2])
meantwoC2D4 = np.mean(AngularerrorCtwo2[3])
meantwoC2D5 = np.mean(AngularerrorCtwo2[4])
stdtwoC2D1 = np.std(AngularerrorCtwo2[0])
stdtwoC2D2 = np.std(AngularerrorCtwo2[1])
stdtwoC2D3 = np.std(AngularerrorCtwo2[2])
stdtwoC2D4 = np.std(AngularerrorCtwo2[3])
stdtwoC2D5 = np.std(AngularerrorCtwo2[4])
meantwoC2 = [meantwoC2D1,meantwoC2D2,meantwoC2D3,meantwoC2D4,meantwoC2D5]
stdtwoC2 = [stdtwoC2D1,stdtwoC2D2,stdtwoC2D3,stdtwoC2D4,stdtwoC2D5]
# Combi3 1,1.25,2.0
distance1 = 1.0
distance2 = 1.25
distance3 = 2.0
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Datatwo[i][j][1], Datatwo[i][j][1]
if Datatwo[i][j][3] == 1.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo3[0][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Datatwo[i][j][3] == 1.25 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo3[1][i] = Datatwo[i][j][9]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.5 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo3[2][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.75 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo3[3][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 2.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo3[4][i] = Datatwo[i][j][9]
break
else:
j += 1
i += 1
print "AngularerrorCtwo1: ", AngularerrorCtwo3[0]
print "AngularerrorCtwo2: ", AngularerrorCtwo3[1]
print "AngularerrorCtwo3: ", AngularerrorCtwo3[2]
print "AngularerrorCtwo4: ", AngularerrorCtwo3[3]
print "AngularerrorCtwo5: ", AngularerrorCtwo3[4]
meantwoC3D1 = np.mean(AngularerrorCtwo3[0])
meantwoC3D2 = np.mean(AngularerrorCtwo3[1])
meantwoC3D3 = np.mean(AngularerrorCtwo3[2])
meantwoC3D4 = np.mean(AngularerrorCtwo3[3])
meantwoC3D5 = np.mean(AngularerrorCtwo3[4])
stdtwoC3D1 = np.std(AngularerrorCtwo3[0])
stdtwoC3D2 = np.std(AngularerrorCtwo3[1])
stdtwoC3D3 = np.std(AngularerrorCtwo3[2])
stdtwoC3D4 = np.std(AngularerrorCtwo3[3])
stdtwoC3D5 = np.std(AngularerrorCtwo3[4])
meantwoC3 = [meantwoC3D1,meantwoC3D2,meantwoC3D3,meantwoC3D4,meantwoC3D5]
stdtwoC3 = [stdtwoC3D1,stdtwoC3D2,stdtwoC3D3,stdtwoC3D4,stdtwoC3D5]
# Combi4 1,1.5,1.75
distance1 = 1.0
distance2 = 1.5
distance3 = 1.75
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Datatwo[i][j][1], Datatwo[i][j][1]
if Datatwo[i][j][3] == 1.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo4[0][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Datatwo[i][j][3] == 1.25 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo4[1][i] = Datatwo[i][j][9]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.5 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo4[2][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.75 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo4[3][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 2.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo4[4][i] = Datatwo[i][j][9]
break
else:
j += 1
i += 1
print "AngularerrorCtwo4: ", AngularerrorCtwo4[0]
print "AngularerrorCtwo2: ", AngularerrorCtwo4[1]
print "AngularerrorCtwo3: ", AngularerrorCtwo4[2]
print "AngularerrorCtwo4: ", AngularerrorCtwo4[3]
print "AngularerrorCtwo5: ", AngularerrorCtwo4[4]
meantwoC4D1 = np.mean(AngularerrorCtwo4[0])
meantwoC4D2 = np.mean(AngularerrorCtwo4[1])
meantwoC4D3 = np.mean(AngularerrorCtwo4[2])
meantwoC4D4 = np.mean(AngularerrorCtwo4[3])
meantwoC4D5 = np.mean(AngularerrorCtwo4[4])
stdtwoC4D1 = np.std(AngularerrorCtwo4[0])
stdtwoC4D2 = np.std(AngularerrorCtwo4[1])
stdtwoC4D3 = np.std(AngularerrorCtwo4[2])
stdtwoC4D4 = np.std(AngularerrorCtwo4[3])
stdtwoC4D5 = np.std(AngularerrorCtwo4[4])
meantwoC4 = [meantwoC4D1,meantwoC4D2,meantwoC4D3,meantwoC4D4,meantwoC4D5]
stdtwoC4 = [stdtwoC4D1,stdtwoC4D2,stdtwoC4D3,stdtwoC4D4,stdtwoC4D5]
# Combi5 1.0,1.5,2.0
distance1 = 1.0
distance2 = 1.5
distance3 = 2.0
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Datatwo[i][j][1], Datatwo[i][j][1]
if Datatwo[i][j][3] == 1.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo5[0][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Datatwo[i][j][3] == 1.25 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo5[1][i] = Datatwo[i][j][9]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.5 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo5[2][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.75 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo5[3][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 2.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo5[4][i] = Datatwo[i][j][9]
break
else:
j += 1
i += 1
print "AngularerrorCtwo5: ", AngularerrorCtwo5[0]
print "AngularerrorCtwo2: ", AngularerrorCtwo5[1]
print "AngularerrorCtwo3: ", AngularerrorCtwo5[2]
print "AngularerrorCtwo4: ", AngularerrorCtwo5[3]
print "AngularerrorCtwo5: ", AngularerrorCtwo5[4]
meantwoC5D1 = np.mean(AngularerrorCtwo5[0])
meantwoC5D2 = np.mean(AngularerrorCtwo5[1])
meantwoC5D3 = np.mean(AngularerrorCtwo5[2])
meantwoC5D4 = np.mean(AngularerrorCtwo5[3])
meantwoC5D5 = np.mean(AngularerrorCtwo5[4])
stdtwoC5D1 = np.std(AngularerrorCtwo5[0])
stdtwoC5D2 = np.std(AngularerrorCtwo5[1])
stdtwoC5D3 = np.std(AngularerrorCtwo5[2])
stdtwoC5D4 = np.std(AngularerrorCtwo5[3])
stdtwoC5D5 = np.std(AngularerrorCtwo5[4])
meantwoC5 = [meantwoC5D1,meantwoC5D2,meantwoC5D3,meantwoC5D4,meantwoC5D5]
stdtwoC5 = [stdtwoC5D1,stdtwoC5D2,stdtwoC5D3,stdtwoC5D4,stdtwoC5D5]
# Combi6 1.0,1.75,2.0
distance1 = 1.0
distance2 = 1.75
distance3 = 2.0
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Datatwo[i][j][1], Datatwo[i][j][1]
if Datatwo[i][j][3] == 1.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo6[0][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Datatwo[i][j][3] == 1.25 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo6[1][i] = Datatwo[i][j][9]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.5 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo6[2][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.75 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo6[3][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 2.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo6[4][i] = Datatwo[i][j][9]
break
else:
j += 1
i += 1
print "AngularerrorCtwo6: ", AngularerrorCtwo6[0]
print "AngularerrorCtwo2: ", AngularerrorCtwo6[1]
print "AngularerrorCtwo3: ", AngularerrorCtwo6[2]
print "AngularerrorCtwo4: ", AngularerrorCtwo6[3]
print "AngularerrorCtwo5: ", AngularerrorCtwo6[4]
meantwoC6D1 = np.mean(AngularerrorCtwo6[0])
meantwoC6D2 = np.mean(AngularerrorCtwo6[1])
meantwoC6D3 = np.mean(AngularerrorCtwo6[2])
meantwoC6D4 = np.mean(AngularerrorCtwo6[3])
meantwoC6D5 = np.mean(AngularerrorCtwo6[4])
stdtwoC6D1 = np.std(AngularerrorCtwo6[0])
stdtwoC6D2 = np.std(AngularerrorCtwo6[1])
stdtwoC6D3 = np.std(AngularerrorCtwo6[2])
stdtwoC6D4 = np.std(AngularerrorCtwo6[3])
stdtwoC6D5 = np.std(AngularerrorCtwo6[4])
meantwoC6 = [meantwoC6D1,meantwoC6D2,meantwoC6D3,meantwoC6D4,meantwoC6D5]
stdtwoC6 = [stdtwoC6D1,stdtwoC6D2,stdtwoC6D3,stdtwoC6D4,stdtwoC6D5]
# Combi7 1.25,1.5,1,75
distance1 = 1.25
distance2 = 1.5
distance3 = 1.75
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Datatwo[i][j][1], Datatwo[i][j][1]
if Datatwo[i][j][3] == 1.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo7[0][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Datatwo[i][j][3] == 1.25 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo7[1][i] = Datatwo[i][j][9]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.5 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo7[2][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.75 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo7[3][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 2.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo7[4][i] = Datatwo[i][j][9]
break
else:
j += 1
i += 1
print "AngularerrorCtwo7: ", AngularerrorCtwo7[0]
print "AngularerrorCtwo2: ", AngularerrorCtwo7[1]
print "AngularerrorCtwo3: ", AngularerrorCtwo7[2]
print "AngularerrorCtwo4: ", AngularerrorCtwo7[3]
print "AngularerrorCtwo5: ", AngularerrorCtwo7[4]
meantwoC7D1 = np.mean(AngularerrorCtwo7[0])
meantwoC7D2 = np.mean(AngularerrorCtwo7[1])
meantwoC7D3 = np.mean(AngularerrorCtwo7[2])
meantwoC7D4 = np.mean(AngularerrorCtwo7[3])
meantwoC7D5 = np.mean(AngularerrorCtwo7[4])
stdtwoC7D1 = np.std(AngularerrorCtwo7[0])
stdtwoC7D2 = np.std(AngularerrorCtwo7[1])
stdtwoC7D3 = np.std(AngularerrorCtwo7[2])
stdtwoC7D4 = np.std(AngularerrorCtwo7[3])
stdtwoC7D5 = np.std(AngularerrorCtwo7[4])
meantwoC7 = [meantwoC7D1,meantwoC7D2,meantwoC7D3,meantwoC7D4,meantwoC7D5]
stdtwoC7 = [stdtwoC7D1,stdtwoC7D2,stdtwoC7D3,stdtwoC7D4,stdtwoC7D5]
# Combi8 1.25,1.5,2.0
distance1 = 1.25
distance2 = 1.5
distance3 = 2.0
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Datatwo[i][j][1], Datatwo[i][j][1]
if Datatwo[i][j][3] == 1.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo8[0][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Datatwo[i][j][3] == 1.25 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo8[1][i] = Datatwo[i][j][9]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.5 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo8[2][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.75 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo8[3][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 2.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo8[4][i] = Datatwo[i][j][9]
break
else:
j += 1
i += 1
print "AngularerrorCtwo8: ", AngularerrorCtwo8[0]
print "AngularerrorCtwo2: ", AngularerrorCtwo8[1]
print "AngularerrorCtwo3: ", AngularerrorCtwo8[2]
print "AngularerrorCtwo4: ", AngularerrorCtwo8[3]
print "AngularerrorCtwo5: ", AngularerrorCtwo8[4]
meantwoC8D1 = np.mean(AngularerrorCtwo8[0])
meantwoC8D2 = np.mean(AngularerrorCtwo8[1])
meantwoC8D3 = np.mean(AngularerrorCtwo8[2])
meantwoC8D4 = np.mean(AngularerrorCtwo8[3])
meantwoC8D5 = np.mean(AngularerrorCtwo8[4])
stdtwoC8D1 = np.std(AngularerrorCtwo8[0])
stdtwoC8D2 = np.std(AngularerrorCtwo8[1])
stdtwoC8D3 = np.std(AngularerrorCtwo8[2])
stdtwoC8D4 = np.std(AngularerrorCtwo8[3])
stdtwoC8D5 = np.std(AngularerrorCtwo8[4])
meantwoC8 = [meantwoC8D1,meantwoC8D2,meantwoC8D3,meantwoC8D4,meantwoC8D5]
stdtwoC8 = [stdtwoC8D1,stdtwoC8D2,stdtwoC8D3,stdtwoC8D4,stdtwoC8D5]
# Combi9 1.25,1.75,2.0
distance1 = 1.25
distance2 = 1.75
distance3 = 2.0
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Datatwo[i][j][1], Datatwo[i][j][1]
if Datatwo[i][j][3] == 1.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo9[0][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Datatwo[i][j][3] == 1.25 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo9[1][i] = Datatwo[i][j][9]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.5 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo9[2][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.75 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo9[3][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 2.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo9[4][i] = Datatwo[i][j][9]
break
else:
j += 1
i += 1
print "AngularerrorCtwo9: ", AngularerrorCtwo9[0]
print "AngularerrorCtwo2: ", AngularerrorCtwo9[1]
print "AngularerrorCtwo3: ", AngularerrorCtwo9[2]
print "AngularerrorCtwo4: ", AngularerrorCtwo9[3]
print "AngularerrorCtwo5: ", AngularerrorCtwo9[4]
meantwoC9D1 = np.mean(AngularerrorCtwo9[0])
meantwoC9D2 = np.mean(AngularerrorCtwo9[1])
meantwoC9D3 = np.mean(AngularerrorCtwo9[2])
meantwoC9D4 = np.mean(AngularerrorCtwo9[3])
meantwoC9D5 = np.mean(AngularerrorCtwo9[4])
stdtwoC9D1 = np.std(AngularerrorCtwo9[0])
stdtwoC9D2 = np.std(AngularerrorCtwo9[1])
stdtwoC9D3 = np.std(AngularerrorCtwo9[2])
stdtwoC9D4 = np.std(AngularerrorCtwo9[3])
stdtwoC9D5 = np.std(AngularerrorCtwo9[4])
meantwoC9 = [meantwoC9D1,meantwoC9D2,meantwoC9D3,meantwoC9D4,meantwoC9D5]
stdtwoC9 = [stdtwoC9D1,stdtwoC9D2,stdtwoC9D3,stdtwoC9D4,stdtwoC9D5]
# Combi10 1.5,1.75,2.0
distance1 = 1.5
distance2 = 1.75
distance3 = 2.0
i = 0
while i < 14:
j = 0
while j < 50:
# print "i: ", i," j: ", j
# print Datatwo[i][j][1], Datatwo[i][j][1]
if Datatwo[i][j][3] == 1.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo10[0][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
# print "i: ", i," j: ", j
if Datatwo[i][j][3] == 1.25 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo10[1][i] = Datatwo[i][j][9]
# i = 14
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.5 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo10[2][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 1.75 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo10[3][i] = Datatwo[i][j][9]
break
else:
j += 1
j = 0
while j < 50:
if Datatwo[i][j][3] == 2.0 and Datatwo[i][j][0] == distance1 and Datatwo[i][j][1] == distance2 and Datatwo[i][j][2] == distance3 :
AngularerrorCtwo10[4][i] = Datatwo[i][j][9]
break
else:
j += 1
i += 1
print "AngularerrorCtwo10: ", AngularerrorCtwo10[0]
print "AngularerrorCtwo2: ", AngularerrorCtwo10[1]
print "AngularerrorCtwo3: ", AngularerrorCtwo10[2]
print "AngularerrorCtwo4: ", AngularerrorCtwo10[3]
print "AngularerrorCtwo5: ", AngularerrorCtwo10[4]
meantwoC10D1 = np.mean(AngularerrorCtwo10[0])
meantwoC10D2 = np.mean(AngularerrorCtwo10[1])
meantwoC10D3 = np.mean(AngularerrorCtwo10[2])
meantwoC10D4 = np.mean(AngularerrorCtwo10[3])
meantwoC10D5 = np.mean(AngularerrorCtwo10[4])
stdtwoC10D1 = np.std(AngularerrorCtwo10[0])
stdtwoC10D2 = np.std(AngularerrorCtwo10[1])
stdtwoC10D3 = np.std(AngularerrorCtwo10[2])
stdtwoC10D4 = np.std(AngularerrorCtwo10[3])
stdtwoC10D5 = np.std(AngularerrorCtwo10[4])
meantwoC10 = [meantwoC10D1,meantwoC10D2,meantwoC10D3,meantwoC10D4,meantwoC10D5]
stdtwoC10 = [stdtwoC10D1,stdtwoC10D2,stdtwoC10D3,stdtwoC10D4,stdtwoC10D5]
#####################################################################################
## C2
# distance = 1.25
# i = 0
# while i < 14:
# j = 0
# while j < 25:
# if Datatwo[i][j][1] == 1.0 and Data[i][j][0] == distance:
# AngularerrorC2[0][i] = Data[i][j][7]
# break
# else:
# j += 1
# j = 0
# while j < 25:
# print "i: ", i," j: ", j
# if Data[i][j][1] == 1.25 and Data[i][j][0] == distance:
# print Data[i][j][7]
# AngularerrorC2[1][i] = Data[i][j][7]
# break
# else:
# j += 1
# j = 0
# while j < 25:
# if Data[i][j][1] == 1.5 and Data[i][j][0] == distance:
# AngularerrorC2[2][i] = Data[i][j][7]
# j = 25
# else:
# j += 1
# j = 0
# while j < 25:
# if Data[i][j][1] == 1.75 and Data[i][j][0] == distance:
# AngularerrorC2[3][i] = Data[i][j][7]
# j = 25
# else:
# j += 1
# j = 0
# while j < 25:
# if Data[i][j][1] == 2.0 and Data[i][j][0] == distance:
# AngularerrorC2[4][i] = Data[i][j][7]
# j = 25
# else:
# j += 1
# i += 1
# print "AngularerrorC2: ", AngularerrorC2[0]
# print "AngularerrorC2: ", AngularerrorC2[1]
# print "AngularerrorC2: ", AngularerrorC2[2]
# print "AngularerrorC2: ", AngularerrorC2[3]
# print "AngularerrorC2: ", AngularerrorC2[4]
# meanC2D1 = np.mean(AngularerrorC2[0])
# meanC2D2 = np.mean(AngularerrorC2[1])
# meanC2D3 = np.mean(AngularerrorC2[2])
# meanC2D4 = np.mean(AngularerrorC2[3])
# meanC2D5 = np.mean(AngularerrorC2[4])
# stdC2D1 = np.std(AngularerrorC2[0])
# stdC2D2 = np.std(AngularerrorC2[1])
# stdC2D3 = np.std(AngularerrorC2[2])
# stdC2D4 = np.std(AngularerrorC2[3])
# stdC2D5 = np.std(AngularerrorC2[4])
#
# meanC2 = [meanC2D1,meanC2D2,meanC2D3,meanC2D4,meanC2D5]
# stdC2 = [stdC2D1,stdC2D2,stdC2D3,stdC2D4,stdC2D5]
## C3
# distance = 1.5
# i = 0
# while i < 14:
# j = 0
# while j < 25:
# if Data[i][j][1] == 1.0 and Data[i][j][0] == distance:
# AngularerrorC3[0][i] = Data[i][j][7]
# break
# else:
# j += 1
# j = 0
# while j < 25:
# print "i: ", i," j: ", j
# if Data[i][j][1] == 1.25 and Data[i][j][0] == distance:
# print Data[i][j][7]
# AngularerrorC3[1][i] = Data[i][j][7]
# break
# else:
# j += 1
# j = 0
# while j < 25:
# if Data[i][j][1] == 1.5 and Data[i][j][0] == distance:
# AngularerrorC3[2][i] = Data[i][j][7]
# j = 25
# else:
# j += 1
# j = 0
# while j < 25:
# if Data[i][j][1] == 1.75 and Data[i][j][0] == distance:
# AngularerrorC3[3][i] = Data[i][j][7]
# j = 25
# else:
# j += 1
# j = 0
# while j < 25:
# if Data[i][j][1] == 2.0 and Data[i][j][0] == distance:
# AngularerrorC3[4][i] = Data[i][j][7]
# j = 25
# else:
# j += 1
# i += 1
# print "AngularerrorC3: ", AngularerrorC3[0]
# print "AngularerrorC3: ", AngularerrorC3[1]
# print "AngularerrorC3: ", AngularerrorC3[2]
# print "AngularerrorC3: ", AngularerrorC3[3]
# print "AngularerrorC3: ", AngularerrorC3[4]
# meanC3D1 = np.mean(AngularerrorC3[0])
# meanC3D2 = np.mean(AngularerrorC3[1])
# meanC3D3 = np.mean(AngularerrorC3[2])
# meanC3D4 = np.mean(AngularerrorC3[3])
# meanC3D5 = np.mean(AngularerrorC3[4])
# stdC3D1 = np.std(AngularerrorC3[0])
# stdC3D2 = np.std(AngularerrorC3[1])
# stdC3D3 = np.std(AngularerrorC3[2])
# stdC3D4 = np.std(AngularerrorC3[3])
# stdC3D5 = np.std(AngularerrorC3[4])
#
# meanC3 = [meanC3D1,meanC3D2,meanC3D3,meanC3D4,meanC3D5]
# stdC3 = [stdC3D1,stdC3D2,stdC3D3,stdC3D4,stdC3D5]
## C4
# distance = 1.75
# i = 0
# while i < 14:
# j = 0
# while j < 25:
# if Data[i][j][1] == 1.0 and Data[i][j][0] == distance:
# AngularerrorC4[0][i] = Data[i][j][7]
# break
# else:
# j += 1
# j = 0
# while j < 25:
# print "i: ", i," j: ", j
# if Data[i][j][1] == 1.25 and Data[i][j][0] == distance:
# print Data[i][j][7]
# AngularerrorC4[1][i] = Data[i][j][7]
# break
# else:
# j += 1
# j = 0
# while j < 25:
# if Data[i][j][1] == 1.5 and Data[i][j][0] == distance:
# AngularerrorC4[2][i] = Data[i][j][7]
# j = 25
# else:
# j += 1
# j = 0
# while j < 25:
# if Data[i][j][1] == 1.75 and Data[i][j][0] == distance:
# AngularerrorC4[3][i] = Data[i][j][7]
# j = 25
# else:
# j += 1
# j = 0
# while j < 25:
# if Data[i][j][1] == 2.0 and Data[i][j][0] == distance:
# AngularerrorC4[4][i] = Data[i][j][7]
# j = 25
# else:
# j += 1
# i += 1
# print "AngularerrorC4: ", AngularerrorC4[0]
# print "AngularerrorC4: ", AngularerrorC4[1]
# print "AngularerrorC4: ", AngularerrorC4[2]
# print "AngularerrorC4: ", AngularerrorC4[3]
# print "AngularerrorC4: ", AngularerrorC4[4]
# meanC4D1 = np.mean(AngularerrorC4[0])
# meanC4D2 = np.mean(AngularerrorC4[1])
# meanC4D3 = np.mean(AngularerrorC4[2])
# meanC4D4 = np.mean(AngularerrorC4[3])
# meanC4D5 = np.mean(AngularerrorC4[4])
# stdC4D1 = np.std(AngularerrorC4[0])
# stdC4D2 = np.std(AngularerrorC4[1])
# stdC4D3 = np.std(AngularerrorC4[2])
# stdC4D4 = np.std(AngularerrorC4[3])
# stdC4D5 = np.std(AngularerrorC4[4])
#
# meanC4 = [meanC4D1,meanC4D2,meanC4D3,meanC4D4,meanC4D5]
# stdC4 = [stdC4D1,stdC4D2,stdC4D3,stdC4D4,stdC4D5]
## C5
# distance = 2.0
# i = 0
# while i < 14:
# j = 0
# while j < 25:
# if Data[i][j][1] == 1.0 and Data[i][j][0] == distance:
# AngularerrorC5[0][i] = Data[i][j][7]
# break
# else:
# j += 1
# j = 0
# while j < 25:
# print "i: ", i," j: ", j
# if Data[i][j][1] == 1.25 and Data[i][j][0] == distance:
# print Data[i][j][7]
# AngularerrorC5[1][i] = Data[i][j][7]
# break
# else:
# j += 1
# j = 0
# while j < 25:
# if Data[i][j][1] == 1.5 and Data[i][j][0] == distance:
# AngularerrorC5[2][i] = Data[i][j][7]
# j = 25
# else:
# j += 1
# j = 0
# while j < 25:
# if Data[i][j][1] == 1.75 and Data[i][j][0] == distance:
# AngularerrorC5[3][i] = Data[i][j][7]
# j = 25
# else:
# j += 1
# j = 0
# while j < 25:
# if Data[i][j][1] == 2.0 and Data[i][j][0] == distance:
# AngularerrorC5[4][i] = Data[i][j][7]
# j = 25
# else:
# j += 1
# i += 1
# print "AngularerrorC5: ", AngularerrorC5[0]
# print "AngularerrorC5: ", AngularerrorC5[1]
# print "AngularerrorC5: ", AngularerrorC5[2]
# print "AngularerrorC5: ", AngularerrorC5[3]
# print "AngularerrorC5: ", AngularerrorC5[4]
# meanC5D1 = np.mean(AngularerrorC5[0])
# meanC5D2 = np.mean(AngularerrorC5[1])
# meanC5D3 = np.mean(AngularerrorC5[2])
# meanC5D4 = np.mean(AngularerrorC5[3])
# meanC5D5 = np.mean(AngularerrorC5[4])
# stdC5D1 = np.std(AngularerrorC5[0])
# stdC5D2 = np.std(AngularerrorC5[1])
# stdC5D3 = np.std(AngularerrorC5[2])
# stdC5D4 = np.std(AngularerrorC5[3])
# stdC5D5 = np.std(AngularerrorC5[4])
#
# meanC5 = [meanC5D1,meanC5D2,meanC5D3,meanC5D4,meanC5D5]
# stdC5 = [stdC5D1,stdC5D2,stdC5D3,stdC5D4,stdC5D5]
N = 5
ind = np.asarray([0.25,1.25,2.25,3.25,4.25])
width = 0.5 # the width of the bars
# x1 = [0.275,1.275,2.275,3.275,4.275]
# x2 = [0.325,1.325,2.325,3.325,4.325]
x1 = [0.375,1.375,2.375,3.375,4.375]
x2 = [0.425,1.425,2.425,3.425,4.425]
x3 = [0.475,1.475,2.475,3.475,4.475]
x4 = [0.525,1.525,2.525,3.525,4.525]
x5 = [0.575,1.575,2.575,3.575,4.575]
x6 = [0.625,1.625,2.625,3.625,4.625]
# x9 = [0.675,1.675,2.675,3.675,4.675]
# x10 = [0.725,1.725,2.725,3.725,4.725]
# x1 = [0.4,1.4,2.4,3.4,4.4]
# x2 = [0.45,1.45,2.45,3.45,4.45]
# x3 = [0.5,1.5,2.5,3.5,4.5]
# x4 = [0.55,1.55,2.55,3.55,4.55]
# x5 = [0.6,1.6,2.6,3.6,4.6]
fig = plt.figure(figsize=(14.0, 10.0))
ax = fig.add_subplot(111)
# rects1 = ax.bar(ind, Participantmean,width, color='r',edgecolor='black',)#, hatch='//')
rects1 = ax.errorbar(x1, meantwoC1,yerr=[stdtwoC1,stdtwoC1],fmt='o',color='blue',ecolor='blue',lw=3, capsize=5, capthick=2)
plt.plot(x1, meantwoC1, marker="o", linestyle='-',lw=3,color='blue',label = r'2D-to-2D Calibration Depth 1 + 2 + 3')
# rects2 =ax.errorbar(x2, meantwoC2,yerr=[stdtwoC2,stdtwoC2],fmt='o',color='red',ecolor='red',lw=3, capsize=5, capthick=2)
# plt.plot(x2, meantwoC2, marker="o", linestyle='-',lw=3,color='red')
#
# rects3 = ax.errorbar(x3, meantwoC3,yerr=[stdtwoC3,stdtwoC3],fmt='o',color='black',ecolor='black',lw=3, capsize=5, capthick=2)
# plt.plot(x3, meantwoC3, marker="o", linestyle='-',lw=3,color='black')
# rects4 =ax.errorbar(x4, meantwoC4,yerr=[stdtwoC4,stdtwoC4],fmt='o',color='green',ecolor='green',lw=3, capsize=5, capthick=2)
# plt.plot(x4, meantwoC4, marker="o", linestyle='-',lw=3,color='green')
# rects5 =ax.errorbar(x5, meantwoC5,yerr=[stdtwoC5,stdtwoC5],fmt='o',color='orange',ecolor='orange',lw=3, capsize=5, capthick=2)
# plt.plot(x5, meantwoC5, marker="o", linestyle='-',lw=3,color='orange')
#
# rects6 =ax.errorbar(x6, meantwoC6,yerr=[stdtwoC6,stdtwoC6],fmt='o',color='cyan',ecolor='cyan',lw=3, capsize=5, capthick=2)
# plt.plot(x6, meantwoC6, marker="o", linestyle='-',lw=3,color='cyan')
rects3 =ax.errorbar(x3, meantwoC7,yerr=[stdtwoC7,stdtwoC7],fmt='o',color='red',ecolor='red',lw=3, capsize=5, capthick=2)
plt.plot(x3, meantwoC7, marker="o", linestyle='-',lw=3,color='red',label = r'2D-to-2D Calibration Depth 2 + 3 + 4')
#
# rects8 =ax.errorbar(x8, meantwoC8,yerr=[stdtwoC8,stdtwoC8],fmt='o',color='darkviolet',ecolor='darkviolet',lw=3, capsize=5, capthick=2)
# plt.plot(x8, meantwoC8, marker="o", linestyle='-',lw=3,color='darkviolet')
#
# rects9 =ax.errorbar(x9, meantwoC9,yerr=[stdtwoC9,stdtwoC9],fmt='o',color='lime',ecolor='lime',lw=3, capsize=5, capthick=2)
# plt.plot(x9, meantwoC9, marker="o", linestyle='-',lw=3,color='lime')
rects5 =ax.errorbar(x5, meantwoC10,yerr=[stdtwoC10,stdtwoC10],fmt='o',color='orange',ecolor='orange',lw=3, capsize=5, capthick=2)
plt.plot(x5, meantwoC10, marker="o", linestyle='-',lw=3,color='orange',label = r'2D-to-2D Calibration Depth 3 + 4 + 5')
# rects1 = ax.bar(ind, Participantmean,width, color='r',edgecolor='black',)#, hatch='//')
rects2 = ax.errorbar(x2, meanC1,yerr=[stdC1,stdC1],fmt='o',color='blue',ecolor='blue',lw=3, capsize=5, capthick=2)
plt.plot(x2, meanC1, marker="o", linestyle='--',lw=3,color='blue',label = r'2D-to-3D Calibration Depth 1 + 2 + 3',)
# rects2 =ax.errorbar(x2, meanC2,yerr=[stdC2,stdC2],fmt='o',color='red',ecolor='red',lw=3, capsize=5, capthick=2)
# plt.plot(x2, meanC2, marker="o", linestyle='-',lw=3,color='red')
#
# rects3 = ax.errorbar(x3, meanC3,yerr=[stdC3,stdC3],fmt='o',color='black',ecolor='black',lw=3, capsize=5, capthick=2)
# plt.plot(x3, meanC3, marker="o", linestyle='-',lw=3,color='black')
# rects4 =ax.errorbar(x4, meanC4,yerr=[stdC4,stdC4],fmt='o',color='green',ecolor='green',lw=3, capsize=5, capthick=2)
# plt.plot(x4, meanC4, marker="o", linestyle='-',lw=3,color='green')
# rects5 =ax.errorbar(x5, meanC5,yerr=[stdC5,stdC5],fmt='o',color='orange',ecolor='orange',lw=3, capsize=5, capthick=2)
# plt.plot(x5, meanC5, marker="o", linestyle='-',lw=3,color='orange')
#
# rects6 =ax.errorbar(x6, meanC6,yerr=[stdC6,stdC6],fmt='o',color='cyan',ecolor='cyan',lw=3, capsize=5, capthick=2)
# plt.plot(x6, meanC6, marker="o", linestyle='-',lw=3,color='cyan')
rects4 =ax.errorbar(x4, meanC7,yerr=[stdC7,stdC7],fmt='o',color='red',ecolor='red',lw=3, capsize=5, capthick=2)
plt.plot(x4, meanC7, marker="o", linestyle='--',lw=3,color='red',label = r'2D-to-3D Calibration Depth 2 + 3 + 4')
#
# rects8 =ax.errorbar(x8, meanC8,yerr=[stdC8,stdC8],fmt='o',color='darkviolet',ecolor='darkviolet',lw=3, capsize=5, capthick=2)
# plt.plot(x8, meanC8, marker="o", linestyle='-',lw=3,color='darkviolet')
#
# rects9 =ax.errorbar(x9, meanC9,yerr=[stdC9,stdC9],fmt='o',color='lime',ecolor='lime',lw=3, capsize=5, capthick=2)
# plt.plot(x9, meanC9, marker="o", linestyle='-',lw=3,color='lime')
rects6 =ax.errorbar(x6, meanC10,yerr=[stdC10,stdC10],fmt='o',color='orange',ecolor='orange',lw=3, capsize=5, capthick=2)
plt.plot(x6, meanC10, marker="o", linestyle='--',lw=3,color='orange',label = r'2D-to-3D Calibration Depth 3 + 4 + 5')
ax.set_ylabel(r'Angular Error',fontsize=22)
ax.set_xlabel(r'Depth',fontsize=22)
ax.set_xticks(ind+0.25)
ax.set_xticklabels( ('D1', 'D2', 'D3','D4', 'D5') ,fontsize=16)
TOPICs = [0.0,0.5,1.5,2.5,3.5,4.5,5.0]#,110]#,120]
print TOPICs
LABELs = ["",r'D1 - 1m',r'D2 - 1.25m', r'D3 - 1.5m', r'D4 - 1.75m', r'D5 - 2.0m', ""]#, ""]#, ""]
# fig.canvas.set_window_title('Distance Error Correlation')
plt.xticks(TOPICs, LABELs,fontsize=18)
# legend1 =
legend(fontsize=20,loc='best')
# legend([rects1,rects2,rects3,rects4,rects5,rects6], [r'\LARGE\textbf{2C-to-2D Calibration Depth 1 + 2 + 3}', r'\LARGE\textbf{2C-to-3D Calibration Depth 1 + 2 + 3}', r'\LARGE\textbf{2C-to-2D Calibration Depth 2 + 3 + 4}', r'\LARGE\textbf{2C-to-3D Calibration Depth 2 + 3 + 4}',r'\LARGE\textbf{2C-to-2D Calibration Depth 3 + 4 + 5}',r'\LARGE\textbf{2C-to-3D Calibration Depth 3 + 4 + 5}'], loc='upper right')
# ax2 = plt.gca().add_artist(legend1)
##
# plt. legend([rects2,rects4,rects6], [r'\LARGE\textbf{2C-to-3D Calibration Depth 1 + 2 + 3}', r'\LARGE\textbf{2C-to-3D Calibration Depth 2 + 3 + 4}',r'\LARGE\textbf{2C-to-3D Calibration Depth 3 + 4 + 5}'], loc='upper right')
TOPICS = [-0.5, 0.0,0.5,1.0,1.5,2.0,2.5,3.0,3.5,4.0,4.5,5.0,5.5,6.0,6.5,7.0,7.5,8.0,8.5,9.0]#,110]#,120]
print TOPICS
LABELS = [ r'',r'0',r'0.5',r'1', r'1.5', r'2', r'2.5', r'3', r'3.5', r'4', r'4.5', r'5', r'5.5', r'6', r'6.5', r'7', r'7.5', r'8', r'8.5', ""]#, ""]#, ""]
# fig.canvas.set_window_title('Accuracy - Activity Statistics')
plt.yticks(TOPICS, LABELS,fontsize=18)
def autolabel(rects):
# attach some text labels
for rect in rects:
height = rect.get_height()
ax.text(0.26+rect.get_x()+rect.get_width()/2., height +0.35, "%.2f"%float(height),
ha='center', va='bottom',fontweight='bold',fontsize=13.5)
# autolabel(rects1)
left = 0.1 # the left side of the subplots of the figure
right = 0.975 # the right side of the subplots of the figure
bottom = 0.075 # the bottom of the subplots of the figure
top = 0.925 # the top of the subplots of the figure
wspace = 0.2 # the amount of width reserved for blank space between subplots
hspace = 0.4 # the amount of height reserved for white space between subplots
plt.subplots_adjust(left=left, bottom=bottom, right=right, top=top, wspace=wspace, hspace=hspace)
plt.show()
means = [meanC1, meanC2, meanC3, meanC4, meanC5, meanC6, meanC7, meanC8, meanC9,meanC10]
print meanC1
print meanC2
print meanC3
print meanC4
print meanC5
fixationinfos_list_path = "MeansC3D2D3.npy"
fixationinfos_list_csv_path = "MeansC3D2D3.csv"
np.save(fixationinfos_list_path,np.asarray(means))
np.savetxt(fixationinfos_list_csv_path,np.asarray(means), delimiter=",", fmt="%f")
if __name__ == "__main__":
main(sys.argv[1:])
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