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VR_analysis.py
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VR_analysis.py
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import numpy as np
import matplotlib.pyplot as plt
import math
from mpl_toolkits.mplot3d import Axes3D
from scipy.spatial import ConvexHull, convex_hull_plot_2d
num_wolves = 15
# num_iteration = 500
path = './Python_TargetChange_Reset/Trial_1/wolf'
suff = '.csv'
files = [(path+str(i)+suff) for i in range(num_wolves)]
data_list = []
for f in files:
data = np.genfromtxt(f, delimiter=',')
data_list.append(data)
distanceList = []
for data in data_list:
targetDistanceData = np.zeros([len(data),2])
for i in range(len(data)):
targetDistanceData[i,0] = i
target = np.array([0,0])
if(i<127):
target = np.array([593,593])
elif(i>=127 and i<389):
target = np.array([-493,-493])
elif(i>=389):
target = np.array([-1000,1000])
targetDistanceData[i,1] = math.log(np.linalg.norm(target - data[i,1:]))
distanceList.append(targetDistanceData)
fig = plt.figure()
index = 1
for distance in distanceList:
fig.add_subplot(3, 5, index)
plt.plot(distance[:,0],distance[:,1])
plt.ylabel('Log of Distance from target')
plt.xlabel('Iteration number')
plt.title('Wolf' + str(index-1))
index = index+1
plt.suptitle('Target Changing in Python - (593,593),(493,493), (393,393) in iterations 127 and 389')
plt.show()
# for folder in folders:
# dataList = []
# for i in range(num_wolves):
# data = np.genfromtxt(folder + path2 +str(i)+path3, delimiter = ',')
# dataList.append(data)
# index = 0
# for data in dataList:
# ax = plt.axes(projection='3d')
# ax.view_init(azim=-65,elev = 15)
# ax.scatter3D(data[:,0],data[:,1],data[:,2])
# ax.set_title('Position of Robot '+str(index)+' over '+ str(num_iteration)+' Iterations')
# ax.set_xlabel('Iteration Number')
# ax.set_ylabel('X Coordinate')
# ax.set_zlabel('Y Coordinate')
# # plt.savefig(path + 'wolf' +str(index)+'_trajectoryScatter.png',bbox_inches='tight', dpi=300)
# index = index+1
# plt.show()
# #Average distance Plot
# index = 0
# for wolf in dataList:
# targetDistanceData = np.empty([num_iteration,2])
# for i in range(num_iteration):
# targetDistanceData[i,0] = wolf[i,0]
# targetDistanceData[i,1] = math.log(np.linalg.norm(np.array([593,593]) - wolf[i,1:]))
# plt.plot(targetDistanceData[:,0],targetDistanceData[:,1])
# plt.xlabel('Iteration Number')
# plt.ylabel('Distance from target')
# plt.title('Distance of Robot ' + str(index)+ ' from target'+' over '+ str(num_iteration)+' Iterations')
# plt.savefig(path + 'wolf' +str(index)+'_distanceFromTarget.png', dpi=300)
# index = index+1
# plt.clf()