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sceneplot.py
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sceneplot.py
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# -*- coding: utf-8 -*-
"""
Created on Tue Feb 20 17:22:47 2018
@author: cz
"""
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import math
import os
class ScenePlot():
def __init__(self, scene = None, saveEnabled = True):
self.sc = scene
self.TYPE_TIME_SEPARATION_ERROR = 2
self.TYPE_TIME_BEARING_ERROR = 3
self.TYPE_TIME_ACTIONS = 6
self.getRobotColor = self.sc.getRobotColor
self.saveEnabled = saveEnabled
if self.saveEnabled == True:
directory = 'fig'
if not os.path.exists(directory):
os.makedirs(directory)
self.directory = directory
count = 0
for filename in os.listdir(directory):
name, _ = os.path.splitext(filename)
n = int(name)
if count < n:
count = n
count = count + 1
self.directory = os.path.join(self.directory, str(count).zfill(3))
os.makedirs(self.directory)
def plot(self, type = 0, tf = 0):
# type 0: (t, x_i - x_id)
# type 1: (t, y_i - y_id)
# type 2: (t, e_i - e_id) (formation error)
# type 3: (x_i, y_i)
# type 4: (t, v1)
# If this is the first time this type of plot is drawn, initialize
if type not in self.sc.ydict.keys():
self.sc.ydict[type] = dict()
self.sc.ydict2[type] = dict() # for type 3 figure only
self.sc.ploted[type] = False
if type == 0 or type == 1:
for i in range(len(self.sc.robots)):
self.sc.ydict[type][i] = []
if self.sc.ploted[type] and type != 6:
pass#return # This type of plot is completed
if type == 0:
if not self.sc.ploted[type]:
for i in range(len(self.sc.robots)):
x = self.sc.robots[i].xi.x - self.sc.robots[i].xid.x
self.sc.ydict[type][i].append(x)
if self.sc.t > tf:
plt.figure(type)
for i in range(len(self.sc.robots)):
try:
plt.plot(self.sc.ts, self.sc.ydict[type][i], '-')
except:
print('type: ', type)
raise
plt.xlabel('t (s)')
plt.ylabel('x_i - x_di (m)')
elif type == 1:
if not self.sc.ploted[type]:
for i in range(len(self.sc.robots)):
x = self.sc.robots[i].xi.y - self.sc.robots[i].xid.y
self.sc.ydict[type][i].append(x)
if self.sc.t > tf:
plt.figure(type)
for i in range(len(self.sc.robots)):
plt.plot(self.sc.ts, self.sc.ydict[type][i], '-')
plt.xlabel('t (s)')
plt.ylabel('y_i - y_di (m)')
elif type == 2: # Formation Error type 2
if not self.sc.ploted[type]:
k = 0
for i in range(0, len(self.sc.robots)):
xi = self.sc.robots[i].xi.x
yi = self.sc.robots[i].xi.y
xid = self.sc.robots[i].xid.x
yid = self.sc.robots[i].xid.y
if self.sc.dynamics == 5:
#jList = range(0, 1)
jList = range(0, len(self.sc.robots))
elif self.sc.dynamics >= 16 and self.sc.dynamics <= 17:
jList = range(0, len(self.sc.robots))
elif self.sc.dynamics == 18:
#lsd = self.sc.robots[i].listSortedDistance
#jList = [lsd[0][0],lsd[1][0]]
jList = range(0, len(self.sc.robots))
else:
raise Exception("Undefined robot dynamics for data recording", self.sc.dynamics)
for j in jList:
if self.sc.adjMatrix[i, j] == 0:
continue
if i > j and self.sc.adjMatrix[j, i] != 0:
continue
xj = self.sc.robots[j].xi.x
yj = self.sc.robots[j].xi.y
xjd = self.sc.robots[j].xid.x
yjd = self.sc.robots[j].xid.y
eji = np.array([xi - xj, yi - yj])
if self.sc.dynamics == 5:
ejid = np.array([xid - xjd, yid - yjd])
elif self.sc.dynamics == 17:
ejid = np.array([xid - xjd, yid - yjd])
else:
ejid = self.sc.alpha
error = np.linalg.norm(eji) - np.linalg.norm(ejid)
# If this is the first time this type of plot is drawn
if k not in self.sc.ydict[type].keys():
self.sc.ydict[type][k] = []
self.sc.ydict2[type][k] = (i, j) # for legend
self.sc.ydict[type][k].append(error)
k += 1
if self.sc.t > tf:
errors = self.sc.ydict[type]
legends = self.sc.ydict2[type]
curves = []
plt.figure(type)
for k in range(0, len(self.sc.ydict[type])):
curve, = plt.plot(self.sc.ts, errors[k], '-', label = str(legends[k]))
curves.append(curve)
if int(matplotlib.__version__[0]) == 2:
plt.legend(handles = curves)
plt.xlabel('t (s)')
plt.ylabel('Formation Separation Error (m)')
elif type == 21: # Formation orientation error
if not self.sc.ploted[type]:
k = 0
for i in range(1, len(self.sc.robots)):
xi = self.sc.robots[i].xi.x
yi = self.sc.robots[i].xi.y
xid = self.sc.robots[i].xid.x
yid = self.sc.robots[i].xid.y
if self.sc.dynamics == 13:
j2 = 1
elif self.sc.dynamics == 14 or self.sc.dynamics == 16 or self.sc.dynamics == 17:
j2 = i
for j in range(0, j2):
if self.sc.adjMatrix[i, j] == 0:
continue
xj = self.sc.robots[j].xi.x
yj = self.sc.robots[j].xi.y
xjd = self.sc.robots[j].xid.x
yjd = self.sc.robots[j].xid.y
eji = np.array([xi - xj, yi - yj])
ejid = np.array([xid - xjd, yid - yjd])
angle = math.acos(np.inner(eji, ejid) /
np.linalg.norm(eji) / np.linalg.norm(ejid))
# If this is the first time this type of plot is drawn
if k not in self.sc.ydict[type].keys():
self.sc.ydict[type][k] = []
self.sc.ydict2[type][k] = (i, j) # for legend
self.sc.ydict[type][k].append(angle)
k += 1
if self.sc.t > tf:
errors = self.sc.ydict[type]
legends = self.sc.ydict2[type]
curves = []
plt.figure(type)
for k in range(0, len(self.sc.ydict[type])):
curve, = plt.plot(self.sc.ts, errors[k], '-', label = str(legends[k]))
curves.append(curve)
if int(matplotlib.__version__[0]) == 2:
plt.legend(handles = curves)
plt.xlabel('t (s)')
plt.ylabel('Formation Orientation Error (rad)')
elif type == 22: # Distance from goal
if not self.sc.ploted[type]:
for i in range(0, len(self.sc.robots)):
# If this is the first time this type of plot is drawn
if i not in self.sc.ydict[type].keys():
self.sc.ydict[type][i] = []
# print(self.sc.ydict[type].keys())
# print('i = ', i, 'j = ', j)
xi = self.sc.robots[i].xi.x
yi = self.sc.robots[i].xi.y
xid = self.sc.robots[i].xid.x
yid = self.sc.robots[i].xid.y
distance = ((xid - xi)**2 + (yid - yi)**2)**0.5
self.sc.ydict[type][i].append(distance)
#print(self.sc.ydict[type][i])
if self.sc.t > tf:
errors = self.sc.ydict[type]
plt.figure(type)
for i in range(0, len(self.sc.robots)):
plt.plot(self.sc.ts, errors[i], '-')
plt.xlabel('t (s)')
plt.ylabel('Distance from goal (m)')
elif type == 23: # Ceter distance from goal
if not self.sc.ploted[type]:
# If this is the first time this type of plot is drawn
if 0 not in self.sc.ydict[type].keys():
self.sc.ydict[type][0] = []
xbar = 0
ybar = 0
for i in range(0, len(self.sc.robots)):
xbar += self.sc.robots[i].xi.x
ybar += self.sc.robots[i].xi.y
xbar /= len(self.sc.robots)
ybar /= len(self.sc.robots)
xd = self.sc.xid.x
yd = self.sc.xid.y
distance = ((xbar - xd)**2 + (ybar - yd)**2)**0.5
self.sc.ydict[type][0].append(distance)
#print(self.sc.ydict[type][0])
if self.sc.t > tf:
error = self.sc.ydict[type][0]
plt.figure(type)
plt.plot(self.sc.ts, error, '-', color = (0,0,0))
plt.xlabel('t (s)')
plt.ylabel('Center distance from goal (m)')
elif type == 24: # Formation Error type 24: epsilon
if len(self.sc.robots) != 3:
raise Exception("Plot type 24 is valid only when the number of robots is 3.")
if self.sc.dynamics != 5:
raise Exception("Plot type 24 is valid only for dynamics 13.")
xi = 3 * [None]
xid = 3 * [None]
if not self.sc.ploted[type]:
for i in range(0, 3):
xi[i] = self.sc.robots[i].xi
xid[i] = self.sc.robots[i].xid
for i in range(0, 3):
error = 0
j1 = None
for j in range(0, 3):
if i == j:
continue
if j1 is None:
j1 = j
else:
j2 = j
xj = self.sc.robots[j].xi.x
yj = self.sc.robots[j].xi.y
xjd = self.sc.robots[j].xid.x
yjd = self.sc.robots[j].xid.y
errorij1 = xi[i].distancepTo(xi[j1]) - xid[i].distancepTo(xid[j1])
errorij2 = xi[i].distancepTo(xi[j2]) - xid[i].distancepTo(xid[j2])
errorj1j2 = xi[j1].distancepTo(xi[j2]) - xid[j1].distancepTo(xid[j2])
ejid = xid[i].distancepTo(xid[j])
epsilon = errorij1 + errorij2 - errorj1j2
# If this is the first time this type of plot is drawn
if i not in self.sc.ydict[type].keys():
self.sc.ydict[type][i] = []
self.sc.ydict2[type][i] = i # for legend
self.sc.ydict[type][i].append(epsilon)
if self.sc.t > tf:
errors = self.sc.ydict[type]
legends = self.sc.ydict2[type]
curves = []
plt.figure(type)
for k in range(0, len(self.sc.ydict[type])):
curve, = plt.plot(self.sc.ts, errors[k], '-',
label = str(legends[k]))
curves.append(curve)
if int(matplotlib.__version__[0]) == 2:
plt.legend(handles = curves)
plt.xlabel('t (s)')
plt.ylabel('Formation Separation Error (m)')
elif type == 3: # Formation Error type 3
if not self.sc.ploted[type]:
for i in range(1, len(self.sc.robots)):
# If this is the first time this type of plot is drawn
if i not in self.sc.ydict[type].keys():
self.sc.ydict[type][i] = []
# print(self.sc.ydict[type].keys())
# print('i = ', i, 'j = ', j)
xi = self.sc.robots[i].xi.x
yi = self.sc.robots[i].xi.y
xid = self.sc.robots[i].xid.x
yid = self.sc.robots[i].xid.y
j = 0
xj = self.sc.robots[j].xi.x
yj = self.sc.robots[j].xi.y
xjd = self.sc.robots[j].xid.x
yjd = self.sc.robots[j].xid.y
phi = math.atan2(yi - yj, xi - xj)
phid = math.atan2(yid - yjd, xid - xjd)
error = phi - phid
while error > math.pi:
error -= 2 * math.pi
while error <= -math.pi:
error += 2 * math.pi
self.sc.ydict[type][i].append(error)
#print(self.sc.ydict[type][i])
if self.sc.t > tf:
errors = self.sc.ydict[type]
plt.figure(type)
for i in range(1, len(self.sc.robots)):
plt.plot(self.sc.ts, errors[i], '-')
plt.xlabel('t (s)')
plt.ylabel('Bearing Error (rad)')
elif type == 4:
# Show formation
if not self.sc.ploted[type]:
# record individual trajectories
for i in range(len(self.sc.robots)):
x = self.sc.robots[i].xi.x
y = self.sc.robots[i].xi.y
if i not in self.sc.ydict[type].keys():
self.sc.ydict2[type][i] = np.array([[x, y]])
else:
self.sc.ydict2[type][i] = np.append(self.sc.ydict2[type][i],
[[x, y]], axis = 0)
# print('time: ', (self.sc.t + 1e-5) % 1)
if (self.sc.t + 1e-5) % 3 < 2e-5:
# print("recording")
self.sc.tss.append(self.sc.t)
for i in range(len(self.sc.robots)):
x = self.sc.robots[i].xi.x
y = self.sc.robots[i].xi.y
theta = self.sc.robots[i].xi.theta*180/math.pi - 90 # convert to deg
if len(self.sc.tss) == 1:
self.sc.ydict[type][i] = np.array([[x, y, theta]])
if i == 0:
self.sc.centerTrajS = np.array([[x, y]])
else:
self.sc.centerTrajS += np.array([[x, y]])
else:
self.sc.ydict[type][i] = np.append(self.sc.ydict[type][i],
[[x, y, theta]], axis = 0)
if i == 0:
self.sc.centerTrajS = np.append(self.sc.centerTrajS, [[x, y]], axis = 0)
else:
self.sc.centerTrajS[-1, :] += np.array([x, y])
#print(self.sc.centerTrajS)
self.sc.centerTrajS[-1, :] /= len(self.sc.robots)
# Show Figure
if self.sc.t > tf:
plt.figure(type)
curves = []
if self.sc.dynamics == 5:
style = 3
else:
style = 0
for i in range(len(self.sc.robots)):
c = self.getRobotColor(i)
curve, = plt.plot(self.sc.ydict2[type][i][:, 0],
self.sc.ydict2[type][i][:, 1],
'-', color = c, label = str(i))
curves.append(curve)
for k in range(len(self.sc.tss)):
plt.plot(self.sc.ydict[type][i][k, 0],
self.sc.ydict[type][i][k, 1],
marker=(3, style, self.sc.ydict[type][i][k, 2]),
markersize=20, linestyle='None',
color=c, fillstyle="none")
if int(matplotlib.__version__[0]) == 2:
plt.legend(handles = curves)
for k in range(len(self.sc.tss)):
for i in range(len(self.sc.robots)):
x1 = self.sc.ydict[type][i][k, 0]
y1 = self.sc.ydict[type][i][k, 1]
for j in range(0, len(self.sc.robots)):
if self.sc.adjMatrix[i, j] == 0:
continue
if i > j and self.sc.adjMatrix[j, i] != 0:
continue
x2 = self.sc.ydict[type][j][k, 0]
y2 = self.sc.ydict[type][j][k, 1]
plt.plot([x1, x2], [y1, y2], ':', color = (0, 0, 0))
# Plot center trajectory
for k in range(len(self.sc.tss)):
plt.plot(self.sc.centerTrajS[k, 0],
self.sc.centerTrajS[k, 1],
'o',
markersize=10, linestyle='None',
color = (0, 0, 0))
plt.plot(self.sc.centerTraj[:, 0],
self.sc.centerTraj[:, 1],
'-',
color = (0, 0, 0))
plt.xlabel('x (m)')
plt.ylabel('y (m)')
plt.axes().set_aspect('equal', 'datalim')
elif type == 5:
# Show speed
if not self.sc.ploted[type]:
for i in range(len(self.sc.robots)):
vDesired = (self.sc.robots[i].v1Desired + self.sc.robots[i].v2Desired)/2
if self.sc.vrepConnected == True:
vActual = self.sc.robots[i].vActual
else:
vActual = vDesired
if i not in self.sc.ydict[type].keys():
self.sc.ydict[type][i] = []
self.sc.ydict2[type][i] = []
self.sc.ydict[type][i].append(vActual)
self.sc.ydict2[type][i].append(vDesired)
if self.sc.t > tf:
plt.figure(type)
for i in range(len(self.sc.robots)):
c = self.getRobotColor(i)
curve1, = plt.plot(self.sc.ts, self.sc.ydict[type][i], '-',
color = c, label = 'Actual')
curve2, = plt.plot(self.sc.ts, self.sc.ydict2[type][i], '--',
color = c, label = 'Desired')
if int(matplotlib.__version__[0]) == 2:
plt.legend(handles = [curve1, curve2])
plt.xlabel('t (s)')
plt.ylabel('v (m/s)')
elif type == 6:
# Show action
if self.sc.dynamics == 13:
j1 = 1
elif self.sc.dynamics == 14 or (self.sc.dynamics >= 16 and self.sc.dynamics <= 18):
j1 = 0
else:
j1 = 0
if not self.sc.ploted[type]:
for i in range(len(self.sc.robots)):
vDesired1 = self.sc.robots[i].v1Desired
vDesired2 = self.sc.robots[i].v2Desired
if i not in self.sc.ydict[type].keys():
self.sc.ydict[type][i] = []
self.sc.ydict2[type][i] = []
self.sc.ydict[type][i].append(vDesired1)
self.sc.ydict2[type][i].append(vDesired2)
if self.sc.t > tf:
plt.figure(type)
for i in range(j1, len(self.sc.robots)): # Show only the follower
#for i in range(len(self.sc.robots)): # Show both the follower and the leader
c = self.getRobotColor(i)
if self.sc.dynamics == 5:
curve1Label = 'Action in x-axis'
curve2Label = 'Action in y-axis'
else:
curve1Label = 'Left Wheel Velocity'
curve2Label = 'Right Wheel Velocity'
curve1, = plt.plot(self.sc.ts, self.sc.ydict[type][i], ':',
color = c, label = curve1Label)
curve2, = plt.plot(self.sc.ts, self.sc.ydict2[type][i], '--',
color = c, label = curve2Label)
if int(matplotlib.__version__[0]) == 2:
plt.legend(handles = [curve1, curve2])
plt.xlabel('t (s)')
plt.ylabel('Robot Actions (m/s)')
elif type == 7:
# Show angular velocity
if not self.sc.ploted[type]:
for i in range(len(self.sc.robots)):
omegaDesired = (self.sc.robots[i].v2Desired -
self.sc.robots[i].v1Desired) / self.sc.robots[i].l
if self.sc.vrepConnected == True:
omegaActual = self.sc.robots[i].omegaActual
else:
omegaActual = omegaDesired
if i not in self.sc.ydict[type].keys():
self.sc.ydict[type][i] = []
self.sc.ydict2[type][i] = []
self.sc.ydict[type][i].append(omegaActual)
self.sc.ydict2[type][i].append(omegaDesired)
if self.sc.t > tf:
plt.figure(type)
for i in range(len(self.sc.robots)):
c = self.getRobotColor(i)
curve1, = plt.plot(self.sc.ts, self.sc.ydict[type][i], '-',
color = c, label = 'Actual')
curve2, = plt.plot(self.sc.ts, self.sc.ydict2[type][i], '--',
color = c, label = 'Desired')
if int(matplotlib.__version__[0]) == 2:
plt.legend(handles = [curve1, curve2])
plt.xlabel('t (s)')
plt.ylabel('omega (rad/s)')
elif type == 8:
# Show Euler angles
if not self.sc.ploted[type]:
if self.sc.vrepConnected == False:
return
for i in range(len(self.sc.robots)):
alpha = self.sc.robots[i].xi.alpha / math.pi * 180
beta = self.sc.robots[i].xi.beta / math.pi * 180
if i not in self.sc.ydict[type].keys():
self.sc.ydict[type][i] = []
self.sc.ydict2[type][i] = []
self.sc.ydict[type][i].append(alpha)
self.sc.ydict2[type][i].append(beta)
if self.sc.t > tf:
if len(self.sc.ts) != len(self.sc.ydict[type][0]):
return
plt.figure(type)
for i in range(len(self.sc.robots)):
c = self.getRobotColor(i)
curve1, = plt.plot(self.sc.ts, self.sc.ydict[type][i], '-',
color = c, label = 'alpha')
curve2, = plt.plot(self.sc.ts, self.sc.ydict2[type][i], '--',
color = c, label = 'beta')
if int(matplotlib.__version__[0]) == 2:
plt.legend(handles = [curve1, curve2])
plt.xlabel('t (s)')
plt.ylabel('angles (deg)')
elif type == 9:
# Show observation1
for i in range(len(self.sc.robots)):
plt.figure(type)
c = self.getRobotColor(i)
pc = self.sc.robots[i].pointCloud
dist = pc.scanVector
angle = pc.scanAngle
for j in range(pc.lenScanVector):
x = -dist[0, j] * math.cos(angle[j])
y = -dist[0, j] * math.sin(angle[j])
plt.plot([0, x], [0, y], '-', color = c)
plt.xlabel('x (m)')
plt.ylabel('y (m)')
plt.axes().set_aspect('equal')
plt.show()
self.sc.ploted[type] = True
else:
raise Exception("Undefined type of plot.")
if self.sc.t > tf:
plt.grid(True)
if self.saveEnabled == True:
# Save plot as eps file
path = os.path.join(self.directory, 'fig' + str(type).zfill(2) + '.eps')
plt.savefig(path, format='eps', dpi=1000)
message = "Plot saved to " + str(path)
self.sc.log(message)
print(message)
plt.show()
else:
plt.show()
self.sc.ploted[type] = True