plotter.py

# Sources: 
# CS 330, Python Plotter v2.py
#
# Require matplotlib
# To install run "pip install matplotlib" in command line / terminal
# To run:
#  1. Place this file and the file to be plotted in the same folder
#  2. Open this file and change the variable filename to the name of the file
#         to be opened.
#  3. Run in IDE, or run "python 'CS 330, Python Plotter v3.py'" in command line /
#         terminal.


import matplotlib.pyplot as plt
import csv
import math

# Change this to data file name
filename = "outputFile.txt" 

#************************** Setup Plotting Axis ****************************
xLineX = [-100, 100]
xLineY = [0, 0]
yLineX = [0, 0]
yLineY = [-100, 100]
plt.figure(figsize=(6, 6))

# add dashed grey lines
plt.plot(xLineX, xLineY, color='grey', linestyle='dashed', linewidth = 1)
plt.plot(yLineX, yLineY, color='grey', linestyle='dashed', linewidth = 1)

# Mover class will hold data for each mover entity on the plot
class Mover:
    def __init__(self, behavior):
        self.behavior = behavior   # steering behavior status code 
        self.z = []      # position z (meters)
        self.x = []      # position x (meters)
        self.vXp = []    # values to plot velocity x (meters per second)
        self.vZp = []    # values to plot velocity z (meters per second)
        self.laXp = []   # values to plot linear acceleration x (meters per second per second)
        self.laZp = []   # values to plot linear acceleration z (meters per second per second)
        self.oXp = []    # values to plot orientation in x
        self.oZp = []    # values to plot orientation in z


movers = {}     # create dictionary to store different movers

with open(filename, 'r') as csvfile:
    csvreader = csv.reader(csvfile)

    for row in csvreader:   
       
        #as we find other 
        if( row[1] not in movers):                  # row[1] holds the id of the Mover
            movers[row[1]] = Mover(int(row[9]))     # if we don't have a Mover object for a particular id yet,
                                                    # we create one and add it to the dictionary
        
        m = movers[row[1]]

        m.x.append(float(row[2]) )     # Position x
        m.z.append(float(row[3]) )     # Position z
        m.vXp.append( (float(row[4]) * 2 ) + float(row[2]) ) # Velocity data is multiplied by constants to increase visiblity
        m.vZp.append( (float(row[5]) * 2) + float(row[3]) )
        m.laXp.append( (float(row[6])) + float(row[2]) )     # Linear acceleration
        m.laZp.append( (float(row[7])) + float(row[3]) )
        m.oXp.append( (math.cos(float(row[8]) ) ) + float(row[2]) )   # Orientation
        m.oZp.append( (math.sin(float(row[8]) ) ) + float(row[3]) )


for mov in movers:                  # for each mover
    m = movers[mov]

    for c in range(0, len(m.x)):    # Plot velocity data
        i = [m.x[c], m.vXp[c]]          # current x, current x + x velocity
        j = [m.z[c], m.vZp[c]]          # current z, current z + z velocity
        
        plt.plot(i, j, color='#5beb34', linewidth=0.5)  #green

    for c in range(0, len(m.x)):    # Plot linear acceleration data
        i = [m.x[c], m.laXp[c]]         # current x, current x + x linear acceleration
        j = [m.z[c], m.laZp[c]]         # current z, current z + z linear acceleration
        
        plt.plot(i, j, color='blue', linewidth=0.5)

    # uncomment this to plot orientation data
    # for c in range(0, len(m.x)):    # Plot orientation data
    #     i = [m.x[c], m.oXp[c]]          # current x, current x + x orientation
    #     j = [m.z[c], m.oZp[c]]          # current z, current z + z orientation

    #     plt.plot(i, j, color='yellow', linewidth=0.5) #, label="position") # plots position


for mov in movers:
    m = movers[mov]

    # Plot labels for steering behavior type
    label = ""
    if(m.behavior == 1):
        label = "Stop"
    elif(m.behavior == 3):
        label = "Seek"
    elif(m.behavior == 4):
        label = "Flee"
    elif(m.behavior == 5):
        label = "Arrive"

    plt.annotate(label, color='red', xy=(m.x[0] + 2 , m.z[0] - 2))

    # add red dots to the start and end of each mover's trail
    plt.plot(m.x[0], m.z[0], color='red', marker='o', markerfacecolor='red', markersize=3)  #mark start position
    plt.plot(m.x[-1], m.z[-1], color='red', marker='o', markerfacecolor='red', markersize=4) #mark end position

    # plot position
    plt.plot(m.x, m.z, color='red', linewidth=1)


# create legend
plt.plot(0, 0, color='red', label='position')
plt.plot(0, 0, color='green', label='velocity')
plt.plot(0, 0, color='blue', label='linear')
#plt.plot(0, 0, color='yellow', label='orientation')


# format plot and save to file
plt.xlabel('x')
plt.ylabel('z')
plt.title('Dynamic Movement PVL Sample')
plt.legend(bbox_to_anchor=(1.0, 0.05), loc='lower right')
plt.xlim(-100, 100)
plt.ylim(100, -100)

#plt.savefig("outputPlot.png",dpi=200)
plt.show()