Modify the main program for Assignment #4, travelSystem.py, by adding three line

Question

Modify the main program for Assignment #4, travelSystem.py, by adding three lines:

from travelPlot import plotTravel

…

# Plot the travel for each item from itemRecords plotTravel(itemRecords) The last line calls a function plotTravel(), which you will write.

2. Create a file travelPlot.py.

a. In this file, you must import the travelItem class definition from travelClass.py, which you completed for Assignment #4: from travelClass import travelItem

b. In this file, you also must import numpy and pyplot,

e.g.: import numpy as np import matplotlib.pyplot as plt

c. In this file, define the function plotTravel(), with the interface: def plotTravel(itemRecords) :

d. Complete the function plotTravel() so that it creates a bar plot to show the start and end availability for each travel item. Figure 1 shows an example that was created by modifying code from the bar chart demonstration program at: http://matplotlib.org/examples/api/barchart_demo.html

Explanation / Answer

import matplotlib.pyplot as plt def plotTSP(path, points, num_iters=1): """ path: List of lists with the different orders in which the nodes are visited points: coordinates for the different nodes num_iters: number of paths that are in the path list """ # Unpack the primary TSP path and transform it into a list of ordered # coordinates x = []; y = [] for i in paths[0]: x.append(points[i][0]) y.append(points[i][1]) plt.plot(x, y, 'co') # Set a scale for the arrow heads (there should be a reasonable default for this, WTF?) a_scale = float(max(x))/float(100) # Draw the older paths, if provided if num_iters > 1: for i in range(1, num_iters): # Transform the old paths into a list of coordinates xi = []; yi = []; for j in paths[i]: xi.append(points[j][0]) yi.append(points[j][1]) plt.arrow(xi[-1], yi[-1], (xi[0] - xi[-1]), (yi[0] - yi[-1]), head_width = a_scale, color = 'r', length_includes_head = True, ls = 'dashed', width = 0.001/float(num_iters)) for i in range(0, len(x) - 1): plt.arrow(xi[i], yi[i], (xi[i+1] - xi[i]), (yi[i+1] - yi[i]), head_width = a_scale, color = 'r', length_includes_head = True, ls = 'dashed', width = 0.001/float(num_iters)) # Draw the primary path for the TSP problem plt.arrow(x[-1], y[-1], (x[0] - x[-1]), (y[0] - y[-1]), head_width = a_scale, color ='g', length_includes_head=True) for i in range(0,len(x)-1): plt.arrow(x[i], y[i], (x[i+1] - x[i]), (y[i+1] - y[i]), head_width = a_scale, color = 'g', length_includes_head = True) #Set axis too slitghtly larger than the set of x and y plt.xlim(0, max(x)*1.1) plt.ylim(0, max(y)*1.1) plt.show() if __name__ == '__main__': # Run an example # Create a randomn list of coordinates, pack them into a list x_cor = [1, 8, 4, 9, 2, 1, 8] y_cor = [1, 2, 3, 4, 9, 5, 7] points = [] for i in range(0, len(x_cor)): points.append((x_cor[i], y_cor[i])) # Create two paths, teh second with two values swapped to simulate a 2-OPT # Local Search operation path4 = [0, 1, 2, 3, 4, 5, 6] path3 = [0, 2, 1, 3, 4, 5, 6] path2 = [0, 2, 1, 3, 6, 5, 4] path1 = [0, 2, 1, 3, 6, 4, 5] # Pack the paths into a list paths = [path1, path2, path3, path4] # Run the function plotTSP(paths, points, 4)

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