def example():
size = 10
maxSize = 20
inputGen = InputGenerator(size, maxSize * 2, maxSize * 2)
inputs = inputGen.generate()
bf = BruteForce(inputs)
bfpath, bftotalDistance = bf.optimise()
bf.plotPath(name="Brute_Force")
nn = NearestNeighbor(inputs)
nnpath, nntotalDistance = nn.optimise()
nn.plotPath(name="NN")
ni = NearestInsertion(inputs)
nipath, nitotalDistance = ni.optimise()
ni.plotPath(name="NI")
to = Two_Opt(inputs)
topath, tototalDistance = to.optimise()
to.plotPath(name="2-opt")
def analyze(bfFlag=False):
runTimeStat = {"nn": [], "bf": [], "ni": [], "to": []}
solutionStat = {"nn": [], "bf": [], "ni": [], "to": []}
maxSize = 500
if bfFlag:
maxSize = 12
'''
Running experiences ....
'''
for size in range(3, maxSize):
inputGen = InputGenerator(size, maxSize * 2, maxSize * 2)
inputs = inputGen.generate()
nn = NearestNeighbor(inputs)
startTime = time.time()
nnpath, nntotalDistance = nn.optimise()
runTime = time.time() - startTime
runTimeStat["nn"].append(runTime)
solutionStat["nn"].append(nntotalDistance)
if bfFlag:
bf = BruteForce(inputs)
startTime = time.time()
bfpath, bftotalDistance = bf.optimise()
runTime = time.time() - startTime
runTimeStat["bf"].append(runTime)
solutionStat["bf"].append(bftotalDistance)
ni = NearestInsertion(inputs)
startTime = time.time()
nipath, nitotalDistance = ni.optimise()
runTime = time.time() - startTime
runTimeStat["ni"].append(runTime)
solutionStat["ni"].append(nitotalDistance)
to = Two_Opt(inputs)
startTime = time.time()
topath, tototalDistance = to.optimise()
runTime = time.time() - startTime
runTimeStat["to"].append(runTime)
solutionStat["to"].append(tototalDistance)
'''
Plotting the results
'''
x = np.arange(3, maxSize)
if not bfFlag:
fig, ax = plt.subplots(nrows=2,
ncols=3,
figsize=(12, 12),
squeeze=False)
ax[0][0].plot(x, runTimeStat["nn"], '-b', label="NN runtime")
ax[0][0].plot(x,
fitParobola(x, runTimeStat["nn"])(x),
'--m',
label="Fitting parabola")
ax[0][0].set_title(
title("Runtime of Nearest Neighbor vs fitting parabola"))
ax[0][0].set_xlabel("Number of nodes")
ax[0][0].set_ylabel("seconds")
ax[0][0].legend()
ax[0][1].plot(x, runTimeStat["ni"], '-r', label="NN runtime")
ax[0][1].plot(x,
fitParobola(x, runTimeStat["ni"])(x),
'--m',
label="Fitting parabola")
ax[0][1].set_title(
title("Runtime of Nearest Insertion vs fitting parabola"))
ax[0][1].set_xlabel("Number of nodes")
ax[0][1].set_ylabel("seconds")
ax[0][1].legend()
ax[0][2].plot(x, runTimeStat["to"], '-g', label="2-Opt runtime")
ax[0][2].plot(x,
fitParobola(x, runTimeStat["to"])(x),
'--m',
label="Fitting parabola")
ax[0][2].set_title(title("Runtime of 2-Opt vs fitting parabola"))
ax[0][2].set_xlabel("Number of nodes")
ax[0][2].set_ylabel("seconds")
ax[0][2].legend()
ax[1][1].plot(x, runTimeStat["nn"], '-b', label="NN runtime")
ax[1][1].plot(x, runTimeStat["ni"], '-r', label="NI runtime")
ax[1][1].plot(x, runTimeStat["to"], '-g', label="2-opt runtime")
ax[1][1].set_title(title("Runtime Comparison"))
ax[1][1].set_xlabel("Number of nodes")
ax[1][1].set_ylabel("seconds")
ax[1][1].legend()
fig.delaxes(ax.flatten()[5])
fig.delaxes(ax.flatten()[3])
plt.tight_layout(True)
plt.savefig("runtime_woBF.png", dpi=800)
plt.close()
else:
fig, ax = plt.subplots()
ax.plot(x, runTimeStat["nn"], '-b', label="NN runtime")
ax.plot(x, runTimeStat["ni"], '-r', label="NI runtime")
ax.plot(x, runTimeStat["to"], '-g', label="2-opt runtime")
ax.plot(x, runTimeStat["bf"], '--k', label="Brute Force runtime")
ax.set_title(title("Runtime Comparison"))
ax.set_xlabel("Number of nodes")
ax.set_ylabel("seconds")
ax.legend()
plt.tight_layout(True)
plt.savefig("runtime_wBF.png", dpi=800)
plt.close()
fig, ax = plt.subplots()
ax.plot(x, solutionStat["nn"], '-b', label="NN solution")
ax.plot(x, solutionStat["ni"], '-r', label="NI solution")
ax.plot(x, solutionStat["to"], '-g', label="2-opt solution")
if bfFlag:
ax.plot(x, solutionStat["bf"], '--k', label="Brute Force solution")
ax.set_title("Total Distance Comparison")
ax.set_xlabel("Number of nodes")
ax.set_ylabel("Distance")
ax.legend()
plt.tight_layout(True)
if bfFlag:
plt.savefig("solution_wBF.png", dpi=800)
else:
plt.savefig("solution_woBF.png", dpi=800)
plt.close()