def test_min_neigh():
"""
Test the impact of the neighbours on metrics
"""
recall = []
precision = []
range_parameter = []
success = []
for i in range(1, 20):
r, p, s = get_metrics(minNeigh=i)
recall.append(r); precision.append(p); range_parameter.append(i); success.append(s)
plot_metrics(range_parameter, "min neighbours", recall, precision, None, "min_neigh_comparison.png")
plt.close()
plt.plot(range_parameter, success)
plt.savefig("output/success_minNeigh.png")
plt.close()
def test_max_size():
"""
Test the impact of the neighbours on metrics
"""
recall = []
precision = []
range_parameter = []
success = []
for i in range(30, 300, 10):
r, p, s = get_metrics(maxSize=i)
recall.append(r); precision.append(p); range_parameter.append(i); success.append(s)
plot_metrics(range_parameter, "max size", recall, precision, None, "max_size_comparison.png")
plt.close()
plt.plot(range_parameter, success)
plt.savefig("output/success_maxSize.png")
plt.close()
def test_scale():
"""
Test the impact of the scale on metrics
"""
recall = []
precision = []
accuracy = []
range_parameter = []
success = []
for i in range(101, 501, 5):
r, p, a, s = get_metrics(scale=i/100.0)
recall.append(r); precision.append(p); accuracy.append(a); range_parameter.append(i/100.0); success.append(s)
plot_metrics(range_parameter, "scale", recall, precision, accuracy, "scale_comparison.png")
plt.close()
plt.plot(range_parameter, success)
plt.savefig("output/success_scale.png")
plt.close()
def test_scale():
"""
Test the impact of the scale on metrics
"""
recall = []
precision = []
range_parameter = []
success = []
for i in range(130 , 301, 2):
print("current scale ", i/100.0)
r, p, s = get_metrics(scale=i/100.0)
recall.append(r); precision.append(p); range_parameter.append(i/100.0); success.append(s)
plot_metrics(range_parameter, "scale", recall, precision, None, "scale_comparison.png")
plt.close()
plt.plot(range_parameter, success)
plt.savefig("output/success_scale.png")
plt.close()