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()