Made graphs look better

Author: vighneshbirodkar

examples/plot_classifier.py

@@ -22,9 +22,20 @@
 X_0 = X_test[y_pred == 0]
 X_1 = X_test[y_pred == 1]
 
-ax0 = plt.scatter(X_0[:, 0], X_0[:, 1], c='crimson', s=30)
-ax1 = plt.scatter(X_1[:, 0], X_1[:, 1], c='deepskyblue', s=30)
 
+p0 = plt.scatter(0, 0, c='red', s=100)
+p1 = plt.scatter(1, 1, c='blue', s=100)
+
+ax0 = plt.scatter(X_0[:, 0], X_0[:, 1], c='crimson', s=50)
+ax1 = plt.scatter(X_1[:, 0], X_1[:, 1], c='deepskyblue', s=50)
+
+leg = plt.legend([p0, p1, ax0, ax1],
+                 ['Point 0', 'Point 1', 'Class 0', 'Class 1'],
+                 loc='upper left', fancybox=True, scatterpoints=1)
+leg.get_frame().set_alpha(0.5)
+
+plt.xlabel('Feature 1')
+plt.ylabel('Feature 2')
+plt.xlim([-.5, 1.5])
 
-plt.legend([ax0, ax1], ['Class 0', 'Class 1'])
 plt.show()

examples/plot_transformer.py

@@ -9,13 +9,18 @@
 from skltemplate import TemplateTransformer
 from matplotlib import pyplot as plt
 
-X = np.arange(50).reshape(-1, 1)
+X = np.arange(50, dtype=np.float).reshape(-1, 1)
+X /= 50
 estimator = TemplateTransformer()
 X_transformed = estimator.fit_transform(X)
 
-plt.plot(X.flatten()/X.max(), label='Original Data')
-plt.plot(X_transformed.flatten()/X_transformed.max(), label='Transformed Data')
-plt.title('Scaled plots of original and transformed data')
+plt.plot(X.flatten(), label='Original Data')
+plt.plot(X_transformed.flatten(), label='Transformed Data')
+plt.title('Plots of original and transformed data')
 
 plt.legend(loc='best')
+plt.grid(True)
+plt.xlabel('Index')
+plt.ylabel('Value of Data')
+
 plt.show()