@@ -0,0 +1,399 @@
+import numpy as np%0Aimport time%0A%0Adef evaluate(query):%0A    noiseless_g  = lambda x: 10*np.sin(x) - x%0A    g            = lambda x: noiseless_g(x) + np.random.randn()/10 # Define the hidden function%0A%0A    %0A    dataset_X = np.atleast_2d(query)%0A    print dataset_X%0A    dataset_Y = np.asarray(%5B%5Bg(dataset_X%5B0, :%5D)%5B0%5D%5D%5D)%0A    dataset = np.concatenate((dataset_X, dataset_Y), axis=1)%0A    return dataset%0A%0A%0A    %0A

Include evaluate model