slight changes to descriptors and prior

surrogate/test_gpr.py

@@ -2,6 +2,46 @@ import numpy as np
 import unittest
 from gpr import gpr
 
+from ase.io import read
+
+# old gpr
+from gaussComparator import gaussComparator
+from featureCalculators_multi.angular_fingerprintFeature_cy import Angular_Fingerprint
+from delta_functions_multi.delta import delta as deltaFunc
+from GPR import GPR
+
+def initialize_old_gpr(atoms):
+    ### Set up feature ###
+
+    # Radial part
+    Rc1 = 6
+    binwidth1 = 0.2
+    sigma1 = 0.2
+    
+    # Angular part
+    Rc2 = 4
+    Nbins2 = 30
+    sigma2 = 0.2
+    gamma = 2
+    
+    # Radial/angular weighting
+    eta = 20
+    use_angular = True
+    
+    # Initialize feature
+    featureCalculator = Angular_Fingerprint(atoms, Rc1=Rc1, Rc2=Rc2, binwidth1=binwidth1, Nbins2=Nbins2, sigma1=sigma1, sigma2=sigma2, gamma=gamma, eta=eta, use_angular=use_angular)
+
+    kernel = C(10, (1e1, 1e6)) * (C(1, (1, 1)) * RBF(10, (1,1000)) + C(0.01, (0.01, 0.01)) * RBF(10, (1,1000)) + WhiteKernel(1e-5, (1e-6,1e-2)))
+    delta = deltaFunc(atoms=a, rcut=6)
+    gpr = GPR(kernel=kernel,
+          featureCalculator=featureCalculator,
+          delta_function=delta,
+          bias_func=None,
+          optimize=False,
+          n_restarts_optimizer=1)
+
+    return gpr
+
 class test_kernel(unittest.TestCase):
 
     @classmethod
@@ -15,30 +55,22 @@ class test_kernel(unittest.TestCase):
     def setUp(self):
         print('setUp')
         #self.kernel = gauss_kernel()
-        self.kernel = double_gauss_kernel()
+        a = read('structures.traj', index='0')
+        self.gpr_old = initialize_old_gpr(a)
+        self.gpr = gpr()
 
     def tearDown(self):
         print('tearDown\n')
     
-    def test_jac(self):
-        x1 = np.array([1.,2.,3.])
-        x2 = np.array([1.5,2.,1.])
-        x3 = np.array([3.,1.,1.])
-        y = np.c_[x1,x2,x3].T
-        np.testing.assert_almost_equal(self.kernel.kernel_jacobian(x1,x2),
-                                       self.kernel.numerical_jacobian(x1,x2))
-        np.testing.assert_almost_equal(self.kernel.kernel_jacobian(x1,y),
-                                       self.kernel.numerical_jacobian(x1,y))
-        np.testing.assert_almost_equal(self.kernel.kernel_jacobian(x2,y),
-                                       self.kernel.numerical_jacobian(x2,y))
-
-    def test_hyper_jac(self):
-        x1 = np.array([1.,2.,3.])
-        x2 = np.array([1.5,2.,1.])
-        x3 = np.array([3.,1.,1.])
-        X = np.c_[x1,x2,x3].T
-        np.testing.assert_almost_equal(self.kernel.kernel_hyperparameter_gradient(X),
-                                       self.kernel.numerical_hyperparameter_gradient(X))
+    def test_compare_with_old(self):
+        traj = read('structures.traj', index=':50')
+        traj_train = traj[:40]
+        traj_predict = traj[40:]
+
+        self.gpr.
+
+    def test_forces(self):
+        pass
 
 if __name__ == '__main__':
     unittest.main()