Fixed ARAD wrapper bug (#6)

Author: andersx

src/wrappers.py

@@ -27,6 +27,7 @@
 from .fkernels import fget_vector_kernels_laplacian
 
 from .arad_kernels import get_atomic_kernels_arad
+from .arad_kernels import get_atomic_symmetric_kernels_arad
 
 
 def get_atomic_kernels_laplacian(mols1, mols2, sigmas):
@@ -100,13 +101,13 @@ def get_atomic_kernels_gaussian(mols1, mols2, sigmas):
 def arad_kernels(mols1, mols2, sigmas,
         width=0.2, cut_distance=5.0, r_width=1.0, c_width=0.5):
 
-    amax = mol1[0].arad_descriptor.shape[1]
+    amax = mols1[0].arad_representation.shape[0]
 
     nm1 = len(mols1)
     nm2 = len(mols2)
 
-    X1 = np.array([mol.arad_descriptor for mol in mols1]).reshape((nm1,amax,5,amax))
-    X2 = np.array([mol.arad_descriptor for mol in mols2]).reshape((nm2,amax,5,amax))
+    X1 = np.array([mol.arad_representation for mol in mols1]).reshape((nm1,amax,5,amax))
+    X2 = np.array([mol.arad_representation for mol in mols2]).reshape((nm2,amax,5,amax))
 
     Z1 = [mol.nuclear_charges for mol in mols1]
     Z2 = [mol.nuclear_charges for mol in mols2]
@@ -120,15 +121,15 @@ def arad_kernels(mols1, mols2, sigmas,
 def arad_symmetric_kernels(mols1, sigmas,
         width=0.2, cut_distance=5.0, r_width=1.0, c_width=0.5):
 
-    amax = mol1[0].arad_descriptor.shape[1]
+    amax = mols1[0].arad_representation.shape[0]
 
     nm1 = len(mols1)
 
-    X1 = np.array([mol.arad_descriptor for mol in mols1]).reshape((nm1,amax,5,amax))
+    X1 = np.array([mol.arad_representation for mol in mols1]).reshape((nm1,amax,5,amax))
 
     Z1 = [mol.nuclear_charges for mol in mols1]
 
-    K = get_symmetric_atomic_kernels_arad(X1, Z1, sigmas, \
+    K = get_atomic_symmetric_kernels_arad(X1, Z1, sigmas, \
         width=width, cut_distance=cut_distance, r_width=r_width, c_width=c_width)
 
     return K

tests/test_wrappers.py

@@ -1 +1,74 @@
-# Test
+import qml
+import numpy as np
+
+from qml.wrappers import arad_kernels, arad_symmetric_kernels
+
+def get_energies(filename):
+    """ Returns a dictionary with heats of formation for each xyz-file.
+    """
+
+    f = open(filename, "r")
+    lines = f.readlines()
+    f.close()
+
+    energies = dict()
+
+    for line in lines:
+        tokens = line.split()
+
+        xyz_name = tokens[0]
+        hof = float(tokens[1])
+
+        energies[xyz_name] = hof
+
+    return energies
+
+
+def test_arad_wrapper():
+
+    # Parse file containing PBE0/def2-TZVP heats of formation and xyz filenames
+    data = get_energies("tests/hof_qm7.txt")
+
+    # Generate a list of qml.Compound() objects
+    mols = []
+
+    for xyz_file in sorted(data.keys())[:50]:
+
+        # Initialize the qml.Compound() objects
+        mol = qml.Compound(xyz="tests/qm7/" + xyz_file)
+
+        # Associate a property (heat of formation) with the object
+        mol.properties = data[xyz_file]
+
+        # This is a Molecular Coulomb matrix sorted by row norm
+        mol.generate_arad_representation(size=23)
+
+        mols.append(mol)
+
+
+    # Shuffle molecules
+    np.random.seed(666)
+    np.random.shuffle(mols)
+
+    # Make training and test sets
+    n_test  = 10
+    n_train = 40
+
+    training = mols[:n_train]
+    test  = mols[-n_test:]
+
+    sigmas = [10.0, 100.0]
+   
+    
+    K1 = arad_symmetric_kernels(training, sigmas)
+    assert np.all(K1 > 0.0), "ERROR: ARAD symmetric kernel negative"
+    assert np.invert(np.all(np.isnan(K1))), "ERROR: ARAD symmetric kernel contains NaN"
+    
+
+    K2 = arad_kernels(training, test, sigmas)
+    assert np.all(K2 > 0.0), "ERROR: ARAD symmetric kernel negative"
+    assert np.invert(np.all(np.isnan(K2))), "ERROR: ARAD symmetric kernel contains NaN"
+
+if __name__ == "__main__":
+
+    test_arad_wrapper()