Add 3D structures downloaded from NIST to unit test set (#146)

.gitattributes

 *.h5 filter=lfs diff=lfs merge=lfs -text
-tests/test_data/* filter=lfs diff=lfs merge=lfs -text
\ No newline at end of file
+tests/test_data/ANI1_subset/* filter=lfs diff=lfs merge=lfs -text
+tests/test_data/NIST/* filter=lfs diff=lfs merge=lfs -text
+tools/diverse_test_set/result.json filter=lfs diff=lfs merge=lfs -text

azure/docs.yml

 queue:
-  name: Hosted Linux Preview
+  name: Hosted Ubuntu 1604
   timeoutInMinutes: 300
 
 variables:

azure/flake8.yml

 queue:
-  name: Hosted Linux Preview
+  name: Hosted Ubuntu 1604
   timeoutInMinutes: 10
 
 variables:

azure/runnable_submodules.yml

 queue:
-  name: Hosted Linux Preview
+  name: Hosted Ubuntu 1604
   timeoutInMinutes: 300
 
 variables:

azure/tests.yml

 queue:
-  name: Hosted Linux Preview
-  timeoutInMinutes: 300
+  name: Hosted Ubuntu 1604
+  timeoutInMinutes: 6000
 
 variables:
   python.version: '3.7'

azure/tools.yml

 queue:
-  name: Hosted Linux Preview
+  name: Hosted Ubuntu 1604
   timeoutInMinutes: 30
 
 variables:

tests/test_aev.py

@@ -3,6 +3,7 @@ import torchani
 import unittest
 import os
 import pickle
+import random
 
 path = os.path.dirname(os.path.realpath(__file__))
 N = 97
@@ -16,6 +17,12 @@ class TestAEV(unittest.TestCase):
         self.radial_length = self.aev_computer.radial_length()
         self.tolerance = 1e-5
 
+    def random_skip(self):
+        return False
+
+    def transform(self, x):
+        return x
+
     def _assertAEVEqual(self, expected_radial, expected_angular, aev):
         radial = aev[..., :self.radial_length]
         angular = aev[..., self.radial_length:]
@@ -28,10 +35,18 @@ class TestAEV(unittest.TestCase):
 
     def testIsomers(self):
         for i in range(N):
-            datafile = os.path.join(path, 'test_data/{}'.format(i))
+            datafile = os.path.join(path, 'test_data/ANI1_subset/{}'.format(i))
             with open(datafile, 'rb') as f:
                 coordinates, species, expected_radial, expected_angular, _, _ \
                     = pickle.load(f)
+                coordinates = torch.from_numpy(coordinates)
+                species = torch.from_numpy(species)
+                expected_radial = torch.from_numpy(expected_radial)
+                expected_angular = torch.from_numpy(expected_angular)
+                coordinates = self.transform(coordinates)
+                species = self.transform(species)
+                expected_radial = self.transform(expected_radial)
+                expected_angular = self.transform(expected_angular)
                 _, aev = self.aev_computer((species, coordinates))
                 self._assertAEVEqual(expected_radial, expected_angular, aev)
 
@@ -39,9 +54,17 @@ class TestAEV(unittest.TestCase):
         species_coordinates = []
         radial_angular = []
         for i in range(N):
-            datafile = os.path.join(path, 'test_data/{}'.format(i))
+            datafile = os.path.join(path, 'test_data/ANI1_subset/{}'.format(i))
             with open(datafile, 'rb') as f:
                 coordinates, species, radial, angular, _, _ = pickle.load(f)
+                coordinates = torch.from_numpy(coordinates)
+                species = torch.from_numpy(species)
+                radial = torch.from_numpy(radial)
+                angular = torch.from_numpy(angular)
+                coordinates = self.transform(coordinates)
+                species = self.transform(species)
+                radial = self.transform(radial)
+                angular = self.transform(angular)
                 species_coordinates.append((species, coordinates))
                 radial_angular.append((radial, angular))
         species, coordinates = torchani.utils.pad_coordinates(
@@ -55,6 +78,20 @@ class TestAEV(unittest.TestCase):
             start += conformations
             self._assertAEVEqual(expected_radial, expected_angular, aev_)
 
+    def testNIST(self):
+        datafile = os.path.join(path, 'test_data/NIST/all')
+        with open(datafile, 'rb') as f:
+            data = pickle.load(f)
+            for coordinates, species, radial, angular, _, _ in data:
+                if self.random_skip():
+                    continue
+                coordinates = torch.from_numpy(coordinates).to(torch.float)
+                species = torch.from_numpy(species)
+                radial = torch.from_numpy(radial).to(torch.float)
+                angular = torch.from_numpy(angular).to(torch.float)
+                _, aev = self.aev_computer((species, coordinates))
+                self._assertAEVEqual(radial, angular, aev)
+
 
 class TestAEVASENeighborList(TestAEV):
 
@@ -62,6 +99,14 @@ class TestAEVASENeighborList(TestAEV):
         super(TestAEVASENeighborList, self).setUp()
         self.aev_computer.neighborlist = torchani.ase.NeighborList()
 
+    def transform(self, x):
+        """To reduce the size of test cases for faster test speed"""
+        return x[:2, ...]
+
+    def random_skip(self):
+        """To reduce the size of test cases for faster test speed"""
+        return random.random() < 0.95
+
 
 if __name__ == '__main__':
     unittest.main()