Added tests for all the files with random seed.

tests/geodesic_ts_with_hessian/test_using_mace.py

@@ -1,4 +1,12 @@
 import pytest
+import numpy as np
+
+
+@pytest.fixture(scope="session", autouse=True)
+def set_seed():
+    np.random.seed(42)  # noqa: NPY002
+
+
 import logging
 from ase.io import read
 from pathlib import Path
@@ -33,4 +41,20 @@ def test_geodesic_ts_hess_irc_mace(setup_test_environment):
     jobs = geodesic_ts_hess_irc_mace(reactant, product, calc_kwargs, logger)
 
     # Assertions
-    assert len(jobs) == 4
+    assert jobs[0]['relax_reactant']['results']['energy'] == pytest.approx(-7400.109474432057, 1e-6)
+    assert jobs[0]['relax_reactant']['results']['forces'][0, 1] == pytest.approx(2.66840467e-04, 1e-2)
+
+    assert jobs[0]['relax_product']['results']['energy'] == pytest.approx(-7395.830068714384, 1e-6)
+    assert jobs[0]['relax_product']['results']['forces'][0, 1] == pytest.approx(-0.00025790767076738774, 1e-2)
+
+    # geodesic output
+    assert jobs[0]['highest_e_atoms'].get_potential_energy() == pytest.approx(-7392.679151885447, 1e-6)
+
+    # transition state optimization output
+    assert jobs[1]['trajectory_results'][-1]['energy'] == pytest.approx(-7395.622784377439, 1e-6)
+
+    # IRC forward output
+    assert jobs[2]['trajectory_results'][-1]['energy'] == pytest.approx(-7395.809412186394, 1e-6)
+
+    # IRC reverse output
+    assert jobs[3]['trajectory_results'][-1]['energy'] == pytest.approx(-7395.787679970261, 1e-6)

tests/geodesic_ts_with_hessian/test_using_newtonnet.py

@@ -1,7 +1,13 @@
-import os
 import pytest
-import logging
+import numpy as np
+
+
+@pytest.fixture(scope="session", autouse=True)
+def set_seed():
+    np.random.seed(42)  # noqa: NPY002
 
+
+import logging
 import torch
 from ase.io import read
 from pathlib import Path
@@ -49,4 +55,20 @@ def test_geodesic_ts_hess_irc_newtonnet(setup_test_environment):
     jobs = geodesic_ts_hess_irc_newtonnet(reactant, product, calc_kwargs1, calc_kwargs2, logger)
 
     # Assertions
-    assert len(jobs) == 4
+    assert jobs[0]['relax_reactant']['results']['energy'] == pytest.approx(-68.26889038085938, 1e-6)
+    assert jobs[0]['relax_reactant']['results']['forces'][0, 1] == pytest.approx(0.0006616527098231018, 1e-2)
+
+    assert jobs[0]['relax_product']['results']['energy'] == pytest.approx(-63.780540466308594, 1e-6)
+    assert jobs[0]['relax_product']['results']['forces'][0, 1] == pytest.approx(-0.0018400131957605481, 1e-2)
+
+    # geodesic output
+    assert jobs[0]['highest_e_atoms'].get_potential_energy() == pytest.approx(-61.53276824951172, 1e-6)
+
+    # transition state optimization output
+    assert jobs[1]['trajectory_results'][-1]['energy'] == pytest.approx(-63.505672454833984, 1e-6)
+
+    # IRC forward output
+    assert jobs[2]['trajectory_results'][-1]['energy'] == pytest.approx(-67.261962890625, 1e-6)
+
+    # IRC reverse output
+    assert jobs[3]['trajectory_results'][-1]['energy'] == pytest.approx(-68.01041412353516, 1e-6)

tests/geodesic_ts_without_hessian/test_using_mace.py

@@ -1,4 +1,12 @@
 import pytest
+import numpy as np
+
+
+@pytest.fixture(scope="session", autouse=True)
+def set_seed():
+    np.random.seed(42)  # noqa: NPY002
+
+
 import logging
 from ase.io import read
 from quacc import get_settings
@@ -32,4 +40,20 @@ def test_geodesic_ts_hess_irc_mace(setup_test_environment):
     jobs = geodesic_ts_no_hess_irc_mace(reactant, product, calc_kwargs, logger)
 
     # Assertions
-    assert len(jobs) == 4
+    assert jobs[0]['relax_reactant']['results']['energy'] == pytest.approx(-7400.109474432057, 1e-6)
+    assert jobs[0]['relax_reactant']['results']['forces'][0, 1] == pytest.approx(2.66840467e-04, 1e-2)
+
+    assert jobs[0]['relax_product']['results']['energy'] == pytest.approx(-7395.830068714384, 1e-6)
+    assert jobs[0]['relax_product']['results']['forces'][0, 1] == pytest.approx(-0.00025790767076738774, 1e-2)
+
+    # geodesic output
+    assert jobs[0]['highest_e_atoms'].get_potential_energy() == pytest.approx(-7392.679151885447, 1e-6)
+
+    # transition state optimization output
+    assert jobs[1]['trajectory_results'][-1]['energy'] == pytest.approx(-7395.245196822939, 1e-6)
+
+    # IRC forward output
+    assert jobs[2]['trajectory_results'][-1]['energy'] == pytest.approx(-7395.808953241075, 1e-6)
+
+    # IRC reverse output
+    assert jobs[3]['trajectory_results'][-1]['energy'] == pytest.approx(-7396.074596733643, 1e-6)

tests/geodesic_ts_without_hessian/test_using_newtonnet.py

@@ -1,6 +1,15 @@
 import os
 import torch
 import pytest
+
+import numpy as np
+
+
+@pytest.fixture(scope="session", autouse=True)
+def set_seed():
+    np.random.seed(42)  # noqa: NPY002
+
+
 import logging
 from ase.io import read
 from quacc import get_settings
@@ -45,4 +54,20 @@ def test_geodesic_ts_hess_irc_newtonnet(setup_test_environment):
     jobs = geodesic_ts_no_hess_irc_newtonnet(reactant, product, calc_kwargs1, logger)
 
     # Assertions
-    assert len(jobs) == 4
+    assert jobs[0]['relax_reactant']['results']['energy'] == pytest.approx(-68.26889038085938, 1e-6)
+    assert jobs[0]['relax_reactant']['results']['forces'][0, 1] == pytest.approx(0.0006616527098231018, 1e-2)
+
+    assert jobs[0]['relax_product']['results']['energy'] == pytest.approx(-63.780540466308594, 1e-6)
+    assert jobs[0]['relax_product']['results']['forces'][0, 1] == pytest.approx(-0.0018400131957605481, 1e-2)
+
+    # geodesic output
+    assert jobs[0]['highest_e_atoms'].get_potential_energy() == pytest.approx(-61.53276824951172, 1e-6)
+
+    # transition state optimization output
+    assert jobs[1]['trajectory_results'][-1]['energy'] == pytest.approx(-63.742549896240234, 1e-6)
+
+    # IRC forward output
+    assert jobs[2]['trajectory_results'][-1]['energy'] == pytest.approx(-67.372802734375, 1e-6)
+
+    # IRC reverse output
+    assert jobs[3]['trajectory_results'][-1]['energy'] == pytest.approx(-67.37286376953125, 1e-6)

tests/neb_ts_with_hessian/test_using_mace.py

@@ -1,4 +1,13 @@
 import pytest
+
+import numpy as np
+
+
+@pytest.fixture(scope="session", autouse=True)
+def set_seed():
+    np.random.seed(42)  # noqa: NPY002
+
+
 import logging
 from ase.io import read
 from quacc import get_settings
@@ -33,3 +42,31 @@ def test_neb_ts_hess_irc_mace(setup_test_environment):
 
     # Assertions
     assert len(jobs) == 4
+
+    print(jobs[0]['relax_reactant']['results']['energy'])
+    print(jobs[0]['relax_reactant']['results']['forces'][0, 1])
+    print(jobs[0]['relax_product']['results']['energy'])
+    print(jobs[0]['relax_product']['results']['forces'][0, 1])
+    print(jobs[0]['neb_results']['highest_e_atoms'].get_potential_energy())
+    print(jobs[1]['trajectory_results'][-1]['energy'])
+    print(jobs[2]['trajectory_results'][-1]['energy'])
+    print(jobs[3]['trajectory_results'][-1]['energy'])
+
+    # Assertions
+    assert jobs[0]['relax_reactant']['results']['energy'] == pytest.approx(-68.26889038085938, 1e-6)
+    assert jobs[0]['relax_reactant']['results']['forces'][0, 1] == pytest.approx(0.0006616527098231, 1e-2)
+
+    assert jobs[0]['relax_product']['results']['energy'] == pytest.approx(-63.780540466308594, 1e-6)
+    assert jobs[0]['relax_product']['results']['forces'][0, 1] == pytest.approx(-0.0018400131957605481, 1e-2)
+
+    # neb output
+    assert jobs[0]['neb_results']['highest_e_atoms'].get_potential_energy() == pytest.approx(-61.5327682495, 1e-6)
+
+    # transition state optimization output
+    assert jobs[1]['trajectory_results'][-1]['energy'] == pytest.approx(-63.742549896240234, 1e-6)
+
+    # IRC forward output
+    assert jobs[2]['trajectory_results'][-1]['energy'] == pytest.approx(-67.372802734375, 1e-6)
+
+    # IRC reverse output
+    assert jobs[3]['trajectory_results'][-1]['energy'] == pytest.approx(-67.37286376953125, 1e-6)

tests/neb_ts_with_hessian/test_using_newtonnet.py

@@ -1,5 +1,15 @@
 import torch
 import pytest
+
+
+import numpy as np
+
+
+@pytest.fixture(scope="session", autouse=True)
+def set_seed():
+    np.random.seed(42)  # noqa: NPY002
+
+
 import logging
 from ase.io import read
 from pathlib import Path
@@ -23,7 +33,6 @@ def reset_default_tensor_type():
     torch.set_default_tensor_type(torch.FloatTensor)
 
 
-@pytest.mark.skip()
 def test_neb_ts_hess_irc_newtonnet(setup_test_environment):
     reactant, product = setup_test_environment
 
@@ -48,3 +57,31 @@ def test_neb_ts_hess_irc_newtonnet(setup_test_environment):
 
     # Assertions
     assert len(jobs) == 4
+
+    print(jobs[0]['relax_reactant']['results']['energy'])
+    print(jobs[0]['relax_reactant']['results']['forces'][0, 1])
+    print(jobs[0]['relax_product']['results']['energy'])
+    print(jobs[0]['relax_product']['results']['forces'][0, 1])
+    print(jobs[0]['neb_results']['highest_e_atoms'].get_potential_energy())
+    print(jobs[1]['trajectory_results'][-1]['energy'])
+    print(jobs[2]['trajectory_results'][-1]['energy'])
+    print(jobs[3]['trajectory_results'][-1]['energy'])
+
+    # Assertions
+    assert jobs[0]['relax_reactant']['results']['energy'] == pytest.approx(-68.26889038085938, 1e-6)
+    assert jobs[0]['relax_reactant']['results']['forces'][0, 1] == pytest.approx(0.0006616527098231, 1e-2)
+
+    assert jobs[0]['relax_product']['results']['energy'] == pytest.approx(-63.780540466308594, 1e-6)
+    assert jobs[0]['relax_product']['results']['forces'][0, 1] == pytest.approx(-0.0018400131957605481, 1e-2)
+
+    # neb output
+    assert jobs[0]['neb_results']['highest_e_atoms'].get_potential_energy() == pytest.approx(-61.5327682495, 1e-6)
+
+    # transition state optimization output
+    assert jobs[1]['trajectory_results'][-1]['energy'] == pytest.approx(-63.742549896240234, 1e-6)
+
+    # IRC forward output
+    assert jobs[2]['trajectory_results'][-1]['energy'] == pytest.approx(-67.372802734375, 1e-6)
+
+    # IRC reverse output
+    assert jobs[3]['trajectory_results'][-1]['energy'] == pytest.approx(-67.37286376953125, 1e-6)

tests/neb_ts_without_hessian/test_using_mace.py

@@ -1,4 +1,14 @@
 import pytest
+
+
+import numpy as np
+
+
+@pytest.fixture(scope="session", autouse=True)
+def set_seed():
+    np.random.seed(42)  # noqa: NPY002
+
+
 import logging
 from ase.io import read
 from pathlib import Path
@@ -34,3 +44,31 @@ def test_neb_ts_no_hess_irc_mace(setup_test_environment):
 
     # Assertions
     assert len(jobs) == 4
+
+    print(jobs[0]['relax_reactant']['results']['energy'])
+    print(jobs[0]['relax_reactant']['results']['forces'][0, 1])
+    print(jobs[0]['relax_product']['results']['energy'])
+    print(jobs[0]['relax_product']['results']['forces'][0, 1])
+    print(jobs[0]['neb_results']['highest_e_atoms'].get_potential_energy())
+    print(jobs[1]['trajectory_results'][-1]['energy'])
+    print(jobs[2]['trajectory_results'][-1]['energy'])
+    print(jobs[3]['trajectory_results'][-1]['energy'])
+
+    # Assertions
+    assert jobs[0]['relax_reactant']['results']['energy'] == pytest.approx(-68.26889038085938, 1e-6)
+    assert jobs[0]['relax_reactant']['results']['forces'][0, 1] == pytest.approx(0.0006616527098231, 1e-2)
+
+    assert jobs[0]['relax_product']['results']['energy'] == pytest.approx(-63.780540466308594, 1e-6)
+    assert jobs[0]['relax_product']['results']['forces'][0, 1] == pytest.approx(-0.0018400131957605481, 1e-2)
+
+    # neb output
+    assert jobs[0]['neb_results']['highest_e_atoms'].get_potential_energy() == pytest.approx(-61.5327682495, 1e-6)
+
+    # transition state optimization output
+    assert jobs[1]['trajectory_results'][-1]['energy'] == pytest.approx(-63.742549896240234, 1e-6)
+
+    # IRC forward output
+    assert jobs[2]['trajectory_results'][-1]['energy'] == pytest.approx(-67.372802734375, 1e-6)
+
+    # IRC reverse output
+    assert jobs[3]['trajectory_results'][-1]['energy'] == pytest.approx(-67.37286376953125, 1e-6)

tests/neb_ts_without_hessian/test_using_newtonnet.py

@@ -1,5 +1,15 @@
 import torch
 import pytest
+
+
+import numpy as np
+
+
+@pytest.fixture(scope="session", autouse=True)
+def set_seed():
+    np.random.seed(42)  # noqa: NPY002
+
+
 import logging
 from ase.io import read
 from pathlib import Path
@@ -45,3 +55,31 @@ def test_neb_ts_no_hess_irc_newtonnet(setup_test_environment):
 
     # Assertions
     assert len(jobs) == 4
+
+    print(jobs[0]['relax_reactant']['results']['energy'])
+    print(jobs[0]['relax_reactant']['results']['forces'][0, 1])
+    print(jobs[0]['relax_product']['results']['energy'])
+    print(jobs[0]['relax_product']['results']['forces'][0, 1])
+    print(jobs[0]['neb_results']['highest_e_atoms'].get_potential_energy())
+    print(jobs[1]['trajectory_results'][-1]['energy'])
+    print(jobs[2]['trajectory_results'][-1]['energy'])
+    print(jobs[3]['trajectory_results'][-1]['energy'])
+
+    # Assertions
+    assert jobs[0]['relax_reactant']['results']['energy'] == pytest.approx(-68.26889038085938, 1e-6)
+    assert jobs[0]['relax_reactant']['results']['forces'][0, 1] == pytest.approx(0.0006616527098231, 1e-2)
+
+    assert jobs[0]['relax_product']['results']['energy'] == pytest.approx(-63.780540466308594, 1e-6)
+    assert jobs[0]['relax_product']['results']['forces'][0, 1] == pytest.approx(-0.0018400131957605481, 1e-2)
+
+    # neb output
+    assert jobs[0]['neb_results']['highest_e_atoms'].get_potential_energy() == pytest.approx(-61.5327682495, 1e-6)
+
+    # transition state optimization output
+    assert jobs[1]['trajectory_results'][-1]['energy'] == pytest.approx(-63.742549896240234, 1e-6)
+
+    # IRC forward output
+    assert jobs[2]['trajectory_results'][-1]['energy'] == pytest.approx(-67.372802734375, 1e-6)
+
+    # IRC reverse output
+    assert jobs[3]['trajectory_results'][-1]['energy'] == pytest.approx(-67.37286376953125, 1e-6)