def test_replicate_gp():
"""
Based on gp_test_al.out, ensures that given hyperparameters and DFT calls
a GP model can be reproduced and correctly re-predict forces and
uncertainties
:return:
"""
os.system('cp test_files/sample_h2_otf.out .')
parsed = OtfAnalysis('sample_h2_otf.out')
positions = parsed.position_list
forces = parsed.force_list
gp_model = parsed.make_gp()
structures = parsed.output_md_structures()
assert np.isclose(structures[-1].positions, positions[-1]).all()
assert np.isclose(structures[-1].forces, forces[-1]).all()
final_structure = structures[-1]
pred_for, pred_stds = predict_on_structure(final_structure, gp_model)
assert np.isclose(final_structure.forces, pred_for).all()
assert np.isclose(final_structure.stds, pred_stds).all()
set_of_structures = structures[-3:-1]
for structure in set_of_structures:
pred_for, pred_stds = predict_on_structure(structure, gp_model)
assert np.isclose(structure.forces, pred_for, atol=1e-6).all()
assert np.isclose(structure.stds, pred_stds, atol=1e-6).all()
os.system('rm sample_slab_otf.out')
def test_replicate_gp():
"""
Based on gp_test_al.out, ensures that given hyperparameters and DFT calls
a GP model can be reproduced and correctly re-predict forces and
uncertainties
:return:
"""
parsed = OtfAnalysis('test_files/VelocityVerlet.log')
positions = parsed.position_list
forces = parsed.force_list
gp_model = parsed.make_gp(kernel_name="two_plus_three_body_mc")
structures = parsed.output_md_structures()
assert np.isclose(structures[-1].positions, positions[-1]).all()
assert np.isclose(structures[-1].forces, forces[-1]).all()
final_structure = structures[-1]
pred_for, pred_stds = predict_on_structure(final_structure, gp_model)
assert np.isclose(final_structure.forces, pred_for, rtol=1e-3).all()
assert np.isclose(final_structure.stds, pred_stds, rtol=1e-3).all()
set_of_structures = structures[-3:-1]
for structure in set_of_structures:
pred_for, pred_stds = predict_on_structure(structure, gp_model)
assert np.isclose(structure.forces, pred_for, rtol=1e-3,
atol=1e-6).all()
assert np.isclose(structure.stds, pred_stds, rtol=1e-3,
atol=1e-6).all()
def test_predict_efs(two_plus_three_gp):
test_structure, _ = \
get_random_structure(np.eye(3), [1, 2], 3)
ens, forces, stresses, en_stds, force_stds, stress_stds = \
predict_on_structure_efs(test_structure, two_plus_three_gp)
forces_2, force_stds_2 = \
predict_on_structure(test_structure, two_plus_three_gp)
ens_p, forces_p, stresses_p, en_stds_p, force_stds_p, stress_stds_p = \
predict_on_structure_efs_par(test_structure, two_plus_three_gp)
# Check agreement between efs and standard prediction.
assert (np.isclose(forces, forces_2).all())
assert (np.isclose(force_stds, force_stds_2).all())
# Check agreement between serial and parallel efs methods.
assert (np.isclose(ens, ens_p).all())
assert (np.isclose(forces, forces_p).all())
assert (np.isclose(stresses, stresses_p).all())
assert (np.isclose(en_stds, en_stds_p).all())
assert (np.isclose(force_stds, force_stds_p).all())
assert (np.isclose(stress_stds, stress_stds_p).all())
# Check that the prediction has been recorded within the structure.
assert(np.equal(stress_stds, test_structure.partial_stress_stds).all())
def test_remove_force_data():
"""
Train a GP on one fake structure. Store forces from prediction.
Add a new fake structure and ensure predictions change; then remove
the structure and ensure predictions go back to normal.
:return:
"""
test_structure, forces = get_random_structure(5.0 * np.eye(3), ["H", "Be"],
5)
test_structure_2, forces_2 = get_random_structure(5.0 * np.eye(3),
["H", "Be"], 5)
gp = GaussianProcess(kernels=["twobody"], cutoffs={"twobody": 0.8})
gp.update_db(test_structure, forces)
with raises(ValueError):
gp.remove_force_data(1000000)
init_forces, init_stds = predict_on_structure(test_structure,
gp,
write_to_structure=False)
init_forces_2, init_stds_2 = predict_on_structure(test_structure_2,
gp,
write_to_structure=False)
# Alternate adding in the entire structure and adding in only one atom.
for custom_range in [None, [0]]:
# Add in data and ensure the predictions change in reponse
gp.update_db(test_structure_2, forces_2, custom_range=custom_range)
new_forces, new_stds = predict_on_structure(test_structure,
gp,
write_to_structure=False)
new_forces_2, new_stds_2 = predict_on_structure(
test_structure_2, gp, write_to_structure=False)
assert not np.array_equal(init_forces, new_forces)
assert not np.array_equal(init_forces_2, new_forces_2)
assert not np.array_equal(init_stds, new_stds)
assert not np.array_equal(init_stds_2, new_stds_2)
# Remove that data and test to see that the predictions revert to
# what they were previously
if custom_range == [0]:
popped_strucs, popped_forces = gp.remove_force_data(5)
else:
popped_strucs, popped_forces = gp.remove_force_data(
[5, 6, 7, 8, 9])
for i in range(len(popped_forces)):
assert np.array_equal(popped_forces[i], forces_2[i])
assert np.array_equal(popped_strucs[i].structure.positions,
test_structure_2.positions)
final_forces, final_stds = predict_on_structure(
test_structure, gp, write_to_structure=False)
final_forces_2, final_stds_2 = predict_on_structure(
test_structure_2, gp, write_to_structure=False)
assert np.array_equal(init_forces, final_forces)
assert np.array_equal(init_stds, final_stds)
assert np.array_equal(init_forces_2, final_forces_2)
assert np.array_equal(init_stds_2, final_stds_2)
