def test_adsorption(self):
images = database_to_list('data/bajdichWO32018_ads.db')
images = images_connectivity(images)
slabs = database_to_list('data/bajdichWO32018_slabs.db')
slabs_dict = {}
for slab in slabs:
slabs_dict[slab.info['id']] = slab
for i, atoms in enumerate(images):
species = atoms.info['key_value_pairs']['species']
atoms.subsets['ads_atoms'] = \
slab_positions2ads_index(atoms, slabs[i], species)
if 'slab_atoms' not in atoms.subsets:
atoms.subsets['slab_atoms'] = slab_index(atoms)
if ('chemisorbed_atoms' not in atoms.subsets
or 'site_atoms' not in atoms.subsets
or 'ligand_atoms' not in atoms.subsets):
chemi, site, ligand = info2primary_index(atoms)
atoms.subsets['chemisorbed_atoms'] = chemi
atoms.subsets['site_atoms'] = site
atoms.subsets['ligand_atoms'] = ligand
attach_cations(atoms, anion_number=8)
charges = formal_charges(atoms)
atoms.set_initial_charges(charges)
gen = FeatureGenerator(nprocs=1)
train_fpv = default_fingerprinters(gen, 'chalcogenides')
matrix = gen.return_vec(images, train_fpv)
labels = gen.return_names(train_fpv)
if __name__ == '__main__':
for i, l in enumerate(labels):
print(i, l)
print(atoms.get_initial_charges())
self.assertTrue(len(labels) == np.shape(matrix)[1])
def test_bulk_fp_gen(self):
"""Test the feature generation."""
images = self.setup_metal()
images = images_connectivity(images)
gen = FeatureGenerator()
train_fpv = default_fingerprinters(gen, 'bulk') + [gen.bag_edges]
matrix = gen.return_vec(images, train_fpv)
labels = gen.return_names(train_fpv)
print(np.shape(matrix), print(type(matrix)))
self.assertTrue(len(labels) == np.shape(matrix)[1])
def autogen_info(images):
"""Return a list of atoms objects with atomic group information
attached to atoms.subsets.
This information is needed by some functions in the
AdsorbateFingerprintGenerator.
Parameters
----------
images : list
list of atoms objects representing adsorbates on slabs.
No further information is required in atoms.subsets.
"""
images = images_connectivity(images)
for i, atoms in tqdm(enumerate(images)):
# Pre-allocate subsets dictionary.
if not hasattr(atoms, 'subsets'):
atoms.subsets = {}
# Identify adsorbate atoms.
if 'ads_atoms' not in atoms.subsets:
ads_atoms = detect_adsorbate(atoms)
atoms.subsets['ads_atoms'] = ads_atoms
if len(ads_atoms) == 0:
continue
# Identify slab atoms.
if 'slab_atoms' not in atoms.subsets:
atoms.subsets['slab_atoms'] = slab_index(atoms)
if not (len(atoms.subsets['slab_atoms']) +
len(atoms.subsets['ads_atoms']) ==
len(atoms)):
raise AssertionError("all atoms must belong to slab or adsorbate.")
# Identify atoms at node distance 0 and 1 from the surface-ads bond.
if ('chemisorbed_atoms' not in atoms.subsets or
'site_atoms' not in atoms.subsets or
'ligand_atoms' not in atoms.subsets):
chemi, site, ligand = info2primary_index(atoms)
atoms.subsets['chemisorbed_atoms'] = chemi
atoms.subsets['site_atoms'] = site
atoms.subsets['ligand_atoms'] = ligand
# Identify surface layers.
if ('bulk_atoms' not in atoms.subsets or
'termination_atoms' not in atoms.subsets or
'subsurf_atoms' not in atoms.subsets):
bulk, term, subsurf = detect_termination(atoms)
atoms.subsets['bulk_atoms'] = bulk
atoms.subsets['termination_atoms'] = term
atoms.subsets['subsurf_atoms'] = subsurf
return images
def test_recontruction(self):
images = database_to_list('data/ads_example.db')
slabs = []
for atoms in images:
slab = atoms.copy()
slab.pop(-1)
slabs.append(slab)
images = autogen_info(images)
slabs = images_connectivity(slabs)
image_pairs = zip(images, slabs)
r_index = check_reconstructions(image_pairs)
for i in range(len(images)):
species = images[i].info['key_value_pairs']['species']
connectivity2ads_index(images[i], species)
self.assertTrue(len(r_index) == 0)
def autogen_info(images):
"""Return a list of atoms objects with atomic group information
attached to atoms.subsets.
This information is needed by some functions in the
AdsorbateFingerprintGenerator.
Parameters
----------
images : list
list of atoms objects representing adsorbates on slabs.
No further information is required in atoms.subsets.
"""
images = images_connectivity(images)
for atoms in tqdm(images):
if not hasattr(atoms, 'subsets'):
atoms.subsets = {}
if 'ads_atoms' not in atoms.subsets:
ads_atoms = detect_adsorbate(atoms)
if ads_atoms is None:
continue
else:
atoms.subsets['ads_atoms'] = ads_atoms
if 'slab_atoms' not in atoms.subsets:
atoms.subsets['slab_atoms'] = slab_index(atoms)
if ('chemisorbed_atoms' not in atoms.subsets
or 'site_atoms' not in atoms.subsets
or 'ligand_atoms' not in atoms.subsets):
chemi, site, ligand = info2primary_index(atoms)
atoms.subsets['chemisorbed_atoms'] = chemi
atoms.subsets['site_atoms'] = site
atoms.subsets['ligand_atoms'] = ligand
if ('key_value_pairs' not in atoms.subsets
or 'term' not in atoms.info['key_value_pairs']
or 'bulk' not in atoms.info['key_value_pairs']):
bulk, subsurf, term = detect_termination(atoms)
atoms.subsets['bulk_atoms'] = bulk
atoms.subsets['termination_atoms'] = term
atoms.subsets['subsurf_atoms'] = subsurf
return images