def DMSP_directory_builder(filepath,
dmsp_predictions_dict,
criteria=no_criteria):
''' Builds out the dmsp directory tree inside the given filepath '''
''' Saves the POSCAR to the appropriate locations within the directory tree '''
''' Needs the dictionary values to be lists of pymatgen.alchemy.materials.TransformedStructure objects '''
''' This way the 'source' tag in the .history dictionary can be used to name the directories '''
''' If an mp-id directory already exists, count is added to the end of the path during directory creation '''
''' References the oxide_check functions as criteria; no_criteria always returns True, meaning criteria was passed '''
dls = DLSVolumePredictor(min_scaling=0.5, max_scaling=2)
for key in dmsp_predictions_dict.keys():
compound_directory_name = key.replace(' ', '_')
compound_directory_path = filepath + '/%s' % compound_directory_name
for structure_object in dmsp_predictions_dict[
key]: # for pymatgen.alchemy.materials.TransformedStructure object
structure = structure_object.final_structure
prim_check = SpacegroupAnalyzer(structure)
if prim_check.find_primitive() != None:
structure = prim_check.find_primitive(
) # get the primitive structure, if it exists
else:
continue
criteria_check = criteria(structure)
if os.path.isdir(
compound_directory_path
) or criteria_check == False: # pre-existing directories, non-oxides
continue
else:
os.mkdir(compound_directory_path)
structure_directory_name = structure_object.history[0][
'source']
structure_directory_path = compound_directory_path + '/%s' % structure_directory_name
scaled_structure = dls.get_predicted_structure(structure)
count = 1
if os.path.isdir(structure_directory_path
): # if mp-id directory already exists
numbered_directory_path = structure_directory_path + '_%s' % count
os.mkdir(numbered_directory_path)
scaled_structure.to(fmt='poscar',
filename=numbered_directory_path +
'/POSCAR')
count += 1
else:
os.mkdir(structure_directory_path)
scaled_structure.to(fmt='poscar',
filename=structure_directory_path +
'/POSCAR')
return
def refine_and_resize_structure(struct, refine_cell=True, resize_volume=True):
if resize_volume:
dls = DLSVolumePredictor()
struct = dls.get_predicted_structure(struct)
struct.apply_strain(0.5)
if refine_cell:
sga = SpacegroupAnalyzer(struct)
# SpacegroupAnalyzer.get_primitive_standard_structure may return incorrect structures
# So we avoid to use SpacegroupAnalyzer.get_primitive_standard_structure
struct = sga.get_refined_structure()
return struct
def volume_predict(structure: Structure) -> (Structure, float):
'''
Returns the scaled structure and volume of given structure according to
pymatgen's prediction
@in
- structure, Structure, given structure
@out
- Structure, scaled structure
- float, volume of the scaled strcture
'''
dls = DLSVolumePredictor()
st = structure
dls_st = dls.get_predicted_structure(st)
volume = dls.predict(st)
return (dls_st, volume)
def test_predict(self):
p = DLSVolumePredictor()
p_fast = DLSVolumePredictor(
cutoff=0.0) # for speed on compressed cells
fen = Structure.from_file(os.path.join(dir_path, "FeN_mp-6988.cif"))
self.assertAlmostEqual(p.predict(fen), 18.2252568873)
fen.scale_lattice(3.0)
self.assertAlmostEqual(p.predict(fen), 18.2252568873)
fen.scale_lattice(0.24)
self.assertAlmostEqual(p.predict(fen), 18.2252568873)
lfpo = PymatgenTest.get_structure("LiFePO4")
lfpo.scale_lattice(10.1)
self.assertAlmostEqual(p.predict(lfpo), 291.62094410192924)
lfpo.scale_lattice(0.2)
self.assertAlmostEqual(p_fast.predict(lfpo), 291.62094410192924)
lmpo = PymatgenTest.get_structure("LiFePO4")
lmpo.replace_species({"Fe": "Mn"})
self.assertAlmostEqual(p.predict(lmpo), 290.795329052)
def test_predict(self):
p = DLSVolumePredictor()
p_fast = DLSVolumePredictor(cutoff=0.0) # for speed on compressed cells
fen = Structure.from_file(os.path.join(dir_path, "FeN_mp-6988.cif"))
self.assertAlmostEqual(p.predict(fen), 18.2252568873)
fen.scale_lattice(3.0)
self.assertAlmostEqual(p.predict(fen), 18.2252568873)
fen.scale_lattice(0.24)
self.assertAlmostEqual(p.predict(fen), 18.2252568873)
lfpo = PymatgenTest.get_structure("LiFePO4")
lfpo.scale_lattice(10.1)
self.assertAlmostEqual(p.predict(lfpo), 291.62094410192924)
lfpo.scale_lattice(0.2)
self.assertAlmostEqual(p_fast.predict(lfpo), 291.62094410192924)
lmpo = PymatgenTest.get_structure("LiFePO4")
lmpo.replace_species({"Fe": "Mn"})
self.assertAlmostEqual(p.predict(lmpo), 290.795329052)
def test_predict(self):
p = DLSVolumePredictor()
p_fast = DLSVolumePredictor(cutoff=0.0) # for speed on compressed cells
p_nolimit = DLSVolumePredictor(min_scaling=None, max_scaling=None) # no limits on scaling
fen = Structure.from_file(os.path.join(dir_path, "FeN_mp-6988.cif"))
self.assertAlmostEqual(p.predict(fen), 18.2252568873)
fen.scale_lattice(fen.volume * 3.0)
self.assertAlmostEqual(p_nolimit.predict(fen), 18.2252568873)
self.assertAlmostEqual(p.predict(fen), fen.volume * 0.5)
fen.scale_lattice(fen.volume * 0.1)
self.assertAlmostEqual(p_nolimit.predict(fen), 18.2252568873)
self.assertAlmostEqual(p.predict(fen), fen.volume * 1.5)
self.assertAlmostEqual(p_fast.predict(fen), fen.volume * 1.5)
lfpo = PymatgenTest.get_structure("LiFePO4")
lfpo.scale_lattice(lfpo.volume * 3.0)
self.assertAlmostEqual(p_nolimit.predict(lfpo), 291.62094410192924)
self.assertAlmostEqual(p.predict(lfpo), lfpo.volume * 0.5)
lfpo.scale_lattice(lfpo.volume * 0.1)
self.assertAlmostEqual(p_nolimit.predict(lfpo), 291.62094410192924)
self.assertAlmostEqual(p.predict(lfpo), lfpo.volume * 1.5)
self.assertAlmostEqual(p_fast.predict(lfpo), lfpo.volume * 1.5)
lmpo = PymatgenTest.get_structure("LiFePO4")
lmpo.replace_species({"Fe": "Mn"})
self.assertAlmostEqual(p.predict(lmpo), 290.795329052)
import numpy as np
import glob
from tqdm import tqdm
from ase.io import read,write
from pymatgen.io.ase import AseAtomsAdaptor
from pymatgen.analysis.structure_prediction.volume_predictor import DLSVolumePredictor
lists = glob.glob('*.cif')
for ll in tqdm(lists):
atoms = read(ll)
struct = AseAtomsAdaptor.get_structure(atoms)
v0 = struct.volume
dls_predictor = DLSVolumePredictor()
ref_struct = dls_predictor.get_predicted_structure(struct)
v1 = ref_struct.volume
name = ll.split('.')[0]+'_dlsVP.cif'
ref_struct.to(filename=name)
print(ll.split('.')[0],(v1/v0)**(1./3.))