def properties(rundir):
"""Report results to properties.calc.json file in configuration directory, after checking for electronic convergence."""
output = dict()
ofile = seqquest.seqquest_io.LcaoOUT(os.path.join(rundir, "lcao.out"))
ogeom = seqquest.seqquest_io.Geom.geom(os.path.join(rundir, "lcao.geom"))
# the calculation is run on the 'sorted' POSCAR, need to report results 'unsorted'
output["atom_type"] = ogeom.type_atoms
output["atoms_per_type"] = ogeom.num_atoms
output["coord_mode"] = ofile.coord_mode
# fake unsort_dict (unsort_dict[i] == i)
unsort_dict = dict(zip(range(0, len(ogeom.basis)), range(0, len(ogeom.basis))))
# as lists
output["relaxed_forces"] = [None for i in range(len(ofile.forces))]
print(noindent.NoIndent(ofile.forces[0]))
for i, v in enumerate(ofile.forces):
output["relaxed_forces"][unsort_dict[i]] = noindent.NoIndent(ofile.forces[i])
output["relaxed_lattice"] = [noindent.NoIndent(v) for v in ofile.cell.lattice]
output["relaxed_basis"] = [None for i in range(len(ogeom.basis))]
for i, v in enumerate(ogeom.basis):
output["relaxed_basis"][unsort_dict[i]] = noindent.NoIndent(ogeom.basis[i].position)
output["relaxed_energy"] = ofile.total_energy
return output
def properties(qedir, outfilename):
"""Report results to properties.calc.json file in configuration directory, after checking for electronic convergence."""
output = dict()
qrun = quantumespresso.qeio.QErun(os.path.join(qedir, outfilename))
output["atom_type"] = qrun.atom_type
output["atoms_per_type"] = qrun.atoms_per_type
if qrun.coord_mode == "crystal":
output["coord_mode"] = "direct"
else:
output["coord_mode"] = "cartesian" + qrun.coord_mode
output["relaxed_forces"] = [
noindent.NoIndent(v) for v in list(
map(
lambda y: list(map(lambda x: x * 13.605698066 / 0.52918, y)
), qrun.forces))
] #convert Ry/bohr to eV/angst
output["relaxed_lattice"] = [
noindent.NoIndent(v) for v in list(
map(lambda y: list(map(lambda x: x * 0.52918, y)),
qrun.lattice))
] #convert bohr to angst
output["relaxed_basis"] = [noindent.NoIndent(v) for v in qrun.basis]
output[
"relaxed_energy"] = qrun.total_energy * 13.605698066 #convert Ry to eV
return output
def write_eci(proj, eci, fit_details=None, clex=None, verbose=False):
"""Write eci.json
Arguments
---------
proj: casm.project.Project
The CASM project
eci: List[(index, value)]
List of tuple containing basis function index and coefficient value:
index (int): linear index of basis function
value (float): ECI value
fit_details: Dict
Description of the fitting method used to generate the ECI, usually as output by `casm.learn.to_json`. It is added to the eci.json file under the attribute `"fit"`.
clex: casm.project.ClexDescription
Specifies where to write the ECI. Default value is `proj.settings.default_clex`.
"""
dir = proj.dir
if clex is None:
clex = proj.settings.default_clex
# read basis.json
filename = dir.basis(clex)
with open(filename, 'r') as f:
j = json.load(f)
# edit to add fitting settings
j["fit"] = fit_details
# make linear_function_index: (linear_orbit_index, cluster_function_index)
function_keys = {}
try:
linear_orbit_index = 0
for orbit in j["orbits"]:
cluster_function_index = 0
for cluster_function in orbit["cluster_functions"]:
linear_function_index = cluster_function[
"linear_function_index"]
function_keys[linear_function_index] = (linear_orbit_index,
cluster_function_index)
cluster_function_index += 1
linear_orbit_index += 1
except:
raise Exception("Formatting error in basis.json")
# edit to add eci
for index, value in eci:
linear_orbit_index = function_keys[index][0]
cluster_function_index = function_keys[index][1]
orbit = j["orbits"][linear_orbit_index]
cluster_function = orbit["cluster_functions"][cluster_function_index]
if cluster_function["linear_function_index"] != index:
msg = "Formatting error in '" + str(filename) + "': "
msg += " linear_function_index mismatch"
raise Exception(msg)
cluster_function["eci"] = value
# pretty printing -- could be improved
cspecs_params = j["bspecs"]["cluster_specs"]["params"]
if "generating_group" in cspecs_params:
cspecs_params["generating_group"] = noindent.NoIndent(
cspecs_params["generating_group"])
for entry in j["orbits"]:
sites = entry["prototype"]["sites"]
for i in range(len(sites)):
sites[i] = noindent.NoIndent(sites[i])
for site in j["prim"]["basis"]:
site["coordinate"] = noindent.NoIndent(site["coordinate"])
site["occupants"] = noindent.NoIndent(site["occupants"])
for i in range(len(j["prim"]["lattice_vectors"])):
j["prim"]["lattice_vectors"][i] = noindent.NoIndent(
j["prim"]["lattice_vectors"][i])
# write eci.json
filename = dir.eci(clex)
if verbose:
print("Writing:", filename, "\n")
with open(filename, 'w') as f:
f.write(json.dumps(j, indent=2, cls=noindent.NoIndentEncoder))
# refresh proj to reflect new eci
proj.refresh(clear_clex=True)
def write_eci(proj, eci, fit_details=None, clex=None, verbose=False):
"""
Write eci.json
Arguments
---------
proj: casm.project.Project instance
The CASM project
eci: List[(index, value)]
index (int): linear index of basis function
value (float): ECI value
fit_details: Dict
Description of the fitting method used to generate the ECI,
usually as output by casm.learn.to_json
clex: ClexDescription instance, optional, default=proj.settings.default_clex
Specifies where to write the ECI
"""
dir = proj.dir
if clex is None:
clex = proj.settings.default_clex
# read basis.json
filename = dir.basis(clex)
with open(filename, 'rb') as f:
j = json.loads(f.read().decode('utf-8'))
#print(json.dumps(j, indent=2))
# edit to add fitting settings
j["fit"] = fit_details
# edit to add eci
for index, value in eci:
j["cluster_functions"][index]["eci"] = value
# pretty printing
for entry in j["site_functions"]:
if entry["basis"] != None:
basis = entry["basis"]
for key, val in basis.items():
basis[key] = noindent.NoIndent(val)
for entry in j["cluster_functions"]:
entry["orbit"] = noindent.NoIndent(entry["orbit"])
sites = entry["prototype"]["sites"]
for i in range(len(sites)):
sites[i] = noindent.NoIndent(sites[i])
# write eci.json
filename = dir.eci(clex)
if verbose:
print("Writing:", filename, "\n")
with open(filename, 'wb') as f:
f.write(
six.u(json.dumps(j, indent=2,
cls=noindent.NoIndentEncoder)).encode('utf-8'))
# refresh proj to reflect new eci
proj.refresh(clear_clex=True)
def properties(vaspdir, super_poscarfile=None, speciesfile=None):
"""Report results to properties.calc.json file in configuration directory, after checking for electronic convergence."""
output = dict()
vrun = vasp.io.Vasprun(os.path.join(vaspdir, "vasprun.xml"))
# load the final OSZICAR, OUTCAR, and INCAR
zcar = vasp.io.Oszicar(os.path.join(vaspdir, "OSZICAR"))
ocar = vasp.io.Outcar(os.path.join(vaspdir, "OUTCAR"))
# the calculation is run on the 'sorted' POSCAR, need to report results 'unsorted'
if (super_poscarfile is not None) and (speciesfile is not None):
species_settings = vasp.io.species_settings(speciesfile)
super = vasp.io.Poscar(super_poscarfile, species_settings)
unsort_dict = super.unsort_dict()
else:
# fake unsort_dict (unsort_dict[i] == i)
unsort_dict = dict(
zip(range(0, len(vrun.basis)), range(0, len(vrun.basis))))
super = vasp.io.Poscar(os.path.join(vaspdir, "POSCAR"))
# unsort_dict:
# Returns 'unsort_dict', for which: unsorted_dict[orig_index] == sorted_index;
# unsorted_dict[sorted_index] == orig_index
# For example:
# 'unsort_dict[0]' returns the index into the unsorted POSCAR of the first atom in the sorted POSCAR
output["atom_type"] = super.type_atoms
output["atoms_per_type"] = super.num_atoms
output["coord_mode"] = vrun.coord_mode
# as lists
output["relaxed_forces"] = [None for i in range(len(vrun.forces))]
for i, v in enumerate(vrun.forces):
output["relaxed_forces"][unsort_dict[i]] = noindent.NoIndent(
vrun.forces[i])
output["relaxed_lattice"] = [
noindent.NoIndent(v) for v in vrun.lattice
]
output["relaxed_basis"] = [None for i in range(len(vrun.basis))]
for i, v in enumerate(vrun.basis):
output["relaxed_basis"][unsort_dict[i]] = noindent.NoIndent(
vrun.basis[i])
output["relaxed_energy"] = vrun.total_energy
# output["relaxed_mag_basis"] = [ None for i in range(len(vrun.basis))]
# output["relaxed_magmom"] = None
if ocar.ispin == 2:
output["relaxed_magmom"] = zcar.mag[-1]
if ocar.lorbit in [1, 2, 11, 12]:
output["relaxed_mag_basis"] = [
None for i in range(len(vrun.basis))
]
for i, v in enumerate(vrun.basis):
output["relaxed_mag_basis"][
unsort_dict[i]] = noindent.NoIndent(ocar.mag[i])
# if output["relaxed_magmom"] is None:
# output.pop("relaxed_magmom", None)
# if output["relaxed_mag_basis"][0] is None:
# output.pop("relaxed_mag_basis", None)
return output
def properties(vaspdir, initial_structurefile=None, speciesfile=None):
""" return a dict of output form a vasp directory"""
dof_info = attribute_info.AttributeInfo(initial_structurefile)
output = dict()
# load the OSZICAR and OUTCAR
zcar = vasp.io.Oszicar(os.path.join(vaspdir, "OSZICAR"))
ocar = vasp.io.Outcar(os.path.join(vaspdir, "OUTCAR"))
# the calculation is run on the 'sorted' POSCAR, need to report results 'unsorted'
if (initial_structurefile is not None) and (speciesfile is not None):
species_settings = vasp.io.species_settings(speciesfile)
initial_structure = vasp.io.Poscar(initial_structurefile,
species_settings)
unsort_dict = initial_structure.unsort_dict()
else:
# fake unsort_dict (unsort_dict[i] == i)
initial_structure = vasp.io.Poscar(os.path.join(vaspdir, "POSCAR"))
unsort_dict = dict(
zip(range(0, len(structure.basis)),
range(0, len(structure.basis))))
contcar = vasp.io.Poscar(os.path.join(vaspdir, "CONTCAR"))
# unsort_dict:
# Returns 'unsort_dict', for which: unsorted_dict[orig_index] == sorted_index;
# unsorted_dict[sorted_index] == orig_index
# For example:
# 'unsort_dict[0]' returns the index into the unsorted POSCAR of the first atom in the sorted POSCAR
output["atom_type"] = initial_structure.atom_type
#output["atoms_per_type"] = initial_structure.num_atoms
output["coord_mode"] = contcar.coord_mode
# as lists
output["lattice"] = [
noindent.NoIndent(list(v)) for v in contcar.lattice()
]
output["atom_coords"] = [None for i in range(len(contcar.basis))]
for i, ba in enumerate(contcar.basis):
output["atom_coords"][unsort_dict[i]] = noindent.NoIndent(
list(ba.position))
output["atom_dofs"] = {}
output["atom_dofs"]["force"] = {}
output["atom_dofs"]["force"]["value"] = [
None for i in range(len(ocar.forces))
]
for i, force in enumerate(ocar.forces):
output["atom_dofs"]["force"]["value"][
unsort_dict[i]] = noindent.NoIndent(force)
output["global_dofs"] = {}
output["global_dofs"]["energy"] = {}
output["global_dofs"]["energy"]["value"] = zcar.E[-1]
if dof_info.atom_dofs is not None:
if "Cmagspin" in list(dof_info.atom_dofs.keys()):
output["global_dofs"]["Cmagspin"] = {}
cmagspin_specific_output = attribute_classes.CmagspinAttr(
dof_info).vasp_output_dictionary(ocar)
output["atom_dofs"].update(cmagspin_specific_output)
#TODO: Need a better way to write global magmom. I don't like what I did here
output["global_dofs"]["Cmagspin"]["value"] = zcar.mag[-1]
#TODO: When you don't have Cmagspin but have magnetic calculations. This part can be removed if you runall magnetic calculations as Cmagspin calculations.
#TODO: Need a better way of doing this. Some code duplication here.
else:
if ocar.ispin == 2:
output["global_dofs"]["Cmagspin"] = {}
output["global_dofs"]["Cmagspin"]["value"] = zcar.mag[-1]
if ocar.lorbit in [1, 2, 11, 12]:
output["atom_dofs"]["Cmagspin"] = {}
output["atom_dofs"]["Cmagspin"]["value"] = [
None for i in range(len(contcar.basis))
]
for i, v in enumerate(contcar.basis):
output["atom_dofs"]["Cmagspin"]["value"][
unsort_dict[i]] = [
noindent.NoIndent(ocar.mag[i])
]
#TODO: Code duplication here. If you have a magnetic calculation without dofs, you still need to write magmom values. This can be removed if you run all the magnetic calculations as Cmagspin dof calculations.
#TODO: If you still want to have this particular functionality, wrap it up in a helper function to avoid code duplication.
else:
if ocar.ispin == 2:
output["global_dofs"]["Cmagspin"]["value"] = zcar.mag[-1]
if ocar.lorbit in [1, 2, 11, 12]:
output["atom_dofs"]["Cmagspin"] = {}
output["atom_dofs"]["Cmagspin"]["value"] = [
None for i in range(len(contcar.basis))
]
for i, v in enumerate(contcar.basis):
output["atom_dofs"]["Cmagspin"]["value"][
unsort_dict[i]] = [noindent.NoIndent(ocar.mag[i])]
return output