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train | ScrTask.open_scr | Open the SIGRES file located in the in self.outdir.
Returns :class:`ScrFile` object, None if file could not be found or file is not readable. | pymatgen/io/abinit/tasks.py | def open_scr(self):
"""
Open the SIGRES file located in the in self.outdir.
Returns :class:`ScrFile` object, None if file could not be found or file is not readable.
"""
scr_path = self.scr_path
if not scr_path:
logger.critical("%s didn't produce a SCR.nc fil... | def open_scr(self):
"""
Open the SIGRES file located in the in self.outdir.
Returns :class:`ScrFile` object, None if file could not be found or file is not readable.
"""
scr_path = self.scr_path
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train | SigmaTask.sigres_path | Absolute path of the SIGRES file. Empty string if file is not present. | pymatgen/io/abinit/tasks.py | def sigres_path(self):
"""Absolute path of the SIGRES file. Empty string if file is not present."""
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"""Absolute path of the SIGRES file. Empty string if file is not present."""
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train | SigmaTask.open_sigres | Open the SIGRES file located in the in self.outdir.
Returns :class:`SigresFile` object, None if file could not be found or file is not readable. | pymatgen/io/abinit/tasks.py | def open_sigres(self):
"""
Open the SIGRES file located in the in self.outdir.
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Open the SIGRES file located in the in self.outdir.
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train | SigmaTask.get_scissors_builder | Returns an instance of :class:`ScissorsBuilder` from the SIGRES file.
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"""
Returns an instance of :class:`ScissorsBuilder` from the SIGRES file.
Raise:
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"""
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return Sciss... | def get_scissors_builder(self):
"""
Returns an instance of :class:`ScissorsBuilder` from the SIGRES file.
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train | BseTask.restart | BSE calculations with Haydock can be restarted only if we have the
excitonic Hamiltonian and the HAYDR_SAVE file. | pymatgen/io/abinit/tasks.py | def restart(self):
"""
BSE calculations with Haydock can be restarted only if we have the
excitonic Hamiltonian and the HAYDR_SAVE file.
"""
# TODO: This version seems to work but the main output file is truncated
# TODO: Handle restart if CG method is used
# TODO... | def restart(self):
"""
BSE calculations with Haydock can be restarted only if we have the
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# TODO: This version seems to work but the main output file is truncated
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train | BseTask.mdf_path | Absolute path of the MDF file. Empty string if file is not present. | pymatgen/io/abinit/tasks.py | def mdf_path(self):
"""Absolute path of the MDF file. Empty string if file is not present."""
# Lazy property to avoid multiple calls to has_abiext.
try:
return self._mdf_path
except AttributeError:
path = self.outdir.has_abiext("MDF.nc")
if path: self... | def mdf_path(self):
"""Absolute path of the MDF file. Empty string if file is not present."""
# Lazy property to avoid multiple calls to has_abiext.
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train | BseTask.open_mdf | Open the MDF file located in the in self.outdir.
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Open the MDF file located in the in self.outdir.
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"""
mdf_path = self.mdf_path
if not mdf_path:
logger.critical("%s didn't produce a MDF file in %s... | def open_mdf(self):
"""
Open the MDF file located in the in self.outdir.
Returns :class:`MdfFile` object, None if file could not be found or file is not readable.
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mdf_path = self.mdf_path
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train | OpticTask.set_workdir | Set the working directory of the task. | pymatgen/io/abinit/tasks.py | def set_workdir(self, workdir, chroot=False):
"""Set the working directory of the task."""
super().set_workdir(workdir, chroot=chroot)
# Small hack: the log file of optics is actually the main output file.
self.output_file = self.log_file | def set_workdir(self, workdir, chroot=False):
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super().set_workdir(workdir, chroot=chroot)
# Small hack: the log file of optics is actually the main output file.
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train | OpticTask.set_vars | Optic does not use `get` or `ird` variables hence we should never try
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kwargs.update(dict(*args))
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train | OpticTask.filesfile_string | String with the list of files and prefixes needed to execute ABINIT. | pymatgen/io/abinit/tasks.py | def filesfile_string(self):
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lines = []
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train | OpticTask.ddk_filepaths | Returns (at runtime) the absolute path of the DDK files produced by the DDK runs. | pymatgen/io/abinit/tasks.py | def ddk_filepaths(self):
"""Returns (at runtime) the absolute path of the DDK files produced by the DDK runs."""
# This to support new version of optic that used DDK.nc
paths = [ddk_task.outdir.has_abiext("DDK.nc") for ddk_task in self.ddk_nodes]
if all(p for p in paths):
ret... | def ddk_filepaths(self):
"""Returns (at runtime) the absolute path of the DDK files produced by the DDK runs."""
# This to support new version of optic that used DDK.nc
paths = [ddk_task.outdir.has_abiext("DDK.nc") for ddk_task in self.ddk_nodes]
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train | OpticTask.make_input | Construct and write the input file of the calculation. | pymatgen/io/abinit/tasks.py | def make_input(self):
"""Construct and write the input file of the calculation."""
# Set the file paths.
all_files ={"ddkfile_" + str(n + 1): ddk for n, ddk in enumerate(self.ddk_filepaths)}
all_files.update({"wfkfile": self.wfk_filepath})
files_nml = {"FILES": all_files}
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# Set the file paths.
all_files ={"ddkfile_" + str(n + 1): ddk for n, ddk in enumerate(self.ddk_filepaths)}
all_files.update({"wfkfile": self.wfk_filepath})
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train | OpticTask.reset_from_scratch | restart from scratch, this is to be used if a job is restarted with more resources after a crash | pymatgen/io/abinit/tasks.py | def reset_from_scratch(self):
"""
restart from scratch, this is to be used if a job is restarted with more resources after a crash
"""
# Move output files produced in workdir to _reset otherwise check_status continues
# to see the task as crashed even if the job did not run
... | def reset_from_scratch(self):
"""
restart from scratch, this is to be used if a job is restarted with more resources after a crash
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train | AnaddbTask.temp_shell_task | Build a :class:`AnaddbTask` with a temporary workdir. The task is executed via
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Args:
mpi_procs: Number of MPI processes to use.
anaddb_input: string with the anaddb variables.
ddb_node: The nod... | pymatgen/io/abinit/tasks.py | def temp_shell_task(cls, inp, ddb_node, mpi_procs=1,
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"""
Build a :class:`AnaddbTask` with a temporary workdir. The task is executed via
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... | materialsproject/pymatgen | python | https://github.com/materialsproject/pymatgen/blob/4ca558cf72f8d5f8a1f21dfdfc0181a971c186da/pymatgen/io/abinit/tasks.py#L4524-L4545 | [
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train | AnaddbTask.filesfile_string | String with the list of files and prefixes needed to execute ABINIT. | pymatgen/io/abinit/tasks.py | def filesfile_string(self):
"""String with the list of files and prefixes needed to execute ABINIT."""
lines = []
app = lines.append
app(self.input_file.path) # 1) Path of the input file
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train | AnaddbTask.ddb_filepath | Returns (at runtime) the absolute path of the input DDB file. | pymatgen/io/abinit/tasks.py | def ddb_filepath(self):
"""Returns (at runtime) the absolute path of the input DDB file."""
# This is not very elegant! A possible approach could to be path self.ddb_node.outdir!
if isinstance(self.ddb_node, FileNode): return self.ddb_node.filepath
path = self.ddb_node.outdir.has_abiext(... | def ddb_filepath(self):
"""Returns (at runtime) the absolute path of the input DDB file."""
# This is not very elegant! A possible approach could to be path self.ddb_node.outdir!
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train | AnaddbTask.md_filepath | Returns (at runtime) the absolute path of the input MD file. | pymatgen/io/abinit/tasks.py | def md_filepath(self):
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"""Returns (at runtime) the absolute path of the input MD file."""
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train | AnaddbTask.gkk_filepath | Returns (at runtime) the absolute path of the input GKK file. | pymatgen/io/abinit/tasks.py | def gkk_filepath(self):
"""Returns (at runtime) the absolute path of the input GKK file."""
if self.gkk_node is None: return "GKK_FILE_DOES_NOT_EXIST"
if isinstance(self.gkk_node, FileNode): return self.gkk_node.filepath
path = self.gkk_node.outdir.has_abiext("GKK")
return path ... | def gkk_filepath(self):
"""Returns (at runtime) the absolute path of the input GKK file."""
if self.gkk_node is None: return "GKK_FILE_DOES_NOT_EXIST"
if isinstance(self.gkk_node, FileNode): return self.gkk_node.filepath
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train | AnaddbTask.ddk_filepath | Returns (at runtime) the absolute path of the input DKK file. | pymatgen/io/abinit/tasks.py | def ddk_filepath(self):
"""Returns (at runtime) the absolute path of the input DKK file."""
if self.ddk_node is None: return "DDK_FILE_DOES_NOT_EXIST"
if isinstance(self.ddk_node, FileNode): return self.ddk_node.filepath
path = self.ddk_node.outdir.has_abiext("DDK")
return path ... | def ddk_filepath(self):
"""Returns (at runtime) the absolute path of the input DKK file."""
if self.ddk_node is None: return "DDK_FILE_DOES_NOT_EXIST"
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train | AnaddbTask.open_phbst | Open PHBST file produced by Anaddb and returns :class:`PhbstFile` object. | pymatgen/io/abinit/tasks.py | def open_phbst(self):
"""Open PHBST file produced by Anaddb and returns :class:`PhbstFile` object."""
from abipy.dfpt.phonons import PhbstFile
phbst_path = os.path.join(self.workdir, "run.abo_PHBST.nc")
if not phbst_path:
if self.status == self.S_OK:
logger.cr... | def open_phbst(self):
"""Open PHBST file produced by Anaddb and returns :class:`PhbstFile` object."""
from abipy.dfpt.phonons import PhbstFile
phbst_path = os.path.join(self.workdir, "run.abo_PHBST.nc")
if not phbst_path:
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train | AnaddbTask.open_phdos | Open PHDOS file produced by Anaddb and returns :class:`PhdosFile` object. | pymatgen/io/abinit/tasks.py | def open_phdos(self):
"""Open PHDOS file produced by Anaddb and returns :class:`PhdosFile` object."""
from abipy.dfpt.phonons import PhdosFile
phdos_path = os.path.join(self.workdir, "run.abo_PHDOS.nc")
if not phdos_path:
if self.status == self.S_OK:
logger.cr... | def open_phdos(self):
"""Open PHDOS file produced by Anaddb and returns :class:`PhdosFile` object."""
from abipy.dfpt.phonons import PhdosFile
phdos_path = os.path.join(self.workdir, "run.abo_PHDOS.nc")
if not phdos_path:
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train | structure_from_ncdata | Reads and returns a pymatgen structure from a NetCDF file
containing crystallographic data in the ETSF-IO format.
Args:
ncdata: filename or NetcdfReader instance.
site_properties: Dictionary with site properties.
cls: The Structure class to instanciate. | pymatgen/io/abinit/netcdf.py | def structure_from_ncdata(ncdata, site_properties=None, cls=Structure):
"""
Reads and returns a pymatgen structure from a NetCDF file
containing crystallographic data in the ETSF-IO format.
Args:
ncdata: filename or NetcdfReader instance.
site_properties: Dictionary with site properties... | def structure_from_ncdata(ncdata, site_properties=None, cls=Structure):
"""
Reads and returns a pymatgen structure from a NetCDF file
containing crystallographic data in the ETSF-IO format.
Args:
ncdata: filename or NetcdfReader instance.
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train | NetcdfReader.walk_tree | Navigate all the groups in the file starting from top.
If top is None, the root group is used. | pymatgen/io/abinit/netcdf.py | def walk_tree(self, top=None):
"""
Navigate all the groups in the file starting from top.
If top is None, the root group is used.
"""
if top is None:
top = self.rootgrp
values = top.groups.values()
yield values
for value in top.groups.values()... | def walk_tree(self, top=None):
"""
Navigate all the groups in the file starting from top.
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"""
if top is None:
top = self.rootgrp
values = top.groups.values()
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train | NetcdfReader.read_dimvalue | Returns the value of a dimension.
Args:
dimname: Name of the variable
path: path to the group.
default: return `default` if `dimname` is not present and
`default` is not `NO_DEFAULT` else raise self.Error. | pymatgen/io/abinit/netcdf.py | def read_dimvalue(self, dimname, path="/", default=NO_DEFAULT):
"""
Returns the value of a dimension.
Args:
dimname: Name of the variable
path: path to the group.
default: return `default` if `dimname` is not present and
`default` is not `NO_D... | def read_dimvalue(self, dimname, path="/", default=NO_DEFAULT):
"""
Returns the value of a dimension.
Args:
dimname: Name of the variable
path: path to the group.
default: return `default` if `dimname` is not present and
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train | NetcdfReader.read_varnames | List of variable names stored in the group specified by path. | pymatgen/io/abinit/netcdf.py | def read_varnames(self, path="/"):
"""List of variable names stored in the group specified by path."""
if path == "/":
return self.rootgrp.variables.keys()
else:
group = self.path2group[path]
return group.variables.keys() | def read_varnames(self, path="/"):
"""List of variable names stored in the group specified by path."""
if path == "/":
return self.rootgrp.variables.keys()
else:
group = self.path2group[path]
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train | NetcdfReader.read_value | Returns the values of variable with name varname in the group specified by path.
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varname: Name of the variable
path: path to the group.
cmode: if cmode=="c", a complex ndarrays is constructed and returned
(netcdf does not provide native support from com... | pymatgen/io/abinit/netcdf.py | def read_value(self, varname, path="/", cmode=None, default=NO_DEFAULT):
"""
Returns the values of variable with name varname in the group specified by path.
Args:
varname: Name of the variable
path: path to the group.
cmode: if cmode=="c", a complex ndarrays... | def read_value(self, varname, path="/", cmode=None, default=NO_DEFAULT):
"""
Returns the values of variable with name varname in the group specified by path.
Args:
varname: Name of the variable
path: path to the group.
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train | NetcdfReader.read_keys | Read a list of variables/dimensions from file. If a key is not present the corresponding
entry in the output dictionary is set to None. | pymatgen/io/abinit/netcdf.py | def read_keys(self, keys, dict_cls=AttrDict, path="/"):
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od = dict_cls()
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"""
Read a list of variables/dimensions from file. If a key is not present the corresponding
entry in the output dictionary is set to None.
"""
od = dict_cls()
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train | ETSF_Reader.chemical_symbols | Chemical symbols char [number of atom species][symbol length]. | pymatgen/io/abinit/netcdf.py | def chemical_symbols(self):
"""Chemical symbols char [number of atom species][symbol length]."""
charr = self.read_value("chemical_symbols")
symbols = []
for v in charr:
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return symbols | def chemical_symbols(self):
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charr = self.read_value("chemical_symbols")
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train | ETSF_Reader.read_structure | Returns the crystalline structure. | pymatgen/io/abinit/netcdf.py | def read_structure(self, cls=Structure):
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train | ETSF_Reader.read_abinit_hdr | Read the variables associated to the Abinit header.
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Read the variables associated to the Abinit header.
Return :class:`AbinitHeader`
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Read the variables associated to the Abinit header.
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train | VoltageProfilePlotter.add_electrode | Add an electrode to the plot.
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electrode: An electrode. All electrodes satisfying the
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label: A label for the electrode. If None, defaults to a counting
system, i.e. 'Electrode 1', 'Electrode 2', ... | pymatgen/apps/battery/plotter.py | def add_electrode(self, electrode, label=None):
"""
Add an electrode to the plot.
Args:
electrode: An electrode. All electrodes satisfying the
AbstractElectrode interface should work.
label: A label for the electrode. If None, defaults to a counting
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train | VoltageProfilePlotter.get_plot | Returns a plot object.
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width: Width of the plot. Defaults to 8 in.
height: Height of the plot. Defaults to 6 in.
Returns:
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width: Width of the plot. Defaults to 8 in.
height: Height of the plot. Defaults to 6 in.
Returns:
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Returns a plot object.
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width: Width of the plot. Defaults to 8 in.
height: Height of the plot. Defaults to 6 in.
Returns:
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train | VoltageProfilePlotter.save | Save the plot to an image file.
Args:
filename: Filename to save to.
image_format: Format to save to. Defaults to eps. | pymatgen/apps/battery/plotter.py | def save(self, filename, image_format="eps", width=8, height=6):
"""
Save the plot to an image file.
Args:
filename: Filename to save to.
image_format: Format to save to. Defaults to eps.
"""
self.get_plot(width, height).savefig(filename, format=image_for... | def save(self, filename, image_format="eps", width=8, height=6):
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Save the plot to an image file.
Args:
filename: Filename to save to.
image_format: Format to save to. Defaults to eps.
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train | get_structure_from_prev_run | Process structure from previous run.
Args:
vasprun (Vasprun): Vasprun that contains the final structure
from previous run.
outcar (Outcar): Outcar that contains the magnetization info from
previous run.
sym_prec (float): Tolerance for symmetry finding for standardiza... | pymatgen/io/vasp/sets.py | def get_structure_from_prev_run(vasprun, outcar=None, sym_prec=0.1,
international_monoclinic=True):
"""
Process structure from previous run.
Args:
vasprun (Vasprun): Vasprun that contains the final structure
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Process structure from previous run.
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vasprun (Vasprun): Vasprun that contains the final structure
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train | batch_write_input | Batch write vasp input for a sequence of structures to
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Args:
structures ([Structure]): Sequence of Structures.
vasp_input_set (VaspInputSet): VaspInputSet class that creates
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train | VaspInputSet.potcar_symbols | List of POTCAR symbols. | pymatgen/io/vasp/sets.py | def potcar_symbols(self):
"""
List of POTCAR symbols.
"""
elements = self.poscar.site_symbols
potcar_symbols = []
settings = self._config_dict["POTCAR"]
if isinstance(settings[elements[-1]], dict):
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List of POTCAR symbols.
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train | VaspInputSet.all_input | Returns all input files as a dict of {filename: vasp object}
Returns:
dict of {filename: object}, e.g., {'INCAR': Incar object, ...} | pymatgen/io/vasp/sets.py | def all_input(self):
"""
Returns all input files as a dict of {filename: vasp object}
Returns:
dict of {filename: object}, e.g., {'INCAR': Incar object, ...}
"""
return {'INCAR': self.incar,
'KPOINTS': self.kpoints,
'POSCAR': self.posc... | def all_input(self):
"""
Returns all input files as a dict of {filename: vasp object}
Returns:
dict of {filename: object}, e.g., {'INCAR': Incar object, ...}
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return {'INCAR': self.incar,
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train | VaspInputSet.write_input | Writes a set of VASP input to a directory.
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output_dir (str): Directory to output the VASP input files
make_dir_if_not_present (bool): Set to True if you want the
directory (and the whole path) to be created if it is not
present.
include_... | pymatgen/io/vasp/sets.py | def write_input(self, output_dir,
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"""
Writes a set of VASP input to a directory.
Args:
output_dir (str): Directory to output the VASP input files
make_dir_if_not_present (bool): Set to True if you want... | def write_input(self, output_dir,
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Writes a set of VASP input to a directory.
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output_dir (str): Directory to output the VASP input files
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train | DictSet.nelect | Gets the default number of electrons for a given structure. | pymatgen/io/vasp/sets.py | def nelect(self):
"""
Gets the default number of electrons for a given structure.
"""
# if structure is not sorted this can cause problems, so must take
# care to remove redundant symbols when counting electrons
site_symbols = list(set(self.poscar.site_symbols))
n... | def nelect(self):
"""
Gets the default number of electrons for a given structure.
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# if structure is not sorted this can cause problems, so must take
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site_symbols = list(set(self.poscar.site_symbols))
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train | DictSet.kpoints | Writes out a KPOINTS file using the fully automated grid method. Uses
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Algorithm:
Uses a simple approach scaling the number of divisions along each
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"""
Writes out a KPOINTS file using the fully automated grid method. Uses
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Algorithm:
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Writes out a KPOINTS file using the fully automated grid method. Uses
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train | MPStaticSet.from_prev_calc | Generate a set of Vasp input files for static calculations from a
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Args:
prev_calc_dir (str): Directory containing the outputs(
vasprun.xml and OUTCAR) of previous vasp run.
standardize (float): Whether to standardize to a primitive... | pymatgen/io/vasp/sets.py | def from_prev_calc(cls, prev_calc_dir, standardize=False, sym_prec=0.1,
international_monoclinic=True, reciprocal_density=100,
small_gap_multiply=None, **kwargs):
"""
Generate a set of Vasp input files for static calculations from a
directory of prev... | def from_prev_calc(cls, prev_calc_dir, standardize=False, sym_prec=0.1,
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"""
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train | MPHSEBSSet.from_prev_calc | Generate a set of Vasp input files for HSE calculations from a
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prev_calc_dir (str): Directory containing the outputs
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"""
Generate a set of Vasp input files for HSE calculations from a
directory of previous Vasp run. if mode=="gap", it explicitly adds VBM
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Generate a set of Vasp input files for HSE calculations from a
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train | MPNonSCFSet.from_prev_calc | Generate a set of Vasp input files for NonSCF calculations from a
directory of previous static Vasp run.
Args:
prev_calc_dir (str): The directory contains the outputs(
vasprun.xml and OUTCAR) of previous vasp run.
copy_chgcar: Whether to copy the old CHGCAR. Defa... | pymatgen/io/vasp/sets.py | def from_prev_calc(cls, prev_calc_dir, copy_chgcar=True,
nbands_factor=1.2, standardize=False, sym_prec=0.1,
international_monoclinic=True, reciprocal_density=100,
kpoints_line_density=20, small_gap_multiply=None,
**kwargs):
... | def from_prev_calc(cls, prev_calc_dir, copy_chgcar=True,
nbands_factor=1.2, standardize=False, sym_prec=0.1,
international_monoclinic=True, reciprocal_density=100,
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train | MPSOCSet.from_prev_calc | Generate a set of Vasp input files for SOC calculations from a
directory of previous static Vasp run. SOC calc requires all 3
components for MAGMOM for each atom in the structure.
Args:
prev_calc_dir (str): The directory contains the outputs(
vasprun.xml and OUTCAR) ... | pymatgen/io/vasp/sets.py | def from_prev_calc(cls, prev_calc_dir, copy_chgcar=True,
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international_monoclinic=True, reciprocal_density=100,
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Generate a set of Vasp input fi... | def from_prev_calc(cls, prev_calc_dir, copy_chgcar=True,
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train | MVLGWSet.kpoints | Generate gamma center k-points mesh grid for GW calc,
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"""
Generate gamma center k-points mesh grid for GW calc,
which is requested by GW calculation.
"""
return Kpoints.automatic_density_by_vol(self.structure,
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Generate gamma center k-points mesh grid for GW calc,
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train | MVLGWSet.from_prev_calc | Generate a set of Vasp input files for GW or BSE calculations from a
directory of previous Exact Diag Vasp run.
Args:
prev_calc_dir (str): The directory contains the outputs(
vasprun.xml of previous vasp run.
copy_wavecar: Whether to copy the old WAVECAR, WAVEDER... | pymatgen/io/vasp/sets.py | def from_prev_calc(cls, prev_calc_dir, copy_wavecar=True, mode="DIAG",
nbands_factor=5, ncores=16, **kwargs):
"""
Generate a set of Vasp input files for GW or BSE calculations from a
directory of previous Exact Diag Vasp run.
Args:
prev_calc_dir (str):... | def from_prev_calc(cls, prev_calc_dir, copy_wavecar=True, mode="DIAG",
nbands_factor=5, ncores=16, **kwargs):
"""
Generate a set of Vasp input files for GW or BSE calculations from a
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train | MVLSlabSet.kpoints | k_product, default to 50, is kpoint number * length for a & b
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Automatic mesh & Gamma is the default setting. | pymatgen/io/vasp/sets.py | def kpoints(self):
"""
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train | MITNEBSet._process_structures | Remove any atom jumps across the cell | pymatgen/io/vasp/sets.py | def _process_structures(structures):
"""
Remove any atom jumps across the cell
"""
input_structures = structures
structures = [input_structures[0]]
for s in input_structures[1:]:
prev = structures[-1]
for i in range(len(s)):
t = np.... | def _process_structures(structures):
"""
Remove any atom jumps across the cell
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train | MITNEBSet.write_input | NEB inputs has a special directory structure where inputs are in 00,
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Args:
output_dir (str): Directory to output the VASP input files
make_dir_if_not_present (bool): Set to True if you want the
directory (and the whole path) to be created if it is no... | pymatgen/io/vasp/sets.py | def write_input(self, output_dir, make_dir_if_not_present=True,
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write_endpoint_inputs=False):
"""
NEB inputs has a special directory structure where inputs are in 00,
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train | get_uvec | Gets a unit vector parallel to input vector | pymatgen/core/tensors.py | def get_uvec(vec):
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return vec / l | def get_uvec(vec):
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train | symmetry_reduce | Function that converts a list of tensors corresponding to a structure
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tensors from the original list
Args:
tensors (list of tensors): list of Tensor objec... | pymatgen/core/tensors.py | def symmetry_reduce(tensors, structure, tol=1e-8, **kwargs):
"""
Function that converts a list of tensors corresponding to a structure
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tensors from the origina... | def symmetry_reduce(tensors, structure, tol=1e-8, **kwargs):
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train | get_tkd_value | Helper function to find a value in a tensor-keyed-
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"""
Helper function to find a value in a tensor-keyed-
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Helper function to find a value in a tensor-keyed-
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train | Tensor.zeroed | returns the matrix with all entries below a certain threshold
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"""
returns the matrix with all entries below a certain threshold
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"""
new_tensor = self.copy()
new_tensor[abs(new_tensor) < tol] = 0
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"""
returns the matrix with all entries below a certain threshold
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new_tensor = self.copy()
new_tensor[abs(new_tensor) < tol] = 0
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train | Tensor.rotate | Applies a rotation directly, and tests input matrix to ensure a valid
rotation.
Args:
matrix (3x3 array-like): rotation matrix to be applied to tensor
tol (float): tolerance for testing rotation matrix validity | pymatgen/core/tensors.py | def rotate(self, matrix, tol=1e-3):
"""
Applies a rotation directly, and tests input matrix to ensure a valid
rotation.
Args:
matrix (3x3 array-like): rotation matrix to be applied to tensor
tol (float): tolerance for testing rotation matrix validity
"""
... | def rotate(self, matrix, tol=1e-3):
"""
Applies a rotation directly, and tests input matrix to ensure a valid
rotation.
Args:
matrix (3x3 array-like): rotation matrix to be applied to tensor
tol (float): tolerance for testing rotation matrix validity
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Calculates the result of an einstein summation expression
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train | Tensor.project | Convenience method for projection of a tensor into a
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n (3x1 array-like): direction to project onto
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n (3x1 array-like): direction to project onto
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train | Tensor.average_over_unit_sphere | Method for averaging the tensor projection over the unit
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Args:
quad (dict): quadrature for integration, should be
dictionary with "points" and "weights" keys defaults
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"""
Method for averaging the tensor projection over the unit
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Args:
quad (dict): quadrature for integration, should be
dictionary with "points" and "weights" keys defaults
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Method for averaging the tensor projection over the unit
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quad (dict): quadrature for integration, should be
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train | Tensor.get_grouped_indices | Gets index sets for equivalent tensor values
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Gets index sets for equivalent tensor values
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voigt (bool): whether to get grouped indices
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Gets index sets for equivalent tensor values
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voigt (bool): whether to get symbol dict for voigt
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zero_index (bool): whether to set initial index to zero,
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"""
Creates a summary dict for tensor with associated symbol
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voigt (bool): whether to get symbol dict for voigt
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Creates a summary dict for tensor with associated symbol
Args:
voigt (bool): whether to get symbol dict for voigt
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train | Tensor.round | Wrapper around numpy.round to ensure object
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decimals :Number of decimal places to round to (default: 0).
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"""
Wrapper around numpy.round to ensure object
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Args:
decimals :Number of decimal places to round to (default: 0).
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Wrapper around numpy.round to ensure object
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train | Tensor.symmetrized | Returns a generally symmetrized tensor, calculated by taking
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"""
Returns a generally symmetrized tensor, calculated by taking
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possible permutations of indices
"""
perms = list(itertools.permutations(range(self.rank)))
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Returns a generally symmetrized tensor, calculated by taking
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train | Tensor.voigt_symmetrized | Returns a "voigt"-symmetrized tensor, i. e. a voigt-notation
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"""
Returns a "voigt"-symmetrized tensor, i. e. a voigt-notation
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"""
if not (self.rank % 2 == 0 and self.rank >= 2):
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Returns a "voigt"-symmetrized tensor, i. e. a voigt-notation
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train | Tensor.fit_to_structure | Returns a tensor that is invariant with respect to symmetry
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structure (Structure): structure from which to generate
symmetry operations
symprec (float): symmetry tolerance for the Spacegroup Analyzer
u... | pymatgen/core/tensors.py | def fit_to_structure(self, structure, symprec=0.1):
"""
Returns a tensor that is invariant with respect to symmetry
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Args:
structure (Structure): structure from which to generate
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Returns a tensor that is invariant with respect to symmetry
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structure (Structure): structure from which to generate
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structure (Structure): structure to be fit to
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Tests whether a tensor is invariant with respect to the
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Tests whether a tensor is invariant with respect to the
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train | Tensor.voigt | Returns the tensor in Voigt notation | pymatgen/core/tensors.py | def voigt(self):
"""
Returns the tensor in Voigt notation
"""
v_matrix = np.zeros(self._vscale.shape, dtype=self.dtype)
this_voigt_map = self.get_voigt_dict(self.rank)
for ind in this_voigt_map:
v_matrix[this_voigt_map[ind]] = self[ind]
if not self.is_... | def voigt(self):
"""
Returns the tensor in Voigt notation
"""
v_matrix = np.zeros(self._vscale.shape, dtype=self.dtype)
this_voigt_map = self.get_voigt_dict(self.rank)
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v_matrix[this_voigt_map[ind]] = self[ind]
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train | Tensor.is_voigt_symmetric | Tests symmetry of tensor to that necessary for voigt-conversion
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Tests symmetry of tensor to that necessary for voigt-conversion
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"""
transpose_pieces = [[[0 for i in range(self... | def is_voigt_symmetric(self, tol=1e-6):
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Tests symmetry of tensor to that necessary for voigt-conversion
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train | Tensor.get_voigt_dict | Returns a dictionary that maps indices in the tensor to those
in a voigt representation based on input rank
Args:
rank (int): Tensor rank to generate the voigt map | pymatgen/core/tensors.py | def get_voigt_dict(rank):
"""
Returns a dictionary that maps indices in the tensor to those
in a voigt representation based on input rank
Args:
rank (int): Tensor rank to generate the voigt map
"""
vdict = {}
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Returns a dictionary that maps indices in the tensor to those
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rank (int): Tensor rank to generate the voigt map
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train | Tensor.from_voigt | Constructor based on the voigt notation vector or matrix.
Args:
voigt_input (array-like): voigt input for a given tensor | pymatgen/core/tensors.py | def from_voigt(cls, voigt_input):
"""
Constructor based on the voigt notation vector or matrix.
Args:
voigt_input (array-like): voigt input for a given tensor
"""
voigt_input = np.array(voigt_input)
rank = sum(voigt_input.shape) // 3
t = cls(np.zeros(... | def from_voigt(cls, voigt_input):
"""
Constructor based on the voigt notation vector or matrix.
Args:
voigt_input (array-like): voigt input for a given tensor
"""
voigt_input = np.array(voigt_input)
rank = sum(voigt_input.shape) // 3
t = cls(np.zeros(... | [
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train | Tensor.get_ieee_rotation | Given a structure associated with a tensor, determines
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Args:
structure (Structure): a structure associated with the
tensor to be converted to the IEEE standard
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Given a structure associated with a tensor, determines
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Args:
structure (Structure): a structure associated with the
... | def get_ieee_rotation(structure, refine_rotation=True):
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train | Tensor.convert_to_ieee | Given a structure associated with a tensor, attempts a
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Args:
structure (Structure): a structure associated with the
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Given a structure associated with a tensor, attempts a
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train | Tensor.structure_transform | Transforms a tensor from one basis for an original structure
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Args:
original_structure (Structure): structure corresponding
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new_structure (Structure): structure corresponding to the
... | pymatgen/core/tensors.py | def structure_transform(self, original_structure, new_structure,
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"""
Transforms a tensor from one basis for an original structure
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Args:
original_structure (Structure): structure c... | def structure_transform(self, original_structure, new_structure,
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Transforms a tensor from one basis for an original structure
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train | Tensor.from_values_indices | Creates a tensor from values and indices, with options
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Args:
values (floats): numbers to place at indices
indices (array-likes): indices to place values at
populate (bool): whether to populate the tensor
structu... | pymatgen/core/tensors.py | def from_values_indices(cls, values, indices, populate=False,
structure=None, voigt_rank=None,
vsym=True, verbose=False):
"""
Creates a tensor from values and indices, with options
for populating the remainder of the tensor.
Args:
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Creates a tensor from values and indices, with options
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train | Tensor.populate | Takes a partially populated tensor, and populates the non-zero
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1. Find non-zero entries
2. Symmetrize the tensor with respect to crystal symmetry and
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"""
Takes a partially populated tensor, and populates the non-zero
entries according to the following procedure, iterated until
the desired convergence (specified via prec) is ... | def populate(self, structure, prec=1e-5, maxiter=200, verbose=False,
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"""
Takes a partially populated tensor, and populates the non-zero
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train | Tensor.as_dict | Serializes the tensor object
Args:
voigt (bool): flag for whether to store entries in
voigt-notation. Defaults to false, as information
may be lost in conversion.
Returns (Dict):
serialized format tensor object | pymatgen/core/tensors.py | def as_dict(self, voigt=False):
"""
Serializes the tensor object
Args:
voigt (bool): flag for whether to store entries in
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Returns (Dict):
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Serializes the tensor object
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voigt (bool): flag for whether to store entries in
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train | SquareTensor.inv | shorthand for matrix inverse on SquareTensor | pymatgen/core/tensors.py | def inv(self):
"""
shorthand for matrix inverse on SquareTensor
"""
if self.det == 0:
raise ValueError("SquareTensor is non-invertible")
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"""
shorthand for matrix inverse on SquareTensor
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train | SquareTensor.is_rotation | Test to see if tensor is a valid rotation matrix, performs a
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and if the determinant is equal to one within the specified
tolerance
Args:
tol (float): tolerance to both tests of whether the
the determ... | pymatgen/core/tensors.py | def is_rotation(self, tol=1e-3, include_improper=True):
"""
Test to see if tensor is a valid rotation matrix, performs a
test to check whether the inverse is equal to the transpose
and if the determinant is equal to one within the specified
tolerance
Args:
to... | def is_rotation(self, tol=1e-3, include_improper=True):
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Test to see if tensor is a valid rotation matrix, performs a
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train | SquareTensor.refine_rotation | Helper method for refining rotation matrix by ensuring
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Args:
tol to test for rotation
... | pymatgen/core/tensors.py | def refine_rotation(self):
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Helper method for refining rotation matrix by ensuring
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Gets new y vector from an orthogonal projection of x onto y
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"""
Helper method for refining rotation matrix by ensuring
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train | compute_average_oxidation_state | Calculates the average oxidation state of a site
Args:
site: Site to compute average oxidation state
Returns:
Average oxidation state of site. | pymatgen/analysis/ewald.py | def compute_average_oxidation_state(site):
"""
Calculates the average oxidation state of a site
Args:
site: Site to compute average oxidation state
Returns:
Average oxidation state of site.
"""
try:
avg_oxi = sum([sp.oxi_state * occu
for sp, occu ... | def compute_average_oxidation_state(site):
"""
Calculates the average oxidation state of a site
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site: Site to compute average oxidation state
Returns:
Average oxidation state of site.
"""
try:
avg_oxi = sum([sp.oxi_state * occu
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train | EwaldSummation.compute_partial_energy | Gives total ewald energy for certain sites being removed, i.e. zeroed
out. | pymatgen/analysis/ewald.py | def compute_partial_energy(self, removed_indices):
"""
Gives total ewald energy for certain sites being removed, i.e. zeroed
out.
"""
total_energy_matrix = self.total_energy_matrix.copy()
for i in removed_indices:
total_energy_matrix[i, :] = 0
tota... | def compute_partial_energy(self, removed_indices):
"""
Gives total ewald energy for certain sites being removed, i.e. zeroed
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"""
total_energy_matrix = self.total_energy_matrix.copy()
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train | EwaldSummation.compute_sub_structure | Gives total ewald energy for an sub structure in the same
lattice. The sub_structure must be a subset of the original
structure, with possible different charges.
Args:
substructure (Structure): Substructure to compute Ewald sum for.
tol (float): Tolerance for site matchi... | pymatgen/analysis/ewald.py | def compute_sub_structure(self, sub_structure, tol=1e-3):
"""
Gives total ewald energy for an sub structure in the same
lattice. The sub_structure must be a subset of the original
structure, with possible different charges.
Args:
substructure (Structure): Substructur... | def compute_sub_structure(self, sub_structure, tol=1e-3):
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Gives total ewald energy for an sub structure in the same
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train | EwaldSummation.total_energy | The total energy. | pymatgen/analysis/ewald.py | def total_energy(self):
"""
The total energy.
"""
return sum(sum(self._recip)) + sum(sum(self._real)) + sum(self._point) + self._charged_cell_energy | def total_energy(self):
"""
The total energy.
"""
return sum(sum(self._recip)) + sum(sum(self._real)) + sum(self._point) + self._charged_cell_energy | [
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train | EwaldSummation.total_energy_matrix | The total energy matrix. Each matrix element (i, j) corresponds to the
total interaction energy between site i and site j.
Note that this does not include the charged-cell energy, which is only important
when the simulation cell is not charge balanced. | pymatgen/analysis/ewald.py | def total_energy_matrix(self):
"""
The total energy matrix. Each matrix element (i, j) corresponds to the
total interaction energy between site i and site j.
Note that this does not include the charged-cell energy, which is only important
when the simulation cell is not charge b... | def total_energy_matrix(self):
"""
The total energy matrix. Each matrix element (i, j) corresponds to the
total interaction energy between site i and site j.
Note that this does not include the charged-cell energy, which is only important
when the simulation cell is not charge b... | [
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train | EwaldSummation.get_site_energy | Compute the energy for a single site in the structure
Args:
site_index (int): Index of site
ReturnS:
(float) - Energy of that site | pymatgen/analysis/ewald.py | def get_site_energy(self, site_index):
"""Compute the energy for a single site in the structure
Args:
site_index (int): Index of site
ReturnS:
(float) - Energy of that site"""
if self._charged:
warn('Per atom energies for charged structures no... | def get_site_energy(self, site_index):
"""Compute the energy for a single site in the structure
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site_index (int): Index of site
ReturnS:
(float) - Energy of that site"""
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train | EwaldSummation._calc_recip | Perform the reciprocal space summation. Calculates the quantity
E_recip = 1/(2PiV) sum_{G < Gmax} exp(-(G.G/4/eta))/(G.G) S(G)S(-G)
where
S(G) = sum_{k=1,N} q_k exp(-i G.r_k)
S(G)S(-G) = |S(G)|**2
This method is heavily vectorized to utilize numpy's C backend for
speed. | pymatgen/analysis/ewald.py | def _calc_recip(self):
"""
Perform the reciprocal space summation. Calculates the quantity
E_recip = 1/(2PiV) sum_{G < Gmax} exp(-(G.G/4/eta))/(G.G) S(G)S(-G)
where
S(G) = sum_{k=1,N} q_k exp(-i G.r_k)
S(G)S(-G) = |S(G)|**2
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"""
Perform the reciprocal space summation. Calculates the quantity
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train | EwaldSummation._calc_real_and_point | Determines the self energy -(eta/pi)**(1/2) * sum_{i=1}^{N} q_i**2 | pymatgen/analysis/ewald.py | def _calc_real_and_point(self):
"""
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fcoords = self._s.frac_coords
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train | EwaldMinimizer.minimize_matrix | This method finds and returns the permutations that produce the lowest
ewald sum calls recursive function to iterate through permutations | pymatgen/analysis/ewald.py | def minimize_matrix(self):
"""
This method finds and returns the permutations that produce the lowest
ewald sum calls recursive function to iterate through permutations
"""
if self._algo == EwaldMinimizer.ALGO_FAST or \
self._algo == EwaldMinimizer.ALGO_BE... | def minimize_matrix(self):
"""
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train | EwaldMinimizer.add_m_list | This adds an m_list to the output_lists and updates the current
minimum if the list is full. | pymatgen/analysis/ewald.py | def add_m_list(self, matrix_sum, m_list):
"""
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"""
if self._output_lists is None:
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train | EwaldMinimizer.best_case | Computes a best case given a matrix and manipulation list.
Args:
matrix: the current matrix (with some permutations already
performed)
m_list: [(multiplication fraction, number_of_indices, indices,
species)] describing the manipulation
indices... | pymatgen/analysis/ewald.py | def best_case(self, matrix, m_list, indices_left):
"""
Computes a best case given a matrix and manipulation list.
Args:
matrix: the current matrix (with some permutations already
performed)
m_list: [(multiplication fraction, number_of_indices, indices,
... | def best_case(self, matrix, m_list, indices_left):
"""
Computes a best case given a matrix and manipulation list.
Args:
matrix: the current matrix (with some permutations already
performed)
m_list: [(multiplication fraction, number_of_indices, indices,
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train | EwaldMinimizer.get_next_index | Returns an index that should have the most negative effect on the
matrix sum | pymatgen/analysis/ewald.py | def get_next_index(self, matrix, manipulation, indices_left):
"""
Returns an index that should have the most negative effect on the
matrix sum
"""
f = manipulation[0]
indices = list(indices_left.intersection(manipulation[2]))
sums = np.sum(matrix[indices], axis=1)... | def get_next_index(self, matrix, manipulation, indices_left):
"""
Returns an index that should have the most negative effect on the
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"""
f = manipulation[0]
indices = list(indices_left.intersection(manipulation[2]))
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train | EwaldMinimizer._recurse | This method recursively finds the minimal permutations using a binary
tree search strategy.
Args:
matrix: The current matrix (with some permutations already
performed).
m_list: The list of permutations still to be performed
indices: Set of indices whi... | pymatgen/analysis/ewald.py | def _recurse(self, matrix, m_list, indices, output_m_list=[]):
"""
This method recursively finds the minimal permutations using a binary
tree search strategy.
Args:
matrix: The current matrix (with some permutations already
performed).
m_list: The... | def _recurse(self, matrix, m_list, indices, output_m_list=[]):
"""
This method recursively finds the minimal permutations using a binary
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Args:
matrix: The current matrix (with some permutations already
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train | average_coordination_number | Calculates the ensemble averaged Voronoi coordination numbers
of a list of Structures using VoronoiNN.
Typically used for analyzing the output of a Molecular Dynamics run.
Args:
structures (list): list of Structures.
freq (int): sampling frequency of coordination number [every freq steps].
... | pymatgen/analysis/structure_analyzer.py | def average_coordination_number(structures, freq=10):
"""
Calculates the ensemble averaged Voronoi coordination numbers
of a list of Structures using VoronoiNN.
Typically used for analyzing the output of a Molecular Dynamics run.
Args:
structures (list): list of Structures.
freq (int... | def average_coordination_number(structures, freq=10):
"""
Calculates the ensemble averaged Voronoi coordination numbers
of a list of Structures using VoronoiNN.
Typically used for analyzing the output of a Molecular Dynamics run.
Args:
structures (list): list of Structures.
freq (int... | [
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train | solid_angle | Helper method to calculate the solid angle of a set of coords from the
center.
Args:
center (3x1 array): Center to measure solid angle from.
coords (Nx3 array): List of coords to determine solid angle.
Returns:
The solid angle. | pymatgen/analysis/structure_analyzer.py | def solid_angle(center, coords):
"""
Helper method to calculate the solid angle of a set of coords from the
center.
Args:
center (3x1 array): Center to measure solid angle from.
coords (Nx3 array): List of coords to determine solid angle.
Returns:
The solid angle.
"""
... | def solid_angle(center, coords):
"""
Helper method to calculate the solid angle of a set of coords from the
center.
Args:
center (3x1 array): Center to measure solid angle from.
coords (Nx3 array): List of coords to determine solid angle.
Returns:
The solid angle.
"""
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train | get_max_bond_lengths | Provides max bond length estimates for a structure based on the JMol
table and algorithms.
Args:
structure: (structure)
el_radius_updates: (dict) symbol->float to update atomic radii
Returns: (dict) - (Element1, Element2) -> float. The two elements are
ordered by Z. | pymatgen/analysis/structure_analyzer.py | def get_max_bond_lengths(structure, el_radius_updates=None):
"""
Provides max bond length estimates for a structure based on the JMol
table and algorithms.
Args:
structure: (structure)
el_radius_updates: (dict) symbol->float to update atomic radii
Returns: (dict) - (Element... | def get_max_bond_lengths(structure, el_radius_updates=None):
"""
Provides max bond length estimates for a structure based on the JMol
table and algorithms.
Args:
structure: (structure)
el_radius_updates: (dict) symbol->float to update atomic radii
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train | get_dimensionality | This method returns whether a structure is 3D, 2D (layered), or 1D (linear
chains or molecules) according to the algorithm published in Gorai, P.,
Toberer, E. & Stevanovic, V. Computational Identification of Promising
Thermoelectric Materials Among Known Quasi-2D Binary Compounds. J. Mater.
Chem. A 2, 4... | pymatgen/analysis/structure_analyzer.py | def get_dimensionality(structure, max_hkl=2, el_radius_updates=None,
min_slab_size=5, min_vacuum_size=5,
standardize=True, bonds=None):
"""
This method returns whether a structure is 3D, 2D (layered), or 1D (linear
chains or molecules) according to the algorithm... | def get_dimensionality(structure, max_hkl=2, el_radius_updates=None,
min_slab_size=5, min_vacuum_size=5,
standardize=True, bonds=None):
"""
This method returns whether a structure is 3D, 2D (layered), or 1D (linear
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train | contains_peroxide | Determines if a structure contains peroxide anions.
Args:
structure (Structure): Input structure.
relative_cutoff: The peroxide bond distance is 1.49 Angstrom.
Relative_cutoff * 1.49 stipulates the maximum distance two O
atoms must be to each other to be considered a peroxid... | pymatgen/analysis/structure_analyzer.py | def contains_peroxide(structure, relative_cutoff=1.1):
"""
Determines if a structure contains peroxide anions.
Args:
structure (Structure): Input structure.
relative_cutoff: The peroxide bond distance is 1.49 Angstrom.
Relative_cutoff * 1.49 stipulates the maximum distance two O... | def contains_peroxide(structure, relative_cutoff=1.1):
"""
Determines if a structure contains peroxide anions.
Args:
structure (Structure): Input structure.
relative_cutoff: The peroxide bond distance is 1.49 Angstrom.
Relative_cutoff * 1.49 stipulates the maximum distance two O... | [
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train | oxide_type | Determines if an oxide is a peroxide/superoxide/ozonide/normal oxide
Args:
structure (Structure): Input structure.
relative_cutoff (float): Relative_cutoff * act. cutoff stipulates the
max distance two O atoms must be from each other.
return_nbonds (bool): Should number of bonds... | pymatgen/analysis/structure_analyzer.py | def oxide_type(structure, relative_cutoff=1.1, return_nbonds=False):
"""
Determines if an oxide is a peroxide/superoxide/ozonide/normal oxide
Args:
structure (Structure): Input structure.
relative_cutoff (float): Relative_cutoff * act. cutoff stipulates the
max distance two O at... | def oxide_type(structure, relative_cutoff=1.1, return_nbonds=False):
"""
Determines if an oxide is a peroxide/superoxide/ozonide/normal oxide
Args:
structure (Structure): Input structure.
relative_cutoff (float): Relative_cutoff * act. cutoff stipulates the
max distance two O at... | [
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train | sulfide_type | Determines if a structure is a sulfide/polysulfide
Args:
structure (Structure): Input structure.
Returns:
(str) sulfide/polysulfide/sulfate | pymatgen/analysis/structure_analyzer.py | def sulfide_type(structure):
"""
Determines if a structure is a sulfide/polysulfide
Args:
structure (Structure): Input structure.
Returns:
(str) sulfide/polysulfide/sulfate
"""
structure = structure.copy()
structure.remove_oxidation_states()
s = Element("S")
comp = ... | def sulfide_type(structure):
"""
Determines if a structure is a sulfide/polysulfide
Args:
structure (Structure): Input structure.
Returns:
(str) sulfide/polysulfide/sulfate
"""
structure = structure.copy()
structure.remove_oxidation_states()
s = Element("S")
comp = ... | [
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train | VoronoiAnalyzer.analyze | Performs Voronoi analysis and returns the polyhedra around atom n
in Schlaefli notation.
Args:
structure (Structure): structure to analyze
n (int): index of the center atom in structure
Returns:
voronoi index of n: <c3,c4,c6,c6,c7,c8,c9,c10>
... | pymatgen/analysis/structure_analyzer.py | def analyze(self, structure, n=0):
"""
Performs Voronoi analysis and returns the polyhedra around atom n
in Schlaefli notation.
Args:
structure (Structure): structure to analyze
n (int): index of the center atom in structure
Returns:
voronoi ... | def analyze(self, structure, n=0):
"""
Performs Voronoi analysis and returns the polyhedra around atom n
in Schlaefli notation.
Args:
structure (Structure): structure to analyze
n (int): index of the center atom in structure
Returns:
voronoi ... | [
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