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train | InterfacialReactivity._get_grand_potential | Computes the grand potential Phi at a given composition and
chemical potential(s).
Args:
composition (Composition): Composition object.
Returns:
Grand potential at a given composition at chemical potential(s). | pymatgen/analysis/interface_reactions.py | def _get_grand_potential(self, composition):
"""
Computes the grand potential Phi at a given composition and
chemical potential(s).
Args:
composition (Composition): Composition object.
Returns:
Grand potential at a given composition at chemical potential... | def _get_grand_potential(self, composition):
"""
Computes the grand potential Phi at a given composition and
chemical potential(s).
Args:
composition (Composition): Composition object.
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train | InterfacialReactivity._get_energy | Computes reaction energy in eV/atom at mixing ratio x : (1-x) for
self.comp1 : self.comp2.
Args:
x (float): Mixing ratio x of reactants, a float between 0 and 1.
Returns:
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"""
Computes reaction energy in eV/atom at mixing ratio x : (1-x) for
self.comp1 : self.comp2.
Args:
x (float): Mixing ratio x of reactants, a float between 0 and 1.
Returns:
Reaction energy.
"""
return self.pd.g... | def _get_energy(self, x):
"""
Computes reaction energy in eV/atom at mixing ratio x : (1-x) for
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Args:
x (float): Mixing ratio x of reactants, a float between 0 and 1.
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Reaction energy.
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train | InterfacialReactivity._get_reaction | Generates balanced reaction at mixing ratio x : (1-x) for
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Args:
x (float): Mixing ratio x of reactants, a float between 0 and 1.
Returns:
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"""
Generates balanced reaction at mixing ratio x : (1-x) for
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Args:
x (float): Mixing ratio x of reactants, a float between 0 and 1.
Returns:
Reaction object.
"""
mix_comp = self.comp1 ... | def _get_reaction(self, x):
"""
Generates balanced reaction at mixing ratio x : (1-x) for
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x (float): Mixing ratio x of reactants, a float between 0 and 1.
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Reaction object.
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train | InterfacialReactivity._get_elmt_amt_in_rxt | Computes total number of atoms in a reaction formula for elements
not in external reservoir. This method is used in the calculation
of reaction energy per mol of reaction formula.
Args:
rxt (Reaction): a reaction.
Returns:
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"""
Computes total number of atoms in a reaction formula for elements
not in external reservoir. This method is used in the calculation
of reaction energy per mol of reaction formula.
Args:
rxt (Reaction): a reaction.
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Computes total number of atoms in a reaction formula for elements
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train | InterfacialReactivity.get_products | List of formulas of potential products. E.g., ['Li','O2','Mn']. | pymatgen/analysis/interface_reactions.py | def get_products(self):
"""
List of formulas of potential products. E.g., ['Li','O2','Mn'].
"""
products = set()
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products = products.union(set([k.reduced_formula
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List of formulas of potential products. E.g., ['Li','O2','Mn'].
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train | InterfacialReactivity._convert | Converts mixing ratio x in comp1 - comp2 tie line to that in
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Args:
x (float): Mixing ratio x in comp1 - comp2 tie line, a float
between 0 and 1.
factor1 (float): Compositional ratio between composition c1 and
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Converts mixing ratio x in comp1 - comp2 tie line to that in
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Args:
x (float): Mixing ratio x in comp1 - comp2 tie line, a float
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Converts mixing ratio x in comp1 - comp2 tie line to that in
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train | InterfacialReactivity._reverse_convert | Converts mixing ratio x in c1 - c2 tie line to that in
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x (float): Mixing ratio x in c1 - c2 tie line, a float between
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factor1 (float): Compositional ratio between composition c1 and
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Converts mixing ratio x in c1 - c2 tie line to that in
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x (float): Mixing ratio x in c1 - c2 tie line, a float between
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x (float): Mixing ratio x in c1 - c2 tie line, a float between
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train | InterfacialReactivity.get_kinks | Finds all the kinks in mixing ratio where reaction products changes
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Returns:
Zip object of tuples (index, mixing ratio,
reaction energy per atom in eV/atom,
... | pymatgen/analysis/interface_reactions.py | def get_kinks(self):
"""
Finds all the kinks in mixing ratio where reaction products changes
along the tie line of composition self.c1 and composition self.c2.
Returns:
Zip object of tuples (index, mixing ratio,
reaction energy per atom in e... | def get_kinks(self):
"""
Finds all the kinks in mixing ratio where reaction products changes
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Zip object of tuples (index, mixing ratio,
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train | InterfacialReactivity.get_critical_original_kink_ratio | Returns a list of molar mixing ratio for each kink between ORIGINAL
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same list as mixing ratio obtained from get_kinks method
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Returns:
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... | pymatgen/analysis/interface_reactions.py | def get_critical_original_kink_ratio(self):
"""
Returns a list of molar mixing ratio for each kink between ORIGINAL
(instead of processed) reactant compositions. This is the
same list as mixing ratio obtained from get_kinks method
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Returns a list of molar mixing ratio for each kink between ORIGINAL
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train | InterfacialReactivity._get_original_composition_ratio | Returns the molar mixing ratio between the reactants with ORIGINAL (
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Args:
reaction (Reaction): Reaction object that contains the original
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Returns:
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"""
Returns the molar mixing ratio between the reactants with ORIGINAL (
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reaction (Reaction): Reaction object that contains the original
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train | InterfacialReactivity.labels | Returns a dictionary containing kink information:
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E.g., {1: 'x= 0.0 energy = 0.0 Mn -> Mn',
2: 'x= 0.5 energy = -15.0 O2 + Mn -> MnO2',
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"""
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train | InterfacialReactivity.plot | Plots reaction energy as a function of mixing ratio x in
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Returns:
Pylab object that plots reaction energy as a function of
mixing ratio x. | pymatgen/analysis/interface_reactions.py | def plot(self):
"""
Plots reaction energy as a function of mixing ratio x in
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Returns:
Pylab object that plots reaction energy as a function of
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"""
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train | InterfacialReactivity.minimum | Finds the minimum reaction energy E_min and corresponding
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Returns:
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"""
Finds the minimum reaction energy E_min and corresponding
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Returns:
Tuple (x_min, E_min).
"""
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"""
Finds the minimum reaction energy E_min and corresponding
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Tuple (x_min, E_min).
"""
return min([(x, energy) for _, x, energy, _, _ in self.get_kinks()],
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train | InterfacialReactivity.get_no_mixing_energy | Generates the opposite number of energy above grand potential
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train | InterfacialReactivity.get_chempot_correction | Get the normalized correction term Δμ for chemical potential of a gas
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T_std = 1 bar). The gas phase is limited to be one of O2, N2, Cl2,
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train | get_atom_map | Returns a dict that maps each atomic symbol to a unique integer starting
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structure (Structure)
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train | get_absorbing_atom_symbol_index | Return the absorbing atom symboll and site index in the given structure.
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Return the absorbing atom symboll and site index in the given structure.
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train | Header.from_cif_file | Static method to create Header object from cif_file
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train | Header.header_string_from_file | Reads Header string from either a HEADER file or feff.inp file
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train | Header.write_file | Writes Header into filename on disk.
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Writes Header into filename on disk.
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filename: Filename and path for file to be written to disk
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train | Atoms._set_cluster | Compute and set the cluster of atoms as a Molecule object. The siteato
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Returns:
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Compute and set the cluster of atoms as a Molecule object. The siteato
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Returns:
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"""
center = self.struct[self.center_index... | def _set_cluster(self):
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train | Atoms.atoms_string_from_file | Reads atomic shells from file such as feff.inp or ATOMS file
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filename (str): path the feff input file
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filename (str): path the feff input file
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train | Atoms.get_lines | Returns a list of string representations of the atomic configuration
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train | Tags.as_dict | Dict representation.
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Dict representation.
Returns:
Dictionary of parameters from fefftags object
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Dict representation.
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d: Dict of feff parameters and values.
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"""
Creates Tags object from a dictionary.
Args:
d: Dict of feff parameters and values.
Returns:
Tags object
"""
i = Tags()
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if k not in ("@module", "@class"):
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d: Dict of feff parameters and values.
Returns:
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Creates a Feff_tag dictionary from a PARAMETER or feff.inp file.
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filename: Filename for either PARAMETER or feff.inp file
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train | Potential.pot_string_from_file | Reads Potential parameters from a feff.inp or FEFFPOT file.
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filename: file name containing potential data.
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Reads Potential parameters from a feff.inp or FEFFPOT file.
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pot_data: potential data in string format
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Creates atomic symbol/potential number dictionary
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Arg:
pot_data: potential data in string format
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forward and reverse atom symbol and potential number dictionaries.
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forward and reverse atom symbol and potential number dictionaries.
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train | Paths.write_file | Write paths.dat. | pymatgen/io/feff/inputs.py | def write_file(self, filename="paths.dat"):
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Write paths.dat.
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train | lattice_from_abivars | Returns a `Lattice` object from a dictionary
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If acell is not given, the Abinit default is used i.e. [1,1,1] Bohr
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cls: Lattice class to be instantiated. pymatgen.core.lattice.Lattice if `cls` is None
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"""
Returns a `Lattice` object from a dictionary
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cls: Lattice class to be instantiated. pym... | def lattice_from_abivars(cls=None, *args, **kwargs):
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train | contract | >>> assert contract("1 1 1 2 2 3") == "3*1 2*2 1*3"
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train | Smearing.as_smearing | Constructs an instance of `Smearing` from obj. Accepts obj in the form:
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* "name:tsmear units" e.g. "gaussian:0.1 eV"
* None --> no smearing
... | def as_smearing(cls, obj):
"""
Constructs an instance of `Smearing` from obj. Accepts obj in the form:
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train | Electrons.as_dict | json friendly dict representation | pymatgen/io/abinit/abiobjects.py | def as_dict(self):
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train | KSampling.gamma_centered | Convenient static constructor for an automatic Gamma centered Kpoint grid.
Args:
kpts: Subdivisions N_1, N_2 and N_3 along reciprocal lattice vectors.
use_symmetries: False if spatial symmetries should not be used
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"""
Convenient static constructor for an automatic Gamma centered Kpoint grid.
Args:
kpts: Subdivisions N_1, N_2 and N_3 along reciprocal lattice vectors.
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Convenient static constructor for an automatic Gamma centered Kpoint grid.
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train | KSampling.monkhorst | Convenient static constructor for a Monkhorst-Pack mesh.
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ngkpt: Subdivisions N_1, N_2 and N_3 along reciprocal lattice vectors.
shiftk: Shift to be applied to the kpoints.
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Convenient static constructor for a Monkhorst-Pack mesh.
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Convenient static constructor for a Monkhorst-Pack mesh.
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train | KSampling.monkhorst_automatic | Convenient static constructor for an automatic Monkhorst-Pack mesh.
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structure: :class:`Structure` object.
ngkpt: Subdivisions N_1, N_2 and N_3 along reciprocal lattice vectors.
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"""
Convenient static constructor for an automatic Monkhorst-Pack mesh.
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structure: :class:`Structure` object.
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Convenient static constructor for an automatic Monkhorst-Pack mesh.
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train | KSampling._path | Static constructor for path in k-space.
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structure: :class:`Structure` object.
kpath_bounds: List with the reduced coordinates of the k-points defining the path.
ndivsm: Number of division for the smallest segment.
comment: Comment string.
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Static constructor for path in k-space.
Args:
structure: :class:`Structure` object.
kpath_bounds: List with the reduced coordinates of the k-points defining the path.
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Static constructor for path in k-space.
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structure: :class:`Structure` object.
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train | KSampling.path_from_structure | See _path for the meaning of the variables | pymatgen/io/abinit/abiobjects.py | def path_from_structure(cls, ndivsm, structure):
"""See _path for the meaning of the variables"""
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train | KSampling.explicit_path | See _path for the meaning of the variables | pymatgen/io/abinit/abiobjects.py | def explicit_path(cls, ndivsm, kpath_bounds):
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train | KSampling.automatic_density | Returns an automatic Kpoint object based on a structure and a kpoint
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Algorithm:
Uses a simple approach scaling the number of divisions along each
reciprocal lattice vector proportional to... | pymatgen/io/abinit/abiobjects.py | def automatic_density(cls, structure, kppa, chksymbreak=None, use_symmetries=True, use_time_reversal=True,
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"""
Returns an automatic Kpoint object based on a structure and a kpoint
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train | RelaxationMethod.to_abivars | Returns a dictionary with the abinit variables | pymatgen/io/abinit/abiobjects.py | def to_abivars(self):
"""Returns a dictionary with the abinit variables"""
# These variables are always present.
out_vars = {
"ionmov" : self.abivars.ionmov,
"optcell": self.abivars.optcell,
"ntime" : self.abivars.ntime,
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# Atom relaxation.
... | def to_abivars(self):
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train | PPModel.as_ppmodel | Constructs an instance of PPModel from obj.
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* string. e.g "godby:12.3 eV", "linden". | pymatgen/io/abinit/abiobjects.py | def as_ppmodel(cls, obj):
"""
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Accepts obj in the form:
* PPmodel instance
* string. e.g "godby:12.3 eV", "linden".
"""
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# obj is a string
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train | HilbertTransform.to_abivars | Returns a dictionary with the abinit variables | pymatgen/io/abinit/abiobjects.py | def to_abivars(self):
"""Returns a dictionary with the abinit variables"""
return {
# Spectral function
"nomegasf": self.nomegasf,
"domegasf": self.domegasf,
"spmeth" : self.spmeth,
# Frequency mesh for the polarizability
... | def to_abivars(self):
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"domegasf": self.domegasf,
"spmeth" : self.spmeth,
# Frequency mesh for the polarizability
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train | Screening.to_abivars | Returns a dictionary with the abinit variables | pymatgen/io/abinit/abiobjects.py | def to_abivars(self):
"""Returns a dictionary with the abinit variables"""
abivars = {
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train | SelfEnergy.gwcalctyp | Returns the value of the gwcalctyp input variable. | pymatgen/io/abinit/abiobjects.py | def gwcalctyp(self):
"""Returns the value of the gwcalctyp input variable."""
dig0 = str(self._SIGMA_TYPES[self.type])
dig1 = str(self._SC_MODES[self.sc_mode])
return dig1.strip() + dig0.strip() | def gwcalctyp(self):
"""Returns the value of the gwcalctyp input variable."""
dig0 = str(self._SIGMA_TYPES[self.type])
dig1 = str(self._SC_MODES[self.sc_mode])
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train | SelfEnergy.to_abivars | Returns a dictionary with the abinit variables. | pymatgen/io/abinit/abiobjects.py | def to_abivars(self):
"""Returns a dictionary with the abinit variables."""
abivars = dict(
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ecuteps=self.ecuteps,
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train | ExcHamiltonian.to_abivars | Returns a dictionary with the abinit variables. | pymatgen/io/abinit/abiobjects.py | def to_abivars(self):
"""Returns a dictionary with the abinit variables."""
abivars = dict(
bs_calctype=1,
bs_loband=self.bs_loband,
#nband=self.nband,
mbpt_sciss=self.mbpt_sciss,
ecuteps=self.ecuteps,
bs_algorithm=self._ALGO2VAR[se... | def to_abivars(self):
"""Returns a dictionary with the abinit variables."""
abivars = dict(
bs_calctype=1,
bs_loband=self.bs_loband,
#nband=self.nband,
mbpt_sciss=self.mbpt_sciss,
ecuteps=self.ecuteps,
bs_algorithm=self._ALGO2VAR[se... | [
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train | BandstructureLoader.set_upper_lower_bands | Set fake upper/lower bands, useful to set the same energy
range in the spin up/down bands when calculating the DOS | pymatgen/electronic_structure/boltztrap2.py | def set_upper_lower_bands(self,e_lower,e_upper):
"""
Set fake upper/lower bands, useful to set the same energy
range in the spin up/down bands when calculating the DOS
"""
lower_band = e_lower*np.ones((1,self.ebands.shape[1]))
upper_band = e_upper*np.ones((1,self.... | def set_upper_lower_bands(self,e_lower,e_upper):
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Set fake upper/lower bands, useful to set the same energy
range in the spin up/down bands when calculating the DOS
"""
lower_band = e_lower*np.ones((1,self.ebands.shape[1]))
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train | VasprunLoader.from_file | Get a vasprun.xml file and return a VasprunLoader | pymatgen/electronic_structure/boltztrap2.py | def from_file(self, vasprun_file):
"""Get a vasprun.xml file and return a VasprunLoader"""
vrun_obj = Vasprun(vasprun_file, parse_projected_eigen=True)
return VasprunLoader(vrun_obj) | def from_file(self, vasprun_file):
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train | VasprunLoader.bandana | Cut out bands outside the range (emin,emax) | pymatgen/electronic_structure/boltztrap2.py | def bandana(self, emin=-np.inf, emax=np.inf):
"""Cut out bands outside the range (emin,emax)"""
bandmin = np.min(self.ebands, axis=1)
bandmax = np.max(self.ebands, axis=1)
ii = np.nonzero(bandmin < emax)
nemax = ii[0][-1]
ii = np.nonzero(bandmax > emin)
nemin = ii... | def bandana(self, emin=-np.inf, emax=np.inf):
"""Cut out bands outside the range (emin,emax)"""
bandmin = np.min(self.ebands, axis=1)
bandmax = np.max(self.ebands, axis=1)
ii = np.nonzero(bandmin < emax)
nemax = ii[0][-1]
ii = np.nonzero(bandmax > emin)
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train | BztInterpolator.get_band_structure | Return a BandStructureSymmLine object interpolating bands along a
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kpath = HighSymmKpath(self.data.structure)
kpt_line = [Kpoint(k, self.data.structure.lattice) for k
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kpath = HighSymmKpath(self.data.structure)
kpt_line = [Kpoint(k, self.data.structure.lattice) for k
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train | BztInterpolator.get_dos | Return a Dos object interpolating bands
Args:
partial_dos: if True, projections will be interpolated as well
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in the loader.
npts_mu: number of energy points of the Dos
... | pymatgen/electronic_structure/boltztrap2.py | def get_dos(self, partial_dos=False, npts_mu=10000, T=None):
"""
Return a Dos object interpolating bands
Args:
partial_dos: if True, projections will be interpolated as well
and partial doses will be return. Projections must be available
... | def get_dos(self, partial_dos=False, npts_mu=10000, T=None):
"""
Return a Dos object interpolating bands
Args:
partial_dos: if True, projections will be interpolated as well
and partial doses will be return. Projections must be available
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train | BztInterpolator.get_partial_doses | Return a CompleteDos object interpolating the projections
tdos: total dos previously calculated
npts_mu: number of energy points of the Dos
T: parameter used to smooth the Dos | pymatgen/electronic_structure/boltztrap2.py | def get_partial_doses(self, tdos, npts_mu, T):
"""
Return a CompleteDos object interpolating the projections
tdos: total dos previously calculated
npts_mu: number of energy points of the Dos
T: parameter used to smooth the Dos
"""
spin = self.data... | def get_partial_doses(self, tdos, npts_mu, T):
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npts_mu: number of energy points of the Dos
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train | BztTransportProperties.compute_properties_doping | Calculate all the properties w.r.t. the doping levels in input.
Args:
doping: numpy array specifing the doping levels
When executed, it add the following variable at the BztTransportProperties
object:
Conductivity_doping, Seebeck_doping, Kappa_doping, Power_Factor_dopin... | pymatgen/electronic_structure/boltztrap2.py | def compute_properties_doping(self, doping, temp_r=None):
"""
Calculate all the properties w.r.t. the doping levels in input.
Args:
doping: numpy array specifing the doping levels
When executed, it add the following variable at the BztTransportProperties
object:
... | def compute_properties_doping(self, doping, temp_r=None):
"""
Calculate all the properties w.r.t. the doping levels in input.
Args:
doping: numpy array specifing the doping levels
When executed, it add the following variable at the BztTransportProperties
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train | BztPlotter.plot_props | Function to plot the transport properties.
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prop_y: property to plot among ("Conductivity","Seebeck","Kappa","Carrier_conc","Hall_carrier_conc_trace"). Abbreviations are possible, like "S" for "Seebeck"
prop_x: independent variable in the x-axis among ('mu','doping','te... | pymatgen/electronic_structure/boltztrap2.py | def plot_props(self, prop_y, prop_x, prop_z='temp',
output='avg_eigs', dop_type='n', doping=None,
temps=None, xlim=(-2, 2), ax=None):
"""
Function to plot the transport properties.
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train | BztPlotter.plot_bands | Plot a band structure on symmetry line using BSPlotter() | pymatgen/electronic_structure/boltztrap2.py | def plot_bands(self):
"""
Plot a band structure on symmetry line using BSPlotter()
"""
if self.bzt_interp is None:
raise BoltztrapError("BztInterpolator not present")
sbs = self.bzt_interp.get_band_structure()
return BSPlotter(sbs).get_plot() | def plot_bands(self):
"""
Plot a band structure on symmetry line using BSPlotter()
"""
if self.bzt_interp is None:
raise BoltztrapError("BztInterpolator not present")
sbs = self.bzt_interp.get_band_structure()
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train | BztPlotter.plot_dos | Plot the total Dos using DosPlotter() | pymatgen/electronic_structure/boltztrap2.py | def plot_dos(self, T=None, npoints=10000):
"""
Plot the total Dos using DosPlotter()
"""
if self.bzt_interp is None:
raise BoltztrapError("BztInterpolator not present")
tdos = self.bzt_interp.get_dos(T=T,npts_mu=npoints)
#print(npoints)
dosPlotter... | def plot_dos(self, T=None, npoints=10000):
"""
Plot the total Dos using DosPlotter()
"""
if self.bzt_interp is None:
raise BoltztrapError("BztInterpolator not present")
tdos = self.bzt_interp.get_dos(T=T,npts_mu=npoints)
#print(npoints)
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train | BalancedReaction.calculate_energy | Calculates the energy of the reaction.
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energies ({Composition: float}): Energy for each composition.
E.g ., {comp1: energy1, comp2: energy2}.
Returns:
reaction energy as a float. | pymatgen/analysis/reaction_calculator.py | def calculate_energy(self, energies):
"""
Calculates the energy of the reaction.
Args:
energies ({Composition: float}): Energy for each composition.
E.g ., {comp1: energy1, comp2: energy2}.
Returns:
reaction energy as a float.
"""
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Calculates the energy of the reaction.
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energies ({Composition: float}): Energy for each composition.
E.g ., {comp1: energy1, comp2: energy2}.
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Args:
comp (Composition): Composition to normalize to
factor (float): Factor to normalize to. Defaults to 1... | pymatgen/analysis/reaction_calculator.py | def normalize_to(self, comp, factor=1):
"""
Normalizes the reaction to one of the compositions.
By default, normalizes such that the composition given has a
coefficient of 1. Another factor can be specified.
Args:
comp (Composition): Composition to normalize to
... | def normalize_to(self, comp, factor=1):
"""
Normalizes the reaction to one of the compositions.
By default, normalizes such that the composition given has a
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comp (Composition): Composition to normalize to
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train | BalancedReaction.normalize_to_element | Normalizes the reaction to one of the elements.
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Another factor can be specified.
Args:
element (Element/Specie): Element to normalize to.
factor (float): Factor to normalize to. Defaults to 1. | pymatgen/analysis/reaction_calculator.py | def normalize_to_element(self, element, factor=1):
"""
Normalizes the reaction to one of the elements.
By default, normalizes such that the amount of the element is 1.
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element (Element/Specie): Element to normalize to.
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Normalizes the reaction to one of the elements.
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train | BalancedReaction.get_el_amount | Returns the amount of the element in the reaction.
Args:
element (Element/Specie): Element in the reaction
Returns:
Amount of that element in the reaction. | pymatgen/analysis/reaction_calculator.py | def get_el_amount(self, element):
"""
Returns the amount of the element in the reaction.
Args:
element (Element/Specie): Element in the reaction
Returns:
Amount of that element in the reaction.
"""
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element (Element/Specie): Element in the reaction
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train | BalancedReaction.reactants | List of reactants | pymatgen/analysis/reaction_calculator.py | def reactants(self):
"""
List of reactants
"""
return [self._all_comp[i] for i in range(len(self._all_comp))
if self._coeffs[i] < 0] | def reactants(self):
"""
List of reactants
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train | BalancedReaction.products | List of products | pymatgen/analysis/reaction_calculator.py | def products(self):
"""
List of products
"""
return [self._all_comp[i] for i in range(len(self._all_comp))
if self._coeffs[i] > 0] | def products(self):
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train | BalancedReaction.as_entry | Returns a ComputedEntry representation of the reaction.
:return: | pymatgen/analysis/reaction_calculator.py | def as_entry(self, energies):
"""
Returns a ComputedEntry representation of the reaction.
:return:
"""
relevant_comp = [comp * abs(coeff) for coeff, comp
in zip(self._coeffs, self._all_comp)]
comp = sum(relevant_comp, Composition())
entry ... | def as_entry(self, energies):
"""
Returns a ComputedEntry representation of the reaction.
:return:
"""
relevant_comp = [comp * abs(coeff) for coeff, comp
in zip(self._coeffs, self._all_comp)]
comp = sum(relevant_comp, Composition())
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train | BalancedReaction.from_string | Generates a balanced reaction from a string. The reaction must
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Args:
rxn_string:
The reaction string. For example, "4 Li + O2-> 2Li2O"
Returns:
BalancedReaction | pymatgen/analysis/reaction_calculator.py | def from_string(rxn_string):
"""
Generates a balanced reaction from a string. The reaction must
already be balanced.
Args:
rxn_string:
The reaction string. For example, "4 Li + O2-> 2Li2O"
Returns:
BalancedReaction
"""
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"""
Generates a balanced reaction from a string. The reaction must
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rxn_string:
The reaction string. For example, "4 Li + O2-> 2Li2O"
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train | ComputedReaction.all_entries | Equivalent of all_comp but returns entries, in the same order as the
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"""
Equivalent of all_comp but returns entries, in the same order as the
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"""
entries = []
for c in self._all_comp:
for e in self._all_entries:
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Equivalent of all_comp but returns entries, in the same order as the
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"""
entries = []
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train | get_energy_tersoff | Compute the energy of a structure using Tersoff potential.
Args:
structure: pymatgen.core.structure.Structure
gulp_cmd: GULP command if not in standard place | pymatgen/command_line/gulp_caller.py | def get_energy_tersoff(structure, gulp_cmd='gulp'):
"""
Compute the energy of a structure using Tersoff potential.
Args:
structure: pymatgen.core.structure.Structure
gulp_cmd: GULP command if not in standard place
"""
gio = GulpIO()
gc = GulpCaller(gulp_cmd)
gin = gio.tersof... | def get_energy_tersoff(structure, gulp_cmd='gulp'):
"""
Compute the energy of a structure using Tersoff potential.
Args:
structure: pymatgen.core.structure.Structure
gulp_cmd: GULP command if not in standard place
"""
gio = GulpIO()
gc = GulpCaller(gulp_cmd)
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train | get_energy_buckingham | Compute the energy of a structure using Buckingham potential.
Args:
structure: pymatgen.core.structure.Structure
gulp_cmd: GULP command if not in standard place
keywords: GULP first line keywords
valence_dict: {El: valence}. Needed if the structure is not charge
neutral. | pymatgen/command_line/gulp_caller.py | def get_energy_buckingham(structure, gulp_cmd='gulp',
keywords=('optimise', 'conp', 'qok'),
valence_dict=None):
"""
Compute the energy of a structure using Buckingham potential.
Args:
structure: pymatgen.core.structure.Structure
gulp_cmd: ... | def get_energy_buckingham(structure, gulp_cmd='gulp',
keywords=('optimise', 'conp', 'qok'),
valence_dict=None):
"""
Compute the energy of a structure using Buckingham potential.
Args:
structure: pymatgen.core.structure.Structure
gulp_cmd: ... | [
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train | get_energy_relax_structure_buckingham | Relax a structure and compute the energy using Buckingham potential.
Args:
structure: pymatgen.core.structure.Structure
gulp_cmd: GULP command if not in standard place
keywords: GULP first line keywords
valence_dict: {El: valence}. Needed if the structure is not charge
n... | pymatgen/command_line/gulp_caller.py | def get_energy_relax_structure_buckingham(structure,
gulp_cmd='gulp',
keywords=('optimise', 'conp'),
valence_dict=None):
"""
Relax a structure and compute the energy using Buckingham pot... | def get_energy_relax_structure_buckingham(structure,
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valence_dict=None):
"""
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train | GulpIO.structure_lines | Generates GULP input string corresponding to pymatgen structure.
Args:
structure: pymatgen Structure object
cell_flg (default = True): Option to use lattice parameters.
fractional_flg (default = True): If True, fractional coordinates
are used. Else, cartesian... | pymatgen/command_line/gulp_caller.py | def structure_lines(self, structure, cell_flg=True, frac_flg=True,
anion_shell_flg=True, cation_shell_flg=False,
symm_flg=True):
"""
Generates GULP input string corresponding to pymatgen structure.
Args:
structure: pymatgen Structure o... | def structure_lines(self, structure, cell_flg=True, frac_flg=True,
anion_shell_flg=True, cation_shell_flg=False,
symm_flg=True):
"""
Generates GULP input string corresponding to pymatgen structure.
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train | GulpIO.library_line | Specifies GULP library file to read species and potential parameters.
If using library don't specify species and potential
in the input file and vice versa. Make sure the elements of
structure are in the library file.
Args:
file_name: Name of GULP library file
Retur... | pymatgen/command_line/gulp_caller.py | def library_line(self, file_name):
"""
Specifies GULP library file to read species and potential parameters.
If using library don't specify species and potential
in the input file and vice versa. Make sure the elements of
structure are in the library file.
Args:
... | def library_line(self, file_name):
"""
Specifies GULP library file to read species and potential parameters.
If using library don't specify species and potential
in the input file and vice versa. Make sure the elements of
structure are in the library file.
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train | GulpIO.buckingham_input | Gets a GULP input for an oxide structure and buckingham potential
from library.
Args:
structure: pymatgen.core.structure.Structure
keywords: GULP first line keywords.
library (Default=None): File containing the species and potential.
uc (Default=True): Un... | pymatgen/command_line/gulp_caller.py | def buckingham_input(self, structure, keywords, library=None,
uc=True, valence_dict=None):
"""
Gets a GULP input for an oxide structure and buckingham potential
from library.
Args:
structure: pymatgen.core.structure.Structure
keywords: GU... | def buckingham_input(self, structure, keywords, library=None,
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"""
Gets a GULP input for an oxide structure and buckingham potential
from library.
Args:
structure: pymatgen.core.structure.Structure
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train | GulpIO.buckingham_potential | Generate species, buckingham, and spring options for an oxide structure
using the parameters in default libraries.
Ref:
1. G.V. Lewis and C.R.A. Catlow, J. Phys. C: Solid State Phys.,
18, 1149-1161 (1985)
2. T.S.Bush, J.D.Gale, C.R.A.Catlow and P.D. Battle,
... | pymatgen/command_line/gulp_caller.py | def buckingham_potential(self, structure, val_dict=None):
"""
Generate species, buckingham, and spring options for an oxide structure
using the parameters in default libraries.
Ref:
1. G.V. Lewis and C.R.A. Catlow, J. Phys. C: Solid State Phys.,
18, 1149-1161 ... | def buckingham_potential(self, structure, val_dict=None):
"""
Generate species, buckingham, and spring options for an oxide structure
using the parameters in default libraries.
Ref:
1. G.V. Lewis and C.R.A. Catlow, J. Phys. C: Solid State Phys.,
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train | GulpIO.tersoff_input | Gets a GULP input with Tersoff potential for an oxide structure
Args:
structure: pymatgen.core.structure.Structure
periodic (Default=False): Flag denoting whether periodic
boundary conditions are used
library (Default=None): File containing the species and po... | pymatgen/command_line/gulp_caller.py | def tersoff_input(self, structure, periodic=False, uc=True, *keywords):
"""
Gets a GULP input with Tersoff potential for an oxide structure
Args:
structure: pymatgen.core.structure.Structure
periodic (Default=False): Flag denoting whether periodic
boundar... | def tersoff_input(self, structure, periodic=False, uc=True, *keywords):
"""
Gets a GULP input with Tersoff potential for an oxide structure
Args:
structure: pymatgen.core.structure.Structure
periodic (Default=False): Flag denoting whether periodic
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train | GulpIO.tersoff_potential | Generate the species, tersoff potential lines for an oxide structure
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Generate the species, tersoff potential lines for an oxide structure
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train | GulpCaller.run | Run GULP using the gin as input
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train | autodoc_event_handlers | Print to the given string, the documentation for the events
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Print to the given string, the documentation for the events
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train | get_event_handler_classes | Return the list of handler classes. | pymatgen/io/abinit/events.py | def get_event_handler_classes(categories=None):
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train | as_event_class | Convert obj into a subclass of AbinitEvent.
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"""
Convert obj into a subclass of AbinitEvent.
obj can be either a class or a string with the class name or the YAML tag
"""
if is_string(obj):
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raise ValueE... | def as_event_class(obj):
"""
Convert obj into a subclass of AbinitEvent.
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train | AbinitEvent.baseclass | The baseclass of self. | pymatgen/io/abinit/events.py | def baseclass(self):
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train | EventReport.append | Add an event to the list. | pymatgen/io/abinit/events.py | def append(self, event):
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train | EventReport.set_run_completed | Set the value of _run_completed. | pymatgen/io/abinit/events.py | def set_run_completed(self, boolean, start_datetime, end_datetime):
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self._run_completed = boolean
if (start_datetime, end_datetime) != (None, None):
# start_datetime: Sat Feb 28 23:54:27 2015
# end_datetime: Sat Feb 28 23:54:30 2015... | def set_run_completed(self, boolean, start_datetime, end_datetime):
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train | EventReport.run_etime | Wall-time of the run as `timedelta` object. | pymatgen/io/abinit/events.py | def run_etime(self):
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train | EventsParser.parse | Parse the given file. Return :class:`EventReport`. | pymatgen/io/abinit/events.py | def parse(self, filename, verbose=0):
"""
Parse the given file. Return :class:`EventReport`.
"""
run_completed, start_datetime, end_datetime = False, None, None
filename = os.path.abspath(filename)
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w = WildCard("*Error|*Warning|*Com... | def parse(self, filename, verbose=0):
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Parse the given file. Return :class:`EventReport`.
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train | EventsParser.report_exception | This method is used when self.parser raises an Exception so that
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"""
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train | EventHandler.count | Return the number of times the event associated to this handler
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"""
Return the number of times the event associated to this handler
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"""
return len([c for c in task.corrections if c["event"]["@class"] == self.event_class]) | def count(self, task):
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"""
Sets the stable charges and transition states for a series of
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Sets the stable charges and transition states for a series of
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train | DefectPhaseDiagram.all_unstable_entries | List all unstable entries (defect+charge) in the DefectPhaseDiagram | pymatgen/analysis/defects/thermodynamics.py | def all_unstable_entries(self):
"""
List all unstable entries (defect+charge) in the DefectPhaseDiagram
"""
all_stable_entries = self.all_stable_entries
return [e for e in self.entries if e not in all_stable_entries] | def all_unstable_entries(self):
"""
List all unstable entries (defect+charge) in the DefectPhaseDiagram
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train | DefectPhaseDiagram.defect_concentrations | Give list of all concentrations at specified efermi in the DefectPhaseDiagram
args:
chemical_potentials = {Element: number} is dictionary of chemical potentials to provide formation energies for
temperature = temperature to produce concentrations from
fermi_level: (float) is ... | pymatgen/analysis/defects/thermodynamics.py | def defect_concentrations(self, chemical_potentials, temperature=300, fermi_level=0.):
"""
Give list of all concentrations at specified efermi in the DefectPhaseDiagram
args:
chemical_potentials = {Element: number} is dictionary of chemical potentials to provide formation energies fo... | def defect_concentrations(self, chemical_potentials, temperature=300, fermi_level=0.):
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Give list of all concentrations at specified efermi in the DefectPhaseDiagram
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train | DefectPhaseDiagram.suggest_charges | Suggest possible charges for defects to computee based on proximity
of known transitions from entires to VBM and CBM
Args:
tolerance (float): tolerance with respect to the VBM and CBM to
` continue to compute new charges | pymatgen/analysis/defects/thermodynamics.py | def suggest_charges(self, tolerance=0.1):
"""
Suggest possible charges for defects to computee based on proximity
of known transitions from entires to VBM and CBM
Args:
tolerance (float): tolerance with respect to the VBM and CBM to
` continue to... | def suggest_charges(self, tolerance=0.1):
"""
Suggest possible charges for defects to computee based on proximity
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Args:
tolerance (float): tolerance with respect to the VBM and CBM to
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train | DefectPhaseDiagram.solve_for_fermi_energy | Solve for the Fermi energy self-consistently as a function of T
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Observations are Defect concentrations, electron and hole conc
Args:
bulk_dos: bulk system dos (pymatgen Dos object)
gap: Can be used to specify experimental gap.
Will be useful if th... | pymatgen/analysis/defects/thermodynamics.py | def solve_for_fermi_energy(self, temperature, chemical_potentials, bulk_dos):
"""
Solve for the Fermi energy self-consistently as a function of T
and p_O2
Observations are Defect concentrations, electron and hole conc
Args:
bulk_dos: bulk system dos (pymatgen Dos obje... | def solve_for_fermi_energy(self, temperature, chemical_potentials, bulk_dos):
"""
Solve for the Fermi energy self-consistently as a function of T
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Observations are Defect concentrations, electron and hole conc
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bulk_dos: bulk system dos (pymatgen Dos obje... | [
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train | XcFunc.asxc | Convert object into Xcfunc. | pymatgen/core/xcfunc.py | def asxc(cls, obj):
"""Convert object into Xcfunc."""
if isinstance(obj, cls): return obj
if is_string(obj): return cls.from_name(obj)
raise TypeError("Don't know how to convert <%s:%s> to Xcfunc" % (type(obj), str(obj))) | def asxc(cls, obj):
"""Convert object into Xcfunc."""
if isinstance(obj, cls): return obj
if is_string(obj): return cls.from_name(obj)
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