Source code for pymatgen.entries.computed_entries

# coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.

"""
This module implements equivalents of the basic ComputedEntry objects, which
is the basic entity that can be used to perform many analyses. ComputedEntries
contain calculated information, typically from VASP or other electronic
structure codes. For example, ComputedEntries can be used as inputs for phase
diagram analysis.
"""

import json
import abc

from monty.json import MontyEncoder, MontyDecoder, MSONable

from pymatgen.core.composition import Composition
from pymatgen.core.structure import Structure
from pymatgen.entries import Entry

__author__ = "Ryan Kingsbury, Shyue Ping Ong, Anubhav Jain"
__copyright__ = "Copyright 2011-2020, The Materials Project"
__version__ = "1.1"
__maintainer__ = "Shyue Ping Ong"
__email__ = "shyuep@gmail.com"
__status__ = "Production"
__date__ = "April 2020"


[docs]class EnergyAdjustment(MSONable): """ Lightweight class to contain information about an energy adjustment or energy correction. """ def __init__(self, value, name="Manual adjustment", cls=None, description=""): """ Args: value: float, value of the energy adjustment in eV name: str, human-readable name of the energy adjustment. (Default: Manual adjustment) cls: dict, Serialized Compatibility class used to generate the energy adjustment. (Default: None) description: str, human-readable explanation of the energy adjustment. """ self.name = name self.cls = cls if cls else {} self.description = description @property @abc.abstractmethod def value(self): """ Return the value of the energy adjustment in eV """ def __repr__(self): output = ["{}:".format(self.__class__.__name__), " Name: {}".format(self.name), " Value: {:.3f} eV".format(self.value), " Description: {}".format(self.description), " Generated by: {}".format(self.cls.get("@class", None))] return "\n".join(output) @abc.abstractmethod def _normalize(self, factor): """ Scale the value of the energy adjustment by factor. This method is utilized in ComputedEntry.normalize() to scale the energies to a formula unit basis (e.g. E_Fe6O9 = 3 x E_Fe2O3). """
[docs]class ConstantEnergyAdjustment(EnergyAdjustment): """ A constant energy adjustment applied to a ComputedEntry. Useful in energy referencing schemes such as the Aqueous energy referencing scheme. """ def __init__(self, value, name="Constant energy adjustment", cls=None, description="Constant energy adjustment"): """ Args: value: float, value of the energy adjustment in eV name: str, human-readable name of the energy adjustment. (Default: Constant energy adjustment) cls: dict, Serialized Compatibility class used to generate the energy adjustment. (Default: None) description: str, human-readable explanation of the energy adjustment. """ description = description + " ({:.3f} eV)".format(value) super().__init__(value, name, cls, description) self._value = value @property def value(self): """ Return the value of the energy correction in eV. """ return self._value @value.setter def value(self, x): self._value = x def _normalize(self, factor): self._value /= factor
[docs]class ManualEnergyAdjustment(ConstantEnergyAdjustment): """ A manual energy adjustment applied to a ComputedEntry. """ def __init__(self, value): """ Args: value: float, value of the energy adjustment in eV """ name = "Manual energy adjustment" description = "Manual energy adjustment" super().__init__(value, name, cls=None, description=description)
[docs]class CompositionEnergyAdjustment(EnergyAdjustment): """ An energy adjustment applied to a ComputedEntry based on the atomic composition. Used in various DFT energy correction schemes. """ def __init__(self, adj_per_atom, n_atoms, name, cls=None, description="Composition-based energy adjustment"): """ Args: adj_per_atom: float, energy adjustment to apply per atom, in eV/atom n_atoms: float or int, number of atoms name: str, human-readable name of the energy adjustment. (Default: "") cls: dict, Serialized Compatibility class used to generate the energy adjustment. (Default: None) description: str, human-readable explanation of the energy adjustment. """ self._value = adj_per_atom self.n_atoms = n_atoms self.cls = cls if cls else {} self.name = name self.description = description + " ({:.3f} eV/atom x {} atoms)".format(self._value, self.n_atoms ) @property def value(self): """ Return the value of the energy adjustment in eV. """ return self._value * self.n_atoms def _normalize(self, factor): self.n_atoms /= factor
[docs]class TemperatureEnergyAdjustment(EnergyAdjustment): """ An energy adjustment applied to a ComputedEntry based on the temperature. Used, for example, to add entropy to DFT energies. """ def __init__(self, adj_per_deg, temp, n_atoms, name="", cls=None, description="Temperature-based energy adjustment"): """ Args: adj_per_deg: float, energy adjustment to apply per degree K, in eV/atom temp: float, temperature in Kelvin n_atoms: float or int, number of atoms name: str, human-readable name of the energy adjustment. (Default: "") cls: dict, Serialized Compatibility class used to generate the energy adjustment. (Default: None) description: str, human-readable explanation of the energy adjustment. """ self._value = adj_per_deg self.temp = temp self.n_atoms = n_atoms self.name = name self.cls = cls if cls else {} self.description = description + " ({:.4f} eV/K/atom x {} K x {} atoms)".format(self._value, self.temp, self.n_atoms, ) @property def value(self): """ Return the value of the energy correction in eV. """ return self._value * self.temp * self.n_atoms def _normalize(self, factor): self.n_atoms /= factor
[docs]class ComputedEntry(Entry): """ Lightweight Entry object for computed data. Contains facilities for applying corrections to the .energy attribute and for storing calculation parameters. """ def __init__(self, composition: Composition, energy: float, correction: float = 0.0, energy_adjustments: list = None, parameters: dict = None, data: dict = None, entry_id: object = None): """ Initializes a ComputedEntry. Args: composition (Composition): Composition of the entry. For flexibility, this can take the form of all the typical input taken by a Composition, including a {symbol: amt} dict, a string formula, and others. energy (float): Energy of the entry. Usually the final calculated energy from VASP or other electronic structure codes. energy_adjustments: An optional list of EnergyAdjustment to be applied to the energy. This is used to modify the energy for certain analyses. Defaults to None. parameters: An optional dict of parameters associated with the entry. Defaults to None. data: An optional dict of any additional data associated with the entry. Defaults to None. entry_id: An optional id to uniquely identify the entry. """ super().__init__(composition, energy) self.uncorrected_energy = self._energy self.energy_adjustments = energy_adjustments if energy_adjustments else [] if correction != 0.0: if energy_adjustments: raise ValueError("Argument conflict! Setting correction = {:.3f} conflicts " "with setting energy_adjustments. Specify one or the " "other.".format(correction)) self.correction = correction self.parameters = parameters if parameters else {} self.data = data if data else {} self.entry_id = entry_id self.name = self.composition.reduced_formula @property def energy(self) -> float: """ :return: the *corrected* energy of the entry. """ return self._energy + self.correction @property def correction(self) -> float: """ Returns: float: the total energy correction / adjustment applied to the entry, in eV. """ return sum([e.value for e in self.energy_adjustments]) @correction.setter def correction(self, x: float) -> None: corr = ManualEnergyAdjustment(x) self.energy_adjustments = [corr]
[docs] def normalize(self, mode: str = "formula_unit") -> None: """ Normalize the entry's composition and energy. Args: mode: "formula_unit" is the default, which normalizes to composition.reduced_formula. The other option is "atom", which normalizes such that the composition amounts sum to 1. """ factor = self._normalization_factor(mode) self.uncorrected_energy /= factor for ea in self.energy_adjustments: ea._normalize(factor) super().normalize(mode)
def __repr__(self): n_atoms = self.composition.num_atoms output = ["{} {:<10} - {:<12} ({})".format(str(self.entry_id), type(self).__name__, self.composition.formula, self.composition.reduced_formula), "{:<24} = {:<9.4f} eV ({:<8.4f} eV/atom)".format("Energy (Uncorrected)", self._energy, self._energy / n_atoms), "{:<24} = {:<9.4f} eV ({:<8.4f} eV/atom)".format("Correction", self.correction, self.correction / n_atoms), "{:<24} = {:<9.4f} eV ({:<8.4f} eV/atom)".format("Energy (Final)", self.energy, self.energy_per_atom), "Energy Adjustments:" ] if len(self.energy_adjustments) == 0: output.append(" None") else: for e in self.energy_adjustments: output.append(" {:<23}: {:<9.4f} eV ({:<8.4f} eV/atom)".format(e.name, e.value, e.value / n_atoms)) output.append("Parameters:") for k, v in self.parameters.items(): output.append(" {:<22} = {}".format(k, v)) output.append("Data:") for k, v in self.data.items(): output.append(" {:<22} = {}".format(k, v)) return "\n".join(output) def __str__(self): return self.__repr__()
[docs] @classmethod def from_dict(cls, d) -> 'ComputedEntry': """ :param d: Dict representation. :return: ComputedEntry """ dec = MontyDecoder() # the first block here is for legacy ComputedEntry that were # serialized before we had the energy_adjustments attribute. if d["correction"] != 0 and not d.get("energy_adjustments"): return cls(d["composition"], d["energy"], d["correction"], parameters={k: dec.process_decoded(v) for k, v in d.get("parameters", {}).items()}, data={k: dec.process_decoded(v) for k, v in d.get("data", {}).items()}, entry_id=d.get("entry_id", None)) # this is the preferred / modern way of instantiating ComputedEntry # we don't pass correction explicitly because it will be calculated # on the fly from energy_adjustments else: return cls(d["composition"], d["energy"], correction=0, energy_adjustments=[dec.process_decoded(e) for e in d.get("energy_adjustments", {})], parameters={k: dec.process_decoded(v) for k, v in d.get("parameters", {}).items()}, data={k: dec.process_decoded(v) for k, v in d.get("data", {}).items()}, entry_id=d.get("entry_id", None))
[docs] def as_dict(self) -> dict: """ :return: MSONable dict. """ return_dict = super().as_dict() return_dict.update({"energy_adjustments": json.loads(json.dumps(self.energy_adjustments, cls=MontyEncoder)), "parameters": json.loads(json.dumps(self.parameters, cls=MontyEncoder)), "data": json.loads(json.dumps(self.data, cls=MontyEncoder)), "entry_id": self.entry_id, "correction": self.correction}) return return_dict
[docs]class ComputedStructureEntry(ComputedEntry): """ A heavier version of ComputedEntry which contains a structure as well. The structure is needed for some analyses. """ def __init__(self, structure: Structure, energy: float, correction: float = 0.0, energy_adjustments: list = None, parameters: dict = None, data: dict = None, entry_id: object = None): """ Initializes a ComputedStructureEntry. Args: structure (Structure): The actual structure of an entry. energy (float): Energy of the entry. Usually the final calculated energy from VASP or other electronic structure codes. energy_adjustments: An optional list of EnergyAdjustment to be applied to the energy. This is used to modify the energy for certain analyses. Defaults to None. parameters: An optional dict of parameters associated with the entry. Defaults to None. data: An optional dict of any additional data associated with the entry. Defaults to None. entry_id: An optional id to uniquely identify the entry. """ super().__init__( structure.composition, energy, correction=correction, energy_adjustments=energy_adjustments, parameters=parameters, data=data, entry_id=entry_id) self.structure = structure
[docs] def as_dict(self) -> dict: """ :return: MSONAble dict. """ d = super().as_dict() d["@module"] = self.__class__.__module__ d["@class"] = self.__class__.__name__ d["structure"] = self.structure.as_dict() return d
[docs] @classmethod def from_dict(cls, d) -> 'ComputedStructureEntry': """ :param d: Dict representation. :return: ComputedStructureEntry """ dec = MontyDecoder() # the first block here is for legacy ComputedEntry that were # serialized before we had the energy_adjustments attribute. if d["correction"] != 0 and not d.get("energy_adjustments"): return cls(dec.process_decoded(d["structure"]), d["energy"], d["correction"], parameters={k: dec.process_decoded(v) for k, v in d.get("parameters", {}).items()}, data={k: dec.process_decoded(v) for k, v in d.get("data", {}).items()}, entry_id=d.get("entry_id", None)) # this is the preferred / modern way of instantiating ComputedEntry # we don't pass correction explicitly because it will be calculated # on the fly from energy_adjustments else: return cls(dec.process_decoded(d["structure"]), d["energy"], correction=0, energy_adjustments=[dec.process_decoded(e) for e in d.get("energy_adjustments", {})], parameters={k: dec.process_decoded(v) for k, v in d.get("parameters", {}).items()}, data={k: dec.process_decoded(v) for k, v in d.get("data", {}).items()}, entry_id=d.get("entry_id", None))