from __future__ import annotations import itertools import json import os import warnings from functools import cache, lru_cache from json import loads from typing import TYPE_CHECKING from emmet.core.electronic_structure import BSPathType from emmet.core.mpid import MPID from emmet.core.settings import EmmetSettings from emmet.core.tasks import TaskDoc from emmet.core.vasp.calc_types import CalcType from monty.json import MontyDecoder from packaging import version from pymatgen.analysis.phase_diagram import PhaseDiagram from pymatgen.analysis.pourbaix_diagram import IonEntry from pymatgen.core import SETTINGS, Composition, Element, Structure from pymatgen.core.ion import Ion from pymatgen.entries.computed_entries import ComputedStructureEntry from pymatgen.io.vasp import Chgcar from pymatgen.symmetry.analyzer import SpacegroupAnalyzer from requests import Session, get from mp_api.client.core import BaseRester, MPRestError from mp_api.client.core.settings import MAPIClientSettings from mp_api.client.core.utils import validate_ids from mp_api.client.routes import GeneralStoreRester, MessagesRester, UserSettingsRester from mp_api.client.routes.materials import ( AbsorptionRester, AlloysRester, BandStructureRester, BondsRester, ChemenvRester, DielectricRester, DOIRester, DosRester, ElasticityRester, ElectrodeRester, ElectronicStructureRester, EOSRester, GrainBoundaryRester, MagnetismRester, OxidationStatesRester, PhononRester, PiezoRester, ProvenanceRester, RobocrysRester, SimilarityRester, SubstratesRester, SummaryRester, SurfacePropertiesRester, SynthesisRester, TaskRester, ThermoRester, XASRester, ) from mp_api.client.routes.materials.materials import MaterialsRester from mp_api.client.routes.molecules import MoleculeRester if TYPE_CHECKING: from typing import Literal _EMMET_SETTINGS = EmmetSettings() _MAPI_SETTINGS = MAPIClientSettings() class MPRester: """Access the new Materials Project API.""" # Type hints for all routes # To re-generate this list, use: # for rester in MPRester()._all_resters: # print(f"{rester.suffix.replace('/', '_')}: {rester.__class__.__name__}") # Materials eos: EOSRester materials: MaterialsRester similarity: SimilarityRester tasks: TaskRester xas: XASRester grain_boundaries: GrainBoundaryRester substrates: SubstratesRester surface_properties: SurfacePropertiesRester phonon: PhononRester elasticity: ElasticityRester thermo: ThermoRester dielectric: DielectricRester piezoelectric: PiezoRester magnetism: MagnetismRester summary: SummaryRester robocrys: RobocrysRester synthesis: SynthesisRester insertion_electrodes: ElectrodeRester electronic_structure: ElectronicStructureRester electronic_structure_bandstructure: BandStructureRester electronic_structure_dos: DosRester oxidation_states: OxidationStatesRester provenance: ProvenanceRester bonds: BondsRester alloys: AlloysRester absorption: AbsorptionRester chemenv: ChemenvRester # Molecules molecules: MoleculeRester # Generic doi: DOIRester _user_settings: UserSettingsRester _general_store: GeneralStoreRester _messages: MessagesRester def __init__( self, api_key: str | None = None, endpoint: str | None = None, notify_db_version: bool = False, include_user_agent: bool = True, monty_decode: bool = True, use_document_model: bool = True, session: Session | None = None, headers: dict | None = None, mute_progress_bars: bool = _MAPI_SETTINGS.MUTE_PROGRESS_BARS, ): """Initialize the MPRester. Arguments: api_key (str): A String API key for accessing the MaterialsProject REST interface. Please obtain your API key at https://next-gen.materialsproject.org/api. If this is None, the code will check if there is a "MP_API_KEY" setting. If so, it will use that environment variable. This makes easier for heavy users to simply add this environment variable to their setups and MPRester can then be called without any arguments. endpoint (str): URL of endpoint to access the MaterialsProject REST interface. Defaults to the standard Materials Project REST address at "https://api.materialsproject.org", but can be changed to other URLs implementing a similar interface. notify_db_version (bool): If True, the current MP database version will be retrieved and logged locally in the ~/.mprester.log.yaml. If the database version changes, you will be notified. The current database version is also printed on instantiation. These local logs are not sent to materialsproject.org and are not associated with your API key, so be aware that a notification may not be presented if you run MPRester from multiple computing environments. include_user_agent (bool): If True, will include a user agent with the HTTP request including information on pymatgen and system version making the API request. This helps MP support pymatgen users, and is similar to what most web browsers send with each page request. Set to False to disable the user agent. monty_decode: Decode the data using monty into python objects use_document_model: If False, skip the creating the document model and return data as a dictionary. This can be simpler to work with but bypasses data validation and will not give auto-complete for available fields. session: Session object to use. By default (None), the client will create one. headers: Custom headers for localhost connections. mute_progress_bars: Whether to mute progress bars. """ # SETTINGS tries to read API key from ~/.config/.pmgrc.yaml api_key = api_key or os.getenv("MP_API_KEY") or SETTINGS.get("PMG_MAPI_KEY") if api_key and len(api_key) != 32: raise ValueError( "Please use a new API key from https://materialsproject.org/api " "Keys for the new API are 32 characters, whereas keys for the legacy " "API are 16 characters." ) self.api_key = api_key self.endpoint = endpoint or os.getenv( "MP_API_ENDPOINT", "https://api.materialsproject.org/" ) self.headers = headers or {} self.session = session or BaseRester._create_session( api_key=self.api_key, include_user_agent=include_user_agent, headers=self.headers, ) self.use_document_model = use_document_model self.monty_decode = monty_decode self.mute_progress_bars = mute_progress_bars self._contribs = None self._deprecated_attributes = [ "eos", "similarity", "tasks", "xas", "fermi", "grain_boundaries", "substrates", "surface_properties", "phonon", "elasticity", "thermo", "dielectric", "piezoelectric", "magnetism", "summary", "robocrys", "synthesis", "insertion_electrodes", "electronic_structure", "electronic_structure_bandstructure", "electronic_structure_dos", "oxidation_states", "provenance", "bonds", "alloys", "absorption", "chemenv", ] # Check if emmet version of server is compatible emmet_version = MPRester.get_emmet_version(self.endpoint) if version.parse(emmet_version.base_version) < version.parse( _MAPI_SETTINGS.MIN_EMMET_VERSION ): warnings.warn( "The installed version of the mp-api client may not be compatible with the API server. " "Please install a previous version if any problems occur." ) if notify_db_version: raise NotImplementedError("This has not yet been implemented.") if not self.endpoint.endswith("/"): self.endpoint += "/" # Dynamically set rester attributes. # First, materials and molecules top level resters are set. # Nested rested are then setup to be loaded dynamically with custom __getattr__ functions. self._all_resters = [] # Get all rester classes for _cls in BaseRester.__subclasses__(): sub_resters = _cls.__subclasses__() if sub_resters: self._all_resters.extend(sub_resters) else: self._all_resters.append(_cls) # Instantiate top level molecules and materials resters and set them as attributes core_suffix = ["molecules/core", "materials/core"] core_resters = { cls.suffix.split("/")[0]: cls( api_key=api_key, endpoint=self.endpoint, include_user_agent=include_user_agent, session=self.session, monty_decode=self.monty_decode, use_document_model=self.use_document_model, headers=self.headers, mute_progress_bars=self.mute_progress_bars, ) for cls in self._all_resters if cls.suffix in core_suffix } # Set remaining top level resters, or get an attribute-class name mapping # for all sub-resters _sub_rester_suffix_map = {"materials": {}, "molecules": {}} for cls in self._all_resters: if cls.suffix not in core_suffix: suffix_split = cls.suffix.split("/") if len(suffix_split) == 1: # Disable monty decode on nested data which may give errors monty_disable = cls in [TaskRester, ProvenanceRester] monty_decode = False if monty_disable else self.monty_decode rester = cls( api_key=api_key, endpoint=self.endpoint, include_user_agent=include_user_agent, session=self.session, monty_decode=monty_decode, use_document_model=self.use_document_model, headers=self.headers, mute_progress_bars=self.mute_progress_bars, ) # type: BaseRester setattr( self, suffix_split[0], rester, ) else: attr = "_".join(suffix_split[1:]) if "materials" in suffix_split: _sub_rester_suffix_map["materials"][attr] = cls elif "molecules" in suffix_split: _sub_rester_suffix_map["molecules"][attr] = cls # TODO: Enable monty decoding when tasks and SNL schema is normalized # # Allow lazy loading of nested resters under materials and molecules using custom __getattr__ methods def __core_custom_getattr(_self, _attr, _rester_map): if _attr in _rester_map: cls = _rester_map[_attr] monty_disable = cls in [TaskRester, ProvenanceRester] monty_decode = False if monty_disable else self.monty_decode rester = cls( api_key=api_key, endpoint=self.endpoint, include_user_agent=include_user_agent, session=self.session, monty_decode=monty_decode, use_document_model=self.use_document_model, headers=self.headers, mute_progress_bars=self.mute_progress_bars, ) # type: BaseRester setattr( _self, _attr, rester, ) return rester else: raise AttributeError( f"{_self.__class__.__name__!r} object has no attribute {_attr!r}" ) def __materials_getattr__(_self, attr): _rester_map = _sub_rester_suffix_map["materials"] rester = __core_custom_getattr(_self, attr, _rester_map) return rester def __molecules_getattr__(_self, attr): _rester_map = _sub_rester_suffix_map["molecules"] rester = __core_custom_getattr(_self, attr, _rester_map) return rester MaterialsRester.__getattr__ = __materials_getattr__ # type: ignore MoleculeRester.__getattr__ = __molecules_getattr__ # type: ignore for attr, rester in core_resters.items(): setattr( self, attr, rester, ) @property def contribs(self): if self._contribs is None: try: from mpcontribs.client import Client self._contribs = Client( self.api_key, # type: ignore headers=self.headers, session=self.session, ) except ImportError: self._contribs = None warnings.warn( "mpcontribs-client not installed. " "Install the package to query MPContribs data, or construct pourbaix diagrams: " "'pip install mpcontribs-client'" ) except Exception as error: self._contribs = None warnings.warn(f"Problem loading MPContribs client: {error}") return self._contribs def __enter__(self): """Support for "with" context.""" return self def __exit__(self, exc_type, exc_val, exc_tb): """Support for "with" context.""" self.session.close() def __getattr__(self, attr): if attr in self._deprecated_attributes: warnings.warn( f"Accessing {attr} data through MPRester.{attr} is deprecated. " f"Please use MPRester.materials.{attr} instead.", DeprecationWarning, stacklevel=2, ) return getattr(super().__getattribute__("materials"), attr) else: raise AttributeError( f"{self.__class__.__name__!r} object has no attribute {attr!r}" ) def __dir__(self): return dir(MPRester) + self._deprecated_attributes + ["materials", "molecules"] def get_task_ids_associated_with_material_id( self, material_id: str, calc_types: list[CalcType] | None = None ) -> list[str]: """Get Task ID values associated with a specific Material ID. Args: material_id (str): Material ID calc_types ([CalcType]): If specified, will restrict to a certain task type, e.g. [CalcType.GGA_STATIC] Returns: ([str]): List of Task ID values. """ tasks = self.materials.search(material_ids=material_id, fields=["calc_types"]) if not tasks: return [] calculations = ( tasks[0].calc_types # type: ignore if self.use_document_model else tasks[0]["calc_types"] # type: ignore ) if calc_types: return [ task for task, calc_type in calculations.items() if calc_type in calc_types ] else: return list(calculations.keys()) def get_structure_by_material_id( self, material_id: str, final: bool = True, conventional_unit_cell: bool = False ) -> Structure | list[Structure]: """Get a Structure corresponding to a material_id. Args: material_id (str): Materials Project material_id (a string, e.g., mp-1234). final (bool): Whether to get the final structure, or the list of initial (pre-relaxation) structures. Defaults to True. conventional_unit_cell (bool): Whether to get the standard conventional unit cell for the final or list of initial structures. Returns: Structure object or list of Structure objects. """ structure_data = self.materials.get_structure_by_material_id( material_id=material_id, final=final ) if conventional_unit_cell and structure_data: if final: structure_data = SpacegroupAnalyzer( structure_data ).get_conventional_standard_structure() else: structure_data = [ SpacegroupAnalyzer(structure).get_conventional_standard_structure() for structure in structure_data ] return structure_data def get_database_version(self): """The Materials Project database is periodically updated and has a database version associated with it. When the database is updated, consolidated data (information about "a material") may and does change, while calculation data about a specific calculation task remains unchanged and available for querying via its task_id. The database version is set as a date in the format YYYY_MM_DD, where "_DD" may be optional. An additional numerical suffix might be added if multiple releases happen on the same day. Returns: database version as a string """ return get(url=self.endpoint + "heartbeat").json()["db_version"] @staticmethod @cache def get_emmet_version(endpoint): """Get the latest version emmet-core and emmet-api used in the current API service. Returns: version as a string """ response = get(url=endpoint + "heartbeat").json() error = response.get("error", None) if error: raise MPRestError(error) return version.parse(response["version"]) def get_material_id_from_task_id(self, task_id: str) -> str | None: """Returns the current material_id from a given task_id. The material_id should rarely change, and is usually chosen from among the smallest numerical id from the group of task_ids for that material. However, in some circumstances it might change, and this method is useful for finding the new material_id. Args: task_id (str): A task id. Returns: material_id (MPID) """ docs = self.materials.search(task_ids=[task_id], fields=["material_id"]) if len(docs) == 1: # pragma: no cover return str(docs[0].material_id) # type: ignore elif len(docs) > 1: # pragma: no cover raise ValueError( f"Multiple documents return for {task_id}, this should not happen, please report it!" ) else: # pragma: no cover warnings.warn( f"No material found containing task {task_id}. Please report it if you suspect a task has gone missing." ) return None def get_material_id_references(self, material_id: str) -> list[str]: """Returns all references for a material id. Args: material_id (str): A material id. Returns: List of BibTeX references ([str]) """ docs = self.materials.provenance.search(material_ids=material_id) if not docs: return [] return docs[0].references if self.use_document_model else docs[0]["references"] # type: ignore def get_material_ids( self, chemsys_formula: str | list[str], ) -> list[MPID]: """Get all materials ids for a formula or chemsys. Args: chemsys_formula (str, List[str]): A chemical system, list of chemical systems (e.g., Li-Fe-O, Si-*, [Si-O, Li-Fe-P]), or single formula (e.g., Fe2O3, Si*). Returns: List of all materials ids ([MPID]) """ if isinstance(chemsys_formula, list) or ( isinstance(chemsys_formula, str) and "-" in chemsys_formula ): input_params = {"chemsys": chemsys_formula} else: input_params = {"formula": chemsys_formula} return sorted( doc.material_id if self.use_document_model else doc["material_id"] # type: ignore for doc in self.materials.search( **input_params, # type: ignore all_fields=False, fields=["material_id"], ) ) def get_structures( self, chemsys_formula: str | list[str], final=True ) -> list[Structure]: """Get a list of Structures corresponding to a chemical system or formula. Args: chemsys_formula (str, List[str]): A chemical system, list of chemical systems (e.g., Li-Fe-O, Si-*, [Si-O, Li-Fe-P]), or single formula (e.g., Fe2O3, Si*). final (bool): Whether to get the final structure, or the list of initial (pre-relaxation) structures. Defaults to True. Returns: List of Structure objects. ([Structure]) """ if isinstance(chemsys_formula, list) or ( isinstance(chemsys_formula, str) and "-" in chemsys_formula ): input_params = {"chemsys": chemsys_formula} else: input_params = {"formula": chemsys_formula} if final: docs = self.materials.search( **input_params, # type: ignore all_fields=False, fields=["structure"], ) if not self.use_document_model: return [doc["structure"] for doc in docs] # type: ignore return [doc.structure for doc in docs] # type: ignore else: structures = [] for doc in self.materials.search( **input_params, # type: ignore all_fields=False, fields=["initial_structures"], ): initial_structures = ( doc.initial_structures # type: ignore if self.use_document_model else doc["initial_structures"] # type: ignore ) structures.extend(initial_structures) return structures def find_structure( self, filename_or_structure: str | Structure, ltol: float = _EMMET_SETTINGS.LTOL, stol: float = _EMMET_SETTINGS.STOL, angle_tol: float = _EMMET_SETTINGS.ANGLE_TOL, allow_multiple_results: bool = False, ) -> list[str] | str: """Finds matching structures from the Materials Project database. Multiple results may be returned of "similar" structures based on distance using the pymatgen StructureMatcher algorithm, however only a single result should match with the same spacegroup, calculated to the default tolerances. Args: filename_or_structure: filename or Structure object ltol: fractional length tolerance stol: site tolerance angle_tol: angle tolerance in degrees allow_multiple_results: changes return type for either a single material_id or list of material_ids Returns: A matching material_id if one is found or list of results if allow_multiple_results is True Raises: MPRestError """ return self.materials.find_structure( filename_or_structure, ltol=ltol, stol=stol, angle_tol=angle_tol, allow_multiple_results=allow_multiple_results, ) def get_entries( self, chemsys_formula_mpids: str | list[str], compatible_only: bool = True, inc_structure: bool | None = None, property_data: list[str] | None = None, conventional_unit_cell: bool = False, additional_criteria: dict | None = None, ) -> list[ComputedStructureEntry]: """Get a list of ComputedEntries or ComputedStructureEntries corresponding to a chemical system or formula. This returns entries for all thermo types represented in the database. Each type corresponds to a different mixing scheme (i.e. GGA/GGA+U, GGA/GGA+U/R2SCAN, R2SCAN). By default the thermo_type of the entry is also returned. Args: chemsys_formula_mpids (str, List[str]): A chemical system, list of chemical systems (e.g., Li-Fe-O, Si-*, [Si-O, Li-Fe-P]), formula, list of formulas (e.g., Fe2O3, Si*, [SiO2, BiFeO3]), Materials Project ID, or list of Materials Project IDs (e.g., mp-22526, [mp-22526, mp-149]). compatible_only (bool): Whether to return only "compatible" entries. Compatible entries are entries that have been processed using the MaterialsProject2020Compatibility class, which performs adjustments to allow mixing of GGA and GGA+U calculations for more accurate phase diagrams and reaction energies. This data is obtained from the core "thermo" API endpoint. inc_structure (str): *This is a deprecated argument*. Previously, if None, entries returned were ComputedEntries. If inc_structure="initial", ComputedStructureEntries with initial structures were returned. Otherwise, ComputedStructureEntries with final structures were returned. This is no longer needed as all entries will contain the final structure data by default. property_data (list): Specify additional properties to include in entry.data. If None, only default data is included. Should be a subset of input parameters in the 'MPRester.thermo.available_fields' list. conventional_unit_cell (bool): Whether to get the standard conventional unit cell additional_criteria (dict): Any additional criteria to pass. The keys and values should correspond to proper function inputs to `MPRester.thermo.search`. For instance, if you are only interested in entries on the convex hull, you could pass {"energy_above_hull": (0.0, 0.0)} or {"is_stable": True}. Returns: List ComputedStructureEntry objects. """ if inc_structure is not None: warnings.warn( "The 'inc_structure' argument is deprecated as structure " "data is now always included in all returned entry objects." ) if isinstance(chemsys_formula_mpids, str): chemsys_formula_mpids = [chemsys_formula_mpids] try: input_params = {"material_ids": validate_ids(chemsys_formula_mpids)} except ValueError: if any("-" in entry for entry in chemsys_formula_mpids): input_params = {"chemsys": chemsys_formula_mpids} else: input_params = {"formula": chemsys_formula_mpids} if additional_criteria: input_params = {**input_params, **additional_criteria} entries = [] fields = ( ["entries", "thermo_type"] if not property_data else ["entries", "thermo_type"] + property_data ) docs = self.materials.thermo.search( **input_params, # type: ignore all_fields=False, fields=fields, ) for doc in docs: entry_list = ( doc.entries.values() # type: ignore if self.use_document_model else doc["entries"].values() # type: ignore ) for entry in entry_list: entry_dict: dict = entry.as_dict() if self.monty_decode else entry # type: ignore if not compatible_only: entry_dict["correction"] = 0.0 entry_dict["energy_adjustments"] = [] if property_data: for property in property_data: entry_dict["data"][property] = ( doc.model_dump()[property] # type: ignore if self.use_document_model else doc[property] # type: ignore ) if conventional_unit_cell: entry_struct = Structure.from_dict(entry_dict["structure"]) s = SpacegroupAnalyzer( entry_struct ).get_conventional_standard_structure() site_ratio = len(s) / len(entry_struct) new_energy = entry_dict["energy"] * site_ratio entry_dict["energy"] = new_energy entry_dict["structure"] = s.as_dict() entry_dict["correction"] = 0.0 for element in entry_dict["composition"]: entry_dict["composition"][element] *= site_ratio for correction in entry_dict["energy_adjustments"]: if "n_atoms" in correction: correction["n_atoms"] *= site_ratio entry = ( ComputedStructureEntry.from_dict(entry_dict) if self.monty_decode else entry_dict ) entries.append(entry) return entries def get_pourbaix_entries( self, chemsys: str | list, solid_compat="MaterialsProject2020Compatibility", use_gibbs: Literal[300] | None = None, ): """A helper function to get all entries necessary to generate a Pourbaix diagram from the rest interface. Args: chemsys (str or [str]): Chemical system string comprising element symbols separated by dashes, e.g., "Li-Fe-O" or List of element symbols, e.g., ["Li", "Fe", "O"]. solid_compat: Compatibility scheme used to pre-process solid DFT energies prior to applying aqueous energy adjustments. May be passed as a class (e.g. MaterialsProject2020Compatibility) or an instance (e.g., MaterialsProject2020Compatibility()). If None, solid DFT energies are used as-is. Default: MaterialsProject2020Compatibility use_gibbs: Set to 300 (for 300 Kelvin) to use a machine learning model to estimate solid free energy from DFT energy (see GibbsComputedStructureEntry). This can slightly improve the accuracy of the Pourbaix diagram in some cases. Default: None. Note that temperatures other than 300K are not permitted here, because MaterialsProjectAqueousCompatibility corrections, used in Pourbaix diagram construction, are calculated based on 300 K data. """ # imports are not top-level due to expense from pymatgen.analysis.pourbaix_diagram import PourbaixEntry from pymatgen.entries.compatibility import ( Compatibility, MaterialsProject2020Compatibility, MaterialsProjectAqueousCompatibility, MaterialsProjectCompatibility, ) from pymatgen.entries.computed_entries import ComputedEntry if solid_compat == "MaterialsProjectCompatibility": solid_compat = MaterialsProjectCompatibility() elif solid_compat == "MaterialsProject2020Compatibility": solid_compat = MaterialsProject2020Compatibility() elif isinstance(solid_compat, Compatibility): pass else: raise ValueError( "Solid compatibility can only be 'MaterialsProjectCompatibility', " "'MaterialsProject2020Compatibility', or an instance of a Compatibility class" ) pbx_entries = [] if isinstance(chemsys, str): chemsys = chemsys.split("-") # capitalize and sort the elements chemsys = sorted(e.capitalize() for e in chemsys) # Get ion entries first, because certain ions have reference # solids that aren't necessarily in the chemsys (Na2SO4) # download the ion reference data from MPContribs ion_data = self.get_ion_reference_data_for_chemsys(chemsys) # build the PhaseDiagram for get_ion_entries ion_ref_comps = [ Ion.from_formula(d["data"]["RefSolid"]).composition for d in ion_data ] ion_ref_elts = set( itertools.chain.from_iterable(i.elements for i in ion_ref_comps) ) # TODO - would be great if the commented line below would work # However for some reason you cannot process GibbsComputedStructureEntry with # MaterialsProjectAqueousCompatibility ion_ref_entries = self.get_entries_in_chemsys( list([str(e) for e in ion_ref_elts] + ["O", "H"]), # use_gibbs=use_gibbs ) # suppress the warning about supplying the required energies; they will be calculated from the # entries we get from MPRester with warnings.catch_warnings(): warnings.filterwarnings( "ignore", message="You did not provide the required O2 and H2O energies.", ) compat = MaterialsProjectAqueousCompatibility(solid_compat=solid_compat) # suppress the warning about missing oxidation states with warnings.catch_warnings(): warnings.filterwarnings( "ignore", message="Failed to guess oxidation states.*" ) ion_ref_entries = compat.process_entries(ion_ref_entries) # type: ignore # TODO - if the commented line above would work, this conditional block # could be removed if use_gibbs: # replace the entries with GibbsComputedStructureEntry from pymatgen.entries.computed_entries import GibbsComputedStructureEntry ion_ref_entries = GibbsComputedStructureEntry.from_entries( ion_ref_entries, temp=use_gibbs ) ion_ref_pd = PhaseDiagram(ion_ref_entries) # type: ignore ion_entries = self.get_ion_entries(ion_ref_pd, ion_ref_data=ion_data) pbx_entries = [PourbaixEntry(e, f"ion-{n}") for n, e in enumerate(ion_entries)] # Construct the solid pourbaix entries from filtered ion_ref entries extra_elts = ( set(ion_ref_elts) - {Element(s) for s in chemsys} - {Element("H"), Element("O")} ) for entry in ion_ref_entries: entry_elts = set(entry.composition.elements) # Ensure no OH chemsys or extraneous elements from ion references if not ( entry_elts <= {Element("H"), Element("O")} or extra_elts.intersection(entry_elts) ): # Create new computed entry form_e = ion_ref_pd.get_form_energy(entry) # type: ignore new_entry = ComputedEntry( entry.composition, form_e, entry_id=entry.entry_id ) pbx_entry = PourbaixEntry(new_entry) pbx_entries.append(pbx_entry) return pbx_entries @lru_cache def get_ion_reference_data(self) -> list[dict]: """Download aqueous ion reference data used in the construction of Pourbaix diagrams. Use this method to examine the ion reference data and to add additional ions if desired. The data returned from this method can be passed to get_ion_entries(). Data are retrieved from the Aqueous Ion Reference Data project hosted on MPContribs. Refer to that project and its associated documentation for more details about the format and meaning of the data. Returns: [dict]: Among other data, each record contains 1) the experimental ion free energy, 2) the formula of the reference solid for the ion, and 3) the experimental free energy of the reference solid. All energies are given in kJ/mol. An example is given below. {'identifier': 'Li[+]', 'formula': 'Li[+]', 'data': {'charge': {'display': '1.0', 'value': 1.0, 'unit': ''}, 'ΔGᶠ': {'display': '-293.71 kJ/mol', 'value': -293.71, 'unit': 'kJ/mol'}, 'MajElements': 'Li', 'RefSolid': 'Li2O', 'ΔGᶠRefSolid': {'display': '-561.2 kJ/mol', 'value': -561.2, 'unit': 'kJ/mol'}, 'reference': 'H. E. Barner and R. V. Scheuerman, Handbook of thermochemical data for compounds and aqueous species, Wiley, New York (1978)'}} """ return self.contribs.query_contributions( # type: ignore query={"project": "ion_ref_data"}, fields=["identifier", "formula", "data"], paginate=True, ).get( "data" ) # type: ignore def get_ion_reference_data_for_chemsys(self, chemsys: str | list) -> list[dict]: """Download aqueous ion reference data used in the construction of Pourbaix diagrams. Use this method to examine the ion reference data and to add additional ions if desired. The data returned from this method can be passed to get_ion_entries(). Data are retrieved from the Aqueous Ion Reference Data project hosted on MPContribs. Refer to that project and its associated documentation for more details about the format and meaning of the data. Args: chemsys (str or [str]): Chemical system string comprising element symbols separated by dashes, e.g., "Li-Fe-O" or List of element symbols, e.g., ["Li", "Fe", "O"]. Returns: [dict]: Among other data, each record contains 1) the experimental ion free energy, 2) the formula of the reference solid for the ion, and 3) the experimental free energy of the reference solid. All energies are given in kJ/mol. An example is given below. {'identifier': 'Li[+]', 'formula': 'Li[+]', 'data': {'charge': {'display': '1.0', 'value': 1.0, 'unit': ''}, 'ΔGᶠ': {'display': '-293.71 kJ/mol', 'value': -293.71, 'unit': 'kJ/mol'}, 'MajElements': 'Li', 'RefSolid': 'Li2O', 'ΔGᶠRefSolid': {'display': '-561.2 kJ/mol', 'value': -561.2, 'unit': 'kJ/mol'}, 'reference': 'H. E. Barner and R. V. Scheuerman, Handbook of thermochemical data for compounds and aqueous species, Wiley, New York (1978)'}} """ ion_data = self.get_ion_reference_data() if isinstance(chemsys, str): chemsys = chemsys.split("-") return [d for d in ion_data if d["data"]["MajElements"] in chemsys] def get_ion_entries( self, pd: PhaseDiagram, ion_ref_data: list[dict] | None = None ) -> list[IonEntry]: """Retrieve IonEntry objects that can be used in the construction of Pourbaix Diagrams. The energies of the IonEntry are calculaterd from the solid energies in the provided Phase Diagram to be consistent with experimental free energies. NOTE! This is an advanced method that assumes detailed understanding of how to construct computational Pourbaix Diagrams. If you just want to build a Pourbaix Diagram using default settings, use get_pourbaix_entries. Args: pd: Solid phase diagram on which to construct IonEntry. Note that this Phase Diagram MUST include O and H in its chemical system. For example, to retrieve IonEntry for Ti, the phase diagram passed here should contain materials in the H-O-Ti chemical system. It is also assumed that solid energies have already been corrected with MaterialsProjectAqueousCompatibility, which is necessary for proper construction of Pourbaix diagrams. ion_ref_data: Aqueous ion reference data. If None (default), the data are downloaded from the Aqueous Ion Reference Data project hosted on MPContribs. To add a custom ionic species, first download data using get_ion_reference_data, then add or customize it with your additional data, and pass the customized list here. Returns: [IonEntry]: IonEntry are similar to PDEntry objects. Their energies are free energies in eV. """ # determine the chemsys from the phase diagram chemsys = "-".join([el.symbol for el in pd.elements]) # raise ValueError if O and H not in chemsys if "O" not in chemsys or "H" not in chemsys: raise ValueError( "The phase diagram chemical system must contain O and H! Your" f" diagram chemical system is {chemsys}." ) if not ion_ref_data: ion_data = self.get_ion_reference_data_for_chemsys(chemsys) else: ion_data = ion_ref_data # position the ion energies relative to most stable reference state ion_entries = [] for _, i_d in enumerate(ion_data): ion = Ion.from_formula(i_d["formula"]) refs = [ e for e in pd.all_entries if e.composition.reduced_formula == i_d["data"]["RefSolid"] ] if not refs: raise ValueError("Reference solid not contained in entry list") stable_ref = sorted(refs, key=lambda x: x.energy_per_atom)[0] rf = stable_ref.composition.get_reduced_composition_and_factor()[1] # TODO - need a more robust way to convert units # use pint here? if i_d["data"]["ΔGᶠRefSolid"]["unit"] == "kJ/mol": # convert to eV/formula unit ref_solid_energy = i_d["data"]["ΔGᶠRefSolid"]["value"] / 96.485 elif i_d["data"]["ΔGᶠRefSolid"]["unit"] == "MJ/mol": # convert to eV/formula unit ref_solid_energy = i_d["data"]["ΔGᶠRefSolid"]["value"] / 96485 else: raise ValueError( f"Ion reference solid energy has incorrect unit {i_d['data']['ΔGᶠRefSolid']['unit']}" ) solid_diff = pd.get_form_energy(stable_ref) - ref_solid_energy * rf elt = i_d["data"]["MajElements"] correction_factor = ion.composition[elt] / stable_ref.composition[elt] # TODO - need a more robust way to convert units # use pint here? if i_d["data"]["ΔGᶠ"]["unit"] == "kJ/mol": # convert to eV/formula unit ion_free_energy = i_d["data"]["ΔGᶠ"]["value"] / 96.485 elif i_d["data"]["ΔGᶠ"]["unit"] == "MJ/mol": # convert to eV/formula unit ion_free_energy = i_d["data"]["ΔGᶠ"]["value"] / 96485 else: raise ValueError( f"Ion free energy has incorrect unit {i_d['data']['ΔGᶠ']['unit']}" ) energy = ion_free_energy + solid_diff * correction_factor ion_entries.append(IonEntry(ion, energy)) return ion_entries def get_entry_by_material_id( self, material_id: str, compatible_only: bool = True, inc_structure: bool | None = None, property_data: list[str] | None = None, conventional_unit_cell: bool = False, ): """Get all ComputedEntry objects corresponding to a material_id. Args: material_id (str): Materials Project material_id (a string, e.g., mp-1234). compatible_only (bool): Whether to return only "compatible" entries. Compatible entries are entries that have been processed using the MaterialsProject2020Compatibility class, which performs adjustments to allow mixing of GGA and GGA+U calculations for more accurate phase diagrams and reaction energies. This data is obtained from the core "thermo" API endpoint. inc_structure (str): *This is a deprecated argument*. Previously, if None, entries returned were ComputedEntries. If inc_structure="initial", ComputedStructureEntries with initial structures were returned. Otherwise, ComputedStructureEntries with final structures were returned. This is no longer needed as all entries will contain structure data by default. property_data (list): Specify additional properties to include in entry.data. If None, only default data is included. Should be a subset of input parameters in the 'MPRester.thermo.available_fields' list. conventional_unit_cell (bool): Whether to get the standard conventional unit cell Returns: List of ComputedEntry or ComputedStructureEntry object. """ return self.get_entries( material_id, compatible_only=compatible_only, inc_structure=inc_structure, property_data=property_data, conventional_unit_cell=conventional_unit_cell, ) def get_entries_in_chemsys( self, elements: str | list[str], use_gibbs: int | None = None, compatible_only: bool = True, inc_structure: bool | None = None, property_data: list[str] | None = None, conventional_unit_cell: bool = False, additional_criteria=None, ): """Helper method to get a list of ComputedEntries in a chemical system. For example, elements = ["Li", "Fe", "O"] will return a list of all entries in the parent Li-Fe-O chemical system, as well as all subsystems (i.e., all LixOy, FexOy, LixFey, LixFeyOz, Li, Fe and O phases). Extremely useful for creating phase diagrams of entire chemical systems. Note that by default this returns mixed GGA/GGA+U entries. For others, pass GGA/GGA+U/R2SCAN, or R2SCAN as thermo_types in additional_criteria. Args: elements (str or [str]): Parent chemical system string comprising element symbols separated by dashes, e.g., "Li-Fe-O" or List of element symbols, e.g., ["Li", "Fe", "O"]. use_gibbs: If None (default), DFT energy is returned. If a number, return the free energy of formation estimated using a machine learning model (see GibbsComputedStructureEntry). The number is the temperature in Kelvin at which to estimate the free energy. Must be between 300 K and 2000 K. compatible_only (bool): Whether to return only "compatible" entries. Compatible entries are entries that have been processed using the MaterialsProject2020Compatibility class, which performs adjustments to allow mixing of GGA and GGA+U calculations for more accurate phase diagrams and reaction energies. This data is obtained from the core "thermo" API endpoint. inc_structure (str): *This is a deprecated argument*. Previously, if None, entries returned were ComputedEntries. If inc_structure="initial", ComputedStructureEntries with initial structures were returned. Otherwise, ComputedStructureEntries with final structures were returned. This is no longer needed as all entries will contain structure data by default. property_data (list): Specify additional properties to include in entry.data. If None, only default data is included. Should be a subset of input parameters in the 'MPRester.thermo.available_fields' list. conventional_unit_cell (bool): Whether to get the standard conventional unit cell additional_criteria (dict): Any additional criteria to pass. The keys and values should correspond to proper function inputs to `MPRester.thermo.search`. For instance, if you are only interested in entries on the convex hull, you could pass {"energy_above_hull": (0.0, 0.0)} or {"is_stable": True}, or if you are only interested in entry data Returns: List of ComputedStructureEntries. """ if isinstance(elements, str): elements = elements.split("-") elements_set = set(elements) # remove duplicate elements all_chemsyses = [] for i in range(len(elements_set)): for els in itertools.combinations(elements_set, i + 1): all_chemsyses.append("-".join(sorted(els))) entries = [] entries.extend( self.get_entries( all_chemsyses, compatible_only=compatible_only, inc_structure=inc_structure, property_data=property_data, conventional_unit_cell=conventional_unit_cell, additional_criteria=additional_criteria or {"thermo_types": ["GGA_GGA+U"]}, ) ) if not self.monty_decode: entries = [ComputedStructureEntry.from_dict(entry) for entry in entries] if use_gibbs: # replace the entries with GibbsComputedStructureEntry from pymatgen.entries.computed_entries import GibbsComputedStructureEntry entries = GibbsComputedStructureEntry.from_entries(entries, temp=use_gibbs) if not self.monty_decode: entries = [entry.as_dict() for entry in entries] return entries def get_bandstructure_by_material_id( self, material_id: str, path_type: BSPathType = BSPathType.setyawan_curtarolo, line_mode=True, ): """Get the band structure pymatgen object associated with a Materials Project ID. Arguments: material_id (str): Materials Project ID for a material path_type (BSPathType): k-point path selection convention line_mode (bool): Whether to return data for a line-mode calculation Returns: bandstructure (Union[BandStructure, BandStructureSymmLine]): BandStructure or BandStructureSymmLine object """ return self.materials.electronic_structure_bandstructure.get_bandstructure_from_material_id( # type: ignore material_id=material_id, path_type=path_type, line_mode=line_mode ) def get_dos_by_material_id(self, material_id: str): """Get the complete density of states pymatgen object associated with a Materials Project ID. Arguments: material_id (str): Materials Project ID for a material Returns: dos (CompleteDos): CompleteDos object """ return self.materials.electronic_structure_dos.get_dos_from_material_id( material_id=material_id ) # type: ignore def get_phonon_dos_by_material_id(self, material_id: str): """Get phonon density of states data corresponding to a material_id. Args: material_id (str): Materials Project material_id. Returns: CompletePhononDos: A phonon DOS object. """ doc = self.materials.phonon.search(material_ids=material_id, fields=["ph_dos"]) if not doc: return None return doc[0].ph_dos if self.use_document_model else doc[0]["ph_dos"] # type: ignore def get_phonon_bandstructure_by_material_id(self, material_id: str): """Get phonon dispersion data corresponding to a material_id. Args: material_id (str): Materials Project material_id. Returns: PhononBandStructureSymmLine: phonon band structure. """ doc = self.materials.phonon.search(material_ids=material_id, fields=["ph_bs"]) if not doc: return None return doc[0].ph_bs if self.use_document_model else doc[0]["ph_bs"] # type: ignore def get_wulff_shape(self, material_id: str): """Constructs a Wulff shape for a material. Args: material_id (str): Materials Project material_id, e.g. 'mp-123'. Returns: pymatgen.analysis.wulff.WulffShape """ from pymatgen.analysis.wulff import WulffShape from pymatgen.symmetry.analyzer import SpacegroupAnalyzer structure = self.get_structure_by_material_id(material_id) doc = self.materials.surface_properties.search(material_ids=material_id) if not doc: return None surfaces: list = ( doc[0].surfaces if self.use_document_model else doc[0]["surfaces"] # type: ignore ) lattice = ( SpacegroupAnalyzer(structure).get_conventional_standard_structure().lattice ) miller_energy_map = {} for surf in surfaces: miller = tuple(surf.miller_index) if surf.miller_index else () # Prefer reconstructed surfaces, which have lower surface energies. if (miller not in miller_energy_map) or surf.is_reconstructed: miller_energy_map[miller] = surf.surface_energy millers, energies = zip(*miller_energy_map.items()) return WulffShape(lattice, millers, energies) def get_charge_density_from_task_id( self, task_id: str, inc_task_doc: bool = False ) -> Chgcar | tuple[Chgcar, TaskDoc | dict] | None: """Get charge density data for a given task_id. Arguments: task_id (str): A task id inc_task_doc (bool): Whether to include the task document in the returned data. Returns: (Chgcar, (Chgcar, TaskDoc | dict), None): Pymatgen Chgcar object, or tuple with object and TaskDoc """ decoder = MontyDecoder().decode if self.monty_decode else json.loads kwargs = dict( bucket="materialsproject-parsed", key=f"chgcars/{str(task_id)}.json.gz", decoder=decoder, ) chgcar = self.materials.tasks._query_open_data(**kwargs)[0] if not chgcar: raise MPRestError(f"No charge density fetched for task_id {task_id}.") chgcar = chgcar[0]["data"] # type: ignore if inc_task_doc: task_doc = self.materials.tasks.search(task_ids=task_id)[0] return chgcar, task_doc return chgcar def get_charge_density_from_material_id( self, material_id: str, inc_task_doc: bool = False ) -> Chgcar | tuple[Chgcar, TaskDoc | dict] | None: """Get charge density data for a given Materials Project ID. Arguments: material_id (str): Material Project ID inc_task_doc (bool): Whether to include the task document in the returned data. Returns: (Chgcar, (Chgcar, TaskDoc | dict), None): Pymatgen Chgcar object, or tuple with object and TaskDoc """ # TODO: really we want a recommended task_id for charge densities here # this could potentially introduce an ambiguity task_ids = self.get_task_ids_associated_with_material_id( material_id, calc_types=[CalcType.GGA_Static, CalcType.GGA_U_Static] ) if not task_ids: return None results: list[TaskDoc] = self.materials.tasks.search( task_ids=task_ids, fields=["last_updated", "task_id"] ) # type: ignore if len(results) == 0: return None latest_doc = max( # type: ignore results, key=lambda x: ( x.last_updated # type: ignore if self.use_document_model else x["last_updated"] ), # type: ignore ) task_id = ( latest_doc.task_id if self.use_document_model else latest_doc["task_id"] ) return self.get_charge_density_from_task_id(task_id, inc_task_doc) def get_download_info(self, material_ids, calc_types=None, file_patterns=None): """Get a list of URLs to retrieve raw VASP output files from the NoMaD repository Args: material_ids (list): list of material identifiers (mp-id's) task_types (list): list of task types to include in download (see CalcType Enum class) file_patterns (list): list of wildcard file names to include for each task Returns: a tuple of 1) a dictionary mapping material_ids to task_ids and calc_types, and 2) a list of URLs to download zip archives from NoMaD repository. Each zip archive will contain a manifest.json with metadata info, e.g. the task/external_ids that belong to a directory. """ # task_id's correspond to NoMaD external_id's calc_types = ( [t.value for t in calc_types if isinstance(t, CalcType)] if calc_types else [] ) meta = {} for doc in self.materials.search( # type: ignore task_ids=material_ids, fields=["calc_types", "deprecated_tasks", "material_id"], ): doc_dict: dict = doc.model_dump() if self.use_document_model else doc # type: ignore for task_id, calc_type in doc_dict["calc_types"].items(): if calc_types and calc_type not in calc_types: continue mp_id = doc_dict["material_id"] if meta.get(mp_id) is None: meta[mp_id] = [{"task_id": task_id, "calc_type": calc_type}] else: meta[mp_id].append({"task_id": task_id, "calc_type": calc_type}) if not meta: raise ValueError(f"No tasks found for material id {material_ids}.") # return a list of URLs for NoMaD Downloads containing the list of files # for every external_id in `task_ids` # For reference, please visit https://nomad-lab.eu/prod/rae/api/ # check if these task ids exist on NOMAD prefix = "https://nomad-lab.eu/prod/rae/api/repo/?" if file_patterns is not None: for file_pattern in file_patterns: prefix += f"file_pattern={file_pattern}&" prefix += "external_id=" task_ids = [t["task_id"] for tl in meta.values() for t in tl] nomad_exist_task_ids = self._check_get_download_info_url_by_task_id( prefix=prefix, task_ids=task_ids ) if len(nomad_exist_task_ids) != len(task_ids): self._print_help_message( nomad_exist_task_ids, task_ids, file_patterns, calc_types ) # generate download links for those that exist prefix = "https://nomad-lab.eu/prod/rae/api/raw/query?" if file_patterns is not None: for file_pattern in file_patterns: prefix += f"file_pattern={file_pattern}&" prefix += "external_id=" urls = [prefix + tids for tids in nomad_exist_task_ids] return meta, urls def _check_get_download_info_url_by_task_id(self, prefix, task_ids) -> list[str]: nomad_exist_task_ids: list[str] = [] prefix = prefix.replace("/raw/query", "/repo/") for task_id in task_ids: url = prefix + task_id if self._check_nomad_exist(url): nomad_exist_task_ids.append(task_id) return nomad_exist_task_ids @staticmethod def _check_nomad_exist(url) -> bool: response = get(url=url) if response.status_code != 200: return False content = loads(response.text) if content["pagination"]["total"] == 0: return False return True @staticmethod def _print_help_message(nomad_exist_task_ids, task_ids, file_patterns, calc_types): non_exist_ids = set(task_ids) - set(nomad_exist_task_ids) warnings.warn( f"For file patterns [{file_patterns}] and calc_types [{calc_types}], \n" f"the following ids are not found on NOMAD [{list(non_exist_ids)}]. \n" f"If you need to upload them, please contact Patrick Huck at phuck@lbl.gov" ) def query(*args, **kwargs): """The MPRester().query method has been replaced with the MPRester().summary.search method. Note this method also no longer supports direct MongoDB-type queries. For more information, please see the new documentation. """ raise NotImplementedError( """ The MPRester().query method has been replaced with the MPRester().summary.search method. Note this method also no longer supports direct MongoDB-type queries. For more information, please see the new documentation. """ ) def get_cohesive_energy( self, material_ids: list[MPID | str], normalization: Literal["atom", "formula_unit"] = "atom", ) -> float | dict[str, float]: """Obtain the cohesive energy of the structure(s) corresponding to multiple MPIDs. Args: material_ids ([MPID | str]) : List of MPIDs to compute cohesive energies. normalization (str = "atom" (default) or "formula_unit") : Whether to normalize the cohesive energy by the number of atoms (default) or by the number of formula units. Note that the current default is inconsistent with the legacy API. Returns: (dict[str,float]) : The cohesive energies (in eV/atom or eV/formula unit) for each material, indexed by MPID. """ entry_preference = { k: i for i, k in enumerate(["GGA", "GGA_U", "SCAN", "R2SCAN"]) } run_type_to_dfa = {"GGA": "PBE", "GGA_U": "PBE", "R2SCAN": "r2SCAN"} energies = {mp_id: {} for mp_id in material_ids} entries = self.get_entries( material_ids, compatible_only=False, inc_structure=True, property_data=None, conventional_unit_cell=False, ) for entry in entries: # Ensure that this works with monty_decode = False and True if not self.monty_decode: entry["uncorrected_energy_per_atom"] = entry["energy"] / sum( entry["composition"].values() ) else: entry = { "data": entry.data, "uncorrected_energy_per_atom": entry.uncorrected_energy_per_atom, "composition": entry.composition, } mp_id = entry["data"]["material_id"] if (run_type := entry["data"]["run_type"]) not in energies[mp_id]: energies[mp_id][run_type] = { "total_energy_per_atom": float("inf"), "composition": None, } # Obtain lowest total energy/atom within a given run type if ( entry["uncorrected_energy_per_atom"] < energies[mp_id][run_type]["total_energy_per_atom"] ): energies[mp_id][run_type] = { "total_energy_per_atom": entry["uncorrected_energy_per_atom"], "composition": entry["composition"], } atomic_energies = self.get_atom_reference_data() e_coh_per_atom = {} for mp_id, entries in energies.items(): if not entries: e_coh_per_atom[str(mp_id)] = None continue # take entry from most reliable and available functional prefered_func = sorted(list(entries), key=lambda k: entry_preference[k])[-1] e_coh_per_atom[str(mp_id)] = self._get_cohesive_energy( entries[prefered_func]["composition"], entries[prefered_func]["total_energy_per_atom"], atomic_energies[run_type_to_dfa.get(prefered_func, prefered_func)], normalization=normalization, ) return e_coh_per_atom @lru_cache def get_atom_reference_data( self, funcs: tuple[str] = ( "PBE", "SCAN", "r2SCAN", ), ) -> dict[str, dict[str, float]]: """Retrieve energies of isolated neutral atoms from MPContribs. Args: funcs ([str] or None) : list of functionals to retrieve data for. Defaults to all available functionals ("PBE", "SCAN", "r2SCAN") when set to None. Returns: (dict[str, dict[str, float]]) : dict containing isolated atom energies, indexed first by the functionals in funcs, and second by the atom. """ _atomic_energies = self.contribs.query_contributions( query={"project": "isolated_atom_energies"}, fields=["formula", *[f"data.{dfa}.energy" for dfa in funcs]], ).get("data") return { dfa: { entry["formula"]: entry["data"][dfa]["energy"]["value"] for entry in _atomic_energies } for dfa in funcs } @staticmethod def _get_cohesive_energy( composition: Composition | dict, energy_per_atom: float, atomic_energies: dict[str, float], normalization: Literal["atom", "formula_unit"] = "atom", ) -> float: """Obtain the cohesive energy of a given composition and energy. Args: composition (Composition or dict) : the composition of the structure. energy_per_atom (float) : the energy per atom of the structure. atomic_energies (dict[str,float]) : a dict containing reference total energies of neutral atoms. normalization (str = "atom" (default) or "formula_unit") : Whether to normalize the cohesive energy by the number of atoms (default) or by the number of formula units. Returns: (float) : the cohesive energy per atom. """ comp = Composition(composition).remove_charges() atomic_energy = sum( coeff * atomic_energies[str(element)] for element, coeff in comp.items() ) natom = sum(comp.values()) if normalization == "atom": return energy_per_atom - atomic_energy / natom elif normalization == "formula_unit": num_form_unit = comp.get_reduced_composition_and_factor()[1] return (energy_per_atom * natom - atomic_energy) / num_form_unit