# coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
"""
This module provides classes to interface with the Materials Project REST
API v2 to enable the creation of data structures and pymatgen objects using
Materials Project data.
To make use of the Materials API, you need to be a registered user of the
Materials Project, and obtain an API key by going to your dashboard at
https://www.materialsproject.org/dashboard.
"""
import sys
import itertools
import json
import platform
import re
import warnings
from time import sleep
import requests
from monty.json import MontyDecoder, MontyEncoder
from enum import Enum, unique
from collections import defaultdict
from copy import deepcopy
from pymatgen import SETTINGS, __version__ as pmg_version
from pymatgen.core.composition import Composition
from pymatgen.core.periodic_table import Element
from pymatgen.core.structure import Structure
from pymatgen.core.surface import get_symmetrically_equivalent_miller_indices
from pymatgen.entries.computed_entries import ComputedEntry, \
ComputedStructureEntry
from pymatgen.entries.exp_entries import ExpEntry
from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
from pymatgen.util.sequence import get_chunks, PBar
__author__ = "Shyue Ping Ong, Shreyas Cholia"
__credits__ = "Anubhav Jain"
__copyright__ = "Copyright 2012, The Materials Project"
__version__ = "1.0"
__maintainer__ = "Shyue Ping Ong"
__email__ = "shyuep@gmail.com"
__date__ = "Feb 22, 2013"
[docs]@unique
class TaskType(Enum):
"""task types available in MP"""
GGA_OPT = "GGA Structure Optimization"
GGAU_OPT = "GGA+U Structure Optimization"
SCAN_OPT = "SCAN Structure Optimization"
GGA_LINE = "GGA NSCF Line"
GGAU_LINE = "GGA+U NSCF Line"
GGA_UNIFORM = "GGA NSCF Uniform"
GGAU_UNIFORM = "GGA+U NSCF Uniform"
GGA_STATIC = "GGA Static"
GGAU_STATIC = "GGA+U Static"
GGA_STATIC_DIEL = "GGA Static Dielectric"
GGAU_STATIC_DIEL = "GGA+U Static Dielectric"
GGA_DEF = "GGA Deformation"
GGAU_DEF = "GGA+U Deformation"
LDA_STATIC_DIEL = "LDA Static Dielectric"
[docs]class MPRester:
"""
A class to conveniently interface with the Materials Project REST
interface. The recommended way to use MPRester is with the "with" context
manager to ensure that sessions are properly closed after usage::
with MPRester("API_KEY") as m:
do_something
MPRester uses the "requests" package, which provides for HTTP connection
pooling. All connections are made via https for security.
For more advanced uses of the Materials API, please consult the API
documentation at https://github.com/materialsproject/mapidoc.
"""
supported_properties = ("energy", "energy_per_atom", "volume",
"formation_energy_per_atom", "nsites",
"unit_cell_formula", "pretty_formula",
"is_hubbard", "elements", "nelements",
"e_above_hull", "hubbards", "is_compatible",
"spacegroup", "task_ids", "band_gap", "density",
"icsd_id", "icsd_ids", "cif", "total_magnetization",
"material_id", "oxide_type", "tags", "elasticity")
supported_task_properties = ("energy", "energy_per_atom", "volume",
"formation_energy_per_atom", "nsites",
"unit_cell_formula", "pretty_formula",
"is_hubbard",
"elements", "nelements", "e_above_hull",
"hubbards",
"is_compatible", "spacegroup",
"band_gap", "density", "icsd_id", "cif")
def __init__(self, api_key=None, endpoint=None, include_user_agent=True):
"""
Args:
api_key (str): A String API key for accessing the MaterialsProject
REST interface. Please obtain your API key at
https://www.materialsproject.org/dashboard. If this is None,
the code will check if there is a "PMG_MAPI_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://materialsproject.org/rest/v2", but
can be changed to other urls implementing a similar interface.
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.
"""
if api_key is not None:
self.api_key = api_key
else:
self.api_key = SETTINGS.get("PMG_MAPI_KEY", "")
if endpoint is not None:
self.preamble = endpoint
else:
self.preamble = SETTINGS.get("PMG_MAPI_ENDPOINT",
"https://materialsproject.org/rest/v2")
if self.preamble != "https://materialsproject.org/rest/v2":
warnings.warn("Non-default endpoint used: {}".format(self.preamble))
self.session = requests.Session()
self.session.headers = {"x-api-key": self.api_key}
if include_user_agent:
pymatgen_info = "pymatgen/" + pmg_version
python_info = "Python/{}.{}.{}".format(
sys.version_info.major, sys.version_info.minor, sys.version_info.micro)
platform_info = "{}/{}".format(platform.system(), platform.release())
self.session.headers["user-agent"] = "{} ({} {})".format(
pymatgen_info, python_info, platform_info)
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 _make_request(self, sub_url, payload=None, method="GET",
mp_decode=True):
response = None
url = self.preamble + sub_url
try:
if method == "POST":
response = self.session.post(url, data=payload, verify=True)
else:
response = self.session.get(url, params=payload, verify=True)
if response.status_code in [200, 400]:
if mp_decode:
data = json.loads(response.text, cls=MontyDecoder)
else:
data = json.loads(response.text)
if data["valid_response"]:
if data.get("warning"):
warnings.warn(data["warning"])
return data["response"]
else:
raise MPRestError(data["error"])
raise MPRestError("REST query returned with error status code {}"
.format(response.status_code))
except Exception as ex:
msg = "{}. Content: {}".format(str(ex), response.content) \
if hasattr(response, "content") else str(ex)
raise MPRestError(msg)
[docs] def get_materials_id_from_task_id(self, task_id):
"""
Returns a new MP materials id from a task id (which can be
equivalent to an old materials id)
Args:
task_id (str): A task id.
Returns:
materials_id (str)
"""
return self._make_request("/materials/mid_from_tid/%s" % task_id)
[docs] def get_materials_id_references(self, material_id):
"""
Returns all references for a materials id.
Args:
material_id (str): A material id.
Returns:
BibTeX (str)
"""
return self._make_request("/materials/%s/refs" % material_id)
[docs] def get_data(self, chemsys_formula_id, data_type="vasp", prop=""):
"""
Flexible method to get any data using the Materials Project REST
interface. Generally used by other methods for more specific queries.
Format of REST return is *always* a list of dict (regardless of the
number of pieces of data returned. The general format is as follows:
[{"material_id": material_id, "property_name" : value}, ...]
This is generally a call to
https://www.materialsproject.org/rest/v2/materials/vasp/<prop>.
See https://github.com/materialsproject/mapidoc for details.
Args:
chemsys_formula_id (str): A chemical system (e.g., Li-Fe-O),
or formula (e.g., Fe2O3) or materials_id (e.g., mp-1234).
data_type (str): Type of data to return. Currently can either be
"vasp" or "exp".
prop (str): Property to be obtained. Should be one of the
MPRester.supported_task_properties. Leave as empty string for a
general list of useful properties.
"""
sub_url = "/materials/%s/%s" % (chemsys_formula_id, data_type)
if prop:
sub_url += "/" + prop
return self._make_request(sub_url)
[docs] def get_materials_ids(self, chemsys_formula):
"""
Get all materials ids for a formula or chemsys.
Args:
chemsys_formula (str): A chemical system (e.g., Li-Fe-O),
or formula (e.g., Fe2O3).
Returns:
([str]) List of all materials ids.
"""
return self._make_request("/materials/%s/mids" % chemsys_formula,
mp_decode=False)
[docs] def get_doc(self, materials_id):
"""
Get the entire data document for one materials id. Use this judiciously.
REST Endpoint: https://www.materialsproject.org/materials/<mp-id>/doc.
Args:
materials_id (str): E.g., mp-1143 for Al2O3
Returns:
Dict of json document of all data that is displayed on a materials
details page.
"""
return self._make_request("/materials/%s/doc" % materials_id,
mp_decode=False)
[docs] def get_xas_data(self, material_id, absorbing_element):
"""
Get X-ray absorption spectroscopy data for absorbing element in the
structure corresponding to a material_id. Only X-ray Absorption Near Edge
Structure (XANES) for K-edge is supported.
REST Endpoint:
https://www.materialsproject.org/materials/<mp-id>/xas/<absorbing_element>.
Args:
material_id (str): E.g., mp-1143 for Al2O3
absorbing_element (str): The absorbing element in the corresponding
structure. E.g., Al in Al2O3
"""
element_list = self.get_data(material_id,
prop="elements")[0]["elements"]
if absorbing_element not in element_list:
raise ValueError(
"{} element not contained in corresponding structure with "
"mp_id: {}".format(absorbing_element, material_id))
data = self._make_request(
"/materials/{}/xas/{}".format(material_id, absorbing_element),
mp_decode=False)
return data[0]
[docs] def get_task_data(self, chemsys_formula_id, prop=""):
"""
Flexible method to get any data using the Materials Project REST
interface. Generally used by other methods for more specific queries.
Unlike the :func:`get_data`_, this method queries the task collection
for specific run information.
Format of REST return is *always* a list of dict (regardless of the
number of pieces of data returned. The general format is as follows:
[{"material_id": material_id, "property_name" : value}, ...]
Args:
chemsys_formula_id (str): A chemical system (e.g., Li-Fe-O),
or formula (e.g., Fe2O3) or materials_id (e.g., mp-1234).
prop (str): Property to be obtained. Should be one of the
MPRester.supported_properties. Leave as empty string for a
general list of useful properties.
"""
sub_url = "/tasks/%s" % chemsys_formula_id
if prop:
sub_url += "/" + prop
return self._make_request(sub_url)
[docs] def get_structures(self, chemsys_formula_id, final=True):
"""
Get a list of Structures corresponding to a chemical system, formula,
or materials_id.
Args:
chemsys_formula_id (str): A chemical system (e.g., Li-Fe-O),
or formula (e.g., Fe2O3) or materials_id (e.g., mp-1234).
final (bool): Whether to get the final structure, or the initial
(pre-relaxation) structure. Defaults to True.
Returns:
List of Structure objects.
"""
prop = "final_structure" if final else "initial_structure"
data = self.get_data(chemsys_formula_id, prop=prop)
return [d[prop] for d in data]
[docs] def find_structure(self, filename_or_structure):
"""
Finds matching structures on the Materials Project site.
Args:
filename_or_structure: filename or Structure object
Returns:
A list of matching structures.
Raises:
MPRestError
"""
try:
if isinstance(filename_or_structure, str):
s = Structure.from_file(filename_or_structure)
elif isinstance(filename_or_structure, Structure):
s = filename_or_structure
else:
raise MPRestError("Provide filename or Structure object.")
payload = {'structure': json.dumps(s.as_dict(), cls=MontyEncoder)}
response = self.session.post(
'{}/find_structure'.format(self.preamble), data=payload
)
if response.status_code in [200, 400]:
resp = json.loads(response.text, cls=MontyDecoder)
if resp['valid_response']:
return resp['response']
else:
raise MPRestError(resp["error"])
raise MPRestError("REST error with status code {} and error {}"
.format(response.status_code, response.text))
except Exception as ex:
raise MPRestError(str(ex))
[docs] def get_entries(self, chemsys_formula_id_criteria, compatible_only=True,
inc_structure=None, property_data=None,
conventional_unit_cell=False, sort_by_e_above_hull=False):
"""
Get a list of ComputedEntries or ComputedStructureEntries corresponding
to a chemical system, formula, or materials_id or full criteria.
Args:
chemsys_formula_id_criteria (str/dict): A chemical system
(e.g., Li-Fe-O), or formula (e.g., Fe2O3) or materials_id
(e.g., mp-1234) or full Mongo-style dict criteria.
compatible_only (bool): Whether to return only "compatible"
entries. Compatible entries are entries that have been
processed using the MaterialsProjectCompatibility class,
which performs adjustments to allow mixing of GGA and GGA+U
calculations for more accurate phase diagrams and reaction
energies.
inc_structure (str): If None, entries returned are
ComputedEntries. If inc_structure="initial",
ComputedStructureEntries with initial structures are returned.
Otherwise, ComputedStructureEntries with final structures
are returned.
property_data (list): Specify additional properties to include in
entry.data. If None, no data. Should be a subset of
supported_properties.
conventional_unit_cell (bool): Whether to get the standard
conventional unit cell
sort_by_e_above_hull (bool): Whether to sort the list of entries by
e_above_hull (will query e_above_hull as a property_data if True).
Returns:
List of ComputedEntry or ComputedStructureEntry objects.
"""
# TODO: This is a very hackish way of doing this. It should be fixed
# on the REST end.
params = ["run_type", "is_hubbard", "pseudo_potential", "hubbards",
"potcar_symbols", "oxide_type"]
props = ["energy", "unit_cell_formula", "task_id"] + params
if sort_by_e_above_hull:
if property_data and "e_above_hull" not in property_data:
property_data.append("e_above_hull")
elif not property_data:
property_data = ["e_above_hull"]
if property_data:
props += property_data
if inc_structure:
if inc_structure == "initial":
props.append("initial_structure")
else:
props.append("structure")
if not isinstance(chemsys_formula_id_criteria, dict):
criteria = MPRester.parse_criteria(chemsys_formula_id_criteria)
else:
criteria = chemsys_formula_id_criteria
data = self.query(criteria, props)
entries = []
for d in data:
d["potcar_symbols"] = [
"%s %s" % (d["pseudo_potential"]["functional"], l)
for l in d["pseudo_potential"]["labels"]]
data = {"oxide_type": d["oxide_type"]}
if property_data:
data.update({k: d[k] for k in property_data})
if not inc_structure:
e = ComputedEntry(d["unit_cell_formula"], d["energy"],
parameters={k: d[k] for k in params},
data=data,
entry_id=d["task_id"])
else:
prim = d["initial_structure"] if inc_structure == "initial" \
else d["structure"]
if conventional_unit_cell:
s = SpacegroupAnalyzer(prim).get_conventional_standard_structure()
energy = d["energy"] * (len(s) / len(prim))
else:
s = prim.copy()
energy = d["energy"]
e = ComputedStructureEntry(
s, energy,
parameters={k: d[k] for k in params},
data=data,
entry_id=d["task_id"])
entries.append(e)
if compatible_only:
from pymatgen.entries.compatibility import \
MaterialsProjectCompatibility
entries = MaterialsProjectCompatibility().process_entries(entries)
if sort_by_e_above_hull:
entries = sorted(entries, key=lambda entry: entry.data["e_above_hull"])
return entries
[docs] def get_pourbaix_entries(self, chemsys):
"""
A helper function to get all entries necessary to generate
a pourbaix diagram from the rest interface.
Args:
chemsys ([str]): A list of elements comprising the chemical
system, e.g. ['Li', 'Fe']
"""
from pymatgen.analysis.pourbaix_diagram import PourbaixEntry, IonEntry
from pymatgen.analysis.phase_diagram import PhaseDiagram
from pymatgen.core.ion import Ion
from pymatgen.entries.compatibility import \
MaterialsProjectAqueousCompatibility
pbx_entries = []
# Get ion entries first, because certain ions have reference
# solids that aren't necessarily in the chemsys (Na2SO4)
url = '/pourbaix_diagram/reference_data/' + '-'.join(chemsys)
ion_data = self._make_request(url)
ion_ref_comps = [Composition(d['Reference Solid']) for d in ion_data]
ion_ref_elts = list(itertools.chain.from_iterable(
i.elements for i in ion_ref_comps))
ion_ref_entries = self.get_entries_in_chemsys(
list(set([str(e) for e in ion_ref_elts] + ['O', 'H'])),
property_data=['e_above_hull'], compatible_only=False)
compat = MaterialsProjectAqueousCompatibility("Advanced")
ion_ref_entries = compat.process_entries(ion_ref_entries)
ion_ref_pd = PhaseDiagram(ion_ref_entries)
# position the ion energies relative to most stable reference state
for n, i_d in enumerate(ion_data):
ion_entry = IonEntry(Ion.from_formula(i_d['Name']), i_d['Energy'])
refs = [e for e in ion_ref_entries
if e.composition.reduced_formula == i_d['Reference Solid']]
if not refs:
raise ValueError("Reference solid not contained in entry list")
stable_ref = sorted(refs, key=lambda x: x.data['e_above_hull'])[0]
rf = stable_ref.composition.get_reduced_composition_and_factor()[1]
solid_diff = ion_ref_pd.get_form_energy(stable_ref) - i_d['Reference solid energy'] * rf
elt = i_d['Major_Elements'][0]
correction_factor = ion_entry.ion.composition[elt] / stable_ref.composition[elt]
ion_entry.energy += solid_diff * correction_factor
pbx_entries.append(PourbaixEntry(ion_entry, 'ion-{}'.format(n)))
# 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)):
# replace energy with formation energy, use dict to
# avoid messing with the ion_ref_pd and to keep all old params
form_e = ion_ref_pd.get_form_energy(entry)
new_entry = deepcopy(entry)
new_entry.uncorrected_energy = form_e
new_entry.correction = 0.0
pbx_entry = PourbaixEntry(new_entry)
pbx_entries.append(pbx_entry)
return pbx_entries
[docs] def get_structure_by_material_id(self, material_id, final=True,
conventional_unit_cell=False):
"""
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 initial
(pre-relaxation) structure. Defaults to True.
conventional_unit_cell (bool): Whether to get the standard
conventional unit cell
Returns:
Structure object.
"""
prop = "final_structure" if final else "initial_structure"
data = self.get_data(material_id, prop=prop)
if conventional_unit_cell:
data[0][prop] = SpacegroupAnalyzer(data[0][prop]). \
get_conventional_standard_structure()
return data[0][prop]
[docs] def get_entry_by_material_id(self, material_id, compatible_only=True,
inc_structure=None, property_data=None,
conventional_unit_cell=False):
"""
Get a ComputedEntry 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 MaterialsProjectCompatibility class,
which performs adjustments to allow mixing of GGA and GGA+U
calculations for more accurate phase diagrams and reaction
energies.
inc_structure (str): If None, entries returned are
ComputedEntries. If inc_structure="final",
ComputedStructureEntries with final structures are returned.
Otherwise, ComputedStructureEntries with initial structures
are returned.
property_data (list): Specify additional properties to include in
entry.data. If None, no data. Should be a subset of
supported_properties.
conventional_unit_cell (bool): Whether to get the standard
conventional unit cell
Returns:
ComputedEntry or ComputedStructureEntry object.
"""
data = self.get_entries(material_id, compatible_only=compatible_only,
inc_structure=inc_structure,
property_data=property_data,
conventional_unit_cell=conventional_unit_cell)
return data[0]
[docs] def get_dos_by_material_id(self, material_id):
"""
Get a Dos corresponding to a material_id.
REST Endpoint: https://www.materialsproject.org/rest/v2/materials/<mp-id>/vasp/dos
Args:
material_id (str): Materials Project material_id (a string,
e.g., mp-1234).
Returns:
A Dos object.
"""
data = self.get_data(material_id, prop="dos")
return data[0]["dos"]
[docs] def get_bandstructure_by_material_id(self, material_id, line_mode=True):
"""
Get a BandStructure corresponding to a material_id.
REST Endpoint: https://www.materialsproject.org/rest/v2/materials/<mp-id>/vasp/bandstructure or
https://www.materialsproject.org/rest/v2/materials/<mp-id>/vasp/bandstructure_uniform
Args:
material_id (str): Materials Project material_id.
line_mode (bool): If True, fetch a BandStructureSymmLine object
(default). If False, return the uniform band structure.
Returns:
A BandStructure object.
"""
prop = "bandstructure" if line_mode else "bandstructure_uniform"
data = self.get_data(material_id, prop=prop)
return data[0][prop]
[docs] def get_phonon_dos_by_material_id(self, material_id):
"""
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.
"""
return self._make_request("/materials/{}/phonondos".format(material_id))
[docs] def get_phonon_bandstructure_by_material_id(self, material_id):
"""
Get phonon dispersion data corresponding to a material_id.
Args:
material_id (str): Materials Project material_id.
Returns:
PhononBandStructureSymmLine: A phonon band structure.
"""
return self._make_request("/materials/{}/phononbs".format(material_id))
[docs] def get_phonon_ddb_by_material_id(self, material_id):
"""
Get ABINIT Derivative Data Base (DDB) output for phonon calculations.
Args:
material_id (str): Materials Project material_id.
Returns:
str: ABINIT DDB file as a string.
"""
return self._make_request("/materials/{}/abinit_ddb"
.format(material_id))
[docs] def get_entries_in_chemsys(self, elements, compatible_only=True,
inc_structure=None, property_data=None,
conventional_unit_cell=False):
"""
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 Li-Fe-O chemical system, i.e., all LixOy,
FexOy, LixFey, LixFeyOz, Li, Fe and O phases. Extremely useful for
creating phase diagrams of entire chemical systems.
Args:
elements (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"].
compatible_only (bool): Whether to return only "compatible"
entries. Compatible entries are entries that have been
processed using the MaterialsProjectCompatibility class,
which performs adjustments to allow mixing of GGA and GGA+U
calculations for more accurate phase diagrams and reaction
energies.
inc_structure (str): If None, entries returned are
ComputedEntries. If inc_structure="final",
ComputedStructureEntries with final structures are returned.
Otherwise, ComputedStructureEntries with initial structures
are returned.
property_data (list): Specify additional properties to include in
entry.data. If None, no data. Should be a subset of
supported_properties.
conventional_unit_cell (bool): Whether to get the standard
conventional unit cell
Returns:
List of ComputedEntries.
"""
if isinstance(elements, str):
elements = elements.split('-')
all_chemsyses = []
for i in range(len(elements)):
for els in itertools.combinations(elements, i + 1):
all_chemsyses.append('-'.join(sorted(els)))
entries = self.get_entries({"chemsys": {"$in": all_chemsyses}},
compatible_only=compatible_only,
inc_structure=inc_structure,
property_data=property_data,
conventional_unit_cell=conventional_unit_cell)
return entries
[docs] def get_exp_thermo_data(self, formula):
"""
Get a list of ThermoData objects associated with a formula using the
Materials Project REST interface.
Args:
formula (str): A formula to search for.
Returns:
List of ThermoData objects.
"""
return self.get_data(formula, data_type="exp")
[docs] def get_exp_entry(self, formula):
"""
Returns an ExpEntry object, which is the experimental equivalent of a
ComputedEntry and can be used for analyses using experimental data.
Args:
formula (str): A formula to search for.
Returns:
An ExpEntry object.
"""
return ExpEntry(Composition(formula),
self.get_exp_thermo_data(formula))
[docs] def query(self, criteria, properties, chunk_size=500, max_tries_per_chunk=5,
mp_decode=True):
r"""
Performs an advanced query using MongoDB-like syntax for directly
querying the Materials Project database. This allows one to perform
queries which are otherwise too cumbersome to perform using the standard
convenience methods.
Please consult the Materials API documentation at
https://github.com/materialsproject/mapidoc, which provides a
comprehensive explanation of the document schema used in the Materials
Project (supported criteria and properties) and guidance on how best to
query for the relevant information you need.
For queries that request data on more than CHUNK_SIZE materials at once,
this method will chunk a query by first retrieving a list of material
IDs that satisfy CRITERIA, and then merging the criteria with a
restriction to one chunk of materials at a time of size CHUNK_SIZE. You
can opt out of this behavior by setting CHUNK_SIZE=0. To guard against
intermittent server errors in the case of many chunks per query,
possibly-transient server errors will result in re-trying a give chunk
up to MAX_TRIES_PER_CHUNK times.
Args:
criteria (str/dict): Criteria of the query as a string or
mongo-style dict.
If string, it supports a powerful but simple string criteria.
E.g., "Fe2O3" means search for materials with reduced_formula
Fe2O3. Wild cards are also supported. E.g., "\\*2O" means get
all materials whose formula can be formed as \\*2O, e.g.,
Li2O, K2O, etc.
Other syntax examples:
mp-1234: Interpreted as a Materials ID.
Fe2O3 or *2O3: Interpreted as reduced formulas.
Li-Fe-O or *-Fe-O: Interpreted as chemical systems.
You can mix and match with spaces, which are interpreted as
"OR". E.g. "mp-1234 FeO" means query for all compounds with
reduced formula FeO or with materials_id mp-1234.
Using a full dict syntax, even more powerful queries can be
constructed. For example, {"elements":{"$in":["Li",
"Na", "K"], "$all": ["O"]}, "nelements":2} selects all Li, Na
and K oxides. {"band_gap": {"$gt": 1}} selects all materials
with band gaps greater than 1 eV.
properties (list): Properties to request for as a list. For
example, ["formula", "formation_energy_per_atom"] returns
the formula and formation energy per atom.
chunk_size (int): Number of materials for which to fetch data at a
time. More data-intensive properties may require smaller chunk
sizes. Use chunk_size=0 to force no chunking -- this is useful
when fetching only properties such as 'material_id'.
max_tries_per_chunk (int): How many times to re-try fetching a given
chunk when the server gives a 5xx error (e.g. a timeout error).
mp_decode (bool): Whether to do a decoding to a Pymatgen object
where possible. In some cases, it might be useful to just get
the raw python dict, i.e., set to False.
Returns:
List of results. E.g.,
[{u'formula': {u'O': 1, u'Li': 2.0}},
{u'formula': {u'Na': 2.0, u'O': 2.0}},
{u'formula': {u'K': 1, u'O': 3.0}},
...]
"""
if not isinstance(criteria, dict):
criteria = self.parse_criteria(criteria)
payload = {"criteria": json.dumps(criteria),
"properties": json.dumps(properties)}
if chunk_size == 0:
return self._make_request(
"/query", payload=payload, method="POST", mp_decode=mp_decode)
count_payload = payload.copy()
count_payload["options"] = json.dumps({"count_only": True})
num_results = self._make_request(
"/query", payload=count_payload, method="POST")
if num_results <= chunk_size:
return self._make_request(
"/query", payload=payload, method="POST", mp_decode=mp_decode)
data = []
mids = [d["material_id"] for d in
self.query(criteria, ["material_id"], chunk_size=0)]
chunks = get_chunks(mids, size=chunk_size)
progress_bar = PBar(total=len(mids))
for chunk in chunks:
chunk_criteria = criteria.copy()
chunk_criteria.update({"material_id": {"$in": chunk}})
num_tries = 0
while num_tries < max_tries_per_chunk:
try:
data.extend(self.query(chunk_criteria, properties,
chunk_size=0, mp_decode=mp_decode))
break
except MPRestError as e:
match = re.search(r"error status code (\d+)", e.message)
if match:
if not match.group(1).startswith("5"):
raise e
else: # 5xx error. Try again
num_tries += 1
print(
"Unknown server error. Trying again in five "
"seconds (will try at most {} times)...".format(
max_tries_per_chunk))
sleep(5)
progress_bar.update(len(chunk))
return data
[docs] def submit_structures(self, structures, authors, projects=None,
references='', remarks=None, data=None,
histories=None, created_at=None):
"""
Submits a list of structures to the Materials Project as SNL files.
The argument list mirrors the arguments for the StructureNL object,
except that a list of structures with the same metadata is used as an
input.
.. note::
As of now, this MP REST feature is open only to a select group of
users. Opening up submissions to all users is being planned for
the future.
Args:
structures: A list of Structure objects
authors (list): List of {"name":'', "email":''} dicts,
*list* of Strings as 'John Doe <johndoe@gmail.com>',
or a single String with commas separating authors
projects ([str]): List of Strings ['Project A', 'Project B'].
This applies to all structures.
references (str): A String in BibTeX format. Again, this applies to
all structures.
remarks ([str]): List of Strings ['Remark A', 'Remark B']
data ([dict]): A list of free form dict. Namespaced at the root
level with an underscore, e.g. {"_materialsproject":<custom
data>}. The length of data should be the same as the list of
structures if not None.
histories: List of list of dicts - [[{'name':'', 'url':'',
'description':{}}], ...] The length of histories should be the
same as the list of structures if not None.
created_at (datetime): A datetime object
Returns:
A list of inserted submission ids.
"""
from pymatgen.util.provenance import StructureNL
snl_list = StructureNL.from_structures(structures, authors, projects,
references, remarks, data,
histories, created_at)
self.submit_snl(snl_list)
[docs] def submit_snl(self, snl):
"""
Submits a list of StructureNL to the Materials Project site.
.. note::
As of now, this MP REST feature is open only to a select group of
users. Opening up submissions to all users is being planned for
the future.
Args:
snl (StructureNL/[StructureNL]): A single StructureNL, or a list
of StructureNL objects
Returns:
A list of inserted submission ids.
Raises:
MPRestError
"""
try:
snl = snl if isinstance(snl, list) else [snl]
jsondata = [s.as_dict() for s in snl]
payload = {"snl": json.dumps(jsondata, cls=MontyEncoder)}
response = self.session.post("{}/snl/submit".format(self.preamble),
data=payload)
if response.status_code in [200, 400]:
resp = json.loads(response.text, cls=MontyDecoder)
if resp["valid_response"]:
if resp.get("warning"):
warnings.warn(resp["warning"])
return resp['inserted_ids']
else:
raise MPRestError(resp["error"])
raise MPRestError("REST error with status code {} and error {}"
.format(response.status_code, response.text))
except Exception as ex:
raise MPRestError(str(ex))
[docs] def delete_snl(self, snl_ids):
"""
Delete earlier submitted SNLs.
.. note::
As of now, this MP REST feature is open only to a select group of
users. Opening up submissions to all users is being planned for
the future.
Args:
snl_ids: List of SNL ids.
Raises:
MPRestError
"""
try:
payload = {"ids": json.dumps(snl_ids)}
response = self.session.post(
"{}/snl/delete".format(self.preamble), data=payload)
if response.status_code in [200, 400]:
resp = json.loads(response.text, cls=MontyDecoder)
if resp["valid_response"]:
if resp.get("warning"):
warnings.warn(resp["warning"])
return resp
else:
raise MPRestError(resp["error"])
raise MPRestError("REST error with status code {} and error {}"
.format(response.status_code, response.text))
except Exception as ex:
raise MPRestError(str(ex))
[docs] def query_snl(self, criteria):
"""
Query for submitted SNLs.
.. note::
As of now, this MP REST feature is open only to a select group of
users. Opening up submissions to all users is being planned for
the future.
Args:
criteria (dict): Query criteria.
Returns:
A dict, with a list of submitted SNLs in the "response" key.
Raises:
MPRestError
"""
try:
payload = {"criteria": json.dumps(criteria)}
response = self.session.post("{}/snl/query".format(self.preamble),
data=payload)
if response.status_code in [200, 400]:
resp = json.loads(response.text)
if resp["valid_response"]:
if resp.get("warning"):
warnings.warn(resp["warning"])
return resp["response"]
else:
raise MPRestError(resp["error"])
raise MPRestError("REST error with status code {} and error {}"
.format(response.status_code, response.text))
except Exception as ex:
raise MPRestError(str(ex))
[docs] def submit_vasp_directory(self, rootdir, authors, projects=None,
references='', remarks=None, master_data=None,
master_history=None, created_at=None,
ncpus=None):
"""
Assimilates all vasp run directories beneath a particular
directory using BorgQueen to obtain structures, and then submits thhem
to the Materials Project as SNL files. VASP related meta data like
initial structure and final energies are automatically incorporated.
.. note::
As of now, this MP REST feature is open only to a select group of
users. Opening up submissions to all users is being planned for
the future.
Args:
rootdir (str): Rootdir to start assimilating VASP runs from.
authors: *List* of {"name":'', "email":''} dicts,
*list* of Strings as 'John Doe <johndoe@gmail.com>',
or a single String with commas separating authors. The same
list of authors should apply to all runs.
projects ([str]): List of Strings ['Project A', 'Project B'].
This applies to all structures.
references (str): A String in BibTeX format. Again, this applies to
all structures.
remarks ([str]): List of Strings ['Remark A', 'Remark B']
master_data (dict): A free form dict. Namespaced at the root
level with an underscore, e.g. {"_materialsproject":<custom
data>}. This data is added to all structures detected in the
directory, in addition to other vasp data on a per structure
basis.
master_history: A master history to be added to all entries.
created_at (datetime): A datetime object
ncpus (int): Number of cpus to use in using BorgQueen to
assimilate. Defaults to None, which means serial.
"""
from pymatgen.apps.borg.hive import VaspToComputedEntryDrone
from pymatgen.apps.borg.queen import BorgQueen
drone = VaspToComputedEntryDrone(inc_structure=True,
data=["filename",
"initial_structure"])
queen = BorgQueen(drone, number_of_drones=ncpus)
queen.parallel_assimilate(rootdir)
structures = []
metadata = []
histories = []
for e in queen.get_data():
structures.append(e.structure)
m = {
"_vasp": {
"parameters": e.parameters,
"final_energy": e.energy,
"final_energy_per_atom": e.energy_per_atom,
"initial_structure": e.data["initial_structure"].as_dict()
}
}
if "history" in e.parameters:
histories.append(e.parameters["history"])
if master_data is not None:
m.update(master_data)
metadata.append(m)
if master_history is not None:
histories = master_history * len(structures)
return self.submit_structures(
structures, authors, projects=projects, references=references,
remarks=remarks, data=metadata, histories=histories,
created_at=created_at)
[docs] def get_stability(self, entries):
"""
Returns the stability of all entries.
"""
try:
payload = {"entries": json.dumps(entries, cls=MontyEncoder)}
response = self.session.post("{}/phase_diagram/calculate_stability"
.format(self.preamble), data=payload)
if response.status_code in [200, 400]:
resp = json.loads(response.text, cls=MontyDecoder)
if resp["valid_response"]:
if resp.get("warning"):
warnings.warn(resp["warning"])
return resp["response"]
else:
raise MPRestError(resp["error"])
raise MPRestError("REST error with status code {} and error {}"
.format(response.status_code, response.text))
except Exception as ex:
raise MPRestError(str(ex))
[docs] def get_cohesive_energy(self, material_id, per_atom=False):
"""
Gets the cohesive for a material (eV per formula unit). Cohesive energy
is defined as the difference between the bulk energy and the sum of
total DFT energy of isolated atoms for atom elements in the bulk.
Args:
material_id (str): Materials Project material_id, e.g. 'mp-123'.
per_atom (bool): Whether or not to return cohesive energy per atom
Returns:
Cohesive energy (eV).
"""
entry = self.get_entry_by_material_id(material_id)
ebulk = entry.energy / entry.composition.get_integer_formula_and_factor()[1]
comp_dict = entry.composition.reduced_composition.as_dict()
isolated_atom_e_sum, n = 0, 0
for el in comp_dict.keys():
e = self._make_request("/element/%s/tasks/isolated_atom" % (el),
mp_decode=False)[0]
isolated_atom_e_sum += e['output']["final_energy_per_atom"] * comp_dict[el]
n += comp_dict[el]
ecoh_per_formula = isolated_atom_e_sum - ebulk
return ecoh_per_formula / n if per_atom else ecoh_per_formula
[docs] def get_reaction(self, reactants, products):
"""
Gets a reaction from the Materials Project.
Args:
reactants ([str]): List of formulas
products ([str]): List of formulas
Returns:
rxn
"""
return self._make_request("/reaction",
payload={"reactants[]": reactants,
"products[]": products}, mp_decode=False)
[docs] def get_substrates(self, material_id, number=50, orient=None):
"""
Get a substrate list for a material id. The list is in order of
increasing elastic energy if a elastic tensor is available for
the material_id. Otherwise the list is in order of increasing
matching area.
Args:
material_id (str): Materials Project material_id, e.g. 'mp-123'.
orient (list) : substrate orientation to look for
number (int) : number of substrates to return
n=0 returns all available matches
Returns:
list of dicts with substrate matches
"""
req = "/materials/{}/substrates?n={}".format(material_id, number)
if orient:
req += "&orient={}".format(" ".join(map(str, orient)))
return self._make_request(req)
[docs] def get_all_substrates(self):
"""
Gets the list of all possible substrates considered in the
Materials Project substrate database
Returns:
list of material_ids corresponding to possible substrates
"""
return self._make_request("/materials/all_substrate_ids")
[docs] def get_surface_data(self, material_id, miller_index=None, inc_structures=False):
"""
Gets surface data for a material. Useful for Wulff shapes.
Reference for surface data:
Tran, R., Xu, Z., Radhakrishnan, B., Winston, D., Sun, W., Persson, K.
A., & Ong, S. P. (2016). Data Descripter: Surface energies of elemental
crystals. Scientific Data, 3(160080), 1–13.
http://dx.doi.org/10.1038/sdata.2016.80
Args:
material_id (str): Materials Project material_id, e.g. 'mp-123'.
miller_index (list of integer): The miller index of the surface.
e.g., [3, 2, 1]. If miller_index is provided, only one dictionary
of this specific plane will be returned.
inc_structures (bool): Include final surface slab structures.
These are unnecessary for Wulff shape construction.
Returns:
Surface data for material. Energies are given in SI units (J/m^2).
"""
req = "/materials/{}/surfaces".format(material_id)
if inc_structures:
req += "?include_structures=true"
if miller_index:
surf_data_dict = self._make_request(req)
surf_list = surf_data_dict['surfaces']
ucell = self.get_structure_by_material_id(material_id,
conventional_unit_cell=True)
eq_indices = get_symmetrically_equivalent_miller_indices(ucell, miller_index)
for one_surf in surf_list:
if tuple(one_surf['miller_index']) in eq_indices:
return one_surf
else:
return self._make_request(req)
[docs] def get_wulff_shape(self, material_id):
"""
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.symmetry.analyzer import SpacegroupAnalyzer
from pymatgen.analysis.wulff import WulffShape
structure = self.get_structure_by_material_id(material_id)
surfaces = self.get_surface_data(material_id)["surfaces"]
lattice = (SpacegroupAnalyzer(structure)
.get_conventional_standard_structure().lattice)
miller_energy_map = {}
for surf in surfaces:
miller = tuple(surf["miller_index"])
# 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)
[docs] def get_gb_data(self, material_id=None, pretty_formula=None,
chemsys=None, sigma=None, gb_plane=None,
rotation_axis=None, include_work_of_separation=False):
"""
Gets grain boundary data for a material.
Args:
material_id (str): Materials Project material_id, e.g., 'mp-129'.
pretty_formula (str): The formula of metals. e.g., 'Fe'
sigma(int): The sigma value of a certain type of grain boundary
gb_plane(list of integer): The Miller index of grain
boundary plane. e.g., [1, 1, 1]
rotation_axis(list of integer): The Miller index of rotation
axis. e.g., [1, 0, 0], [1, 1, 0], and [1, 1, 1]
Sigma value is determined by the combination of rotation axis and
rotation angle. The five degrees of freedom (DOF) of one grain boundary
include: rotation axis (2 DOFs), rotation angle (1 DOF), and grain
boundary plane (2 DOFs).
include_work_of_separation (bool): whether to include the work of separation
(in unit of (J/m^2)). If you want to query the work of separation, please
specify the material_id.
Returns:
A list of grain boundaries that satisfy the query conditions (sigma, gb_plane).
Energies are given in SI units (J/m^2).
"""
if gb_plane:
gb_plane = ','.join([str(i) for i in gb_plane])
if rotation_axis:
rotation_axis = ','.join([str(i) for i in rotation_axis])
payload = {"material_id": material_id,
"pretty_formula": pretty_formula,
"chemsys": chemsys,
"sigma": sigma,
"gb_plane": gb_plane,
"rotation_axis": rotation_axis}
if include_work_of_separation and material_id:
list_of_gbs = self._make_request("/grain_boundaries",
payload=payload)
for i, gb_dict in enumerate(list_of_gbs):
gb_energy = gb_dict['gb_energy']
gb_plane_int = gb_dict['gb_plane']
surface_energy = self.get_surface_data(material_id=material_id,
miller_index=gb_plane_int)['surface_energy']
wsep = 2 * surface_energy - gb_energy # calculate the work of separation
gb_dict['work_of_separation'] = wsep
return list_of_gbs
else:
return self._make_request("/grain_boundaries",
payload=payload)
[docs] def get_interface_reactions(self, reactant1, reactant2,
open_el=None, relative_mu=None,
use_hull_energy=False):
"""
Gets critical reactions between two reactants.
Get critical reactions ("kinks" in the mixing ratio where
reaction products change) between two reactants. See the
`pymatgen.analysis.interface_reactions` module for more info.
Args:
reactant1 (str): Chemical formula for reactant
reactant2 (str): Chemical formula for reactant
open_el (str): Element in reservoir available to system
relative_mu (float): Relative chemical potential of element in
reservoir with respect to pure substance. Must be non-positive.
use_hull_energy (bool): Whether to use the convex hull energy for a
given composition for the reaction energy calculation. If false,
the energy of the ground state structure will be preferred; if a
ground state can not be found for a composition, the convex hull
energy will be used with a warning message.
Returns:
list: list of dicts of form {ratio,energy,rxn} where `ratio` is the
reactant mixing ratio, `energy` is the reaction energy
in eV/atom, and `rxn` is a
`pymatgen.analysis.reaction_calculator.Reaction`.
"""
payload = {"reactants": " ".join([reactant1, reactant2]),
"open_el": open_el,
"relative_mu": relative_mu,
"use_hull_energy": use_hull_energy}
return self._make_request("/interface_reactions",
payload=payload, method="POST")
[docs] def get_download_info(self, material_ids, task_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 TaskType 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
task_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
task_types = [t.value for t in task_types if isinstance(t, TaskType)] if task_types else []
meta = defaultdict(list)
for doc in self.query({'material_id': {'$in': material_ids}},
['material_id', 'blessed_tasks']):
for task_type, task_id in doc['blessed_tasks'].items():
if task_types and task_type not in task_types:
continue
meta[doc["material_id"]].append(
{'task_id': task_id, 'task_type': task_type}
)
if not meta:
raise ValueError('No tasks found.')
# return a list of URLs for NoMaD Downloads containing the list of files
# for every external_id in `task_ids`
prefix = 'http://labdev-nomad.esc.rzg.mpg.de/fairdi/nomad/mp/api/raw/query?'
if file_patterns is not None:
for file_pattern in file_patterns:
prefix += f'file_pattern={file_pattern}&'
prefix += 'external_id='
# NOTE: IE has 2kb URL char limit
nmax = int((2000 - len(prefix)) / 11) # mp-<7-digit> + , = 11
task_ids = [t['task_id'] for tl in meta.values() for t in tl]
chunks = get_chunks(task_ids, size=nmax)
urls = [prefix + ','.join(tids) for tids in chunks]
return meta, urls
[docs] @staticmethod
def parse_criteria(criteria_string):
"""
Parses a powerful and simple string criteria and generates a proper
mongo syntax criteria.
Args:
criteria_string (str): A string representing a search criteria.
Also supports wild cards. E.g.,
something like "*2O" gets converted to
{'pretty_formula': {'$in': [u'B2O', u'Xe2O', u"Li2O", ...]}}
Other syntax examples:
mp-1234: Interpreted as a Materials ID.
Fe2O3 or *2O3: Interpreted as reduced formulas.
Li-Fe-O or *-Fe-O: Interpreted as chemical systems.
You can mix and match with spaces, which are interpreted as
"OR". E.g., "mp-1234 FeO" means query for all compounds with
reduced formula FeO or with materials_id mp-1234.
Returns:
A mongo query dict.
"""
toks = criteria_string.split()
def parse_sym(sym):
if sym == "*":
return [el.symbol for el in Element]
else:
m = re.match(r"\{(.*)\}", sym)
if m:
return [s.strip() for s in m.group(1).split(",")]
else:
return [sym]
def parse_tok(t):
if re.match(r"\w+-\d+", t):
return {"task_id": t}
elif "-" in t:
elements = [parse_sym(sym) for sym in t.split("-")]
chemsyss = []
for cs in itertools.product(*elements):
if len(set(cs)) == len(cs):
# Check for valid symbols
cs = [Element(s).symbol for s in cs]
chemsyss.append("-".join(sorted(cs)))
return {"chemsys": {"$in": chemsyss}}
else:
all_formulas = set()
explicit_els = []
wild_card_els = []
for sym in re.findall(
r"(\*[\.\d]*|\{.*\}[\.\d]*|[A-Z][a-z]*)[\.\d]*", t):
if ("*" in sym) or ("{" in sym):
wild_card_els.append(sym)
else:
m = re.match(r"([A-Z][a-z]*)[\.\d]*", sym)
explicit_els.append(m.group(1))
nelements = len(wild_card_els) + len(set(explicit_els))
parts = re.split(r"(\*|\{.*\})", t)
parts = [parse_sym(s) for s in parts if s != ""]
for f in itertools.product(*parts):
c = Composition("".join(f))
if len(c) == nelements:
# Check for valid Elements in keys.
for e in c.keys():
Element(e.symbol)
all_formulas.add(c.reduced_formula)
return {"pretty_formula": {"$in": list(all_formulas)}}
if len(toks) == 1:
return parse_tok(toks[0])
else:
return {"$or": list(map(parse_tok, toks))}
[docs]class MPRestError(Exception):
"""
Exception class for MPRestAdaptor.
Raised when the query has problems, e.g., bad query format.
"""
pass