encyclopedia.py

# Copyright 2018 Markus Scheidgen
#
# Licensed under the Apache License, Version 2.0 (the 'License');
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an'AS IS' BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from typing import Dict, List, Any
from math import gcd as gcd
from functools import reduce
from abc import abstractmethod
from collections import OrderedDict
import re
import json
import ase
import ase.data
from ase import Atoms
import numpy as np
from matid import SymmetryAnalyzer
import matid.geometry

from nomad.normalizing.normalizer import (
    Normalizer,
    s_run,
    s_scc,
    s_system,
    s_method,
    s_frame_sequence,
    r_frame_sequence_to_sampling,
    s_sampling_method,
    r_frame_sequence_local_frames,
)
from nomad.metainfo.encyclopedia import (
    Encyclopedia,
    Material,
    Method,
    Properties,
    RunType,
    WyckoffSet,
    WyckoffVariables,
    ElectronicBandStructure,
    BandGap,
)
from nomad.parsing.backend import Section, LocalBackend
from nomad.normalizing.settingsbasisset import get_basis_set_settings
from nomad.normalizing import structure
from nomad.utils import hash, RestrictedDict, timer
from nomad import config

J_to_Ry = 4.587425e+17


class Context():
    """A simple class for holding the context related to an Encylopedia entry.
    """
    def __init__(
        self,
        system_type: str,
        method_type: str,
        run_type: str,
        representative_system,
        representative_method,
        representative_scc,
        representative_scc_idx,
    ):
        self.system_type = system_type
        self.method_type = method_type
        self.run_type = run_type
        self.representative_system = representative_system
        self.representative_method = representative_method
        self.representative_scc = representative_scc
        self.representative_scc_idx = representative_scc_idx
        self.greatest_common_divisor: int = None


class EncyclopediaNormalizer(Normalizer):
    """
    This normalizer emulates the functionality of the old Encyclopedia backend.
    The data used by the encyclopedia have been assigned under new metainfo
    within section_encyclopedia. In the future these separate metainfos could
    be absorbed into the existing metainfo hiearchy.
    """
    def __init__(self, backend: LocalBackend):
        super().__init__(backend)
        self.backend: LocalBackend = backend

    def run_type(self, run_type_sec: RunType) -> str:
        """Decides what type of calculation this is: single_point, md,
        geometry_optimization, etc.
        """
        run_enums = RunType.run_type.type
        run_type = run_enums.unavailable

        try:
            sccs = self._backend[s_scc]
        except Exception:
            sccs = []
        try:
            frame_sequences = self._backend[s_frame_sequence]
        except Exception:
            frame_sequences = []

        n_scc = len(sccs)
        n_frame_seq = len(frame_sequences)

        # No sequences, only a few calculations
        if n_scc <= 3 and n_frame_seq == 0:
            program_name = self._backend["program_name"]
            if program_name == "elastic":
                # TODO move to taylor expansion as soon as data is correct in archive
                run_type = run_enums.elastic_constants
            else:
                run_type = run_enums.single_point

        # One sequence. Currently calculations with multiple sequences are
        # unsupported.
        elif n_frame_seq == 1:
            frame_seq = frame_sequences[0]

            # See if sampling_method is present
            try:
                i_sampling_method = frame_seq[r_frame_sequence_to_sampling]
            except KeyError:
                self.logger.info(
                    "Cannot determine encyclopedia run type because missing "
                    "value for frame_sequence_to_sampling_ref."
                )
                return run_type

            # See if local frames are present
            try:
                frames = frame_seq[r_frame_sequence_local_frames]
            except KeyError:
                self.logger.info(
                    "section_frame_sequence_local_frames not found although a "
                    "frame_sequence exists."
                )
                return run_type
            if len(frames) == 0:
                self.logger.info("No frames referenced in section_frame_sequence_local_frames.")
                return run_type

            section_sampling_method = self._backend[s_sampling_method][i_sampling_method]
            sampling_method = section_sampling_method["sampling_method"]

            if sampling_method == "molecular_dynamics":
                run_type = run_enums.molecular_dynamics
            if sampling_method == "geometry_optimization":
                run_type = run_enums.geometry_optimization
            if sampling_method == "taylor_expansion":
                run_type = run_enums.phonon_calculation

        run_type_sec.run_type = run_type
        return run_type

    def system_type(self, material: Material) -> tuple:
        # Try to fetch representative system
        system = None
        system_type = config.services.unavailable_value
        system_enums = Material.system_type.type
        system_idx = self._backend["section_run"][0].tmp["representative_system_idx"]
        if system_idx is not None:
            # Try to find system type information from backend for the selected system.
            try:
                system = self._backend[s_system][system_idx]
                stype = system["system_type"]
            except KeyError:
                pass
            else:
                if stype == system_enums.one_d or stype == system_enums.two_d:
                    system_type = stype
                # For bulk systems we also ensure that the symmetry information is available
                if stype == system_enums.bulk:
                    try:
                        system["section_symmetry"][0]
                    except (KeyError, IndexError):
                        self.logger.info("Symmetry information is not available for a bulk system. No Encylopedia entry created.")
                    else:
                        system_type = stype

        material.system_type = system_type
        return system, system_type

    def method_type(self, method: Method) -> tuple:
        repr_method = None
        method_id = config.services.unavailable_value
        methods = self._backend[s_method]
        n_methods = len(methods)

        if n_methods == 1:
            repr_method = methods[0]
            method_id = repr_method.get("electronic_structure_method", config.services.unavailable_value)
        elif n_methods > 1:
            for sec_method in self._backend[s_method]:
                # GW
                electronic_structure_method = sec_method.get("electronic_structure_method", None)
                if electronic_structure_method in {"G0W0", "scGW"}:
                    repr_method = sec_method
                    method_id = "GW"
                    break

                # Methods linked to each other through references. Get all
                # linked methods, try to get electronic_structure_method from
                # each.
                try:
                    refs = sec_method["section_method_to_method_refs"]
                except KeyError:
                    pass
                else:
                    linked_methods = [sec_method]
                    for ref in refs:
                        method_to_method_kind = ref["method_to_method_kind"]
                        method_to_method_ref = ref["method_to_method_ref"]
                        if method_to_method_kind == "core_settings":
                            linked_methods.append(methods[method_to_method_ref])

                    for i_method in linked_methods:
                        try:
                            electronic_structure_method = i_method["electronic_structure_method"]
                        except KeyError:
                            pass
                        else:
                            repr_method = sec_method
                            method_id = electronic_structure_method

        method.method_type = method_id
        return repr_method, method_id

    def mainfile_uri(self, encyclopedia: Encyclopedia):
        entry_info = self._backend["section_entry_info"][0]
        upload_id = entry_info["upload_id"]
        mainfile_path = entry_info["mainfile"]
        uri = f"nmd://R{upload_id}/data/{mainfile_path}"
        encyclopedia.mainfile_uri = uri

    # def similar_materials(self) -> None:
        # pass

    # def calculation_pid(self):
        # pass

    # def calculation(self) -> None:
        # pass

    # def contributor_first_name(self) -> None:
        # pass

    # def contributor_last_name(self) -> None:
        # pass

    # def contributor_type(self) -> None:
        # pass

    # def contributors(self) -> None:
        # pass

    # def number_of_calculations(self) -> None:
        # pass

    def fill(self, ctx: Context):
        # Fill structure related metainfo
        struct: Any = None
        if ctx.system_type == Material.system_type.type.bulk:
            struct = MaterialBulkNormalizer(self.backend, self.logger)
        elif ctx.system_type == Material.system_type.type.two_d:
            struct = Material2DNormalizer(self.backend, self.logger)
        elif ctx.system_type == Material.system_type.type.one_d:
            struct = Material1DNormalizer(self.backend, self.logger)
        if struct is not None:
            struct.normalize(ctx)

        # Fill method related metainfo
        method = None
        if ctx.method_type == Method.method_type.type.DFT or ctx.method_type == Method.method_type.type.DFTU:
            method = MethodDFTNormalizer(self._backend, self.logger)
        elif ctx.method_type == Method.method_type.type.GW:
            method = MethodGWNormalizer(self._backend, self.logger)
        if method is not None:
            method.normalize(ctx)

        # Fill properties related metainfo
        properties = PropertiesNormalizer(self.backend, self.logger)
        properties.normalize(ctx)

    def normalize(self, logger=None) -> None:
        with timer(self.logger, 'EncyclopediaNormalizer finished') as log:
            try:
                super().normalize(logger)

                # Initialise metainfo structure
                sec_enc = Encyclopedia()
                material = sec_enc.m_create(Material)
                method = sec_enc.m_create(Method)
                sec_enc.m_create(Properties)
                run_type = sec_enc.m_create(RunType)

                # Get generic data
                self.mainfile_uri(sec_enc)

                # Determine run type, stop if unknown
                run_type_name = self.run_type(run_type)
                if run_type_name == config.services.unavailable_value:
                    log["enc_status"] = "unknown_run_type"
                    log["enc_message"] = "Unknown run type for encyclopedia, encyclopedia metainfo not created."
                    return

                # Get the system type, stop if unknown
                system_enums = Material.system_type.type
                representative_system, system_type = self.system_type(material)
                if system_type != system_enums.bulk and system_type != system_enums.two_d and system_type != system_enums.one_d:
                    log["enc_status"] = "unknown_system_type"
                    log["enc_message"] = "Unknown system type for encyclopedia, encyclopedia metainfo not created."
                    return

                # Get the method type, stop if unknown
                representative_method, method_type = self.method_type(method)

                # Get representative scc
                try:
                    representative_scc_idx = self._backend[s_run][0].tmp["representative_scc_idx"]
                    representative_scc = self._backend[s_scc][representative_scc_idx]
                except (KeyError, IndexError):
                    representative_scc = None
                    representative_scc_idx = None

                # Create one context that holds all details
                context = Context(
                    system_type=system_type,
                    method_type=method_type,
                    run_type=run_type_name,
                    representative_system=representative_system,
                    representative_method=representative_method,
                    representative_scc=representative_scc,
                    representative_scc_idx=representative_scc_idx,
                )

                # Put the encyclopedia section into backend
                self._backend.add_mi2_section(sec_enc)
                self.fill(context)

            except Exception as e:
                log["enc_status"] = "failure"
                log["enc_message"] = "Failed to create an Encyclopedia entry due to an unhandlable exception."
                log["exc_info"] = e
            else:
                log["enc_status"] = "success"
                log["enc_message"] = "Successfully created metainfo for Encyclopedia."


class MaterialNormalizer():
    """A base class that is used for processing material-related information
    in the Encylopedia.
    """
    def __init__(self, backend: LocalBackend, logger):
        self.backend = backend
        self.logger = logger

    def atom_labels(self, material: Material, std_atoms: Atoms) -> None:
        material.atom_labels = std_atoms.get_chemical_symbols()

    def atom_positions(self, material: Material, std_atoms: Atoms) -> None:
        material.atom_positions = std_atoms.get_scaled_positions(wrap=False)

    @abstractmethod
    def cell_normalized(self, material: Material, std_atoms: Atoms) -> None:
        pass

    def cell_volume(self, material: Material, std_atoms: Atoms) -> None:
        material.cell_volume = float(std_atoms.get_volume() * 1e-10**3)

    def formula(self, material: Material, names: List[str], counts: List[int]) -> None:
        formula = structure.get_formula_string(names, counts)
        material.formula = formula

    def formula_reduced(self, material: Material, names: list, counts_reduced: list) -> None:
        formula = structure.get_formula_string(names, counts_reduced)
        material.formula_reduced = formula

    def material_hash(self, material: Material, spg_number: int, wyckoff_sets: List[WyckoffSet]) -> None:
        # Create and store hash based on SHA512
        norm_hash_string = structure.get_symmetry_string(spg_number, wyckoff_sets)
        material.material_hash = hash(norm_hash_string)

    def number_of_atoms(self, material: Material, std_atoms: Atoms) -> None:
        material.number_of_atoms = len(std_atoms)

    @abstractmethod
    def normalize(self, ctx: Context) -> None:
        pass


class MaterialBulkNormalizer(MaterialNormalizer):
    """Processes structure related metainfo for Encyclopedia bulk structures.
    """
    def atomic_density(self, properties: Properties, repr_system: Atoms) -> None:
        orig_n_atoms = len(repr_system)
        orig_volume = repr_system.get_volume() * (1e-10)**3
        properties.atomic_density = float(orig_n_atoms / orig_volume)

    def bravais_lattice(self, material: Material, section_symmetry: Section) -> None:
        bravais_lattice = section_symmetry["bravais_lattice"]
        material.bravais_lattice = bravais_lattice

    def cell_normalized(self, material: Material, std_atoms: Atoms) -> None:
        cell_normalized = std_atoms.get_cell()
        cell_normalized *= 1e-10
        material.cell_normalized = cell_normalized

    def cell_primitive(self, material: Material, prim_atoms: Atoms) -> None:
        cell_prim = prim_atoms.get_cell()
        cell_prim *= 1e-10
        material.cell_primitive = cell_prim

    def crystal_system(self, material: Material, section_symmetry: Section) -> None:
        material.crystal_system = section_symmetry["crystal_system"]

    def has_free_wyckoff_parameters(self, material: Material, symmetry_analyzer: SymmetryAnalyzer) -> None:
        has_free_param = symmetry_analyzer.get_has_free_wyckoff_parameters()
        material.has_free_wyckoff_parameters = has_free_param

    def lattice_parameters(self, material: Material, std_atoms: Atoms) -> None:
        cell_normalized = std_atoms.get_cell() * 1E-10
        material.lattice_parameters = structure.get_lattice_parameters(cell_normalized)

    def mass_density(self, properties: Properties, repr_system: Atoms) -> None:
        mass = structure.get_summed_atomic_mass(repr_system.get_atomic_numbers())
        orig_volume = repr_system.get_volume() * (1e-10)**3
        properties.mass_density = float(mass / orig_volume)

    def material_name(self, material: Material, symbols: list, numbers: list) -> None:
        # Systems with one element are named after it
        if len(symbols) == 1:
            number = ase.data.atomic_numbers[symbols[0]]
            name = ase.data.atomic_names[number]
            material.material_name = name

        # Binary systems have specific names
        if len(symbols) == 2:
            atomicnumbers = [ase.data.atomic_numbers[i] for i in symbols]
            names = [ase.data.atomic_names[i] for i in atomicnumbers]

            # Non-metal elements are anions in the binary compounds and receive the -ide suffix
            if names[1] == "Antimony":
                names[1] = names[1][:-1] + "ide"
            if names[1] == "Arsenic":
                names[1] = names[1][:-1] + "de"
            if names[1] == "Boron" or names[1] == "Carbon":
                names[1] = names[1][:-2] + "ide"
            if names[1] == "Chlorine" or names[1] == "Germanium" or names[1] == "Selenium" or names[1] == "Bromine" \
               or names[1] == "Tellurium" or names[1] == "Iodine" or names[1] == "Polonium" or names[1] == "Astatine" or \
               names[1] == "Fluorine":
                names[1] = names[1][:-2] + "de"
            if names[1] == "Silicon" or names[1] == "Sulfur":
                names[1] = names[1][:-2] + "ide"
            if names[1] == "Nitrogen" or names[1] == "Oxygen" or names[1] == "Hydrogen" or names[1] == "Phosphorus":
                names[1] = names[1][:-4] + "ide"

            name = names[0] + " " + names[1]

            if names[1] == "Fluoride" or names[1] == "Chloride" or names[1] == "Bromide" or \
               names[1] == "Iodide" or names[1] == "Hydride":

                # Non-metals with elements of variable valence, therefore we remove alkaline and
                # alkaline-earth elements, which have fixed valence
                # Only the most electronegative non-metals are supposed to make ionic compounds
                if names[0] != "Lithium" and names[0] != "Sodium" and names[0] != "Potassium" and \
                   names[0] != "Rubidium" and names[0] != "Cesium" and names[0] != "Francium" and \
                   names[0] != "Beryllium" and names[0] != "Magnesium" and names[0] != "Calcium" and \
                   names[0] != "Strontium" and names[0] != "Barium" and names[0] != "Radium" and \
                   names[0] != "Aluminum":

                    if numbers[1] == 2:
                        name = names[0] + "(II)" + " " + names[1]
                    elif numbers[1] == 3:
                        name = names[0] + "(III)" + " " + names[1]
                    elif numbers[1] == 4:
                        name = names[0] + "(IV)" + " " + names[1]
                    elif numbers[1] == 5:
                        name = names[0] + "(V)" + " " + names[1]
                    elif numbers[1] == 6:
                        name = names[0] + "(VI)" + " " + names[1]
                    elif numbers[1] == 7:
                        name = names[0] + "(VII)" + " " + names[1]

            if names[1] == "Oxide" or names[1] == "Sulfide" or names[1] == "Selenide":
                if names[0] != "Lithium" and names[0] != "Sodium" and names[0] != "Potassium" and \
                   names[0] != "Rubidium" and names[0] != "Cesium" and names[0] != "Francium" and \
                   names[0] != "Beryllium" and names[0] != "Magnesium" and names[0] != "Calcium" and \
                   names[0] != "Strontium" and names[0] != "Barium" and names[0] != "Radium" and \
                   names[0] != "Aluminum":

                    if numbers[0] == 1 and numbers[1] == 1:
                        name = names[0] + "(II)" + " " + names[1]
                    elif numbers[0] == 2 and numbers[1] == 1:
                        name = names[0] + "(I)" + " " + names[1]
                    elif numbers[0] == 1 and numbers[1] == 2:
                        name = names[0] + "(IV)" + " " + names[1]
                    elif numbers[0] == 2 and numbers[1] == 3:
                        name = names[0] + "(III)" + " " + names[1]
                    elif numbers[0] == 2 and numbers[1] == 5:
                        name = names[0] + "(V)" + " " + names[1]
                    elif numbers[0] == 1 and numbers[1] == 3:
                        name = names[0] + "(VI)" + " " + names[1]
                    elif numbers[0] == 2 and numbers[1] == 7:
                        name = names[0] + "(VII)" + " " + names[1]

            if names[1] == "Nitride" or names[1] == "Phosphide":
                if names[0] != "Lithium" and names[0] != "Sodium" and names[0] != "Potassium" and \
                   names[0] != "Rubidium" and names[0] != "Cesium" and names[0] != "Francium" and \
                   names[0] != "Beryllium" and names[0] != "Magnesium" and names[0] != "Calcium" and \
                   names[0] != "Strontium" and names[0] != "Barium" and names[0] != "Radium" and \
                   names[0] != "Aluminum":

                    if numbers[0] == 1 and numbers[1] == 1:
                        name = names[0] + "(III)" + " " + names[1]
                    if numbers[0] == 1 and numbers[1] == 2:
                        name = names[0] + "(VI)" + " " + names[1]
                    elif numbers[0] == 3 and numbers[1] == 2:
                        name = names[0] + "(II)" + " " + names[1]
                    elif numbers[0] == 3 and numbers[1] == 4:
                        name = names[0] + "(IV)" + " " + names[1]
                    elif numbers[0] == 3 and numbers[1] == 5:
                        name = names[0] + "(V)" + " " + names[1]
                    elif numbers[0] == 3 and numbers[1] == 7:
                        name = names[0] + "(VII)" + " " + names[1]

            if names[1] == "Carbide":
                if names[0] != "Lithium" and names[0] != "Sodium" and names[0] != "Potassium" and \
                   names[0] != "Rubidium" and names[0] != "Cesium" and names[0] != "Francium" and \
                   names[0] != "Beryllium" and names[0] != "Magnesium" and names[0] != "Calcium" and \
                   names[0] != "Strontium" and names[0] != "Barium" and names[0] != "Radium" and \
                   names[0] != "Aluminum":

                    if numbers[0] == 1 and numbers[1] == 1:
                        name = names[0] + "(IV)" + " " + names[1]
                    if numbers[0] == 2 and numbers[1] == 1:
                        name = names[0] + "(II)" + " " + names[1]
                    if numbers[0] == 4 and numbers[1] == 1:
                        name = names[0] + "(I)" + " " + names[1]
                    if numbers[0] == 4 and numbers[1] == 3:
                        name = names[0] + "(III)" + " " + names[1]
                    if numbers[0] == 4 and numbers[1] == 5:
                        name = names[0] + "(V)" + " " + names[1]
                    if numbers[0] == 2 and numbers[1] == 3:
                        name = names[0] + "(VI)" + " " + names[1]
                    if numbers[0] == 4 and numbers[1] == 7:
                        name = names[0] + "(VII)" + " " + names[1]

            material.material_name = name

    def periodicity(self, material: Material) -> None:
        material.periodicity = np.array([True, True, True], dtype=np.bool)

    def point_group(self, material: Material, section_symmetry: Section) -> None:
        point_group = section_symmetry["point_group"]
        material.point_group = point_group

    def space_group_number(self, material: Material, spg_number: int) -> None:
        material.space_group_number = spg_number

    def space_group_international_short_symbol(self, material: Material, symmetry_analyzer: SymmetryAnalyzer) -> None:
        spg_int_symb = symmetry_analyzer.get_space_group_international_short()
        material.space_group_international_short_symbol = spg_int_symb

    def material_classification(self, material: Material, section_system: Section) -> None:
        try:
            sec_springer = section_system["section_springer_material"][0]
        except Exception:
            return

        classes: Dict[str, List[str]] = {}
        try:
            classifications = sec_springer['springer_classification']
        except KeyError:
            pass
        else:
            classes["material_class_springer"] = classifications
        try:
            compound_classes = sec_springer['springer_compound_class']
        except KeyError:
            pass
        else:
            classes["compound_class_springer"] = compound_classes
        if classes:
            material.material_classification = json.dumps(classes)

    def structure_type(self, material: Material, section_system: Section) -> None:
        try:
            sec_prototype = section_system["section_prototype"][0]
            notes = sec_prototype.tmp['prototype_notes']
        except Exception:
            return

        # Only relevant information hidden in "notes" is handed over TODO:
        # review and eventually add more ****ites which are commonly used
        # (see wurzite)
        note_map = {
            "CaTiO<sub>3</sub> Pnma Perovskite Structure": "perovskite",
            "Hypothetical Tetrahedrally Bonded Carbon with 4&ndash;Member Rings": "4-member ring",
            "In (A6) Structure": "fct",
            "$\\alpha$&ndash;Pa (A<sub>a</sub>) Structure": "bct",
            "Hypothetical BCT5 Si Structure": "bct5",
            "Wurtzite (ZnS, B4) Structure": "wurtzite",
            "Hexagonal Close Packed (Mg, A3) Structure": "hcp",
            "Half&ndash;Heusler (C1<sub>b</sub>) Structure": "half-Heusler",
            "Zincblende (ZnS, B3) Structure": "zincblende",
            "Cubic Perovskite (CaTiO<sub>3</sub>, E2<sub>1</sub>) Structure": "cubic perovskite",
            "$\\alpha$&ndash;Po (A<sub>h</sub>) Structure": "simple cubic",
            "Si<sub>46</sub> Clathrate Structure": "clathrate",
            "Cuprite (Cu<sub>2</sub>O, C3) Structure": "cuprite",
            "Heusler (L2<sub>1</sub>) Structure": "Heusler",
            "Rock Salt (NaCl, B1) Structure": "rock salt",
            "Face&ndash;Centered Cubic (Cu, A1) Structure": "fcc",
            "Diamond (A4) Structure": "diamond",
            "Body&ndash;Centered Cubic (W, A2) Structure": "bcc",
        }
        enc_note = note_map.get(notes, None)
        if enc_note is not None:
            material.structure_type = enc_note

    def structure_prototype(self, material: Material, section_system: Section) -> None:
        try:
            sec_prototype = section_system["section_prototype"][0]
            name = sec_prototype.tmp['prototype_name']
        except Exception:
            return

        material.structure_prototype = name

    def strukturbericht_designation(self, material: Material, section_system: Section) -> None:
        try:
            sec_prototype = section_system["section_prototype"][0]
            strukturbericht = sec_prototype.tmp["strukturbericht_designation"]
        except Exception:
            return

        # In the current GUI we replace LaTeX with plain text
        strukturbericht = re.sub('[$_{}]', '', strukturbericht)
        material.strukturbericht_designation = strukturbericht

    def wyckoff_sets(self, material: Material, wyckoff_sets: Dict) -> None:
        for group in wyckoff_sets:
            wset = material.m_create(WyckoffSet)
            if group.x is not None or group.y is not None or group.z is not None:
                variables = wset.m_create(WyckoffVariables)
                if group.x is not None:
                    variables.x = float(group.x)
                if group.y is not None:
                    variables.y = float(group.y)
                if group.z is not None:
                    variables.z = float(group.z)
            wset.indices = group.indices
            wset.element = group.element
            wset.wyckoff_letter = group.wyckoff_letter

    def normalize(self, ctx: Context) -> None:
        # Fetch resources
        sec_system = ctx.representative_system
        sec_enc = self.backend.get_mi2_section(Encyclopedia.m_def)
        material = sec_enc.material
        properties = sec_enc.properties
        sec_symmetry = sec_system["section_symmetry"][0]
        symmetry_analyzer = sec_system["section_symmetry"][0].tmp["symmetry_analyzer"]
        spg_number = symmetry_analyzer.get_space_group_number()
        std_atoms = symmetry_analyzer.get_conventional_system()
        prim_atoms = symmetry_analyzer.get_primitive_system()
        repr_atoms = sec_system.tmp["representative_atoms"]  # Temporary value stored by SystemNormalizer
        wyckoff_sets = symmetry_analyzer.get_wyckoff_sets_conventional(return_parameters=True)
        names, counts = structure.get_hill_decomposition(prim_atoms.get_chemical_symbols(), reduced=False)
        greatest_common_divisor = reduce(gcd, counts)
        ctx.greatest_common_divisor = greatest_common_divisor
        reduced_counts = np.array(counts) / greatest_common_divisor

        # Fill structural information
        self.mass_density(properties, repr_atoms)
        self.material_hash(material, spg_number, wyckoff_sets)
        self.number_of_atoms(material, std_atoms)
        self.atom_labels(material, std_atoms)
        self.atom_positions(material, std_atoms)
        self.atomic_density(properties, repr_atoms)
        self.bravais_lattice(material, sec_symmetry)
        self.cell_normalized(material, std_atoms)
        self.cell_volume(material, std_atoms)
        self.crystal_system(material, sec_symmetry)
        self.cell_primitive(material, prim_atoms)
        self.formula(material, names, counts)
        self.formula_reduced(material, names, reduced_counts)
        self.has_free_wyckoff_parameters(material, symmetry_analyzer)
        self.lattice_parameters(material, std_atoms)
        self.material_name(material, names, reduced_counts)
        self.material_classification(material, sec_system)
        self.periodicity(material)
        self.point_group(material, sec_symmetry)
        self.space_group_number(material, spg_number)
        self.space_group_international_short_symbol(material, symmetry_analyzer)
        self.structure_type(material, sec_system)
        self.structure_prototype(material, sec_system)
        self.strukturbericht_designation(material, sec_system)
        self.wyckoff_sets(material, wyckoff_sets)


class Material2DNormalizer(MaterialNormalizer):
    """Processes structure related metainfo for Encyclopedia 2D structures.
    """
    def cell_normalized(self, material: Material, std_atoms: Atoms) -> None:
        cell_normalized = std_atoms.get_cell()
        cell_normalized *= 1e-10
        material.cell_normalized = cell_normalized

    def cell_primitive(self, material: Material, prim_atoms: Atoms) -> None:
        cell_prim = prim_atoms.get_cell()
        cell_prim *= 1e-10
        material.cell_primitive = cell_prim

    def lattice_parameters(self, material: Material, std_atoms: Atoms, periodicity: np.array) -> None:
        # 2D systems only have three lattice parameter: two length and angle between them
        periodic_indices = np.where(np.array(periodicity) == True)[0]  # noqa: E712
        cell = std_atoms.get_cell()
        a_vec = cell[periodic_indices[0], :] * 1e-10
        b_vec = cell[periodic_indices[1], :] * 1e-10
        a = np.linalg.norm(a_vec)
        b = np.linalg.norm(b_vec)
        alpha = np.clip(np.dot(a_vec, b_vec) / (a * b), -1.0, 1.0)
        alpha = np.arccos(alpha)
        material.lattice_parameters = np.array([a, b, 0.0, alpha, 0.0, 0.0])

    def periodicity(self, material: Material, std_atoms: Atoms) -> None:
        # MatID already provides the correct periodicity
        material.periodicity = std_atoms.get_pbc()

    def get_symmetry_analyzer(self, original_system: Atoms) -> SymmetryAnalyzer:
        # Get dimension of system by also taking into account the covalent radii
        dimensions = matid.geometry.get_dimensions(original_system, [True, True, True])
        basis_dimensions = np.linalg.norm(original_system.get_cell(), axis=1)
        gaps = basis_dimensions - dimensions
        periodicity = gaps <= config.normalize.cluster_threshold

        # If two axis are not periodic, return. This only happens if the vacuum
        # gap is not aligned with a cell vector or if the linear gap search is
        # unsufficient (the structure is "wavy" making also the gap highly
        # nonlinear).
        if sum(periodicity) != 2:
            raise ValueError("Could not detect the periodic dimensions in a 2D system.")

        # Center the system in the non-periodic direction, also taking
        # periodicity into account. The get_center_of_mass()-function in MatID
        # takes into account periodicity and can produce the correct CM unlike
        # the similar function in ASE.
        pbc_cm = matid.geometry.get_center_of_mass(original_system)
        cell_center = 0.5 * np.sum(original_system.get_cell(), axis=0)
        translation = cell_center - pbc_cm
        translation[periodicity] = 0
        symm_system = original_system.copy()
        symm_system.translate(translation)
        symm_system.wrap()

        # Set the periodicity according to detected periodicity in order for
        # SymmetryAnalyzer to use the symmetry analysis designed for 2D
        # systems.
        symm_system.set_pbc(periodicity)
        symmetry_analyzer = SymmetryAnalyzer(
            symm_system,
            config.normalize.symmetry_tolerance,
            config.normalize.flat_dim_threshold
        )
        return symmetry_analyzer

    def normalize(self, ctx: Context) -> None:
        # Fetch resources
        sec_enc = self.backend.get_mi2_section(Encyclopedia.m_def)
        material = sec_enc.material
        repr_atoms = ctx.representative_system.tmp["representative_atoms"]  # Temporary value stored by SystemNormalizer
        symmetry_analyzer = self.get_symmetry_analyzer(repr_atoms)
        spg_number = symmetry_analyzer.get_space_group_number()
        wyckoff_sets = symmetry_analyzer.get_wyckoff_sets_conventional(return_parameters=False)
        std_atoms = symmetry_analyzer.get_conventional_system()
        prim_atoms = symmetry_analyzer.get_primitive_system()
        names, counts = structure.get_hill_decomposition(prim_atoms.get_chemical_symbols(), reduced=False)
        greatest_common_divisor = reduce(gcd, counts)
        ctx.greatest_common_divisor = greatest_common_divisor
        reduced_counts = np.array(counts) / greatest_common_divisor

        # Fill metainfo
        self.periodicity(material, std_atoms)
        self.material_hash(material, spg_number, wyckoff_sets)
        self.number_of_atoms(material, std_atoms)
        self.atom_labels(material, std_atoms)
        self.atom_positions(material, std_atoms)
        self.cell_normalized(material, std_atoms)
        self.cell_primitive(material, prim_atoms)
        self.formula(material, names, counts)
        self.formula_reduced(material, names, reduced_counts)
        self.lattice_parameters(material, std_atoms, material.periodicity)


class Material1DNormalizer(MaterialNormalizer):
    """Processes structure related metainfo for Encyclopedia 1D structures.
    """
    def material_hash_1d(self, material: Material, prim_atoms: Atoms) -> None:
        """Hash to be used as identifier for a material. Different 1D
        materials are defined by their Coulomb matrix eigenvalues and their
        Hill formulas.
        """
        fingerprint = self.get_structure_fingerprint(prim_atoms)
        formula = material.formula
        id_strings = []
        id_strings.append(formula)
        id_strings.append(fingerprint)
        hash_seed = ", ".join(id_strings)
        hash_val = hash(hash_seed)
        material.material_hash = hash_val

    def cell_normalized(self, material: Material, std_atoms: Atoms) -> None:
        cell_normalized = std_atoms.get_cell()
        cell_normalized *= 1e-10
        material.cell_normalized = cell_normalized

    def lattice_parameters(self, material: Material, std_atoms: Atoms, periodicity: np.array) -> None:
        # 1D systems only have one lattice parameter: length in periodic dimension
        periodic_indices = np.where(np.array(periodicity) == True)[0]  # noqa: E712
        cell = std_atoms.get_cell()
        a = np.linalg.norm(cell[periodic_indices[0], :]) * 1e-10
        material.lattice_parameters = np.array([a, 0.0, 0.0, 0.0, 0.0, 0.0])

    def periodicity(self, material: Material, prim_atoms: Atoms) -> None:
        # Get dimension of system by also taking into account the covalent radii
        dimensions = matid.geometry.get_dimensions(prim_atoms, [True, True, True])
        basis_dimensions = np.linalg.norm(prim_atoms.get_cell(), axis=1)
        gaps = basis_dimensions - dimensions
        periodicity = gaps <= config.normalize.cluster_threshold

        # If one axis is not periodic, return. This only happens if the vacuum
        # gap is not aligned with a cell vector.
        if sum(periodicity) != 1:
            raise ValueError("Could not detect the periodic dimensions in a 1D system.")

        material.periodicity = periodicity

    def get_structure_fingerprint(self, prim_atoms: Atoms) -> str:
        """Calculates a numeric fingerprint that coarsely encodes the atomic
        positions and species.

        The fingerprint is based on calculating a discretized version of a
        sorted Coulomb matrix eigenspectrum (Grégoire Montavon, Katja Hansen,
        Siamac Fazli, Matthias Rupp, Franziska Biegler, Andreas Ziehe,
        Alexandre Tkatchenko, Anatole V. Lilienfeld, and Klaus-Robert Müller.
        Learning invariant representations of molecules for atomization energy
        prediction. In F. Pereira, C. J. C. Burges, L. Bottou, and K. Q.
        Weinberger, editors, Advances in Neural Information Processing Systems
        25, pages 440–448. Curran Associates, Inc., 2012.).

        The fingerprints are discretized in order to perform O(n) matching
        between structures (no need to compare fingerprints against each
        other). As regular discretization is susceptible to the "edge problem",
        a robust discretization is used instead (Birget, Jean-Camille & Hong,
        Dawei & Memon, Nasir. (2003). Robust discretization, with an
        application to graphical passwords. IACR Cryptology ePrint Archive.
        2003. 168.) Basically for the 1-dimensional domain two grids are
        created and the points are mapped to the first grid in which they are
        robust using a minimum tolerance parameter r, with the maximum
        tolerance being 5r.

        There are other robust discretization methods that can guarantee exact
        r-tolerance (e.g. Sonia Chiasson, Jayakumar Srinivasan, Robert Biddle,
        and P. C. van Oorschot. 2008. Centered discretization with application
        to graphical passwords. In Proceedings of the 1st Conference on
        Usability, Psychology, and Security (UPSEC’08). USENIX Association,
        USA, Article 6, 1–9.). This method however requires that a predefined
        "correct" structure exists against which the search is done.

        Args:
            prim_atoms: Primitive system.

        Returns:
            The numeric fingerprint for the system encoded as a string.
        """
        # Calculate charge part
        q = prim_atoms.get_atomic_numbers()
        qiqj = np.sqrt(q[None, :] * q[:, None])

        # Calculate distance part. Notice that the minimum image convention
        # must be used. Without it, differently oriented atoms in the same cell
        # may be detected as the same material.
        pos = prim_atoms.get_positions()
        cell = prim_atoms.get_cell()
        cmat = 10 - matid.geometry.get_distance_matrix(pos, pos, cell, pbc=True, mic=True)
        cmat = np.clip(cmat, a_min=0, a_max=None)
        np.fill_diagonal(cmat, 0)
        cmat = qiqj * cmat

        # Calculate eigenvalues
        eigval, _ = np.linalg.eigh(cmat)

        # Sort eigenvalues
        eigval = np.array(sorted(eigval))

        # Perform robust discretization (see function docstring for details). r
        # = 0.5 ensures that all grids are integers which can be uniquely
        # mapped to strings. If finer grid is needed adjust the eigenvalue scale
        # instead.
        eigval /= 25  # Go to smaller scale where integer numbers are meaningful
        dimension = 1
        r = 0.5
        spacing = 2 * r * (dimension + 1)
        phi_k = 2 * r * np.array(range(dimension + 1))
        t = np.mod((eigval[None, :] + phi_k[:, None]), (2 * r * (dimension + 1)))
        grid_mask = (r <= t) & (t < r * (2 * dimension + 1))
        safe_grid_k = np.argmax(grid_mask == True, axis=0)   # noqa: E712
        discretization = spacing * np.floor((eigval + (2 * r * safe_grid_k)) / spacing)
        discretization[safe_grid_k == 1] += 2 * r

        # Form string
        strings = []
        for number in discretization:
            num_str = str(int(number))
            strings.append(num_str)
        fingerprint = ";".join(strings)

        return fingerprint

    def get_symmetry_analyzer(self, original_system: Atoms) -> SymmetryAnalyzer:
        """For 1D systems the symmetry is analyzed from the original system
        with enforced full periodicity.

        Args:
            original_system: The original simulation system.

        Returns:
            The SymmetryAnalyzer that is instantiated with the original system.
        """
        symm_system = original_system.copy()
        symm_system.set_pbc(True)
        symmetry_analyzer = SymmetryAnalyzer(
            symm_system,
            config.normalize.symmetry_tolerance,
            config.normalize.flat_dim_threshold
        )

        return symmetry_analyzer

    def get_std_atoms(self, periodicity: np.array, prim_atoms: Atoms) -> Atoms:
        """For 1D systems the standardized system is based on a primitive
        system. This primitive system is translated to the center of mass and
        the non-periodic dimensions are minimized so that the atoms just fit.

        Args:
            periodicity: List of periodic indices, in 1D case a list containing
                one index.
            prim_atoms: Primitive system

        Returns
            Standardized structure that represents this material and from which
            the material hash will be constructed from.
        """
        std_atoms = prim_atoms.copy()

        # Translate to center of mass
        pbc_cm = matid.geometry.get_center_of_mass(prim_atoms)
        cell_center = 0.5 * np.sum(std_atoms.get_cell(), axis=0)
        translation = cell_center - pbc_cm
        translation[periodicity] = 0
        std_atoms.translate(translation)
        std_atoms.wrap()

        # Reduce cell size to just fit the system in the non-periodic dimensions.
        pos = std_atoms.get_scaled_positions(wrap=False)
        cell = std_atoms.get_cell()
        new_cell = np.array(cell)
        translation = np.zeros(3)
        for index, periodic in enumerate(periodicity):
            if not periodic:
                imin = np.min(pos[:, index])
                imax = np.max(pos[:, index])
                translation -= cell[index, :] * imin
                new_cell[index] = cell[index, :] * (imax - imin)
        std_atoms.translate(translation)
        std_atoms.set_cell(new_cell)

        return std_atoms

    def normalize(self, ctx: Context) -> None:
        # Fetch resources
        sec_system = ctx.representative_system
        sec_enc = self.backend.get_mi2_section(Encyclopedia.m_def)
        material = sec_enc.material
        repr_atoms = sec_system.tmp["representative_atoms"]  # Temporary value stored by SystemNormalizer
        symmetry_analyzer = self.get_symmetry_analyzer(repr_atoms)
        prim_atoms = symmetry_analyzer.get_primitive_system()
        prim_atoms.set_pbc(True)
        names, counts = structure.get_hill_decomposition(prim_atoms.get_chemical_symbols(), reduced=False)
        greatest_common_divisor = reduce(gcd, counts)
        ctx.greatest_common_divisor = greatest_common_divisor
        reduced_counts = np.array(counts) / greatest_common_divisor