<gh_stars>100-1000
"""
Site featurizers requiring external libraries for core functionality.
"""
from monty.dev import requires
from pymatgen.io.ase import AseAtomsAdaptor
from sklearn.exceptions import NotFittedError
from pymatgen.core import Structure

from matminer.featurizers.base import BaseFeaturizer

# SOAPFeaturizer
try:
    import dscribe
    from dscribe.descriptors import SOAP as SOAP_dscribe
except ImportError:
    dscribe, SOAP_dscribe = None, None


class SOAP(BaseFeaturizer):
    """
    Smooth overlap of atomic positions (interface via DScribe).

    Class for generating a partial power spectrum from Smooth Overlap of Atomic
    Orbitals (SOAP). This implementation uses real (tesseral) spherical
    harmonics as the angular basis set and provides two orthonormalized
    alternatives for the radial basis functions: spherical primitive gaussian
    type orbitals ("gto") or the polynomial basis set ("polynomial"). By
    default the faster gto-basis is used. Please see the DScribe SOAP
    documentation for more details.

    Note that SOAP is only featurized for elements identified by "fit" (see
    following), thus "fit" must be called before "featurize", or else an error
    will be raised.

    Based originally on the following publications:

    "On representing chemical environments, <NAME>, <NAME>, and <NAME>, Phys. Rev. B 87, 184115, (2013),
        https://doi.org/10.1103/PhysRevB.87.184115

    "Comparing molecules and solids across structural and alchemical
        space", <NAME>, <NAME>, <NAME> and <NAME>,
        Phys.  Chem. Chem. Phys. 18, 13754 (2016),
        https://doi.org/10.1039/c6cp00415f

    Implementation (and some documentation) originally based on DScribe:
    https://github.com/SINGROUP/dscribe.

    "DScribe: Library of descriptors for machine learning in materials science",
        <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., <NAME>. and <NAME>.
        Computer Physics Communications, 106949 (2019),
        https://doi.org/10.1016/j.cpc.2019.106949

    Args:
        rcut (float): A cutoff for local region in angstroms. Should be
            bigger than 1 angstrom.
        nmax (int): The number of radial basis functions.
        lmax (int): The maximum degree of spherical harmonics.
        sigma (float): The standard deviation of the gaussians used to expand the
            atomic density.
        rbf (str): The radial basis functions to use. The available options are:

            * "gto": Spherical gaussian type orbitals defined as :math:`g_{nl}(r) = \sum_{n'=1}^{n_\mathrm{max}}\,\\beta_{nn'l} r^l e^{-\\alpha_{n'l}r^2}`
            * "polynomial": Polynomial basis defined as :math:`g_{n}(r) = \sum_{n'=1}^{n_\mathrm{max}}\,\\beta_{nn'} (r-r_\mathrm{cut})^{n'+2}`

        periodic (bool): Determines whether the system is considered to be
            periodic.
        crossover (bool): Determines if crossover of atomic types should
            be included in the power spectrum. If enabled, the power
            spectrum is calculated over all unique species combinations Z
            and Z'. If disabled, the power spectrum does not contain
            cross-species information and is only run over each unique
            species Z. Turned on by default to correspond to the original
            definition
    """

    @requires(
        dscribe,
        "SOAPFeaturizer requires DScribe. Install from github.com/SINGROUP/dscribe",
    )
    def __init__(
        self,
        rcut,
        nmax,
        lmax,
        sigma,
        periodic,
        rbf="gto",
        crossover=True,
    ):
        self.rcut = rcut
        self.nmax = nmax
        self.lmax = lmax
        self.sigma = sigma
        self.rbf = rbf
        self.periodic = periodic
        self.crossover = crossover
        self.adaptor = AseAtomsAdaptor()
        self.length = None
        self.atomic_numbers = None
        self.soap = None
        self.n_elements = None

    @classmethod
    def from_preset(cls, preset):
        """
        Create a SOAP featurizer object from sensible or published presets.
        Args:
            preset (str): Choose from:
                "formation energy": Preset used for formation energy prediction
                    in the original Dscribe paper.
        Returns:
        """
        valid_presets = ["formation_energy"]
        if preset == "formation_energy":
            return cls(6, 8, 8, 0.4, True, "gto", True)
        else:
            raise ValueError(f"'{preset}' is not a valid preset. Choose from {valid_presets}")

    def _check_fitted(self):
        if not self.soap:
            raise NotFittedError("Please fit SOAP before featurizing.")

    def fit(self, X, y=None):
        """
        Fit the SOAP featurizer to a dataframe.

        Args:
            X ([SiteCollection]): For example, a list of pymatgen Structures.
            y : unused (added for consistency with overridden method signature)

        Returns:
            self
        """
        # Check that pymatgen.Structures are provided
        if not all([isinstance(struct, Structure) for struct in X]):
            raise TypeError("This fit requires an array-like input of Pymatgen " "Structures and sites!")

        elements = set()
        for s in X:
            c = s.composition.elements
            for e in c:
                if e.Z not in elements:
                    elements.add(e.Z)
        self.elements_sorted = sorted(list(elements))

        self.atomic_numbers = elements
        self.soap = SOAP_dscribe(
            species=self.atomic_numbers,
            rcut=self.rcut,
            nmax=self.nmax,
            lmax=self.lmax,
            sigma=self.sigma,
            rbf=self.rbf,
            periodic=self.periodic,
            crossover=self.crossover,
            average="off",
            sparse=False,
        )

        self.length = self.soap.get_number_of_features()
        return self

    def featurize(self, struct, idx):
        self._check_fitted()
        s_ase = self.adaptor.get_atoms(struct)
        return self.soap.create(s_ase, positions=[idx], n_jobs=self.n_jobs).tolist()[0]

    def feature_labels(self):
        self._check_fitted()
        return [f"SOAP_{i}" for i in range(self.length)]

    def citations(self):
        return [
            "@article{PhysRevB.87.184115,"
            "title = {On representing chemical environments},"
            "author = {Bart'ok, <NAME>. and <NAME> and Cs'anyi, "
            "G'abor},"
            "journal = {Phys. Rev. B},"
            "volume = {87},"
            "issue = {18},"
            "pages = {184115},"
            "numpages = {16},"
            "year = {2013},"
            "month = {May},"
            "publisher = {American Physical Society},"
            "doi = {10.1103/PhysRevB.87.184115},"
            "url = {https://link.aps.org/doi/10.1103/PhysRevB.87.184115}}",
            "@Article{C6CP00415F,"
            "author ={<NAME> BartÃ³k, <NAME>. and CsÃ¡nyi, GÃ¡bor"
            " and Ceriotti, Michele},"
            "title  ={Comparing molecules and solids across structural and "
            "alchemical space},"
            "journal = {Phys. Chem. Chem. Phys.},"
            "year = {2016},"
            "volume = {18},"
            "issue = {20},"
            "pages = {13754-13769},"
            "publisher = {The Royal Society of Chemistry},"
            "doi = {10.1039/C6CP00415F},"
            "url = {http://dx.doi.org/10.1039/C6CP00415F},}",
            "@article{dscribe, "
            'author = {<NAME> and J{"a}ger, <NAME>. and '
            "Morooka, <NAME>. and <NAME>, Filippo and Ranawat, "
            "<NAME>. and Gao, <NAME>. and Rinke, Patrick and Foster, "
            "<NAME>.}, "
            "title = {{DScribe: Library of descriptors for machine "
            "learning in materials science}}, "
            "journal = {Computer Physics Communications}, "
            "year = {2019}, pages = {106949}, "
            "doi = {https://doi.org/10.1016/j.cpc.2019.106949}}",
        ]

    def implementors(self):
        return ["<NAME> and the DScribe team", "<NAME>"]

"""
Site featurizers requiring external libraries for core functionality.
"""
from monty.dev import requires
from pymatgen.io.ase import AseAtomsAdaptor
from sklearn.exceptions import NotFittedError
from pymatgen.core import Structure

from matminer.featurizers.base import BaseFeaturizer

# SOAPFeaturizer
try:
    import dscribe
    from dscribe.descriptors import SOAP as SOAP_dscribe
except ImportError:
    dscribe, SOAP_dscribe = None, None


class SOAP(BaseFeaturizer):
    """
    Smooth overlap of atomic positions (interface via DScribe).

    Class for generating a partial power spectrum from Smooth Overlap of Atomic
    Orbitals (SOAP). This implementation uses real (tesseral) spherical
    harmonics as the angular basis set and provides two orthonormalized
    alternatives for the radial basis functions: spherical primitive gaussian
    type orbitals ("gto") or the polynomial basis set ("polynomial"). By
    default the faster gto-basis is used. Please see the DScribe SOAP
    documentation for more details.

    Note that SOAP is only featurized for elements identified by "fit" (see
    following), thus "fit" must be called before "featurize", or else an error
    will be raised.

    Based originally on the following publications:

    "On representing chemical environments, <NAME>, <NAME>, and <NAME>, Phys. Rev. B 87, 184115, (2013),
        https://doi.org/10.1103/PhysRevB.87.184115

    "Comparing molecules and solids across structural and alchemical
        space", <NAME>, <NAME>, <NAME> and <NAME>,
        Phys.  Chem. Chem. Phys. 18, 13754 (2016),
        https://doi.org/10.1039/c6cp00415f

    Implementation (and some documentation) originally based on DScribe:
    https://github.com/SINGROUP/dscribe.

    "DScribe: Library of descriptors for machine learning in materials science",
        <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., <NAME>. and <NAME>.
        Computer Physics Communications, 106949 (2019),
        https://doi.org/10.1016/j.cpc.2019.106949

    Args:
        rcut (float): A cutoff for local region in angstroms. Should be
            bigger than 1 angstrom.
        nmax (int): The number of radial basis functions.
        lmax (int): The maximum degree of spherical harmonics.
        sigma (float): The standard deviation of the gaussians used to expand the
            atomic density.
        rbf (str): The radial basis functions to use. The available options are:

            * "gto": Spherical gaussian type orbitals defined as :math:`g_{nl}(r) = \sum_{n'=1}^{n_\mathrm{max}}\,\\beta_{nn'l} r^l e^{-\\alpha_{n'l}r^2}`
            * "polynomial": Polynomial basis defined as :math:`g_{n}(r) = \sum_{n'=1}^{n_\mathrm{max}}\,\\beta_{nn'} (r-r_\mathrm{cut})^{n'+2}`

        periodic (bool): Determines whether the system is considered to be
            periodic.
        crossover (bool): Determines if crossover of atomic types should
            be included in the power spectrum. If enabled, the power
            spectrum is calculated over all unique species combinations Z
            and Z'. If disabled, the power spectrum does not contain
            cross-species information and is only run over each unique
            species Z. Turned on by default to correspond to the original
            definition
    """

    @requires(
        dscribe,
        "SOAPFeaturizer requires DScribe. Install from github.com/SINGROUP/dscribe",
    )
    def __init__(
        self,
        rcut,
        nmax,
        lmax,
        sigma,
        periodic,
        rbf="gto",
        crossover=True,
    ):
        self.rcut = rcut
        self.nmax = nmax
        self.lmax = lmax
        self.sigma = sigma
        self.rbf = rbf
        self.periodic = periodic
        self.crossover = crossover
        self.adaptor = AseAtomsAdaptor()
        self.length = None
        self.atomic_numbers = None
        self.soap = None
        self.n_elements = None

    @classmethod
    def from_preset(cls, preset):
        """
        Create a SOAP featurizer object from sensible or published presets.
        Args:
            preset (str): Choose from:
                "formation energy": Preset used for formation energy prediction
                    in the original Dscribe paper.
        Returns:
        """
        valid_presets = ["formation_energy"]
        if preset == "formation_energy":
            return cls(6, 8, 8, 0.4, True, "gto", True)
        else:
            raise ValueError(f"'{preset}' is not a valid preset. Choose from {valid_presets}")

    def _check_fitted(self):
        if not self.soap:
            raise NotFittedError("Please fit SOAP before featurizing.")

    def fit(self, X, y=None):
        """
        Fit the SOAP featurizer to a dataframe.

        Args:
            X ([SiteCollection]): For example, a list of pymatgen Structures.
            y : unused (added for consistency with overridden method signature)

        Returns:
            self
        """
        # Check that pymatgen.Structures are provided
        if not all([isinstance(struct, Structure) for struct in X]):
            raise TypeError("This fit requires an array-like input of Pymatgen " "Structures and sites!")

        elements = set()
        for s in X:
            c = s.composition.elements
            for e in c:
                if e.Z not in elements:
                    elements.add(e.Z)
        self.elements_sorted = sorted(list(elements))

        self.atomic_numbers = elements
        self.soap = SOAP_dscribe(
            species=self.atomic_numbers,
            rcut=self.rcut,
            nmax=self.nmax,
            lmax=self.lmax,
            sigma=self.sigma,
            rbf=self.rbf,
            periodic=self.periodic,
            crossover=self.crossover,
            average="off",
            sparse=False,
        )

        self.length = self.soap.get_number_of_features()
        return self

    def featurize(self, struct, idx):
        self._check_fitted()
        s_ase = self.adaptor.get_atoms(struct)
        return self.soap.create(s_ase, positions=[idx], n_jobs=self.n_jobs).tolist()[0]

    def feature_labels(self):
        self._check_fitted()
        return [f"SOAP_{i}" for i in range(self.length)]

    def citations(self):
        return [
            "@article{PhysRevB.87.184115,"
            "title = {On representing chemical environments},"
            "author = {Bart'ok, <NAME>. and <NAME> and Cs'anyi, "
            "G'abor},"
            "journal = {Phys. Rev. B},"
            "volume = {87},"
            "issue = {18},"
            "pages = {184115},"
            "numpages = {16},"
            "year = {2013},"
            "month = {May},"
            "publisher = {American Physical Society},"
            "doi = {10.1103/PhysRevB.87.184115},"
            "url = {https://link.aps.org/doi/10.1103/PhysRevB.87.184115}}",
            "@Article{C6CP00415F,"
            "author ={<NAME> BartÃ³k, <NAME>. and CsÃ¡nyi, GÃ¡bor"
            " and Ceriotti, Michele},"
            "title  ={Comparing molecules and solids across structural and "
            "alchemical space},"
            "journal = {Phys. Chem. Chem. Phys.},"
            "year = {2016},"
            "volume = {18},"
            "issue = {20},"
            "pages = {13754-13769},"
            "publisher = {The Royal Society of Chemistry},"
            "doi = {10.1039/C6CP00415F},"
            "url = {http://dx.doi.org/10.1039/C6CP00415F},}",
            "@article{dscribe, "
            'author = {<NAME> and J{"a}ger, <NAME>. and '
            "Morooka, <NAME>. and <NAME>, Filippo and Ranawat, "
            "<NAME>. and Gao, <NAME>. and Rinke, Patrick and Foster, "
            "<NAME>.}, "
            "title = {{DScribe: Library of descriptors for machine "
            "learning in materials science}}, "
            "journal = {Computer Physics Communications}, "
            "year = {2019}, pages = {106949}, "
            "doi = {https://doi.org/10.1016/j.cpc.2019.106949}}",
        ]

    def implementors(self):
        return ["<NAME> and the DScribe team", "<NAME>"]
Site featurizers requiring external libraries for core functionality. # SOAPFeaturizer Smooth overlap of atomic positions (interface via DScribe).      Class for generating a partial power spectrum from Smooth Overlap of Atomic     Orbitals (SOAP). This implementation uses real (tesseral) spherical     harmonics as the angular basis set and provides two orthonormalized     alternatives for the radial basis functions: spherical primitive gaussian     type orbitals ("gto") or the polynomial basis set ("polynomial"). By     default the faster gto-basis is used. Please see the DScribe SOAP     documentation for more details.      Note that SOAP is only featurized for elements identified by "fit" (see     following), thus "fit" must be called before "featurize", or else an error     will be raised.      Based originally on the following publications:      "On representing chemical environments, <NAME>, <NAME>, and <NAME>, Phys. Rev. B 87, 184115, (2013),         https://doi.org/10.1103/PhysRevB.87.184115      "Comparing molecules and solids across structural and alchemical         space", <NAME>, <NAME>, <NAME> and <NAME>,         Phys.  Chem. Chem. Phys. 18, 13754 (2016),         https://doi.org/10.1039/c6cp00415f      Implementation (and some documentation) originally based on DScribe:     https://github.com/SINGROUP/dscribe.      "DScribe: Library of descriptors for machine learning in materials science",         <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., <NAME>., <NAME>. and <NAME>.         Computer Physics Communications, 106949 (2019),         https://doi.org/10.1016/j.cpc.2019.106949      Args:         rcut (float): A cutoff for local region in angstroms. Should be             bigger than 1 angstrom.         nmax (int): The number of radial basis functions.         lmax (int): The maximum degree of spherical harmonics.         sigma (float): The standard deviation of the gaussians used to expand the             atomic density.         rbf (str): The radial basis functions to use. The available options are:              * "gto": Spherical gaussian type orbitals defined as :math:`g_{nl}(r) = \sum_{n'=1}^{n_\mathrm{max}}\,\\beta_{nn'l} r^l e^{-\\alpha_{n'l}r^2}`             * "polynomial": Polynomial basis defined as :math:`g_{n}(r) = \sum_{n'=1}^{n_\mathrm{max}}\,\\beta_{nn'} (r-r_\mathrm{cut})^{n'+2}`          periodic (bool): Determines whether the system is considered to be             periodic.         crossover (bool): Determines if crossover of atomic types should             be included in the power spectrum. If enabled, the power             spectrum is calculated over all unique species combinations Z             and Z'. If disabled, the power spectrum does not contain             cross-species information and is only run over each unique             species Z. Turned on by default to correspond to the original             definition Create a SOAP featurizer object from sensible or published presets.         Args:             preset (str): Choose from:                 "formation energy": Preset used for formation energy prediction                     in the original Dscribe paper.         Returns: Fit the SOAP featurizer to a dataframe.          Args:             X ([SiteCollection]): For example, a list of pymatgen Structures.             y : unused (added for consistency with overridden method signature)          Returns:             self # Check that pymatgen.Structures are provided