Descriptor

The descriptor module contains methods for describing the local atomic environment; that is, feature fectors that can be fed to machine-learning modules.

Gaussian

class amp.descriptor.gaussian.FingerprintCalculator(neighborlist, Gs, cutoff, fortran)[source]

Bases: object

For integration with .utilities.Data

Parameters:

  • neighborlist (list of str) – List of neighbors.

  • Gs (dict) –

    Dictionary of symbols and lists of dictionaries for making symmetry functions. Either auto-genetrated, or given in the following form, for example:

    >>> Gs = {"O": [{"type":"G2", "element":"O", "eta":10.,
...              "offset": 2.},
...             {"type":"G4", "elements":["O", "Au"],
...              "eta":5., "gamma":1., "zeta":1.0}],
...       "Au": [{"type":"G2", "element":"O", "eta":2.},
...              {"type":"G4", "elements":["O", "Au"],
...               "eta":2., "gamma":1., "zeta":5.0}]}

  • cutoff (float) – Radius above which neighbor interactions are ignored.

  • fortran (bool) – If True, will use fortran modules, if False, will not.

calculate(image, key)[source]

Makes a list of fingerprints, one per atom, for the fed image.

Parameters:

  • image (object) – ASE atoms object.

  • key (str) – key of the image after being hashed.

get_fingerprint(index, symbol, neighborsymbols, neighborpositions)[source]

Returns the fingerprint of symmetry function values for atom specified by its index and symbol.

neighborsymbols and neighborpositions are lists of neighbors’ symbols and Cartesian positions, respectively.

Parameters:

  • index (int) – Index of the center atom.

  • symbol (str) – Symbol of the center atom.

  • neighborsymbols (numpy.ndarray of str) – Array of neighbors’ symbols.

  • neighborpositions (numpy.ndarray of float) – Array of Cartesian atomic positions.

Returns:

symbol, fingerprint – fingerprints for atom specified by its index and symbol.

Return type:

list of float

class amp.descriptor.gaussian.FingerprintPrimeCalculator(neighborlist, Gs, cutoff, fortran)[source]

Bases: object

For integration with .utilities.Data

Parameters:

  • neighborlist (list of str) – List of neighbors.

  • Gs (dict) –

    Dictionary of symbols and lists of dictionaries for making symmetry functions. Either auto-genetrated, or given in the following form, for example:

    >>> Gs = {"O": [{"type":"G2", "element":"O", "eta":10.,
...              "offset": 2.},
...             {"type":"G4", "elements":["O", "Au"],
...              "eta":5., "gamma":1., "zeta":1.0}],
...       "Au": [{"type":"G2", "element":"O", "eta":2.},
...              {"type":"G4", "elements":["O", "Au"],
...               "eta":2., "gamma":1., "zeta":5.0}]}

  • cutoff (float) – Radius above which neighbor interactions are ignored.

  • fortran (bool) – If True, will use fortran modules, if False, will not.

calculate(image, key)[source]

Makes a list of fingerprint derivatives, one per atom, for the fed image.

Parameters:

  • image (object) – ASE atoms object.

  • key (str) – key of the image after being hashed.

get_fingerprintprime(index, symbol, neighborindices, neighborsymbols, neighborpositions, m, l)[source]

Returns the value of the derivative of G for atom with index and symbol with respect to coordinate x_{l} of atom index m.

neighborindices, neighborsymbols and neighborpositions are lists of neighbors’ indices, symbols and Cartesian positions, respectively.

Parameters:

  • index (int) – Index of the center atom.

  • symbol (str) – Symbol of the center atom.

  • neighborindices (list of int) – List of neighbors’ indices.

  • neighborsymbols (numpy.ndarray of str) – Array of neighbors’ symbols.

  • neighborpositions (numpy.ndarray of float) – Array of Cartesian atomic positions.

  • m (int) – Index of the pair atom.

  • l (int) – Direction of the derivative; is an integer from 0 to 2.

Returns:

fingerprintprime – The value of the derivative of the fingerprints for atom with index and symbol with respect to coordinate x_{l} of atom index m.

Return type:

list of float

class amp.descriptor.gaussian.Gaussian(cutoff=<Cosine cutoff with Rc=6.500 from amp.descriptor.cutoffs>, Gs=None, dblabel=None, elements=None, version=None, fortran=True, mode='atom-centered')[source]

Bases: object

Class that calculates Gaussian fingerprints (i.e., Behler-style).

Parameters:

  • cutoff (object or float) – Cutoff function, typically from amp.descriptor.cutoffs. Can be also fed as a float representing the radius above which neighbor interactions are ignored; in this case a cosine cutoff function will be employed. Default is a 6.5-Angstrom cosine cutoff.

  • Gs (dict or list) –

    Dictionary of symbols and lists of dictionaries for making symmetry functions. Either auto-genetrated, or given in the following form, for example:

    >>> Gs = {"O": [{"type":"G2", "element":"O", "eta":10.,
...              "offset": 2.},
...             {"type":"G4", "elements":["O", "Au"],
...              "eta":5., "gamma":1., "zeta":1.0}],
...       "Au": [{"type":"G2", "element":"O", "eta":2.},
...              {"type":"G4", "elements":["O", "Au"],
...               "eta":2., "gamma":1., "zeta":5.0}]}

    You can use amp.model.gaussian.make_symmetry_functions to help create these lists of dictionaries. If you supply a list instead of a dictionary, it will assume you want identical symmetry functions for each element.

  • dblabel (str, None, or False) – Prefix/location for fingerprint database files (neighborlists, fingerprints, fingerprint derivatives). If None, defaults to the parent Amp label. Set to False to disable all disk writes and keep fingerprints only in memory, discarding each image’s data as soon as it is used; recommended for inference and MD runs where images are never revisited. A shared string path can be supplied to let multiple calculator instances reuse the same on-disk cache.

  • elements (list) – List of allowed elements present in the system. If not provided, will be found automatically.

  • version (str) – Version of fingerprints.

  • fortran (bool) – If True, will use fortran modules (if compiled), if False, will not.

  • mode (str) – Can be either ‘atom-centered’ or ‘image-centered’.

Raises:

RuntimeError –

calculate_fingerprints(images, parallel=None, log=None, calculate_derivatives=False)[source]

Calculates the fingerpints of the images, for the ones not already done.

Parameters:

  • images (dict) – Dictionary of images; the key is a unique ID assigned to each image and each value is an ASE atoms object. Typically created from amp.utilities.hash_images.

  • parallel (dict) – Configuration for parallelization. Should be in same form as in amp.Amp.

  • log (Logger object) – Write function at which to log data. Note this must be a callable function.

  • calculate_derivatives (bool) – Decides whether or not fingerprintprimes should also be calculated.

tostring()[source]

Returns an evaluatable representation of the calculator that can be used to restart the calculator.

amp.descriptor.gaussian.Kronecker(i, j)[source]

Kronecker delta function.

Parameters:

  • i (int) – First index of Kronecker delta.

  • j (int) – Second index of Kronecker delta.

Returns:

The value of the Kronecker delta.

Return type:

int

class amp.descriptor.gaussian.NeighborlistCalculator(cutoff)[source]

Bases: object

For integration with .utilities.Data

For each image fed to calculate, a list of neighbors with offset distances is returned.

Parameters:

cutoff (float) – Radius above which neighbor interactions are ignored.

calculate(image, key)[source]

For integration with .utilities.Data

For each image fed to calculate, a list of neighbors with offset distances is returned.

Parameters:

  • image (object) – ASE atoms object.

  • key (str) – key of the image after being hashed.

amp.descriptor.gaussian.calculate_G2(neighbornumbers, neighborsymbols, neighborpositions, G_element, eta, offset, cutoff, Ri, fortran)[source]

Calculate G2 symmetry function.

Ideally this will not be used but will be a template for how to build the fortran version (and serves as a slow backup if the fortran one goes uncompiled). See Eq. 13a of the supplementary information of Khorshidi, Peterson, CPC(2016).

Parameters:

  • neighbornumbers (list of int) – List of neighbors’ chemical numbers.

  • neighborsymbols (numpy.ndarray of str) – Array of neighbors’ symbols.

  • neighborpositions (numpy.ndarray of float) – Array of Cartesian atomic positions.

  • G_element (str) – Chemical symbol of the center atom.

  • eta (float) – Parameter of Gaussian symmetry functions.

  • offset (float) – offset values for gaussians in G2 fingerprints

  • cutoff (dict) – Cutoff function, typically from amp.descriptor.cutoffs. Should be also formatted as a dictionary by todict method, e.g. cutoff=Cosine(6.5).todict()

  • Ri (list) – Position of the center atom. Should be fed as a list of three floats.

  • fortran (bool) – If True, will use the fortran subroutines, else will not.

Returns:

ridge – G2 fingerprint.

Return type:

float

amp.descriptor.gaussian.calculate_G2_prime(neighborindices, neighbornumbers, neighborsymbols, neighborpositions, G_element, eta, offset, cutoff, i, Ri, m, l, fortran)[source]

Calculates coordinate derivative of G2 symmetry function for atom at index i and position Ri with respect to coordinate x_{l} of atom index m.

See Eq. 13b of the supplementary information of Khorshidi, Peterson, CPC(2016).

Parameters:

  • neighborindices (list of int) – List of int of neighboring atoms.

  • neighbornumbers (list of int) – List of neighbors’ chemical numbers.

  • neighborsymbols (numpy.ndarray of str) – Array of neighbors’ symbols.

  • neighborpositions (numpy.ndarray of float) – Array of Cartesian atomic positions.

  • G_element (dict) – Symmetry functions of the center atom.

  • eta (float) – Parameter of Behler symmetry functions.

  • offset (float) – Offset for gaussians in G2 fingerprints

  • cutoff (dict) – Cutoff function, typically from amp.descriptor.cutoffs. Should be also formatted as a dictionary by todict method, e.g. cutoff=Cosine(6.5).todict()

  • i (int) – Index of the center atom.

  • Ri (list) – Position of the center atom. Should be fed as a list of three floats.

  • m (int) – Index of the atom force is acting on.

  • l (int) – Direction of force.

  • fortran (bool) – If True, will use the fortran subroutines, else will not.

Returns:

ridge – Coordinate derivative of G2 symmetry function for atom at index a and position Ri with respect to coordinate x_{l} of atom index m.

Return type:

float

amp.descriptor.gaussian.calculate_G4(neighbornumbers, neighborsymbols, neighborpositions, G_elements, gamma, zeta, eta, cutoff, Ri, fortran)[source]

Calculate G4 symmetry function.

Ideally this will not be used but will be a template for how to build the fortran version (and serves as a slow backup if the fortran one goes uncompiled). See Eq. 13c of the supplementary information of Khorshidi, Peterson, CPC(2016).

Parameters:

  • neighbornumbers (list of int) – List of neighbors’ chemical numbers.

  • neighborsymbols (numpy.ndarray of str) – Array of neighbors’ symbols.

  • neighborpositions (numpy.ndarray of float) – Array of Cartesian atomic positions.

  • G_elements (list of str) – A list of two members, each member is the chemical species of one of the neighboring atoms forming the triangle with the center atom.

  • gamma (float) – Parameter of Gaussian symmetry functions.

  • zeta (float) – Parameter of Gaussian symmetry functions.

  • eta (float) – Parameter of Gaussian symmetry functions.

  • cutoff (dict) – Cutoff function, typically from amp.descriptor.cutoffs. Should be also formatted as a dictionary by todict method, e.g. cutoff=Cosine(6.5).todict()

  • Ri (list) – Position of the center atom. Should be fed as a list of three floats.

  • fortran (bool) – If True, will use the fortran subroutines, else will not.

Returns:

ridge – G4 fingerprint.

Return type:

float

amp.descriptor.gaussian.calculate_G4_prime(neighborindices, neighbornumbers, neighborsymbols, neighborpositions, G_elements, gamma, zeta, eta, cutoff, i, Ri, m, l, fortran)[source]

Calculates coordinate derivative of G4 symmetry function for atom at index i and position Ri with respect to coordinate x_{l} of atom index m.

See Eq. 13d of the supplementary information of Khorshidi, Peterson, CPC(2016).

Parameters:

  • neighborindices (list of int) – List of int of neighboring atoms.

  • neighbornumbers (list of int) – List of neighbors’ chemical numbers.

  • neighborsymbols (numpy.ndarray of str) – Array of neighbors’ symbols.

  • neighborpositions (numpy.ndarray of float) – Array of Cartesian atomic positions.

  • G_elements (list of str) – A list of two members, each member is the chemical species of one of the neighboring atoms forming the triangle with the center atom.

  • gamma (float) – Parameter of Behler symmetry functions.

  • zeta (float) – Parameter of Behler symmetry functions.

  • eta (float) – Parameter of Behler symmetry functions.

  • cutoff (dict) – Cutoff function, typically from amp.descriptor.cutoffs. Should be also formatted as a dictionary by todict method, e.g. cutoff=Cosine(6.5).todict()

  • i (int) – Index of the center atom.

  • Ri (list) – Position of the center atom. Should be fed as a list of three floats.

  • m (int) – Index of the atom force is acting on.

  • l (int) – Direction of force.

  • fortran (bool) – If True, will use the fortran subroutines, else will not.

Returns:

ridge – Coordinate derivative of G4 symmetry function for atom at index i and position Ri with respect to coordinate x_{l} of atom index m.

Return type:

float

amp.descriptor.gaussian.calculate_G5(neighbornumbers, neighborsymbols, neighborpositions, G_elements, gamma, zeta, eta, cutoff, Ri, fortran)[source]

Calculate G5 symmetry function.

Ideally this will not be used but will be a template for how to build the fortran version (and serves as a slow backup if the fortran one goes uncompiled). In G5, the Gaussians and cutoff functions with respect to R_ijk are omitted. This symmetry function is more useful for larger atomic separations, and useful for angular configurations in which R_jk is larger than Rc but still inside the cutoff radius e.g. triplets of 180 degrees.

For more information see: J. Behler, Int. J. Quantum Chem. 115, 1032 (2015).

Parameters:

  • neighbornumbers (list of int) – List of neighbors’ chemical numbers.

  • neighborsymbols (numpy.ndarray of str) – Array of neighbors’ symbols.

  • neighborpositions (numpy.ndarray of float) – Array of Cartesian atomic positions.

  • G_elements (list of str) – A list of two members, each member is the chemical species of one of the neighboring atoms forming the triangle with the center atom.

  • gamma (float) – Parameter of Gaussian symmetry functions.

  • zeta (float) – Parameter of Gaussian symmetry functions.

  • eta (float) – Parameter of Gaussian symmetry functions.

  • cutoff (dict) – Cutoff function, typically from amp.descriptor.cutoffs. Should be also formatted as a dictionary by todict method, e.g. cutoff=Cosine(6.5).todict()

  • Ri (list) – Position of the center atom. Should be fed as a list of three floats.

  • fortran (bool) – If True, will use the fortran subroutines, else will not.

Returns:

ridge – G5 fingerprint.

Return type:

float

amp.descriptor.gaussian.calculate_G5_prime(neighborindices, neighbornumbers, neighborsymbols, neighborpositions, G_elements, gamma, zeta, eta, cutoff, i, Ri, m, l, fortran)[source]

Calculates coordinate derivative of G5 symmetry function for atom at index i and position Ri with respect to coordinate x_{l} of atom index m.

See Eq. 13d of the supplementary information of Khorshidi, Peterson, CPC(2016).

Parameters:

  • neighborindices (list of int) – List of int of neighboring atoms.

  • neighborsymbols (numpy.ndarray of str) – Array of neighbors’ symbols.

  • neighborpositions (numpy.ndarray of float) – Array of Cartesian atomic positions.

  • G_elements (list of str) – A list of two members, each member is the chemical species of one of the neighboring atoms forming the triangle with the center atom.

  • gamma (float) – Parameter of Behler symmetry functions.

  • zeta (float) – Parameter of Behler symmetry functions.

  • eta (float) – Parameter of Behler symmetry functions.

  • cutoff (dict) – Cutoff function, typically from amp.descriptor.cutoffs. Should be also formatted as a dictionary by todict method, e.g. cutoff=Cosine(6.5).todict()

  • i (int) – Index of the center atom.

  • Ri (list) – Position of the center atom. Should be fed as a list of three floats.

  • m (int) – Index of the atom force is acting on.

  • l (int) – Direction of force.

  • fortran (bool) – If True, will use the fortran subroutines, else will not.

Returns:

ridge – Coordinate derivative of G5 symmetry function for atom at index i and position Ri with respect to coordinate x_{l} of atom index m.

Return type:

float

amp.descriptor.gaussian.dCos_theta_ijk_dR_ml(i, j, k, Ri, Rj, Rk, m, l)[source]

Returns the derivative of Cos(theta_{ijk}) with respect to x_{l} of atomic index m.

See Eq. 14f of the supplementary information of Khorshidi, Peterson, CPC(2016).

Parameters:

  • i (int) – Index of the center atom.

  • j (int) – Index of the first atom.

  • k (int) – Index of the second atom.

  • Ri (float) – Position of the center atom.

  • Rj (float) – Position of the first atom.

  • Rk (float) – Position of the second atom.

  • m (int) – Index of the atom force is acting on.

  • l (int) – Direction of force.

Returns:

dCos_theta_ijk_dR_ml – Derivative of Cos(theta_{ijk}) with respect to x_{l} of atomic index m.

Return type:

float

amp.descriptor.gaussian.dRij_dRml(i, j, Ri, Rj, m, l)[source]

Returns the derivative of the norm of position vector R_{ij} with respect to coordinate x_{l} of atomic index m.

See Eq. 14c of the supplementary information of Khorshidi, Peterson, CPC(2016).

Parameters:

  • i (int) – Index of the first atom.

  • j (int) – Index of the second atom.

  • Ri (float) – Position of the first atom.

  • Rj (float) – Position of the second atom.

  • m (int) – Index of the atom force is acting on.

  • l (int) – Direction of force.

Returns:

dRij_dRml – The derivative of the noRi of position vector R_{ij} with respect to x_{l} of atomic index m.

Return type:

list of float

amp.descriptor.gaussian.dRij_dRml_vector(i, j, m, l)[source]

Returns the derivative of the position vector R_{ij} with respect to x_{l} of itomic index m.

See Eq. 14d of the supplementary information of Khorshidi, Peterson, CPC(2016).

Parameters:

  • i (int) – Index of the first atom.

  • j (int) – Index of the second atom.

  • m (int) – Index of the atom force is acting on.

  • l (int) – Direction of force.

Returns:

The derivative of the position vector R_{ij} with respect to x_{l} of atomic index m.

Return type:

list of float

amp.descriptor.gaussian.make_default_symmetry_functions(elements)[source]

Makes default set of G2 and G4 symmetry functions.

Parameters:

elements (list of str) – List of the elements, as in: [“C”, “O”, “H”, “Cu”].

Returns:

G – The generated symmetry function parameters.

Return type:

dict of lists

amp.descriptor.gaussian.make_symmetry_functions(elements, type, etas, offsets=None, zetas=None, gammas=None)[source]

Helper function to create Gaussian symmetry functions. Returns a list of dictionaries with symmetry function parameters in the format expected by the Gaussian class.

Parameters:

  • elements (list of str) – List of element types to be observed in this fingerprint.

  • type (str) – Either G2, G4, or G5.

  • etas (list of floats) – eta values to use in G2, G4 or G5 fingerprints

  • offsets (list of floats) – offset values to use in G2 fingerprints

  • zetas (list of floats) – zeta values to use in G4, and G5 fingerprints

  • gammas (list of floats) – gamma values to use in G4, and G5 fingerprints

Returns:

G – A list, each item in the list contains a dictionary of fingerprint parameters.

Return type:

list of dicts

Zernike

class amp.descriptor.zernike.FingerprintCalculator(neighborlist, Gs, nmax, cutoff, fortran)[source]

Bases: object

For integration with .utilities.Data

calculate(image, key)[source]

Makes a list of fingerprints, one per atom, for the fed image.

Parameters:

  • image (object) – ASE atoms object.

  • key (str) – Key of the image after being hashed.

get_fingerprint(index, symbol, n_symbols, Rs)[source]

Returns the fingerprint of symmetry function values for atom specified by its index and symbol.

n_symbols and Rs are lists of neighbors’ symbols and Cartesian positions, respectively.

Parameters:

  • index (int) – Index of the center atom.

  • symbol (str) – Symbol of the center atom.

  • n_symbols (list of str) – List of neighbors’ symbols.

  • Rs (list of list of float) – List of Cartesian atomic positions of neighbors.

Returns:

symbols, fingerprints – Fingerprints for atom specified by its index and symbol.

Return type:

list of float

class amp.descriptor.zernike.FingerprintPrimeCalculator(neighborlist, Gs, nmax, cutoff, fortran)[source]

Bases: object

For integration with .utilities.Data

calculate(image, key)[source]

Makes a list of fingerprint derivatives, one per atom, for the fed image.

Parameters:

  • image (object) – ASE atoms object.

  • key (str) – Key of the image after being hashed.

get_fingerprintprime(index, symbol, n_indices, n_symbols, Rs, p, q)[source]

Returns the value of the derivative of G for atom with index and symbol with respect to coordinate x_{i} of atom index m. n_indices, n_symbols and Rs are lists of neighbors’ indices, symbols and Cartesian positions, respectively.

Parameters:

  • index (int) – Index of the center atom.

  • symbol (str) – Symbol of the center atom.

  • n_indices (list of int) – List of neighbors’ indices.

  • n_symbols (list of str) – List of neighbors’ symbols.

  • Rs (list of list of float) – List of Cartesian atomic positions.

  • p (int) – Index of the pair atom.

  • q (int) – Direction of the derivative; is an integer from 0 to 2.

Returns:

fingerprint_prime – The value of the derivative of the fingerprints for atom with index and symbol with respect to coordinate x_{i} of atom index m.

Return type:

list of float

amp.descriptor.zernike.Kronecker(i, j)[source]

Kronecker delta function.

iint

First index of Kronecker delta.

jint

Second index of Kronecker delta.

Returns:

Kronecker delta

Return type:

int

class amp.descriptor.zernike.NeighborlistCalculator(cutoff)[source]

Bases: object

For integration with .utilities.Data

For each image fed to calculate, a list of neighbors with offset distances is returned.

Parameters:

cutoff (object or float) – Cutoff function, typically from amp.descriptor.cutoffs. Can be also fed as a float representing the radius above which neighbor interactions are ignored; in this case a cosine cutoff function will be employed. Default is a 6.5-Angstrom cosine cutoff.

calculate(image, key)[source]

For integration with .utilities.Data For each image fed to calculate, a list of neighbors with offset distances is returned.

Parameters:

  • image (object) – ASE atoms object.

  • key (str) – Key of the image after being hashed.

class amp.descriptor.zernike.Zernike(cutoff=<Cosine cutoff with Rc=6.500 from amp.descriptor.cutoffs>, Gs=None, nmax=5, dblabel=None, elements=None, version='2016.02', mode='atom-centered', fortran=True)[source]

Bases: object

Class that calculates Zernike fingerprints.

Parameters:

  • cutoff (object or float) – Cutoff function, typically from amp.descriptor.cutoffs. Can be also fed as a float representing the radius above which neighbor interactions are ignored; in this case a cosine cutoff function will be employed. Default is a 6.5-Angstrom cosine cutoff.

  • Gs (dict) –

    Dictionary containing coefficients of atomic density function. These are typically taken as the atomic numbers; this is what is used when auto-generated. Otherwise, they can be supplied in the following form, for example:

    >>> Gs = {"Au": {"Au": 3., "O": 2.}, "O": {"Au": 5., "O": 10.}}

    This is basically the same as eta in Eq. (16) of https://doi.org/10.1016/j.cpc.2016.05.010.

  • nmax (integer or dict) – Maximum degree of Zernike polynomials that will be included in the fingerprint vector. Can be different values for different species fed as a dictionary with chemical elements as keys. The length of the fingerprint vector is quadratically proportional to nmax: If nmax is even, then the length of fingerprint vector is nmax + (nmax / 2)^2 + 1. If nmax is odd, then the length of fingerprint vector is nmax + (nmax^2 - 1) / 4 + 1, regardless of how many chemical species exist.

  • dblabel (str, None, or False) – Prefix/location for fingerprint database files (neighborlists, fingerprints, fingerprint derivatives). If None, defaults to the parent Amp label. Set to False to disable all disk writes and keep fingerprints only in memory, discarding each image’s data as soon as it is used; recommended for inference and MD runs where images are never revisited. A shared string path can be supplied to let multiple calculator instances reuse the same on-disk cache.

  • elements (list) – List of allowed elements present in the system. If not provided, will be found automatically.

  • version (str) – Version of fingerprints.

  • mode (str) – Can be either ‘atom-centered’ or ‘image-centered’.

  • fortran (bool) – If True, will use fortran modules, if False, will not.

Raises:

RuntimeError, TypeError –

calculate_fingerprints(images, parallel=None, log=None, calculate_derivatives=False)[source]

Calculates the fingerpints of the images, for the ones not already done.

Parameters:

  • images (list or str) – List of ASE atoms objects with positions, symbols, energies, and forces in ASE format. This is the training set of data. This can also be the path to an ASE trajectory (.traj) or database (.db) file. Energies can be obtained from any reference, e.g. DFT calculations.

  • parallel (dict) – Configuration for parallelization. Should be in same form as in amp.Amp.

  • log (Logger object) – Write function at which to log data. Note this must be a callable function.

  • calculate_derivatives (bool) – Decides whether or not fingerprintprimes should also be calculated.

tostring()[source]

Returns an evaluatable representation of the calculator that can be used to restart the calculator.

amp.descriptor.zernike.binomial(n, k, factorial)[source]

Returns C(n,k) = n!/(k!(n-k)!).

amp.descriptor.zernike.calculate_R(n, l, rho, factorial)[source]

Calculates R_{n}^{l}(rho) according to the last equation of wikipedia.

amp.descriptor.zernike.calculate_Z(n, l, m, x, y, z, factorial)[source]

Calculates Z_{nl}^{m}(x, y, z) according to the unnumbered equation afer Eq. (11) of “3D Zernike Descriptors for Content Based Shape Retrieval”, Computer-Aided Design 36 (2004) 1047-1062.

amp.descriptor.zernike.calculate_Z_prime(n, l, m, x, y, z, p, factorial)[source]

Calculates dZ_{nl}^{m}(x, y, z)/dR_{p} according to the unnumbered equation afer Eq. (11) of “3D Zernike Descriptors for Content Based Shape Retrieval”, Computer-Aided Design 36 (2004) 1047-1062.

amp.descriptor.zernike.calculate_q(nu, k, l, factorial)[source]

Calculates q_{kl}^{nu} according to the unnumbered equation afer Eq. (7) of “3D Zernike Descriptors for Content Based Shape Retrieval”, Computer-Aided Design 36 (2004) 1047-1062.

amp.descriptor.zernike.der_position(m, n, Rm, Rn, l, i)[source]

Returns the derivative of the norm of position vector R_{mn} with respect to x_{i} of atomic index l.

Parameters:

  • m (int) – Index of the first atom.

  • n (int) – Index of the second atom.

  • Rm (float) – Position of the first atom.

  • Rn (float) – Position of the second atom.

  • l (int) – Index of the atom force is acting on.

  • i (int) – Direction of force.

Returns:

der_position – The derivative of the norm of position vector R_{mn} with respect to x_{i} of atomic index l.

Return type:

list of float

amp.descriptor.zernike.generate_coefficients(elements)[source]

Automatically generates coefficients if not given by the user.

Parameters:

elements (list of str) – List of symbols of all atoms.

Returns:

G

Return type:

dict of dicts

Bispectrum

class amp.descriptor.bispectrum.Bispectrum(cutoff=<Cosine cutoff with Rc=6.500 from amp.descriptor.cutoffs>, Gs=None, jmax=5, dblabel=None, elements=None, version='2016.02', mode='atom-centered')[source]

Bases: object

Class that calculates spherical harmonic bispectrum fingerprints.

Parameters:

  • cutoff (object or float) – Cutoff function, typically from amp.descriptor.cutoffs. Can be also fed as a float representing the radius above which neighbor interactions are ignored; in this case a cosine cutoff function will be employed. Default is a 6.5-Angstrom cosine cutoff.

  • Gs (dict) –

    Dictionary of symbols and dictionaries for making fingerprints. Either auto-genetrated, or given in the following form, for example:

    >>> Gs = {"Au": {"Au": 3., "O": 2.}, "O": {"Au": 5., "O": 10.}}

  • jmax (integer or half-integer or dict) – Maximum degree of spherical harmonics that will be included in the fingerprint vector. Can be also fed as a dictionary with chemical species as keys.

  • dblabel (str, None, or False) – Prefix/location for fingerprint database files (neighborlists, fingerprints, fingerprint derivatives). If None, defaults to the parent Amp label. Set to False to disable all disk writes and keep fingerprints only in memory, discarding each image’s data as soon as it is used; recommended for inference and MD runs where images are never revisited. A shared string path can be supplied to let multiple calculator instances reuse the same on-disk cache.

  • elements (list) – List of allowed elements present in the system. If not provided, will be found automatically.

  • version (str) – Version of fingerprints.

  • Raises

  • ------- – RuntimeError, TypeError

calculate_fingerprints(images, parallel=None, log=None, calculate_derivatives=False)[source]

Calculates the fingerpints of the images, for the ones not already done.

Parameters:

  • images (list or str) – List of ASE atoms objects with positions, symbols, energies, and forces in ASE format. This is the training set of data. This can also be the path to an ASE trajectory (.traj) or database (.db) file. Energies can be obtained from any reference, e.g. DFT calculations.

  • parallel (dict) – Configuration for parallelization. Should be in same form as in amp.Amp.

  • log (Logger object) – Write function at which to log data. Note this must be a callable function.

  • calculate_derivatives (bool) – Decides whether or not fingerprintprimes should also be calculated.

tostring()[source]

Returns an evaluatable representation of the calculator that can be used to restart the calculator.

amp.descriptor.bispectrum.CG(a, alpha, b, beta, c, gamma, factorial)[source]

Clebsch-Gordan coefficient C_{a alpha b beta}^{c gamma} is calculated acoording to the expression given in Varshalovich Eq. (3), Section 8.2, Page 238.

class amp.descriptor.bispectrum.FingerprintCalculator(neighborlist, Gs, jmax, cutoff)[source]

Bases: object

For integration with .utilities.Data

calculate(image, key)[source]

Makes a list of fingerprints, one per atom, for the fed image.

Parameters:

  • image (object) – ASE atoms object.

  • key (str) – key of the image after being hashed.

get_fingerprint(index, symbol, n_symbols, Rs)[source]

Returns the fingerprint of symmetry function values for atom specified by its index and symbol.

n_symbols and Rs are lists of neighbors’ symbols and Cartesian positions, respectively.

Parameters:

  • index (int) – Index of the center atom.

  • symbol (str) – Symbol of the center atom.

  • n_symbols (list of str) – List of neighbors’ symbols.

  • Rs (list of list of float) – List of Cartesian atomic positions of neighbors.

Returns:

symbols, fingerprints – fingerprints for atom specified by its index and symbol.

Return type:

list of float

class amp.descriptor.bispectrum.NeighborlistCalculator(cutoff)[source]

Bases: object

For integration with .utilities.Data

For each image fed to calculate, a list of neighbors with offset distances is returned.

calculate(image, key)[source]
amp.descriptor.bispectrum.U(j, m, mp, omega, theta, phi, factorial)[source]

Calculates rotation matrix U_{MM’}^{J} in terms of rotation angle omega as well as rotation axis angles theta and phi, according to Varshalovich, Eq. (3), Section 4.5, Page 81. j, m, mp, and mpp here are J, M, M’, and M’’ in Eq. (3).

amp.descriptor.bispectrum.WignerD(j, m, mp, alpha, beta, gamma, factorial)[source]

Returns the Wigner-D matrix. alpha, beta, and gamma are the Euler angles.

amp.descriptor.bispectrum.binomial(n, k, factorial)[source]

Returns C(n,k) = n!/(k!(n-k)!).

amp.descriptor.bispectrum.calculate_B(j1, j2, j, G_element, cutoff, cutofffn, factorial, n_symbols, rs, psis, thetas, phis)[source]

Calculates bi-spectrum B_{j1, j2, j} according to Eq. (5) of “Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons”, Phys. Rev. Lett. 104, 136403.

amp.descriptor.bispectrum.calculate_c(j, mp, m, G_element, cutoff, cutofffn, factorial, n_symbols, rs, psis, thetas, phis)[source]

Calculates c^{j}_{m’m} according to Eq. (4) of “Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons”, Phys. Rev. Lett. 104, 136403

amp.descriptor.bispectrum.generate_coefficients(elements)[source]

Automatically generates coefficients if not given by the user.

Parameters:

elements (list of str) – List of symbols of all atoms.

Returns:

G

Return type:

dict of dicts

amp.descriptor.bispectrum.m_values(j)[source]

Returns a list of m values for a given j.

Cutoff functions

This script contains different cutoff function forms.

Note all cutoff functions need to have a “todict” method to support saving/loading as an Amp object.

All cutoff functions also need to have an Rc attribute which is the maximum distance at which properties are calculated; this will be used in calculating neighborlists.

class amp.descriptor.cutoffs.Cosine(Rc)[source]

Bases: object

Cosine functional form suggested by Behler.

Parameters:

Rc (float) – Radius above which neighbor interactions are ignored.

prime(Rij)[source]

Derivative (dfc_dRij) of the Cosine cutoff function with respect to Rij.

Parameters:

Rij (float) – Distance between pair atoms.

Returns:

The value of derivative of the cutoff function.

Return type:

float

todict()[source]
class amp.descriptor.cutoffs.Polynomial(Rc, gamma=4)[source]

Bases: object

Polynomial functional form suggested by Khorshidi and Peterson.

Parameters:

  • gamma (float) – The power of polynomial.

  • Rc (float) – Radius above which neighbor interactions are ignored.

prime(Rij)[source]

Derivative (dfc_dRij) of the Polynomial cutoff function with respect to Rij.

Parameters:

Rij (float) – Distance between pair atoms.

Returns:

The value of derivative of the cutoff function.

Return type:

float

todict()[source]
amp.descriptor.cutoffs.dict2cutoff(dct)[source]

This function converts a dictionary (which was created with the to_dict method of one of the cutoff classes) into an instantiated version of the class. Modeled after ASE’s dict2constraint function.

Example

(This contains just a minimal example of how to build your own descriptor.)

class amp.descriptor.example.AtomCenteredExample(cutoff=<Cosine cutoff with Rc=6.500 from amp.descriptor.cutoffs>, anotherparameter=12.2, dblabel=None, elements=None, version=None, mode='atom-centered')[source]

Bases: object

Class that calculates fingerprints.

This is an example class that doesn’t do much; it just shows the code structure. If making your own module, you can copy and modify this one.

Parameters:

  • cutoff (object or float) – Cutoff function. Can be also fed as a float representing the radius above which neighbor interactions are ignored. Default is 6.5 Angstroms.

  • anotherparameter (float) – Just an example.

  • dblabel (str) – Optional separate prefix/location for database files, including fingerprints, fingerprint derivatives, and neighborlists. This file location can be shared between calculator instances to avoid re-calculating redundant information. If not supplied, just uses the value from label.

  • elements (list) – List of allowed elements present in the system. If not provided, will be found automatically.

  • version (str) – Version of fingerprints.

Raises:

RuntimeError, TypeError –

calculate_fingerprints(images, parallel=None, log=None, calculate_derivatives=False)[source]

Calculates the fingerpints of the images, for the ones not already done.

Parameters:

  • images (list or str) – List of ASE atoms objects with positions, symbols, energies, and forces in ASE format. This is the training set of data. This can also be the path to an ASE trajectory (.traj) or database (.db) file. Energies can be obtained from any reference, e.g. DFT calculations.

  • parallel (dict) – Configuration for parallelization. Should be in same form as in amp.Amp.

  • log (Logger object) – Write function at which to log data. Note this must be a callable function.

  • calculate_derivatives (bool) – Decides whether or not fingerprintprimes should also be calculated.

tostring()[source]

Returns an evaluatable representation of the calculator that can be used to restart the calculator.

class amp.descriptor.example.FingerprintCalculator(neighborlist, anotherparamter, cutoff, cutofffn)[source]

Bases: object

For integration with .utilities.Data

calculate(image, key)[source]

Makes a list of fingerprints, one per atom, for the fed image.

get_fingerprint(index, symbol, n_symbols, Rs)[source]

Returns the fingerprint of symmetry function values for atom specified by its index and symbol.

n_symbols and Rs are lists of neighbors’ symbols and Cartesian positions, respectively.

This function doesn’t actually do anything but sleep and return a vector of ones.

Parameters:

  • index (int) – index: Index of the center atom.

  • symbol (str) – Symbol of the center atom.

  • n_symbols (list of str) – List of neighbors’ symbols.

  • Rs (list of list of float) – List of Cartesian atomic positions.

Returns:

symbols, fingerprints – Fingerprints for atom specified by its index and symbol.

Return type:

list of float

class amp.descriptor.example.NeighborlistCalculator(cutoff)[source]

Bases: object

For integration with .utilities.Data

For each image fed to calculate, a list of neighbors with offset distances is returned.

Parameters:

cutoff (float) – Radius above which neighbor interactions are ignored.

calculate(image, key)[source]

For integration with .utilities.Data

For each image fed to calculate, a list of neighbors with offset distances is returned.

Parameters:

  • image (object) – ASE atoms object.

  • key (str) – key of the image after being hashed.