Core components

The low-level functions and classes described here are part of the hiPhive core components and not intended to be used directly during normal operation.

config

class hiphive.core.config.config

class eigensymmetries

crystal_symmetries = True

class iterative

method = 'symbolic'

simplify = True

simplify_tolerance = None

zero_tolerance = 1e-12

method = 'iterative'

rotation_integer_tolerance = 1e-12

hiphive.core.config.constraint_vectors_compress_mode = 'symbolic'

True, False

hiphive.core.config.constraint_vectors_simplify_before_compress = True

‘symbolic’, ‘numeric’, None

hiphive.core.config.constraint_vectors_simplify_before_solve = True

‘symbolic’, ‘numeric’

hiphive.core.config.eigentensor_compress_before_solve = None

This might make the nullspace() more stable True, False

hiphive.core.config.eigentensor_compress_mode = None

If this is True, before every symbolic compression the values will be simplified by sympy, potentially turning them into exact rational or irrational numbers. This can be useful for systems with non-integer rotation matrices in cartesian coordinates e.g. hcp. The main purpose is to make the rref more stable against repeating rounding errors. True, False

hiphive.core.config.eigentensor_simplify_before_compress = False

If non compress was used during construction but used before solving True, False

hiphive.core.config.eigentensor_simplify_before_last_compress = False

If the compress_mode is None the constraint matrix might be compressed right before the nullspace() solver ‘numeric’, ‘symbolic’, None

hiphive.core.config.eigentensor_simplify_before_solve = True

‘symbolic’, ‘numeric’

hiphive.core.config.eigentensor_solve_mode = 'symbolic'

‘symbolic’, ‘numeric’

hiphive.core.config.integer_tolerance = 1e-12

For each symmetry, the constraint matrix can be reduced to square again. This can be done either by ‘symbolic’, ‘numeric’ or not at all (None). Default is None since the matrix is often small enough to fit in memory. ‘symbolic’, ‘numeric’, None

hiphive.core.config.sum_rule_constraint_mode = 'symbolic'

True, False

hiphive.core.config.sum_rule_constraint_simplify = True

True, False

cluster_space_builder

hiphive.core.cluster_space_builder.build_cluster_space(cluster_space, prototype_structure)

The permutation list is an indexed fast lookup table for permutation vectors.

clusters

hiphive.core.clusters.create_neighbor_matrices(atoms, cutoff)

hiphive.core.clusters.extend_cluster(cluster, order)

hiphive.core.clusters.generate_geometrical_clusters(atoms, n_prim, cutoff, order)

hiphive.core.clusters.get_clusters(atoms, cutoffs, nPrim, multiplicity=True, use_geometrical_order=False)

Generate a list of all clusters in the atoms object which includes the center atoms with positions within the cell metric. The cutoff determines up to which order and range clusters should be generated.

With multiplicity set to True clusters like [0,0] and [3,3,4 etc will be generated. This is useful when doing force constants but not so much for cluster expansions.

The geometrical order is the total number of different atoms in the cluster. [0,0,1] would have geometrical order 2 and [1,2,3,4] would have order 4. If the key word is True the cutoff criteria will be based on the geometrical order of the cluster. This is based on the observation that many body interactions decrease fast with cutoff but anharmonic interactions can be quite long ranged.

Parameters:

• atoms (ase.Atoms) – can be a general atoms object but must have pbc=False.

• cutoffs (dict) – the keys specify the order while the values specify the cutoff radii

• multiplicity (bool) – includes clusters where same atom appears more than once

• geometrical_order (bool) – specifies if the geometrical order should be used as cutoff_order, otherwise the normal order of the cluster is used

Returns:

a list of clusters where each entry is a tuple of indices, which refer to the atoms in the input supercell

Return type:

list(tuple(int))

orbits

Contains the Orbit class which hold onformation about equivalent clusters.

class hiphive.core.orbits.Orbit

This class serves as a container for storing data pertaining to an orbit.

orientation_families

orientation families of the orbit

Type:

list of OrientationFamily objs

eigensymmetries

each eigensymmetry corresponds to a pair where the first index is the symmetry and the second is the permutation

Type:

list of tuples

eigentensors

decomposition of the force constant into symmetry elements

Type:

list(numpy.ndarray)

property prototype_index

index of cluster that serves as prototype for this orbit

In the code the first symmetry is always the identity so the first orientation family should always correspond to the prototype

Type:

int

static read(f)

Load a ClusterSpace from file

Parameters:

f (string or file object) – name of input file (string) or stream to load from (file object)

write(f)

Write a Orbit instance to a file.

Parameters:

f (str or file object) – name of input file (str) or stream to write to (file object)

class hiphive.core.orbits.OrientationFamily(symmetry_index=None)

A container for storing information for a “family of orientations”.

An orbit contains many clusters. Some of the clusters can be tranlsated onto each other and other must first be rotated. A set of clusters in the orbit which can all be translated onto each other are oriented in the same way and belongs to the same orientation family. The family is haracterized by the symmetry (rotation) which relates it to the prototype structure of the orbit.

Since the clusters are generally stored sorted the permutation information must also be stored.

Parameters:

symmetry_index (int) – The index of the symmetry corresponding to spglibs symmetry

symmetry_index

The index of the symmetry corresponding to spglibs symmetry

Type:

int

cluster_indices

The indices of the clusters belonging to this family

Type:

list of ints

permutation_indices

The indices of the permutation vector

Type:

list of ints

static read(f)

Load a OrientationFamily object from a pickle file.

Parameters:

f (str or file object) – name of input file (str) or stream to load from (file object)

Return type:

OrientationFamily object

write(f)

Write the object to file.

Parameters:

f (str or file object) – name of input file (str) or stream to write to (file object)

hiphive.core.orbits.generate_translated_clusters(cluster, extended_atoms)

hiphive.core.orbits.get_geometrical_radius(positions)

Compute the geometrical size of a 3-dimensional point cloud. The geometrical size is defined as the average distance to the geometric center.

Parameters:

positions (list of 3-dimensional vectors) – positions of points in cloud

Returns:

geometric size of point cloud

Return type:

float

hiphive.core.orbits.get_maximum_distance(positions)

Compute the maximum distance between any two points in a 3-dimensional point cloud. This is equivalent to the “size” criterion used when imposing a certain (pair) cutoff criterion during construction of a set of clusters.

Parameters:

positions (list of 3-dimensional vectors) – positions of points in cloud

Returns:

maximum distance betwee any two points

Return type:

float

hiphive.core.orbits.get_orbits(cluster_list, atom_list, rotation_matrices, translation_vectors, permutations, prim, symprec)

Generate a list of the orbits for the clusters in a supercell configuration.

This method requires as input a list of the clusters in a supercell configuration as well as a set of symmetry operations (rotations and translations). From this information it will generate a list of the orbits, i.e. the set of symmetry inequivalent clusters each associated with its respective set of equivalent clusters.

Parameters:

• cluster_list (BiMap object) – a list of clusters

• atom_list (BiMap object) – a list of atoms in a supercell

• rotation_matrices (list of NumPy (3,3) arrays) – rotational symmetries to be imposed (e.g., from spglib)

• translation_vectors (list of NumPy (3) arrays) – translational symmetries to be imposed (e.g., from spglib)

• permutations (list of permutations) – lookup table for permutations

• prim (hiPhive Atoms object) – primitive structure

Returns:

orbits associated with the list of input clusters

Return type:

list of Orbits objs

hiphive.core.orbits.get_permutation_map(atoms, rotations, translations, basis, symprec)

hiphive.core.orbits.populate_orbit(orbit, permutations, clusters, cluster, permutation_map, extended_atoms, cluster_is_found)

hiphive.core.orbits.prepare_atoms(atom_list)

hiphive.core.orbits.prepare_clusters(cluster_list)

hiphive.core.orbits.prepare_permutations(permutations)

hiphive.core.orbits.prepare_rotations(rotation_matrices)

hiphive.core.orbits.prepare_translations(translation_vectors)

rotational_constraints

Functionality for enforcing rotational sum rules

hiphive.core.rotational_constraints.enforce_rotational_sum_rules(cs, parameters, sum_rules=None, alpha=1e-06, **ridge_kwargs)

Enforces rotational sum rules by projecting parameters.

Note

The interface to this function might change in future releases.

Parameters:

• cs (ClusterSpace) – the underlying cluster space

• parameters (ndarray) – parameters to be constrained

• sum_rules (Optional[List[str]]) – type of sum rules to enforce; possible values: ‘Huang’, ‘Born-Huang’

• alpha (float) – hyperparameter to the ridge regression algorithm; keyword argument passed to the optimizer; larger values specify stronger regularization, i.e., less correction but higher stability [default: 1e-6]

• ridge_kwargs (dict) – kwargs to be passed to sklearn Ridge

Returns:

constrained parameters

Return type:

numpy.ndarray

Examples

The rotational sum rules can be enforced to the parameters before constructing a force constant potential as illustrated by the following snippet:

cs = ClusterSpace(reference_structure, cutoffs)
sc = StructureContainer(cs)
# add structures to structure container
opt = Optimizer(sc.get_fit_data())
opt.train()
new_params = enforce_rotational_sum_rules(cs, opt.parameters,
    sum_rules=['Huang', 'Born-Huang'])
fcp = ForceConstantPotential(cs, new_params)

hiphive.core.rotational_constraints.get_rotational_constraint_matrix(cs, sum_rules=None)

translational_constraints

Functionality for enforcing translational sum rules

hiphive.core.translational_constraints.create_constraint_map(cs)

hiphive.core.translational_constraints.get_translational_constraint_matrix(cs)

atoms

Collection of functions and classes for handling information concerning atoms and structures, including the relationship between primitive cell and supercells that are derived thereof.

class hiphive.core.atoms.Atom(site, offset)

Unique representation of an atom in a lattice with a basis

Class for storing information about the position of an atom in a supercell relative to the origin of the underlying primitive cell. This class is used for handling the relationship between a primitive cell and supercells derived thereof.

Parameters:

• site (int) – site index

• offset (list(float) or numpy.ndarray) – must contain three elements, offset_x, offset_y, offset_z

property offset

translational offset of the supercell site relative to the origin of the primitive cell in units of primitive lattice vectors

Type:

list(int)

pos(basis, cell)

property site

index of corresponding site in the primitive basis

Type:

int

spos(basis)

static spos_to_atom(spos, basis, tol=None)

class hiphive.core.atoms.Atoms(symbols=None, positions=None, numbers=None, tags=None, momenta=None, masses=None, magmoms=None, charges=None, scaled_positions=None, cell=None, pbc=None, celldisp=None, constraint=None, calculator=None, info=None, velocities=None)

Minimally augmented version of the ASE Atoms class suitable for handling primitive cell information.

Saves and loads by pickle.

property basis

scaled coordinates of the sites in the primitive basis

Type:

numpy.ndarray

static read(f)

Load an hiPhive Atoms object from file.

Parameters:

f (str or file object) – name of input file (str) or stream to load from (file object)

Return type:

hiPhive Atoms object

write(f)

Writes the object to file.

Note: Only the cell, basis and numbers are stored!

Parameters:

f (str or file object) – name of input file (str) or stream to write to (file object)

hiphive.core.atoms.atom_to_spos(atom, basis)

Helper function for obtaining the position of a supercell atom in scaled coordinates.

Parameters:

• atom (hiPhive.Atom) – supercell atom

• basis (list(list(float)) or numpy.ndarray) – positions of sites in the primitive basis

Returns:

scaled coordinates of an atom in a supercell

Return type:

numpy.ndarray

hiphive.core.atoms.spos_to_atom(spos, basis, tol=0.0001)

Helper function for transforming a supercell position to the primitive basis.

Parameters:

• spos (list(list(float)) or numpy.ndarray) – scaled coordinates of an atom in a supercell

• basis (list(list(float)) or numpy.ndarray) – positions of sites in the primitive basis

• tol (float) – a general tolerance

Returns:

supercell atom

Return type:

hiphive.Atom

structures

class hiphive.core.structures.Atom(*args, **kwargs)

This class represents a crystal atom in a given structure

property number

property pos

class hiphive.core.structures.BaseAtom(site, offset)

This class represents an atom placed in an infinite crustal

astype(dtype)

Useful arguments: list, tuple, np.int64

property offset

property site

class hiphive.core.structures.Structure(atoms, symprec=1e-06)

This class essentially wraps the ase.Atoms class but is a bit more carefull about pbc and scaled coordinates. It also returns hiphive.Atom objects instead

atom_from_pos(pos, symprec=None)

property cell

property spos

class hiphive.core.structures.Supercell(supercell, prim, symprec)

This class tries to represent atoms in a supercell as positioned on the primitve lattice

index(site, offset)

wrap_atom(atom)

class hiphive.core.structures.SupercellAtom(*args, **kwargs)

Represents an atom in a supercell but site and offset given by an underlying primitve cell

property index

hiphive.core.structures.pos_to_site_offset(pos, cell, basis_spos, symprec)

helper to map pos -> spos -> site/offset

hiphive.core.structures.pos_to_spos(pos, cell)

Inverse of sps_to_pos

hiphive.core.structures.site_offset_to_pos(site, offset, cell, basis_spos)

helper to map site/offset -> spos -> pos

hiphive.core.structures.site_offset_to_spos(site, offset, basis_spos)

Returns the scaled position of an atom at specified site and offset relative to the basis in scaled coordinates

hiphive.core.structures.spos_to_pos(spos, cell)

Returns the Cartesian coordinate given the scaled coordinate and cell metric (cell vectors as rows)

hiphive.core.structures.spos_to_site_offset(spos, basis_spos, symprec)

Returns the site and offset of the atom at the specified scaled coordinate given the scaled positions of the basis atoms

structure_alignment

hiphive.core.structure_alignment.align_supercell(supercell, prim, symprec=None)

Rotate and translate a supercell configuration such that it is aligned with the target primitive cell.

Parameters:

• sc (ase.Atoms) – supercell configuration

• prim (ase.Atoms) – target primitive configuration

• symprec (float) – precision parameter forwarded to spglib

Returns:

aligned supercell configuration as well as rotation matrix (3x3 array) and translation vector (3x1 array) that relate the input to the aligned supercell configuration.

Return type:

tuple(ase.Atoms, numpy.ndarray, numpy.ndarray)

hiphive.core.structure_alignment.are_nonpaired_configurations_equal(atoms1, atoms2)

Checks whether two configurations are identical. To be considered equal the structures must have the same cell metric, elemental occupation, scaled positions (modulo one), and periodic boundary conditions.

Unlike the __eq__ operator of ase.Atoms the order of the atoms does not matter.

Parameters:

• atoms1 (ase.Atoms)

• atoms2 (ase.Atoms)

Returns:

• bool – True if atoms are equal, False otherwise

• TODO (tol)

hiphive.core.structure_alignment.get_primitive_cell(atoms, to_primitive=True, no_idealize=True, symprec=1e-05)

Gets primitive cell from spglib.

Parameters:

• atoms (ase.Atoms) – atomic structure

• to_primitive (bool) – passed to spglib

• no_idealize (bool) – passed to spglib

hiphive.core.structure_alignment.is_rotation(R, cell_metric=None)

Checks if rotation matrix is orthonormal

A cell metric can be passed of the rotation matrix is in scaled coordinates

Parameters:

• R (numpy.ndarray) – rotation matrix (3x3 array)

• cell_metric (numpy.ndarray) – cell metric if the rotation is in scaled coordinates

hiphive.core.structure_alignment.relate_structures(reference, target, symprec=1e-05)

Finds rotation and translation operations that align two structures with periodic boundary conditions.

The rotation and translation in Cartesian coordinates will map the reference structure onto the target

Aligning reference with target can be achieved via the transformations:

R, T = relate_structures(atoms_ref, atoms_target)
atoms_ref_rotated = rotate_atoms(atoms_ref, R)
atoms_ref_rotated.translate(T)
atoms_ref_rotated.wrap()
atoms_ref_rotated == atoms_target

Parameters:

• reference (ase.Atoms) – The reference structure to be mapped

• target (ase.Atoms) – The target structure

Returns:

• R (numpy.ndarray) – rotation matrix in Cartesian coordinates (3x3 array)

• T (numpy.ndarray) – translation vector in Cartesian coordinates

hiphive.core.structure_alignment.rotate_atoms(atoms, rotation)

Rotates the cell and positions of Atoms and returns a copy

Parameters:

• atoms (ase.Atoms) – atomic structure

• rotation (numpy.ndarray) – rotation matrix (3x3 array)

tensors

Module containing tensor related functions

hiphive.core.tensors.rotate_tensor(T, R, path=None)

Equivalent to T_abc… = T_ijk… R_ia R_jb R_kc …

hiphive.core.tensors.rotate_tensor_precalc(T, R)

hiphive.core.tensors.rotation_tensor_as_matrix(R, order)

hiphive.core.tensors.rotation_to_cart_coord(R, cell)

Return the rotation matrix in cart coord given a cell metric

utilities

The utilities module contains various support functions and classes.

class hiphive.core.utilities.Progress(tot=None, mode='frac', estimate_remaining=True)

Progress bar like functionality.

close()

tick()