Source code for hiphive.cutoffs

import pickle
import numpy as np
from ase.neighborlist import NeighborList

# TODO: Use another base class to hide internals from user
[docs]class Cutoffs: """ This class maintains information about the cutoff configuration, i.e. which clusters will be included (="inside cutoff"). It also encapsulates functionality that is used e.g., during cluster space construction. Here, `n-body` refers to number of atoms in a cluster. For example the cluster (0011) is a two-body cluster of fourth order and the cluster (123) is a three-body cluster of third order. Parameters ---------- cutoff_matrix : numpy.ndarray the matrix element `ij` provides to the cutoff for order `i+2` and nbody `j+2`; elements with `j>i` will be ignored """ def __init__(self, cutoff_matrix): self._cutoff_matrix = np.array(cutoff_matrix) for i in range(len(self._cutoff_matrix) - 1): assert max(self._cutoff_matrix[i, :]) >= \ max(self._cutoff_matrix[i+1, :]),\ 'Make sure cutoffs are in decreasing order' @property def cutoff_matrix(self): """ numpy.ndarray : copy of cutoff matrix """ return self._cutoff_matrix.copy() @property def orders(self): """ list(int) : allowed orders """ return list(range(2, self.max_order + 1)) @property def nbodies(self): """ list(int) : allowed bodies """ return list(range(2, self.max_nbody + 1))
[docs] def get_cutoff(self, order, nbody): """ Returns cutoff for a given body and order. Parameters ---------- order : int nbody : int Raises ------ ValueError if order is not in orders ValueError if nbody is not in nbodies ValueError if nbody is larger than order Returns ------- float """ if order not in self.orders: raise ValueError('order not in orders') if nbody not in self.nbodies: raise ValueError('nbody not in nbodies') if nbody > order: raise ValueError('nbody can not be larger than order') return self._cutoff_matrix[nbody - 2, order - 2]
@property def max_cutoff(self): """ float : maximum cutoff """ max_cutoff = 0 for i, row in enumerate(self._cutoff_matrix): max_cutoff = max(max_cutoff, np.max(row[i:])) return max_cutoff @property def max_nbody(self): """ int : maximum body """ return self._cutoff_matrix.shape[0] + 1 @property def max_order(self): """ int : maximum order """ return self._cutoff_matrix.shape[1] + 1
[docs] def max_nbody_cutoff(self, nbody): """ Return maximum cutoff for a given body. """ if nbody not in self.nbodies: raise ValueError('nbody not in nbodies') return np.max(self._cutoff_matrix[nbody - 2, max(0, nbody - 2):])
[docs] def max_nbody_order(self, nbody): """ Returns maximum order for a given body """ if nbody not in self.nbodies: raise ValueError('nbody not in nbodies') arr = self._cutoff_matrix[nbody - 2, max(0, nbody - 2):] return np.count_nonzero(arr) + (nbody - 1)
[docs] def write(self, fileobj): """ Writes instance to file. Parameters ---------- fileobj : file-like object file-like object to which the cutoffs will be written to """ pickle.dump(self._cutoff_matrix, fileobj)
[docs] def read(fileobj): """ Reads an instance from file. Parameters ---------- fileobj : file-like object input file to read from """ data = pickle.load(fileobj) if type(data) is np.ndarray: return Cutoffs(data) else: cutoffs = data['cutoffs'] return CutoffMaximumBody(cutoffs, len(cutoffs) + 1)
def __str__(self): return str(self._cutoff_matrix)
[docs]class CutoffMaximumBody(Cutoffs): """ Specify cutoff-list plus maximum body Usefull when creating e.g. 6th order expansions but with only 3-body interactions. Parameters ---------- cutoff_list : list list of cutoffs for order 2, 3, etc. Must be in decresing order max_nbody : int No clusters containing more than max_nbody atoms will be generated """ def __init__(self, cutoff_list, max_nbody): cutoff_matrix = np.zeros((max_nbody - 1, len(cutoff_list))) for order, cutoff in enumerate(cutoff_list, start=2): cutoff_matrix[:, order - 2] = cutoff super().__init__(cutoff_matrix)
[docs]def is_cutoff_allowed(atoms, cutoff): """ Checks if atoms is compatible with cutoff Parameters ---------- atoms : ase.Atoms structure used for checking compatibility with cutoff cutoff : float cutoff to be tested Returns ------- bool True if cutoff compatible with atoms object, else False """ nbrlist = NeighborList(cutoffs=[cutoff / 2] * len(atoms), skin=0, self_interaction=False, bothways=True) nbrlist.update(atoms) for i in range(len(atoms)): neighbors, _ = nbrlist.get_neighbors(i) if i in neighbors: return False if len(neighbors) != len(set(neighbors)): return False return True
[docs]def estimate_maximum_cutoff(atoms, max_iter=11): """ Estimates the maximum possible cutoff given the atoms object Parameters ---------- atoms : ase.Atoms structure used for checking compatibility with cutoff max_iter : int number of iterations in binary search """ # First upper boundary of cutoff upper_cutoff = min(np.linalg.norm(atoms.cell, axis=1)) # generate all possible offsets given upper_cutoff nbrlist = NeighborList(cutoffs=[upper_cutoff / 2] * len(atoms), skin=0, self_interaction=False, bothways=True) nbrlist.update(atoms) all_offsets = [] for i in range(len(atoms)): _, offsets = nbrlist.get_neighbors(i) all_offsets.extend([tuple(offset) for offset in offsets]) # find lower boundary and new upper boundary unique_offsets = set(all_offsets) unique_offsets.discard((0, 0, 0)) upper = min(np.linalg.norm(, atoms.cell)) for offset in unique_offsets) lower = upper / 2.0 # run binary search between the upper and lower bounds for _ in range(max_iter): cutoff = (upper + lower) / 2 if is_cutoff_allowed(atoms, cutoff): lower = cutoff else: upper = cutoff return lower