Tools for building things¶

ase.build.
cut
(atoms, a=(1, 0, 0), b=(0, 1, 0), c=None, clength=None, origo=(0, 0, 0), nlayers=None, extend=1.0, tolerance=0.01, maxatoms=None)[source]¶ Cuts out a cell defined by a, b, c and origo from a sufficiently repeated copy of atoms.
Typically, this function is used to create slabs of different sizes and orientations. The vectors a, b and c are in scaled coordinates and defines the returned cell and should normally be integervalued in order to end up with a periodic structure. However, for systems with subtranslations, like fcc, integer multiples of 1/2 or 1/3 might also make sence for some directions (and will be treated correctly).
Parameters:
 atoms: Atoms instance
 This should correspond to a repeatable unit cell.
 a: int  3 floats
 The avector in scaled coordinates of the cell to cut out. If integer, the avector will be the scaled vector from origo to the atom with index a.
 b: int  3 floats
 The bvector in scaled coordinates of the cell to cut out. If integer, the bvector will be the scaled vector from origo to the atom with index b.
 c: None  int  3 floats
 The cvector in scaled coordinates of the cell to cut out. if integer, the cvector will be the scaled vector from origo to the atom with index c. If None it will be along cross(a, b) converted to real space and normalised with the cube root of the volume. Note that this in general is not perpendicular to a and b for noncubic systems. For cubic systems however, this is redused to c = cross(a, b).
 clength: None  float
 If not None, the length of the cvector will be fixed to clength Angstroms. Should not be used together with nlayers.
 origo: int  3 floats
 Position of origo of the new cell in scaled coordinates. If integer, the position of the atom with index origo is used.
 nlayers: None  int
 If nlayers is not None, the returned cell will have nlayers atomic layers in the cdirection.
 extend: 1 or 3 floats
 The extend argument scales the effective cell in which atoms will be included. It must either be three floats or a single float scaling all 3 directions. By setting to a value just above one, e.g. 1.05, it is possible to all the corner and edge atoms in the returned cell. This will of cause make the returned cell nonrepeatable, but is very useful for visualisation.
 tolerance: float
 Determines what is defined as a plane. All atoms within tolerance Angstroms from a given plane will be considered to belong to that plane.
 maxatoms: None  int
 This option is used to autotune tolerance when nlayers is given for high zone axis systems. For high zone axis one needs to reduce tolerance in order to distinguise the atomic planes, resulting in the more atoms will be added and eventually MemoryError. A too small tolerance, on the other hand, might result in inproper splitting of atomic planes and that too few layers are returned. If maxatoms is not None, tolerance will automatically be gradually reduced until nlayers atomic layers is obtained, when the number of atoms exceeds maxatoms.
Example:
>>> import ase >>> from ase.spacegroup import crystal >>> # Create an aluminium (111) slab with three layers # # First an unit cell of Al >>> a = 4.05 >>> aluminium = crystal('Al', [(0,0,0)], spacegroup=225, ... cellpar=[a, a, a, 90, 90, 90]) >>> # Then cut out the slab >>> al111 = cut(aluminium, (1,1,0), (0,1,1), nlayers=3) >>> # Visualisation of the skutterudite unit cell # # Again, create a skutterudite unit cell >>> a = 9.04 >>> skutterudite = crystal( ... ('Co', 'Sb'), ... basis=[(0.25,0.25,0.25), (0.0, 0.335, 0.158)], ... spacegroup=204, ... cellpar=[a, a, a, 90, 90, 90]) >>> # Then use *origo* to put 'Co' at the corners and *extend* to # include all corner and edge atoms. >>> s = cut(skutterudite, origo=(0.25, 0.25, 0.25), extend=1.01) >>> ase.view(s)

ase.build.
stack
(atoms1, atoms2, axis=2, cell=None, fix=0.5, maxstrain=0.5, distance=None, reorder=False, output_strained=False)[source]¶ Return a new Atoms instance with atoms2 stacked on top of atoms1 along the given axis. Periodicity in all directions is ensured.
The size of the final cell is determined by cell, except that the length alongh axis will be the sum of atoms1.cell[axis] and atoms2.cell[axis]. If cell is None, it will be interpolated between atoms1 and atoms2, where fix determines their relative weight. Hence, if fix equals zero, the final cell will be determined purely from atoms1 and if fix equals one, it will be determined purely from atoms2.
An ase.geometry.IncompatibleCellError exception is raised if the cells of atoms1 and atoms2 are incopatible, e.g. if the far corner of the unit cell of either atoms1 or atoms2 is displaced more than maxstrain. Setting maxstrain to None, disable this check.
If distance is not None, the size of the final cell, along the direction perpendicular to the interface, will be adjusted such that the distance between the closest atoms in atoms1 and atoms2 will be equal to distance. This option uses scipy.optimize.fmin() and hence require scipy to be installed.
If reorder is True, then the atoms will be reordred such that all atoms with the same symbol will follow sequensially after each other, eg: ‘Al2MnAl10Fe’ > ‘Al12FeMn’.
If output_strained is True, then the strained versions of atoms1 and atoms2 are returned in addition to the stacked structure.
Example:
>>> import ase >>> from ase.spacegroup import crystal >>> # Create an Ag(110)Si(110) interface with three atomic layers # on each side. >>> a_ag = 4.09 >>> ag = crystal(['Ag'], basis=[(0,0,0)], spacegroup=225, ... cellpar=[a_ag, a_ag, a_ag, 90., 90., 90.]) >>> ag110 = cut(ag, (0, 0, 3), (1.5, 1.5, 0), nlayers=3) >>> >>> a_si = 5.43 >>> si = crystal(['Si'], basis=[(0,0,0)], spacegroup=227, ... cellpar=[a_si, a_si, a_si, 90., 90., 90.]) >>> si110 = cut(si, (0, 0, 2), (1, 1, 0), nlayers=3) >>> >>> interface = stack(ag110, si110, maxstrain=1) >>> ase.view(interface) >>> # Once more, this time adjusted such that the distance between # the closest Ag and Si atoms will be 2.3 Angstrom (requires scipy). >>> interface2 = stack(ag110, si110, ... maxstrain=1, distance=2.3) Optimization terminated successfully. ... >>> ase.view(interface2)

ase.build.
sort
(atoms, tags=None)[source]¶ Return a new Atoms object with sorted atomic order. The default is to order according to chemical symbols, but if tags is not None, it will be used instead. A stable sorting algorithm is used.
Example:
>>> from ase.build import bulk >>> # Two unit cells of NaCl: >>> a = 5.64 >>> nacl = bulk('NaCl', 'rocksalt', a=a) * (2, 1, 1) >>> nacl.get_chemical_symbols() ['Na', 'Cl', 'Na', 'Cl'] >>> nacl_sorted = sort(nacl) >>> nacl_sorted.get_chemical_symbols() ['Cl', 'Cl', 'Na', 'Na'] >>> np.all(nacl_sorted.cell == nacl.cell) True

ase.build.
rotate
(atoms, a1, a2, b1, b2, rotate_cell=True, center=(0, 0, 0))[source]¶ Rotate atoms, such that a1 will be rotated in the direction of a2 and b1 in the direction of b2. The point at center is fixed. Use center=’COM’ to fix the center of mass. If rotate_cell is true, the cell will be rotated together with the atoms.
Note that the 000corner of the cell is by definition fixed at origo. Hence, setting center to something other than (0, 0, 0) will rotate the atoms out of the cell, even if rotate_cell is True.

ase.build.
niggli_reduce
(atoms)[source]¶ Convert the supplied atoms object’s unit cell into its maximallyreduced Niggli unit cell. Even if the unit cell is already maximally reduced, it will be converted into its unique Niggli unit cell. This will also wrap all atoms into the new unit cell.
References:
Niggli, P. “Krystallographische und strukturtheoretische Grundbegriffe. Handbuch der Experimentalphysik”, 1928, Vol. 7, Part 1, 108176.
Krivy, I. and Gruber, B., “A Unified Algorithm for Determining the Reduced (Niggli) Cell”, Acta Cryst. 1976, A32, 297298.
GrosseKunstleve, R.W.; Sauter, N. K.; and Adams, P. D. “Numerically stable algorithms for the computation of reduced unit cells”, Acta Cryst. 2004, A60, 16.

ase.build.
minimize_tilt
(atoms, order=range(0, 3), fold_atoms=True)[source]¶ Minimize the tilt angles of the unit cell.

ase.build.
minimize_rotation_and_translation
(target, atoms)[source]¶ Minimize RMSD between atoms and target.
Rotate and translate atoms to best match target. For more details, see:
Melander et al. J. Chem. Theory Comput., 2015, 11,1055

ase.build.
find_optimal_cell_shape
(cell, target_size, target_shape, lower_limit=2, upper_limit=2, verbose=False)[source]¶ Returns the transformation matrix that produces a supercell corresponding to a certain number of unit cells (target_size) based on a primitive metric (cell) that most closely approximates a desired shape (target_shape).
Note: This implementation uses inlineC via scipy.weave to achieve a significant speedup (about two orders of magnitude) compared to the pure python implementation in the
find_optimal_cell_shape_pure_python()
function.Parameters:
 cell: 2D array of floats
 Metric given as a (3x3 matrix) of the input structure.
 target_size: integer
 Size of desired super cell in number of unit cells.
 target_shape: str
 Desired supercell shape. Can be ‘sc’ for simple cubic or ‘fcc’ for facecentered cubic.
 lower_limit: int
 Lower limit of search range.
 upper_limit: int
 Upper limit of search range.
 verbose: bool
 Set to True to obtain additional information regarding construction of transformation matrix.

ase.build.
find_optimal_cell_shape_pure_python
(cell, target_size, target_shape, lower_limit=2, upper_limit=2, verbose=False)[source]¶ Returns the transformation matrix that produces a supercell corresponding to target_size unit cells with metric cell that most closely approximates the shape defined by target_shape.
Note: This pure python implementation of the is much slower than the inlineC version provided in
find_optimal_cell_shape()
.Parameters:
 cell: 2D array of floats
 Metric given as a (3x3 matrix) of the input structure.
 target_size: integer
 Size of desired super cell in number of unit cells.
 target_shape: str
 Desired supercell shape. Can be ‘sc’ for simple cubic or ‘fcc’ for facecentered cubic.
 lower_limit: int
 Lower limit of search range.
 upper_limit: int
 Upper limit of search range.
 verbose: bool
 Set to True to obtain additional information regarding construction of transformation matrix.

ase.build.
get_deviation_from_optimal_cell_shape
(cell, target_shape=’sc’, norm=None)[source]¶ Calculate the deviation of the given cell metric from the ideal cell metric defining a certain shape. Specifically, the function evaluates the expression \(\Delta =  Q \mathbf{h}  \mathbf{h}_{target}_2\), where \(\mathbf{h}\) is the input metric (cell) and \(Q\) is a normalization factor (norm) while the target metric \(\mathbf{h}_{target}\) (via target_shape) represent simple cubic (‘sc’) or facecentered cubic (‘fcc’) cell shapes.
Parameters:
 cell: 2D array of floats
 Metric given as a (3x3 matrix) of the input structure.
 target_shape: str
 Desired supercell shape. Can be ‘sc’ for simple cubic or ‘fcc’ for facecentered cubic.
 norm: float
 Specify the normalization factor. This is useful to avoid recomputing the normalization factor when computing the deviation for a series of P matrices.

ase.build.
make_supercell
(prim, P)[source]¶ Generate a supercell by applying a general transformation (P) to the input configuration (prim).
The transformation is described by a 3x3 integer matrix \(\mathbf{P}\). Specifically, the new cell metric \(\mathbf{h}\) is given in terms of the metric of the input configuraton \(\mathbf{h}_p\) by \(\mathbf{P h}_p = \mathbf{h}\).
Internally this function uses the
cut()
function.Parameters:
 prim: ASE Atoms object
 Input configuration.
 P: 3x3 integer matrix
 Transformation matrix \(\mathbf{P}\).