Source code for

import numpy as np

from ase.atoms import Atoms
from ase.units import Hartree
from import atomic_numbers
from ase.calculators.singlepoint import SinglePointCalculator
from ase.utils import writer, reader

[docs]@writer def write_xsf(fileobj, images, data=None, origin=None, span_vectors=None): is_anim = len(images) > 1 if is_anim: fileobj.write('ANIMSTEPS %d\n' % len(images)) numbers = images[0].get_atomic_numbers() pbc = images[0].get_pbc() npbc = sum(pbc) if pbc[2]: fileobj.write('CRYSTAL\n') assert npbc == 3 elif pbc[1]: fileobj.write('SLAB\n') assert npbc == 2 elif pbc[0]: fileobj.write('POLYMER\n') assert npbc == 1 else: # (Header written as part of image loop) assert npbc == 0 cell_variable = False for image in images[1:]: if np.abs(images[0].cell - image.cell).max() > 1e-14: cell_variable = True break for n, atoms in enumerate(images): anim_token = ' %d' % (n + 1) if is_anim else '' if pbc.any(): write_cell = (n == 0 or cell_variable) if write_cell: if cell_variable: fileobj.write('PRIMVEC%s\n' % anim_token) else: fileobj.write('PRIMVEC\n') cell = atoms.get_cell() for i in range(3): fileobj.write(' %.14f %.14f %.14f\n' % tuple(cell[i])) fileobj.write('PRIMCOORD%s\n' % anim_token) else: fileobj.write('ATOMS%s\n' % anim_token) # Get the forces if it's not too expensive: calc = atoms.calc if (calc is not None and (hasattr(calc, 'calculation_required') and not calc.calculation_required(atoms, ['forces']))): forces = atoms.get_forces() / Hartree else: forces = None pos = atoms.get_positions() if pbc.any(): fileobj.write(' %d 1\n' % len(pos)) for a in range(len(pos)): fileobj.write(' %2d' % numbers[a]) fileobj.write(' %20.14f %20.14f %20.14f' % tuple(pos[a])) if forces is None: fileobj.write('\n') else: fileobj.write(' %20.14f %20.14f %20.14f\n' % tuple(forces[a])) if data is None: return fileobj.write('BEGIN_BLOCK_DATAGRID_3D\n') fileobj.write(' data\n') fileobj.write(' BEGIN_DATAGRID_3Dgrid#1\n') data = np.asarray(data) if data.dtype == complex: data = np.abs(data) shape = data.shape fileobj.write(' %d %d %d\n' % shape) cell = atoms.get_cell() if origin is None: origin = np.zeros(3) for i in range(3): if not pbc[i]: origin += cell[i] / shape[i] fileobj.write(' %f %f %f\n' % tuple(origin)) for i in range(3): # XXXX is this not just supposed to be the cell? # What's with the strange division? # This disagrees with the output of Octopus. Investigate if span_vectors is None: fileobj.write(' %f %f %f\n' % tuple(cell[i] * (shape[i] + 1) / shape[i])) else: fileobj.write(' %f %f %f\n' % tuple(span_vectors[i])) for k in range(shape[2]): for j in range(shape[1]): fileobj.write(' ') fileobj.write(' '.join(['%f' % d for d in data[:, j, k]])) fileobj.write('\n') fileobj.write('\n') fileobj.write(' END_DATAGRID_3D\n') fileobj.write('END_BLOCK_DATAGRID_3D\n')
@reader def iread_xsf(fileobj, read_data=False): """Yield images and optionally data from xsf file. Yields image1, image2, ..., imageN[, data, origin, span_vectors]. Images are Atoms objects and data is a numpy array. It also returns the origin of the simulation box as a numpy array and its spanning vectors as a list of numpy arrays, if data is returned. Presently supports only a single 3D datagrid.""" def _line_generator_func(): for line in fileobj: line = line.strip() if not line or line.startswith('#'): continue # Discard comments and empty lines yield line _line_generator = _line_generator_func() def readline(): return next(_line_generator) line = readline() if line.startswith('ANIMSTEPS'): nimages = int(line.split()[1]) line = readline() else: nimages = 1 if line == 'CRYSTAL': pbc = (True, True, True) elif line == 'SLAB': pbc = (True, True, False) elif line == 'POLYMER': pbc = (True, False, False) else: assert line.startswith('ATOMS'), line # can also be ATOMS 1 pbc = (False, False, False) cell = None for n in range(nimages): if any(pbc): line = readline() if line.startswith('PRIMCOORD'): assert cell is not None # cell read from previous image else: assert line.startswith('PRIMVEC') cell = [] for i in range(3): cell.append([float(x) for x in readline().split()]) line = readline() if line.startswith('CONVVEC'): # ignored; for i in range(3): readline() line = readline() assert line.startswith('PRIMCOORD') natoms = int(readline().split()[0]) lines = [readline() for _ in range(natoms)] else: assert line.startswith('ATOMS'), line line = readline() lines = [] while not (line.startswith('ATOMS') or line.startswith('BEGIN')): lines.append(line) try: line = readline() except StopIteration: break if line.startswith('BEGIN'): # We read "too far" and accidentally got the header # of the data section. This happens only when parsing # ATOMS blocks, because one cannot infer their length. # We will remember the line until later then. data_header_line = line numbers = [] positions = [] for positionline in lines: tokens = positionline.split() symbol = tokens[0] if symbol.isdigit(): numbers.append(int(symbol)) else: numbers.append(atomic_numbers[symbol.capitalize()]) positions.append([float(x) for x in tokens[1:]]) positions = np.array(positions) if len(positions[0]) == 3: forces = None else: forces = positions[:, 3:] * Hartree positions = positions[:, :3] image = Atoms(numbers, positions, cell=cell, pbc=pbc) if forces is not None: image.calc = SinglePointCalculator(image, forces=forces) yield image if read_data: if any(pbc): line = readline() else: line = data_header_line assert line.startswith('BEGIN_BLOCK_DATAGRID_3D') readline() # name line = readline() assert line.startswith('BEGIN_DATAGRID_3D') shape = [int(x) for x in readline().split()] assert len(shape) == 3 origin = [float(x) for x in readline().split()] origin = np.array(origin) span_vectors = [] for i in range(3): span_vector = [float(x) for x in readline().split()] span_vector = np.array(span_vector) span_vectors.append(span_vector) span_vectors = np.array(span_vectors) assert len(span_vectors) == len(shape) npoints = data = [] line = readline() # First line of data while not line.startswith('END_DATAGRID_3D'): data.extend([float(x) for x in line.split()]) line = readline() assert len(data) == npoints data = np.array(data, float).reshape(shape[::-1]).T # Note that data array is Fortran-ordered yield data, origin, span_vectors
[docs]def read_xsf(fileobj, index=-1, read_data=False): images = list(iread_xsf(fileobj, read_data=read_data)) if read_data: array, origin, span_vectors = images[-1] images = images[:-1] return array, origin, span_vectors, images[index] return images[index]