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import numpy as np
import re
from collections import deque
from dynasor.trajectory.abstract_trajectory_reader import AbstractTrajectoryReader
from dynasor.trajectory.trajectory_frame import ReaderFrame
from itertools import count
from numpy import array, arange, zeros
class LammpsTrajectoryReader(AbstractTrajectoryReader):
"""Read LAMMPS trajectory file
This is a naive (and comparatively slow) implementation,
written entirely in python.
Parameters
----------
filename
Name of input file.
length_unit
Unit of length for the input trajectory (``'Angstrom'``, ``'nm'``, ``'pm'``, ``'fm'``).
time_unit
Unit of time for the input trajectory (``'fs'``, ``'ps'``, ``'ns'``).
"""
def __init__(
self,
filename: str,
length_unit: str = 'Angstrom',
time_unit: str = 'fs'
):
if filename.endswith('.gz'):
import gzip
self._fh = gzip.open(filename, 'rt')
elif filename.endswith('.bz2'):
import bz2
self._fh = bz2.open(filename, 'rt')
else:
self._fh = open(filename, 'r')
self._open = True
regexp = r'^ITEM: (TIMESTEP|NUMBER OF ATOMS|BOX BOUNDS|ATOMS) ?(.*)$'
self._item_re = re.compile(regexp)
self._first_called = False
self._frame_index = count(0)
# setup units
if length_unit not in self.lengthunits_to_nm_table:
raise ValueError(f'Specified length unit {length_unit} is not an available option.')
else:
self.x_factor = self.lengthunits_to_nm_table[length_unit]
if time_unit not in self.timeunits_to_fs_table:
raise ValueError(f'Specified time unit {time_unit} is not an available option.')
else:
self.t_factor = self.timeunits_to_fs_table[time_unit]
self.v_factor = self.x_factor / self.t_factor
# ITEM: TIMESTEP
# 81000
# ITEM: NUMBER OF ATOMS
# 1536
# ITEM: BOX BOUNDS pp pp pp
# 1.54223 26.5378
# 1.54223 26.5378
# 1.54223 26.5378
# ITEM: ATOMS id type x y z vx vy vz
# 247 1 3.69544 2.56202 3.27701 0.00433856 -0.00099307 -0.00486166
# 249 2 3.73324 3.05962 4.14359 0.00346029 0.00332502 -0.00731005
# 463 1 3.5465 4.12841 5.34888 0.000523332 0.00145597 -0.00418675
def _read_frame_header(self):
while True:
L = self._fh.readline()
m = self._item_re.match(L)
if not m:
if L == '':
self._fh.close()
self._open = False
raise StopIteration
if L.strip() == '':
continue
raise IOError('TRJ_reader: Failed to parse TRJ frame header')
if m.group(1) == 'TIMESTEP':
step = int(self._fh.readline())
elif m.group(1) == 'NUMBER OF ATOMS':
n_atoms = int(self._fh.readline())
elif m.group(1) == 'BOX BOUNDS':
bbounds = [deque(map(float, self._fh.readline().split()))
for _ in range(3)]
x = array(bbounds)
cell = np.diag(x[:, 1] - x[:, 0])
if x.shape == (3, 3):
cell[1, 0] = x[0, 2]
cell[2, 0] = x[1, 2]
cell[2, 1] = x[2, 2]
elif x.shape != (3, 2):
raise IOError('TRJ_reader: Malformed cell bounds')
elif m.group(1) == 'ATOMS':
cols = tuple(m.group(2).split())
# At this point, there should be only atomic data left
return (step, n_atoms, cell, cols)
def _get_first(self):
# Read first frame, update state of self, create indeces etc
step, N, cell, cols = self._read_frame_header()
self._n_atoms = N
self._step = step
self._cols = cols
self._cell = cell
def _all_in_cols(keys):
for k in keys:
if k not in cols:
return False
return True
self._x_map = None
if _all_in_cols(('id', 'xu', 'yu', 'zu')):
self._x_I = array(deque(map(cols.index, ('xu', 'yu', 'zu'))))
elif _all_in_cols(('id', 'x', 'y', 'z')):
self._x_I = array(deque(map(cols.index, ('x', 'y', 'z'))))
elif _all_in_cols(('id', 'xs', 'ys', 'zs')):
self._x_I = array(deque(map(cols.index, ('xs', 'ys', 'zs'))))
_x_factor = self._cell.diagonal()
# xs.shape == (n, 3)
self._x_map = lambda xs: xs * _x_factor
else:
raise RuntimeError('TRJ file must contain at least atom-id, x, y,'
' and z coordinates to be useful.')
self._id_I = cols.index('id')
if _all_in_cols(('vx', 'vy', 'vz')):
self._v_I = array(deque(map(cols.index, ('vx', 'vy', 'vz'))))
else:
self._v_I = None
if 'type' in cols:
self._type_I = cols.index('type')
else:
self._type_I = None
data = array([list(map(float, self._fh.readline().split())) for _ in range(N)])
# data.shape == (N, Ncols)
II = np.asarray(data[:, self._id_I], dtype=np.int_)
# Unless dump is done for group 'all' ...
II[np.argsort(II)] = arange(len(II))
self._x = zeros((N, 3))
if self._x_map is None:
self._x[II] = data[:, self._x_I]
else:
self._x[II] = self._x_map(data[:, self._x_I])
if self._v_I is not None:
self._v = zeros((N, 3))
self._v[II] = data[:, self._v_I]
self._first_called = True
def _get_next(self):
# get next frame, update state of self
step, N, cell, cols = self._read_frame_header()
assert self._n_atoms == N
assert self._cols == cols
self._step = step
self._cell = cell
data = array([deque(map(float, self._fh.readline().split()))
for _ in range(N)])
II = np.asarray(data[:, self._id_I], dtype=np.int_) - 1
if self._x_map is None:
self._x[II] = data[:, self._x_I]
else:
self._x[II] = self._x_map(data[:, self._x_I])
if self._v_I is not None:
self._v[II] = data[:, self._v_I]
def __iter__(self):
return self
def close(self):
if not self._fh.closed:
self._fh.close()
def __next__(self):
if not self._open:
raise StopIteration
if self._first_called:
self._get_next()
else:
self._get_first()
if self._v_I is not None:
frame = ReaderFrame(frame_index=next(self._frame_index),
n_atoms=int(self._n_atoms),
cell=self.x_factor * self._cell.copy('F'),
positions=self.x_factor * self._x,
velocities=self.v_factor * self._v
)
else:
frame = ReaderFrame(frame_index=next(self._frame_index),
n_atoms=int(self._n_atoms),
cell=self.x_factor * self._cell.copy('F'),
positions=self.x_factor * self._x
)
return frame
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