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Merge branch 'master' into mliappy3

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Richard Berger
2020-12-18 09:16:44 -05:00
parent 3dea3188aa 79833f9b83
commit 4c7f71bef3
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python/lammps/__init__.py Normal file
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from .constants import *
from .core import *
from .data import *
from .pylammps import *

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# ----------------------------------------------------------------------
# LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
# http://lammps.sandia.gov, Sandia National Laboratories
# Steve Plimpton, sjplimp@sandia.gov
#
# Copyright (2003) Sandia Corporation. Under the terms of Contract
# DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
# certain rights in this software. This software is distributed under
# the GNU General Public License.
#
# See the README file in the top-level LAMMPS directory.
# -------------------------------------------------------------------------
from ctypes import c_int, c_int32, c_int64
# various symbolic constants to be used
# in certain calls to select data formats
LAMMPS_AUTODETECT = None
LAMMPS_INT = 0
LAMMPS_INT_2D = 1
LAMMPS_DOUBLE = 2
LAMMPS_DOUBLE_2D = 3
LAMMPS_INT64 = 4
LAMMPS_INT64_2D = 5
LAMMPS_STRING = 6
# these must be kept in sync with the enums in library.h
LMP_STYLE_GLOBAL = 0
LMP_STYLE_ATOM = 1
LMP_STYLE_LOCAL = 2
LMP_TYPE_SCALAR = 0
LMP_TYPE_VECTOR = 1
LMP_TYPE_ARRAY = 2
LMP_SIZE_VECTOR = 3
LMP_SIZE_ROWS = 4
LMP_SIZE_COLS = 5
LMP_VAR_EQUAL = 0
LMP_VAR_ATOM = 1
# -------------------------------------------------------------------------
def get_ctypes_int(size):
if size == 4:
return c_int32
elif size == 8:
return c_int64
return c_int

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# ----------------------------------------------------------------------
# LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
# http://lammps.sandia.gov, Sandia National Laboratories
# Steve Plimpton, sjplimp@sandia.gov
#
# Copyright (2003) Sandia Corporation. Under the terms of Contract
# DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
# certain rights in this software. This software is distributed under
# the GNU General Public License.
#
# See the README file in the top-level LAMMPS directory.
# -------------------------------------------------------------------------
################################################################################
# LAMMPS data structures
# Written by Richard Berger <richard.berger@temple.edu>
################################################################################
class NeighList:
"""This is a wrapper class that exposes the contents of a neighbor list.
It can be used like a regular Python list. Each element is a tuple of:
* the atom local index
* its number of neighbors
* and a pointer to an c_int array containing local atom indices of its
neighbors
Internally it uses the lower-level LAMMPS C-library interface.
:param lmp: reference to instance of :py:class:`lammps`
:type lmp: lammps
:param idx: neighbor list index
:type idx: int
"""
def __init__(self, lmp, idx):
self.lmp = lmp
self.idx = idx
def __str__(self):
return "Neighbor List ({} atoms)".format(self.size)
def __repr__(self):
return self.__str__()
@property
def size(self):
"""
:return: number of elements in neighbor list
"""
return self.lmp.get_neighlist_size(self.idx)
def get(self, element):
"""
:return: tuple with atom local index, numpy array of neighbor local atom indices
:rtype: (int, int, ctypes.POINTER(c_int))
"""
iatom, numneigh, neighbors = self.lmp.get_neighlist_element_neighbors(self.idx, element)
return iatom, numneigh, neighbors
# the methods below implement the iterator interface, so NeighList can be used like a regular Python list
def __getitem__(self, element):
return self.get(element)
def __len__(self):
return self.size
def __iter__(self):
inum = self.size
for ii in range(inum):
yield self.get(ii)

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# ----------------------------------------------------------------------
# LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
# http://lammps.sandia.gov, Sandia National Laboratories
# Steve Plimpton, sjplimp@sandia.gov
#
# Copyright (2003) Sandia Corporation. Under the terms of Contract
# DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
# certain rights in this software. This software is distributed under
# the GNU General Public License.
#
# See the README file in the top-level LAMMPS directory.
# -------------------------------------------------------------------------
################################################################################
# NumPy additions
# Written by Richard Berger <richard.berger@temple.edu>
################################################################################
import warnings
from ctypes import POINTER, c_double, c_int, c_int32, c_int64, cast
from .constants import *
from .data import NeighList
class numpy_wrapper:
"""lammps API NumPy Wrapper
This is a wrapper class that provides additional methods on top of an
existing :py:class:`lammps` instance. The methods transform raw ctypes
pointers into NumPy arrays, which give direct access to the
original data while protecting against out-of-bounds accesses.
There is no need to explicitly instantiate this class. Each instance
of :py:class:`lammps` has a :py:attr:`numpy <lammps.numpy>` property
that returns an instance.
:param lmp: instance of the :py:class:`lammps` class
:type lmp: lammps
"""
def __init__(self, lmp):
self.lmp = lmp
# -------------------------------------------------------------------------
def _ctype_to_numpy_int(self, ctype_int):
import numpy as np
if ctype_int == c_int32:
return np.int32
elif ctype_int == c_int64:
return np.int64
return np.intc
# -------------------------------------------------------------------------
def extract_atom(self, name, dtype=LAMMPS_AUTODETECT, nelem=LAMMPS_AUTODETECT, dim=LAMMPS_AUTODETECT):
"""Retrieve per-atom properties from LAMMPS as NumPy arrays
This is a wrapper around the :py:meth:`lammps.extract_atom()` method.
It behaves the same as the original method, but returns NumPy arrays
instead of ``ctypes`` pointers.
.. note::
While the returned arrays of per-atom data are dimensioned
for the range [0:nmax] - as is the underlying storage -
the data is usually only valid for the range of [0:nlocal],
unless the property of interest is also updated for ghost
atoms. In some cases, this depends on a LAMMPS setting, see
for example :doc:`comm_modify vel yes <comm_modify>`.
:param name: name of the property
:type name: string
:param dtype: type of the returned data (see :ref:`py_datatype_constants`)
:type dtype: int, optional
:param nelem: number of elements in array
:type nelem: int, optional
:param dim: dimension of each element
:type dim: int, optional
:return: requested data as NumPy array with direct access to C data or None
:rtype: numpy.array or NoneType
"""
if dtype == LAMMPS_AUTODETECT:
dtype = self.lmp.extract_atom_datatype(name)
if nelem == LAMMPS_AUTODETECT:
if name == "mass":
nelem = self.lmp.extract_global("ntypes") + 1
else:
nelem = self.lmp.extract_global("nlocal")
if dim == LAMMPS_AUTODETECT:
if dtype in (LAMMPS_INT_2D, LAMMPS_DOUBLE_2D, LAMMPS_INT64_2D):
# TODO add other fields
if name in ("x", "v", "f", "angmom", "torque", "csforce", "vforce"):
dim = 3
else:
dim = 2
else:
dim = 1
raw_ptr = self.lmp.extract_atom(name, dtype)
if dtype in (LAMMPS_DOUBLE, LAMMPS_DOUBLE_2D):
return self.darray(raw_ptr, nelem, dim)
elif dtype in (LAMMPS_INT, LAMMPS_INT_2D):
return self.iarray(c_int32, raw_ptr, nelem, dim)
elif dtype in (LAMMPS_INT64, LAMMPS_INT64_2D):
return self.iarray(c_int64, raw_ptr, nelem, dim)
return raw_ptr
# -------------------------------------------------------------------------
def extract_atom_iarray(self, name, nelem, dim=1):
warnings.warn("deprecated, use extract_atom instead", DeprecationWarning)
if name in ['id', 'molecule']:
c_int_type = self.lmp.c_tagint
elif name in ['image']:
c_int_type = self.lmp.c_imageint
else:
c_int_type = c_int
if dim == 1:
raw_ptr = self.lmp.extract_atom(name, LAMMPS_INT)
else:
raw_ptr = self.lmp.extract_atom(name, LAMMPS_INT_2D)
return self.iarray(c_int_type, raw_ptr, nelem, dim)
# -------------------------------------------------------------------------
def extract_atom_darray(self, name, nelem, dim=1):
warnings.warn("deprecated, use extract_atom instead", DeprecationWarning)
if dim == 1:
raw_ptr = self.lmp.extract_atom(name, LAMMPS_DOUBLE)
else:
raw_ptr = self.lmp.extract_atom(name, LAMMPS_DOUBLE_2D)
return self.darray(raw_ptr, nelem, dim)
# -------------------------------------------------------------------------
def extract_compute(self, cid, style, type):
"""Retrieve data from a LAMMPS compute
This is a wrapper around the
:py:meth:`lammps.extract_compute() <lammps.lammps.extract_compute()>` method.
It behaves the same as the original method, but returns NumPy arrays
instead of ``ctypes`` pointers.
:param id: compute ID
:type id: string
:param style: style of the data retrieve (global, atom, or local), see :ref:`py_style_constants`
:type style: int
:param type: type of the returned data (scalar, vector, or array), see :ref:`py_type_constants`
:type type: int
:return: requested data either as float, as NumPy array with direct access to C data, or None
:rtype: float, numpy.array, or NoneType
"""
value = self.lmp.extract_compute(cid, style, type)
if style in (LMP_STYLE_GLOBAL, LMP_STYLE_LOCAL):
if type == LMP_TYPE_VECTOR:
nrows = self.lmp.extract_compute(cid, style, LMP_SIZE_VECTOR)
return self.darray(value, nrows)
elif type == LMP_TYPE_ARRAY:
nrows = self.lmp.extract_compute(cid, style, LMP_SIZE_ROWS)
ncols = self.lmp.extract_compute(cid, style, LMP_SIZE_COLS)
return self.darray(value, nrows, ncols)
elif style == LMP_STYLE_ATOM:
if type == LMP_TYPE_VECTOR:
nlocal = self.lmp.extract_global("nlocal")
return self.darray(value, nlocal)
elif type == LMP_TYPE_ARRAY:
nlocal = self.lmp.extract_global("nlocal")
ncols = self.lmp.extract_compute(cid, style, LMP_SIZE_COLS)
return self.darray(value, nlocal, ncols)
return value
# -------------------------------------------------------------------------
def extract_fix(self, fid, style, type, nrow=0, ncol=0):
"""Retrieve data from a LAMMPS fix
This is a wrapper around the :py:meth:`lammps.extract_fix() <lammps.lammps.extract_fix()>` method.
It behaves the same as the original method, but returns NumPy arrays
instead of ``ctypes`` pointers.
:param id: fix ID
:type id: string
:param style: style of the data retrieve (global, atom, or local), see :ref:`py_style_constants`
:type style: int
:param type: type or size of the returned data (scalar, vector, or array), see :ref:`py_type_constants`
:type type: int
:param nrow: index of global vector element or row index of global array element
:type nrow: int
:param ncol: column index of global array element
:type ncol: int
:return: requested data
:rtype: integer or double value, pointer to 1d or 2d double array or None
"""
value = self.lmp.extract_fix(fid, style, type, nrow, ncol)
if style == LMP_STYLE_ATOM:
if type == LMP_TYPE_VECTOR:
nlocal = self.lmp.extract_global("nlocal")
return self.darray(value, nlocal)
elif type == LMP_TYPE_ARRAY:
nlocal = self.lmp.extract_global("nlocal")
ncols = self.lmp.extract_fix(fid, style, LMP_SIZE_COLS, 0, 0)
return self.darray(value, nlocal, ncols)
elif style == LMP_STYLE_LOCAL:
if type == LMP_TYPE_VECTOR:
nrows = self.lmp.extract_fix(fid, style, LMP_SIZE_ROWS, 0, 0)
return self.darray(value, nrows)
elif type == LMP_TYPE_ARRAY:
nrows = self.lmp.extract_fix(fid, style, LMP_SIZE_ROWS, 0, 0)
ncols = self.lmp.extract_fix(fid, style, LMP_SIZE_COLS, 0, 0)
return self.darray(value, nrows, ncols)
return value
# -------------------------------------------------------------------------
def extract_variable(self, name, group=None, vartype=LMP_VAR_EQUAL):
""" Evaluate a LAMMPS variable and return its data
This function is a wrapper around the function
:py:meth:`lammps.extract_variable() <lammps.lammps.extract_variable()>`
method. It behaves the same as the original method, but returns NumPy arrays
instead of ``ctypes`` pointers.
:param name: name of the variable to execute
:type name: string
:param group: name of group for atom-style variable (ignored for equal-style variables)
:type group: string
:param vartype: type of variable, see :ref:`py_vartype_constants`
:type vartype: int
:return: the requested data or None
:rtype: c_double, numpy.array, or NoneType
"""
import numpy as np
value = self.lmp.extract_variable(name, group, vartype)
if vartype == LMP_VAR_ATOM:
return np.ctypeslib.as_array(value)
return value
# -------------------------------------------------------------------------
def get_neighlist(self, idx):
"""Returns an instance of :class:`NumPyNeighList` which wraps access to the neighbor list with the given index
:param idx: index of neighbor list
:type idx: int
:return: an instance of :class:`NumPyNeighList` wrapping access to neighbor list data
:rtype: NumPyNeighList
"""
if idx < 0:
return None
return NumPyNeighList(self.lmp, idx)
# -------------------------------------------------------------------------
def get_neighlist_element_neighbors(self, idx, element):
"""Return data of neighbor list entry
This function is a wrapper around the function
:py:meth:`lammps.get_neighlist_element_neighbors() <lammps.lammps.get_neighlist_element_neighbors()>`
method. It behaves the same as the original method, but returns a NumPy array containing the neighbors
instead of a ``ctypes`` pointer.
:param element: neighbor list index
:type element: int
:param element: neighbor list element index
:type element: int
:return: tuple with atom local index and numpy array of neighbor local atom indices
:rtype: (int, numpy.array)
"""
iatom, numneigh, c_neighbors = self.lmp.get_neighlist_element_neighbors(idx, element)
neighbors = self.iarray(c_int, c_neighbors, numneigh, 1)
return iatom, neighbors
# -------------------------------------------------------------------------
def iarray(self, c_int_type, raw_ptr, nelem, dim=1):
import numpy as np
np_int_type = self._ctype_to_numpy_int(c_int_type)
if dim == 1:
ptr = cast(raw_ptr, POINTER(c_int_type * nelem))
else:
ptr = cast(raw_ptr[0], POINTER(c_int_type * nelem * dim))
a = np.frombuffer(ptr.contents, dtype=np_int_type)
a.shape = (nelem, dim)
return a
# -------------------------------------------------------------------------
def darray(self, raw_ptr, nelem, dim=1):
import numpy as np
if dim == 1:
ptr = cast(raw_ptr, POINTER(c_double * nelem))
else:
ptr = cast(raw_ptr[0], POINTER(c_double * nelem * dim))
a = np.frombuffer(ptr.contents)
a.shape = (nelem, dim)
return a
# -------------------------------------------------------------------------
class NumPyNeighList(NeighList):
"""This is a wrapper class that exposes the contents of a neighbor list.
It can be used like a regular Python list. Each element is a tuple of:
* the atom local index
* a NumPy array containing the local atom indices of its neighbors
Internally it uses the lower-level LAMMPS C-library interface.
:param lmp: reference to instance of :py:class:`lammps`
:type lmp: lammps
:param idx: neighbor list index
:type idx: int
"""
def __init__(self, lmp, idx):
super(NumPyNeighList, self).__init__(lmp, idx)
def get(self, element):
"""
:return: tuple with atom local index, numpy array of neighbor local atom indices
:rtype: (int, numpy.array)
"""
iatom, neighbors = self.lmp.numpy.get_neighlist_element_neighbors(self.idx, element)
return iatom, neighbors

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# ----------------------------------------------------------------------
# LAMMPS - Large-scale Atomic/Molecular Massively Parallel Simulator
# http://lammps.sandia.gov, Sandia National Laboratories
# Steve Plimpton, sjplimp@sandia.gov
#
# Copyright (2003) Sandia Corporation. Under the terms of Contract
# DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
# certain rights in this software. This software is distributed under
# the GNU General Public License.
#
# See the README file in the top-level LAMMPS directory.
# -------------------------------------------------------------------------
################################################################################
# Alternative Python Wrapper
# Written by Richard Berger <richard.berger@temple.edu>
################################################################################
# for python2/3 compatibility
from __future__ import print_function
import os
import re
import select
import sys
from collections import namedtuple
from .core import lammps
class OutputCapture(object):
""" Utility class to capture LAMMPS library output """
def __init__(self):
self.stdout_pipe_read, self.stdout_pipe_write = os.pipe()
self.stdout_fd = 1
def __enter__(self):
self.stdout = os.dup(self.stdout_fd)
os.dup2(self.stdout_pipe_write, self.stdout_fd)
return self
def __exit__(self, type, value, tracebac):
os.dup2(self.stdout, self.stdout_fd)
os.close(self.stdout)
os.close(self.stdout_pipe_read)
os.close(self.stdout_pipe_write)
# check if we have more to read from the pipe
def more_data(self, pipe):
r, _, _ = select.select([pipe], [], [], 0)
return bool(r)
# read the whole pipe
def read_pipe(self, pipe):
out = ""
while self.more_data(pipe):
out += os.read(pipe, 1024).decode()
return out
@property
def output(self):
return self.read_pipe(self.stdout_pipe_read)
# -------------------------------------------------------------------------
class Variable(object):
def __init__(self, pylammps_instance, name, style, definition):
self._pylmp = pylammps_instance
self.name = name
self.style = style
self.definition = definition.split()
@property
def value(self):
if self.style == 'atom':
return list(self._pylmp.lmp.extract_variable(self.name, "all", 1))
else:
value = self._pylmp.lmp_print('"${%s}"' % self.name).strip()
try:
return float(value)
except ValueError:
return value
# -------------------------------------------------------------------------
class AtomList(object):
"""
A dynamic list of atoms that returns either an :py:class:`Atom` or
:py:class:`Atom2D` instance for each atom. Instances are only allocated
when accessed.
:ivar natoms: total number of atoms
:ivar dimensions: number of dimensions in system
"""
def __init__(self, pylammps_instance):
self._pylmp = pylammps_instance
self.natoms = self._pylmp.system.natoms
self.dimensions = self._pylmp.system.dimensions
self._loaded = {}
def __getitem__(self, index):
"""
Return Atom with given local index
:param index: Local index of atom
:type index: int
:rtype: Atom or Atom2D
"""
if index not in self._loaded:
if self.dimensions == 2:
atom = Atom2D(self._pylmp, index + 1)
else:
atom = Atom(self._pylmp, index + 1)
self._loaded[index] = atom
return self._loaded[index]
def __len__(self):
return self.natoms
# -------------------------------------------------------------------------
class Atom(object):
"""
A wrapper class then represents a single atom inside of LAMMPS
It provides access to properties of the atom and allows you to change some of them.
"""
def __init__(self, pylammps_instance, index):
self._pylmp = pylammps_instance
self.index = index
@property
def id(self):
"""
Return the atom ID
:type: int
"""
return int(self._pylmp.eval("id[%d]" % self.index))
@property
def type(self):
"""
Return the atom type
:type: int
"""
return int(self._pylmp.eval("type[%d]" % self.index))
@property
def mol(self):
"""
Return the atom molecule index
:type: int
"""
return self._pylmp.eval("mol[%d]" % self.index)
@property
def mass(self):
"""
Return the atom mass
:type: float
"""
return self._pylmp.eval("mass[%d]" % self.index)
@property
def position(self):
"""
:getter: Return position of atom
:setter: Set position of atom
:type: tuple (float, float, float)
"""
return (self._pylmp.eval("x[%d]" % self.index),
self._pylmp.eval("y[%d]" % self.index),
self._pylmp.eval("z[%d]" % self.index))
@position.setter
def position(self, value):
"""
:getter: Return velocity of atom
:setter: Set velocity of atom
:type: tuple (float, float, float)
"""
self._pylmp.set("atom", self.index, "x", value[0])
self._pylmp.set("atom", self.index, "y", value[1])
self._pylmp.set("atom", self.index, "z", value[2])
@property
def velocity(self):
return (self._pylmp.eval("vx[%d]" % self.index),
self._pylmp.eval("vy[%d]" % self.index),
self._pylmp.eval("vz[%d]" % self.index))
@velocity.setter
def velocity(self, value):
self._pylmp.set("atom", self.index, "vx", value[0])
self._pylmp.set("atom", self.index, "vy", value[1])
self._pylmp.set("atom", self.index, "vz", value[2])
@property
def force(self):
"""
Return the total force acting on the atom
:type: tuple (float, float, float)
"""
return (self._pylmp.eval("fx[%d]" % self.index),
self._pylmp.eval("fy[%d]" % self.index),
self._pylmp.eval("fz[%d]" % self.index))
@property
def charge(self):
"""
Return the atom charge
:type: float
"""
return self._pylmp.eval("q[%d]" % self.index)
# -------------------------------------------------------------------------
class Atom2D(Atom):
"""
A wrapper class then represents a single 2D atom inside of LAMMPS
Inherits all properties from the :py:class:`Atom` class, but returns 2D versions
of position, velocity, and force.
It provides access to properties of the atom and allows you to change some of them.
"""
def __init__(self, pylammps_instance, index):
super(Atom2D, self).__init__(pylammps_instance, index)
@property
def position(self):
"""
:getter: Return position of atom
:setter: Set position of atom
:type: tuple (float, float)
"""
return (self._pylmp.eval("x[%d]" % self.index),
self._pylmp.eval("y[%d]" % self.index))
@position.setter
def position(self, value):
self._pylmp.set("atom", self.index, "x", value[0])
self._pylmp.set("atom", self.index, "y", value[1])
@property
def velocity(self):
"""
:getter: Return velocity of atom
:setter: Set velocity of atom
:type: tuple (float, float)
"""
return (self._pylmp.eval("vx[%d]" % self.index),
self._pylmp.eval("vy[%d]" % self.index))
@velocity.setter
def velocity(self, value):
self._pylmp.set("atom", self.index, "vx", value[0])
self._pylmp.set("atom", self.index, "vy", value[1])
@property
def force(self):
"""
Return the total force acting on the atom
:type: tuple (float, float)
"""
return (self._pylmp.eval("fx[%d]" % self.index),
self._pylmp.eval("fy[%d]" % self.index))
# -------------------------------------------------------------------------
class variable_set:
def __init__(self, name, variable_dict):
self._name = name
array_pattern = re.compile(r"(?P<arr>.+)\[(?P<index>[0-9]+)\]")
for key, value in variable_dict.items():
m = array_pattern.match(key)
if m:
g = m.groupdict()
varname = g['arr']
idx = int(g['index'])
if varname not in self.__dict__:
self.__dict__[varname] = {}
self.__dict__[varname][idx] = value
else:
self.__dict__[key] = value
def __str__(self):
return "{}({})".format(self._name, ','.join(["{}={}".format(k, self.__dict__[k]) for k in self.__dict__.keys() if not k.startswith('_')]))
def __repr__(self):
return self.__str__()
# -------------------------------------------------------------------------
def get_thermo_data(output):
""" traverse output of runs and extract thermo data columns """
if isinstance(output, str):
lines = output.splitlines()
else:
lines = output
runs = []
columns = []
in_run = False
current_run = {}
for line in lines:
if line.startswith("Per MPI rank memory allocation"):
in_run = True
elif in_run and len(columns) == 0:
# first line after memory usage are column names
columns = line.split()
current_run = {}
for col in columns:
current_run[col] = []
elif line.startswith("Loop time of "):
in_run = False
columns = None
thermo_data = variable_set('ThermoData', current_run)
r = {'thermo' : thermo_data }
runs.append(namedtuple('Run', list(r.keys()))(*list(r.values())))
elif in_run and len(columns) > 0:
items = line.split()
# Convert thermo output and store it.
# It must have the same number of columns and
# all of them must be convertible to floats.
# Otherwise we ignore the line
if len(items) == len(columns):
try:
values = [float(x) for x in items]
for i, col in enumerate(columns):
current_run[col].append(values[i])
except ValueError:
pass
return runs
# -------------------------------------------------------------------------
# -------------------------------------------------------------------------
class PyLammps(object):
"""
This is a Python wrapper class around the lower-level
:py:class:`lammps` class, exposing a more Python-like,
object-oriented interface for prototyping system inside of IPython and
Jupyter notebooks.
It either creates its own instance of :py:class:`lammps` or can be
initialized with an existing instance. The arguments are the same of the
lower-level interface. The original interface can still be accessed via
:py:attr:`PyLammps.lmp`.
:param name: "machine" name of the shared LAMMPS library ("mpi" loads ``liblammps_mpi.so``, "" loads ``liblammps.so``)
:type name: string
:param cmdargs: list of command line arguments to be passed to the :cpp:func:`lammps_open` function. The executable name is automatically added.
:type cmdargs: list
:param ptr: pointer to a LAMMPS C++ class instance when called from an embedded Python interpreter. None means load symbols from shared library.
:type ptr: pointer
:param comm: MPI communicator (as provided by `mpi4py <mpi4py_docs_>`_). ``None`` means use ``MPI_COMM_WORLD`` implicitly.
:type comm: MPI_Comm
:ivar lmp: instance of original LAMMPS Python interface
:vartype lmp: :py:class:`lammps`
:ivar runs: list of completed runs, each storing the thermo output
:vartype run: list
"""
def __init__(self, name="", cmdargs=None, ptr=None, comm=None):
self.has_echo = False
if cmdargs:
if '-echo' in cmdargs:
idx = cmdargs.index('-echo')
# ensures that echo line is ignored during output capture
self.has_echo = idx+1 < len(cmdargs) and cmdargs[idx+1] in ('screen', 'both')
if ptr:
if isinstance(ptr,PyLammps):
self.lmp = ptr.lmp
elif isinstance(ptr,lammps):
self.lmp = ptr
else:
self.lmp = lammps(name=name,cmdargs=cmdargs,ptr=ptr,comm=comm)
else:
self.lmp = lammps(name=name,cmdargs=cmdargs,ptr=None,comm=comm)
print("LAMMPS output is captured by PyLammps wrapper")
self._cmd_history = []
self.runs = []
def __del__(self):
if self.lmp: self.lmp.close()
self.lmp = None
def close(self):
"""Explicitly delete a LAMMPS instance
This is a wrapper around the :py:meth:`lammps.close` of the Python interface.
"""
if self.lmp: self.lmp.close()
self.lmp = None
def version(self):
"""Return a numerical representation of the LAMMPS version in use.
This is a wrapper around the :py:meth:`lammps.version` function of the Python interface.
:return: version number
:rtype: int
"""
return self.lmp.version()
def file(self, file):
"""Read LAMMPS commands from a file.
This is a wrapper around the :py:meth:`lammps.file` function of the Python interface.
:param path: Name of the file/path with LAMMPS commands
:type path: string
"""
self.lmp.file(file)
def write_script(self, filepath):
"""
Write LAMMPS script file containing all commands executed up until now
:param filepath: path to script file that should be written
:type filepath: string
"""
with open(filepath, "w") as f:
for cmd in self._cmd_history:
print(cmd, file=f)
def command(self, cmd):
"""
Execute LAMMPS command
All commands executed will be stored in a command history which can be
written to a file using :py:meth:`PyLammps.write_script()`
:param cmd: command string that should be executed
:type: cmd: string
"""
self.lmp.command(cmd)
self._cmd_history.append(cmd)
def run(self, *args, **kwargs):
"""
Execute LAMMPS run command with given arguments
All thermo output during the run is captured and saved as new entry in
:py:attr:`PyLammps.runs`. The latest run can be retrieved by
:py:attr:`PyLammps.last_run`.
"""
output = self.__getattr__('run')(*args, **kwargs)
comm = self.lmp.get_mpi_comm()
if comm:
output = self.lmp.comm.bcast(output, root=0)
self.runs += get_thermo_data(output)
return output
@property
def last_run(self):
"""
Return data produced of last completed run command
:getter: Returns an object containing information about the last run command
:type: dict
"""
if len(self.runs) > 0:
return self.runs[-1]
return None
@property
def atoms(self):
"""
All atoms of this LAMMPS instance
:getter: Returns a list of atoms currently in the system
:type: AtomList
"""
return AtomList(self)
@property
def system(self):
"""
The system state of this LAMMPS instance
:getter: Returns an object with properties storing the current system state
:type: namedtuple
"""
output = self.info("system")
d = self._parse_info_system(output)
return namedtuple('System', d.keys())(*d.values())
@property
def communication(self):
"""
The communication state of this LAMMPS instance
:getter: Returns an object with properties storing the current communication state
:type: namedtuple
"""
output = self.info("communication")
d = self._parse_info_communication(output)
return namedtuple('Communication', d.keys())(*d.values())
@property
def computes(self):
"""
The list of active computes of this LAMMPS instance
:getter: Returns a list of computes that are currently active in this LAMMPS instance
:type: list
"""
output = self.info("computes")
return self._parse_element_list(output)
@property
def dumps(self):
"""
The list of active dumps of this LAMMPS instance
:getter: Returns a list of dumps that are currently active in this LAMMPS instance
:type: list
"""
output = self.info("dumps")
return self._parse_element_list(output)
@property
def fixes(self):
"""
The list of active fixes of this LAMMPS instance
:getter: Returns a list of fixes that are currently active in this LAMMPS instance
:type: list
"""
output = self.info("fixes")
return self._parse_element_list(output)
@property
def groups(self):
"""
The list of active atom groups of this LAMMPS instance
:getter: Returns a list of atom groups that are currently active in this LAMMPS instance
:type: list
"""
output = self.info("groups")
return self._parse_groups(output)
@property
def variables(self):
"""
Returns a dictionary of all variables defined in the current LAMMPS instance
:getter: Returns a dictionary of all variables that are defined in this LAMMPS instance
:type: dict
"""
output = self.info("variables")
vars = {}
for v in self._parse_element_list(output):
vars[v['name']] = Variable(self, v['name'], v['style'], v['def'])
return vars
def eval(self, expr):
"""
Evaluate expression
:param expr: the expression string that should be evaluated inside of LAMMPS
:type expr: string
:return: the value of the evaluated expression
:rtype: float if numeric, string otherwise
"""
value = self.lmp_print('"$(%s)"' % expr).strip()
try:
return float(value)
except ValueError:
return value
def _split_values(self, line):
return [x.strip() for x in line.split(',')]
def _get_pair(self, value):
return [x.strip() for x in value.split('=')]
def _parse_info_system(self, output):
lines = output[6:-2]
system = {}
for line in lines:
if line.startswith("Units"):
system['units'] = self._get_pair(line)[1]
elif line.startswith("Atom style"):
system['atom_style'] = self._get_pair(line)[1]
elif line.startswith("Atom map"):
system['atom_map'] = self._get_pair(line)[1]
elif line.startswith("Atoms"):
parts = self._split_values(line)
system['natoms'] = int(self._get_pair(parts[0])[1])
system['ntypes'] = int(self._get_pair(parts[1])[1])
system['style'] = self._get_pair(parts[2])[1]
elif line.startswith("Kspace style"):
system['kspace_style'] = self._get_pair(line)[1]
elif line.startswith("Dimensions"):
system['dimensions'] = int(self._get_pair(line)[1])
elif line.startswith("Orthogonal box"):
system['orthogonal_box'] = [float(x) for x in self._get_pair(line)[1].split('x')]
elif line.startswith("Boundaries"):
system['boundaries'] = self._get_pair(line)[1]
elif line.startswith("xlo"):
keys, values = [self._split_values(x) for x in self._get_pair(line)]
for key, value in zip(keys, values):
system[key] = float(value)
elif line.startswith("ylo"):
keys, values = [self._split_values(x) for x in self._get_pair(line)]
for key, value in zip(keys, values):
system[key] = float(value)
elif line.startswith("zlo"):
keys, values = [self._split_values(x) for x in self._get_pair(line)]
for key, value in zip(keys, values):
system[key] = float(value)
elif line.startswith("Molecule type"):
system['molecule_type'] = self._get_pair(line)[1]
elif line.startswith("Bonds"):
parts = self._split_values(line)
system['nbonds'] = int(self._get_pair(parts[0])[1])
system['nbondtypes'] = int(self._get_pair(parts[1])[1])
system['bond_style'] = self._get_pair(parts[2])[1]
elif line.startswith("Angles"):
parts = self._split_values(line)
system['nangles'] = int(self._get_pair(parts[0])[1])
system['nangletypes'] = int(self._get_pair(parts[1])[1])
system['angle_style'] = self._get_pair(parts[2])[1]
elif line.startswith("Dihedrals"):
parts = self._split_values(line)
system['ndihedrals'] = int(self._get_pair(parts[0])[1])
system['ndihedraltypes'] = int(self._get_pair(parts[1])[1])
system['dihedral_style'] = self._get_pair(parts[2])[1]
elif line.startswith("Impropers"):
parts = self._split_values(line)
system['nimpropers'] = int(self._get_pair(parts[0])[1])
system['nimpropertypes'] = int(self._get_pair(parts[1])[1])
system['improper_style'] = self._get_pair(parts[2])[1]
return system
def _parse_info_communication(self, output):
lines = output[6:-3]
comm = {}
for line in lines:
if line.startswith("MPI library"):
comm['mpi_version'] = line.split(':')[1].strip()
elif line.startswith("Comm style"):
parts = self._split_values(line)
comm['comm_style'] = self._get_pair(parts[0])[1]
comm['comm_layout'] = self._get_pair(parts[1])[1]
elif line.startswith("Processor grid"):
comm['proc_grid'] = [int(x) for x in self._get_pair(line)[1].split('x')]
elif line.startswith("Communicate velocities for ghost atoms"):
comm['ghost_velocity'] = (self._get_pair(line)[1] == "yes")
elif line.startswith("Nprocs"):
parts = self._split_values(line)
comm['nprocs'] = int(self._get_pair(parts[0])[1])
comm['nthreads'] = int(self._get_pair(parts[1])[1])
return comm
def _parse_element_list(self, output):
lines = output[6:-3]
elements = []
for line in lines:
element_info = self._split_values(line.split(':')[1].strip())
element = {'name': element_info[0]}
for key, value in [self._get_pair(x) for x in element_info[1:]]:
element[key] = value
elements.append(element)
return elements
def _parse_groups(self, output):
lines = output[6:-3]
groups = []
group_pattern = re.compile(r"(?P<name>.+) \((?P<type>.+)\)")
for line in lines:
m = group_pattern.match(line.split(':')[1].strip())
group = {'name': m.group('name'), 'type': m.group('type')}
groups.append(group)
return groups
def lmp_print(self, s):
""" needed for Python2 compatibility, since print is a reserved keyword """
return self.__getattr__("print")(s)
def __dir__(self):
return ['angle_coeff', 'angle_style', 'atom_modify', 'atom_style', 'atom_style',
'bond_coeff', 'bond_style', 'boundary', 'change_box', 'communicate', 'compute',
'create_atoms', 'create_box', 'delete_atoms', 'delete_bonds', 'dielectric',
'dihedral_coeff', 'dihedral_style', 'dimension', 'dump', 'fix', 'fix_modify',
'group', 'improper_coeff', 'improper_style', 'include', 'kspace_modify',
'kspace_style', 'lattice', 'mass', 'minimize', 'min_style', 'neighbor',
'neigh_modify', 'newton', 'nthreads', 'pair_coeff', 'pair_modify',
'pair_style', 'processors', 'read', 'read_data', 'read_restart', 'region',
'replicate', 'reset_timestep', 'restart', 'run', 'run_style', 'thermo',
'thermo_modify', 'thermo_style', 'timestep', 'undump', 'unfix', 'units',
'variable', 'velocity', 'write_restart']
def __getattr__(self, name):
"""
This method is where the Python 'magic' happens. If a method is not
defined by the class PyLammps, it assumes it is a LAMMPS command. It takes
all the arguments, concatinates them to a single string, and executes it using
:py:meth:`lammps.PyLammps.command()`.
:param verbose: Print output of command
:type verbose: bool
:return: line or list of lines of output, None if no output
:rtype: list or string
"""
def handler(*args, **kwargs):
cmd_args = [name] + [str(x) for x in args]
with OutputCapture() as capture:
cmd = ' '.join(cmd_args)
self.command(cmd)
output = capture.output
if 'verbose' in kwargs and kwargs['verbose']:
print(output)
lines = output.splitlines()
if self.has_echo:
lines = lines[1:]
if len(lines) > 1:
return lines
elif len(lines) == 1:
return lines[0]
return None
return handler
class IPyLammps(PyLammps):
"""
IPython wrapper for LAMMPS which adds embedded graphics capabilities to PyLammmps interface
It either creates its own instance of :py:class:`lammps` or can be
initialized with an existing instance. The arguments are the same of the
lower-level interface. The original interface can still be accessed via
:py:attr:`PyLammps.lmp`.
:param name: "machine" name of the shared LAMMPS library ("mpi" loads ``liblammps_mpi.so``, "" loads ``liblammps.so``)
:type name: string
:param cmdargs: list of command line arguments to be passed to the :cpp:func:`lammps_open` function. The executable name is automatically added.
:type cmdargs: list
:param ptr: pointer to a LAMMPS C++ class instance when called from an embedded Python interpreter. None means load symbols from shared library.
:type ptr: pointer
:param comm: MPI communicator (as provided by `mpi4py <mpi4py_docs_>`_). ``None`` means use ``MPI_COMM_WORLD`` implicitly.
:type comm: MPI_Comm
"""
def __init__(self,name="",cmdargs=None,ptr=None,comm=None):
super(IPyLammps, self).__init__(name=name,cmdargs=cmdargs,ptr=ptr,comm=comm)
def image(self, filename="snapshot.png", group="all", color="type", diameter="type",
size=None, view=None, center=None, up=None, zoom=1.0, background_color="white"):
""" Generate image using write_dump command and display it
See :doc:`dump image <dump_image>` for more information.
:param filename: Name of the image file that should be generated. The extension determines whether it is PNG or JPEG
:type filename: string
:param group: the group of atoms write_image should use
:type group: string
:param color: name of property used to determine color
:type color: string
:param diameter: name of property used to determine atom diameter
:type diameter: string
:param size: dimensions of image
:type size: tuple (width, height)
:param view: view parameters
:type view: tuple (theta, phi)
:param center: center parameters
:type center: tuple (flag, center_x, center_y, center_z)
:param up: vector pointing to up direction
:type up: tuple (up_x, up_y, up_z)
:param zoom: zoom factor
:type zoom: float
:param background_color: background color of scene
:type background_color: string
:return: Image instance used to display image in notebook
:rtype: :py:class:`IPython.core.display.Image`
"""
cmd_args = [group, "image", filename, color, diameter]
if size:
width = size[0]
height = size[1]
cmd_args += ["size", width, height]
if view:
theta = view[0]
phi = view[1]
cmd_args += ["view", theta, phi]
if center:
flag = center[0]
Cx = center[1]
Cy = center[2]
Cz = center[3]
cmd_args += ["center", flag, Cx, Cy, Cz]
if up:
Ux = up[0]
Uy = up[1]
Uz = up[2]
cmd_args += ["up", Ux, Uy, Uz]
if zoom:
cmd_args += ["zoom", zoom]
cmd_args.append("modify backcolor " + background_color)
self.write_dump(*cmd_args)
from IPython.core.display import Image
return Image(filename)
def video(self, filename):
"""
Load video from file
Can be used to visualize videos from :doc:`dump movie <dump_image>`.
:param filename: Path to video file
:type filename: string
:return: HTML Video Tag used by notebook to embed a video
:rtype: :py:class:`IPython.display.HTML`
"""
from IPython.display import HTML
return HTML("<video controls><source src=\"" + filename + "\"></video>")