Split core.py into more files

This commit is contained in:
Richard Berger
2020-12-15 16:33:21 -05:00
parent 9e188a3818
commit 33f9a29639
5 changed files with 462 additions and 409 deletions

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@ -1,2 +1,4 @@
from .constants import *
from .core import * from .core import *
from .data import *
from .pylammps import * from .pylammps import *

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@ -0,0 +1,49 @@
# ----------------------------------------------------------------------
# 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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@ -25,40 +25,8 @@ from ctypes import *
from os.path import dirname,abspath,join from os.path import dirname,abspath,join
from inspect import getsourcefile from inspect import getsourcefile
# various symbolic constants to be used from .constants import *
# in certain calls to select data formats from .data import *
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
# ------------------------------------------------------------------------- # -------------------------------------------------------------------------
@ -71,94 +39,6 @@ class MPIAbortException(Exception):
# ------------------------------------------------------------------------- # -------------------------------------------------------------------------
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)
# -------------------------------------------------------------------------
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
# -------------------------------------------------------------------------
# -------------------------------------------------------------------------
class lammps(object): class lammps(object):
"""Create an instance of the LAMMPS Python class. """Create an instance of the LAMMPS Python class.
@ -521,6 +401,7 @@ class lammps(object):
:rtype: numpy_wrapper :rtype: numpy_wrapper
""" """
if not self._numpy: if not self._numpy:
from .numpy import numpy_wrapper
self._numpy = numpy_wrapper(self) self._numpy = numpy_wrapper(self)
return self._numpy return self._numpy
@ -1789,290 +1670,3 @@ class lammps(object):
computeid = computeid.encode() computeid = computeid.encode()
idx = self.lib.lammps_find_compute_neighlist(self.lmp, computeid, request) idx = self.lib.lammps_find_compute_neighlist(self.lmp, computeid, request)
return idx return idx
# -------------------------------------------------------------------------
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

73
python/lammps/data.py Normal file
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@ -0,0 +1,73 @@
# ----------------------------------------------------------------------
# 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)

335
python/lammps/numpy.py Normal file
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@ -0,0 +1,335 @@
# ----------------------------------------------------------------------
# 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
import numpy as np
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):
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
"""
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):
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):
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