LAMMPS.py 14.3 KB
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#MDANSE : Molecular Dynamics Analysis for Neutron Scattering Experiments
#------------------------------------------------------------------------------------------
#Copyright (C)
#2015- Eric C. Pellegrini Institut Laue-Langevin
#BP 156
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#71 avenue des Martyrs
#38000 Grenoble Cedex 9
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#France
#pellegrini[at]ill.fr
#goret[at]ill.fr
#aoun[at]ill.fr
#
#This library is free software; you can redistribute it and/or
#modify it under the terms of the GNU Lesser General Public
#License as published by the Free Software Foundation; either
#version 2.1 of the License, or (at your option) any later version.
#
#This library is distributed in the hope that it will be useful,
#but WITHOUT ANY WARRANTY; without even the implied warranty of
#MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
#Lesser General Public License for more details.
#
#You should have received a copy of the GNU Lesser General Public
#License along with this library; if not, write to the Free Software
#Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA

''' 
Created on Apr 10, 2015

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:author: Eric C. Pellegrini
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'''

import collections
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import os
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import re

import numpy

from MMTK import Atom, AtomCluster
from MMTK import Units
from MMTK.Trajectory import Trajectory, SnapshotGenerator, TrajectoryOutput
from MMTK.Universe import ParallelepipedicPeriodicUniverse

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from MDANSE import ELEMENTS, REGISTRY
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from MDANSE.Core.Error import Error
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from MDANSE.Framework.Jobs.Converter import Converter
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from MDANSE.Mathematics.Graph import Graph

class LAMMPSConfigFileError(Error):
    pass

class LAMMPSTrajectoryFileError(Error):
    pass

class LAMMPSConfigFile(dict):

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    def __init__(self, filename,tolerance):
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        self._filename = filename
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        self._tolerance = tolerance
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        self['n_bonds'] = None

        self['bonds'] = []
                
        self['n_atoms'] = None
        
        self["n_atom_types"] = None
        
        self["elements"] = {}
                
        unit = open(self._filename, 'r')
        lines = []
        for l in unit.readlines():
            l = l.strip()
            if l:
                lines.append(l)        
        unit.close()
    
        for i, line in enumerate(lines):
                                        
            if self['n_atoms'] is None:
                m = re.match("^(\d+) atoms$",line, re.I) 
                if m:
                    self['n_atoms'] = int(m.groups()[0])
                  
            if self["n_atom_types"] is None: 
                m = re.match("^(\d+) atom types$",line, re.I)             
                if m:
                    self["n_atom_types"] = int(m.groups()[0])

            if self['n_bonds'] is None:
                m = re.match("^(\d+) bonds$",line, re.I) 
                if m:
                    self['n_bonds'] = int(m.groups()[0])

            if re.match("^masses$", line, re.I):
                
                if self["n_atom_types"] is None:
                    raise LAMMPSConfigFileError("Did not find the number of atom types.")
                                                                    
                for j in range(1, self["n_atom_types"]+1):
                    idx, mass = lines[i+j].strip().split()
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                    idx = int(idx)
                    mass = float(mass)
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                    el = ELEMENTS.match_numeric_property("atomic_weight", mass, tolerance=self._tolerance)
                    nElements = len(el)
                    if nElements == 0:
                        raise LAMMPSConfigFileError("The atom %d with defined mass %f could not be assigned with a tolerance of %f. Please modify the mass in the config file to comply with MDANSE internal database" % (idx,mass,self._tolerance))
                    elif nElements > 1:
                        raise LAMMPSConfigFileError("The atoms %s of MDANSE database matches the mass %f with a tolerance of %f. Please modify the mass in the config file to comply with MDANSE internal database" % (el,mass,self._tolerance))
                    else:                    
                        self["elements"][idx] = el[0]
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            m = re.match("^bonds$",line, re.I)
            if m:
                for j in range(1, self['n_bonds']+1):
                    _,_,at1,at2 = lines[i+j].split()
                    at1 = int(at1)-1
                    at2 = int(at2)-1
                    self['bonds'].append([at1,at2])
                self['bonds'] = numpy.array(self['bonds'], dtype=numpy.int32)
                                                   
        unit.close()

                
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class LAMMPSConverter(Converter):
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    """
    Converts a LAMMPS trajectory to a MMTK trajectory.
    """
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    label = "LAMMPS"

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    settings = collections.OrderedDict()        
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    settings['config_file'] = ('input_file', {'label':"LAMMPS configuration file",
                                              'default':os.path.join('..','..','..','Data','Trajectories','LAMMPS','glycyl_L_alanine_charmm.config')})
    settings['trajectory_file'] = ('input_file', {'label':"LAMMPS trajectory file",
                                                  'default':os.path.join('..','..','..','Data','Trajectories','LAMMPS','glycyl_L_alanine_charmm.lammps')})
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    settings['mass_tolerance'] = ('float', {'label':"mass tolerance (uma)", 'default':1.0e-5, 'mini':1.0e-9})        
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    settings['time_step'] = ('float', {'label':"time step (fs)", 'default':1.0, 'mini':1.0e-9})        
    settings['n_steps'] = ('integer', {'label':"number of time steps", 'default':1, 'mini':0})        
    settings['output_file'] = ('output_files', {'formats':["netcdf"]})
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    def initialize(self):
        '''
        Initialize the job.
        '''
                
        # The number of steps of the analysis.
        self.numberOfSteps = self.configuration["n_steps"]["value"]
        
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        self._lammpsConfig = LAMMPSConfigFile(self.configuration["config_file"]["value"],self.configuration["mass_tolerance"]["value"])
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        self.parse_first_step()
        
        # A MMTK trajectory is opened for writing.
        self._trajectory = Trajectory(self._universe, self.configuration['output_file']['files'][0], mode='w')

        self._nameToIndex = dict([(at.name,at.index) for at in self._universe.atomList()])

        # A frame generator is created.
        self._snapshot = SnapshotGenerator(self._universe, actions = [TrajectoryOutput(self._trajectory, ["all"], 0, None, 1)])

        self._lammps.seek(0,0)

        self._start = 0

    def run_step(self, index):
        """Runs a single step of the job.
        
        @param index: the index of the step.
        @type index: int.

        @note: the argument index is the index of the loop note the index of the frame.      
        """

        for _ in range(self._itemsPosition["TIMESTEP"][0]):
            line = self._lammps.readline()
            if not line:
                return index, None

        timeStep = Units.fs*float(self._lammps.readline())*self.configuration['time_step']['value']

        for _ in range(self._itemsPosition["TIMESTEP"][1], self._itemsPosition["BOX BOUNDS"][0]):
            self._lammps.readline()

        abcVectors = numpy.zeros((9), dtype=numpy.float64)
        temp = [float(v) for v in self._lammps.readline().split()]
        if len(temp) == 2:
            xlo, xhi = temp
            xy = 0.0
        elif len(temp) == 3:
            xlo, xhi, xy = temp
        else:
            raise LAMMPSTrajectoryFileError("Bad format for A vector components")

        temp = [float(v) for v in self._lammps.readline().split()]
        if len(temp) == 2:
            ylo, yhi = temp
            xz = 0.0
        elif len(temp) == 3:
            ylo, yhi, xz = temp
        else:
            raise LAMMPSTrajectoryFileError("Bad format for B vector components")

        temp = [float(v) for v in self._lammps.readline().split()]
        if len(temp) == 2:
            zlo, zhi = temp
            yz = 0.0
        elif len(temp) == 3:
            zlo, zhi, yz = temp
        else:
            raise LAMMPSTrajectoryFileError("Bad format for C vector components")
                      
        # The ax component.                                      
        abcVectors[0] = xhi - xlo
        
        # The bx and by components.                                      
        abcVectors[3] = xy
        abcVectors[4] = yhi - ylo
        
        # The cx, cy and cz components.                                      
        abcVectors[6] = xz
        abcVectors[7] = yz
        abcVectors[8] = zhi - zlo

        abcVectors *= Units.Ang

        for _ in range(self._itemsPosition["BOX BOUNDS"][1], self._itemsPosition["ATOMS"][0]):
            self._lammps.readline()

        self._universe.setCellParameters(abcVectors)

        conf = self._universe.configuration()

        for i,_ in enumerate(range(self._itemsPosition["ATOMS"][0], self._itemsPosition["ATOMS"][1])):
            temp = self._lammps.readline().split()
            idx = self._nameToIndex[self._rankToName[i]]
            conf.array[idx,:] = numpy.array([temp[self._x],temp[self._y],temp[self._z]],dtype=numpy.float64)

        if self._fractionalCoordinates:
            conf.array = self._universe._boxToRealPointArray(conf.array)
        else:
            conf.array *= Units.Ang
            
        # The whole configuration is folded in to the simulation box.
        self._universe.foldCoordinatesIntoBox()

        # A snapshot is created out of the current configuration.
        self._snapshot(data = {'time': timeStep})

        self._start += self._last
        
        return index, None

    def combine(self, index, x):
        """
        @param index: the index of the step.
        @type index: int.
        
        @param x:
        @type x: any.
        """

        pass

    def finalize(self):
        """
        Finalize the job.
        """
        
        self._lammps.close()

        if self._lammpsConfig["n_bonds"] is not None:
            netcdf = self._trajectory.trajectory.file
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            netcdf.createDimension("MDANSE_NBONDS",self._lammpsConfig["n_bonds"])
            netcdf.createDimension("MDANSE_TWO",2)
            VAR = netcdf.createVariable("mdanse_bonds", numpy.dtype(numpy.int32).char, ("MDANSE_NBONDS","MDANSE_TWO"))
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            VAR.assignValue(self._lammpsConfig["bonds"]) 
                
        # Close the output trajectory.
        self._trajectory.close()
                        
    def parse_first_step(self):

        self._lammps = open(self.configuration["trajectory_file"]["value"], 'r')        

        self._itemsPosition = collections.OrderedDict()

        self._universe = None
        comp = -1

        while True:

            line = self._lammps.readline()
            comp += 1

            if not line:
                break

            if line.startswith("ITEM: TIMESTEP"):
                self._itemsPosition["TIMESTEP"] = [comp+1, comp+2]
                continue

            elif line.startswith("ITEM: BOX BOUNDS"):
                self._itemsPosition["BOX BOUNDS"] = [comp+1, comp+4]
                continue

            elif line.startswith("ITEM: ATOMS"):
                
                keywords = line.split()[2:]
                
                self._id = keywords.index("id")
                self._type = keywords.index("type")
                
                try:
                    self._x = keywords.index("x")
                    self._y = keywords.index("y")
                    self._z = keywords.index("z")
                except ValueError:
                    try:
                        self._x = keywords.index("xs")
                        self._y = keywords.index("ys")
                        self._z = keywords.index("zs")
                    except ValueError:
                        raise LAMMPSTrajectoryFileError("No coordinates could be found in the trajectory")
                    else:
                        self._fractionalCoordinates = True
                        
                else:
                    self._fractionalCoordinates = False
                    
                self._rankToName = {}
                
                g = Graph()
                self._universe = ParallelepipedicPeriodicUniverse()
                self._itemsPosition["ATOMS"] = [comp+1,comp+self._nAtoms+1]                                
                for i in range(self._nAtoms):
                    temp = self._lammps.readline().split()
                    idx = int(temp[self._id])-1
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                    ty = int(temp[self._type])
                    name = "%s%d" % (self._lammpsConfig["elements"][ty],idx)
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                    self._rankToName[i] = name
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                    g.add_node(idx, element=self._lammpsConfig["elements"][ty], atomName=name)
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                if self._lammpsConfig["n_bonds"] is not None:
                    for idx1,idx2 in self._lammpsConfig["bonds"]:
                        g.add_link(idx1,idx2)
                
                for cluster in g.build_connected_components():
                    if len(cluster) == 1:
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                        node = cluster.pop()
                        obj = Atom(node.element, name=node.atomName)
                        obj.index = node.name
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                    else:
                        atList = []
                        for atom in cluster:
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                            at = Atom(atom.element, name=atom.atomName)
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                            atList.append(at) 
                        c = collections.Counter([at.element for at in cluster])
                        name = "".join(["%s%d" % (k,v) for k,v in sorted(c.items())])
                        obj = AtomCluster(atList, name=name)
                        
                    self._universe.addObject(obj)
                self._last = comp + self._nAtoms + 1

                break
                    
            elif line.startswith("ITEM: NUMBER OF ATOMS"):
                self._nAtoms = int(self._lammps.readline())
                comp += 1
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                continue
            
REGISTRY['lammps'] = LAMMPSConverter