コード例 #1
0
ファイル: _chamberparm.py プロジェクト: davidlmobley/ParmEd
    def fill_LJ(self):
        """
        Fills the LJ_radius, LJ_depth arrays and LJ_types dictionary with data
        from LENNARD_JONES_ACOEF and LENNARD_JONES_BCOEF sections of the prmtop
        files, by undoing the canonical combining rules.
        """
        AmberParm.fill_LJ(self)

        acoef = self.parm_data['LENNARD_JONES_14_ACOEF']
        bcoef = self.parm_data['LENNARD_JONES_14_BCOEF']
        ntypes = self.pointers['NTYPES']

        self.LJ_14_radius = []  # empty LJ_radii so it can be re-filled
        self.LJ_14_depth = []   # empty LJ_depths so it can be re-filled
        one_sixth = 1.0 / 6.0 # we need to raise some numbers to the 1/6th power

        for i in range(ntypes):
            lj_index = self.parm_data["NONBONDED_PARM_INDEX"][ntypes*i+i] - 1
            if acoef[lj_index] < 1.0e-6:
                self.LJ_14_radius.append(0)
                self.LJ_14_depth.append(0)
            else:
                factor = 2 * acoef[lj_index] / bcoef[lj_index]
                self.LJ_14_radius.append(pow(factor, one_sixth) * 0.5)
                self.LJ_14_depth.append(bcoef[lj_index] / 2 / factor)
コード例 #2
0
    def fill_LJ(self):
        """
        Fills the LJ_radius, LJ_depth arrays and LJ_types dictionary with data
        from LENNARD_JONES_ACOEF and LENNARD_JONES_BCOEF sections of the prmtop
        files, by undoing the canonical combining rules.
        """
        AmberParm.fill_LJ(self)

        acoef = self.parm_data['LENNARD_JONES_14_ACOEF']
        bcoef = self.parm_data['LENNARD_JONES_14_BCOEF']
        ntypes = self.pointers['NTYPES']

        self.LJ_14_radius = []  # empty LJ_radii so it can be re-filled
        self.LJ_14_depth = []   # empty LJ_depths so it can be re-filled
        one_sixth = 1.0 / 6.0 # we need to raise some numbers to the 1/6th power

        for i in xrange(ntypes):
            lj_index = self.parm_data["NONBONDED_PARM_INDEX"][ntypes*i+i] - 1
            if acoef[lj_index] < 1.0e-6:
                self.LJ_14_radius.append(0)
                self.LJ_14_depth.append(0)
            else:
                factor = 2 * acoef[lj_index] / bcoef[lj_index]
                self.LJ_14_radius.append(pow(factor, one_sixth) * 0.5)
                self.LJ_14_depth.append(bcoef[lj_index] / 2 / factor)
コード例 #3
0
ファイル: _chamberparm.py プロジェクト: davidlmobley/ParmEd
 def initialize_topology(self, rst7_name=None):
     """
     Initializes topology data structures, like the list of atoms, bonds,
     etc., after the topology file has been read. The following methods are
     called:
     """
     self.LJ_14_radius = []
     self.LJ_14_depth = []
     AmberParm.initialize_topology(self, rst7_name)
コード例 #4
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 def initialize_topology(self, rst7_name=None):
     """
     Initializes topology data structures, like the list of atoms, bonds,
     etc., after the topology file has been read. The following methods are
     called:
     """
     self.LJ_14_radius = []
     self.LJ_14_depth = []
     AmberParm.initialize_topology(self, rst7_name)
コード例 #5
0
ファイル: _chamberparm.py プロジェクト: davidlmobley/ParmEd
 def load_pointers(self):
     """
     Loads the data in POINTERS section into a pointers dictionary with each
     key being the pointer name according to http://ambermd.org/formats.html
     """
     AmberParm.load_pointers(self)
     # Other pointers
     nub, nubtypes = self.parm_data['CHARMM_UREY_BRADLEY_COUNT'][:2]
     self.pointers['NUB'] = nub
     self.pointers['NUBTYPES'] = nubtypes
     self.pointers['NIMPHI'] = self.parm_data['CHARMM_NUM_IMPROPERS'][0]
     self.pointers['NIMPRTYPES'] = self.parm_data['CHARMM_NUM_IMPR_TYPES'][0]
     # If CMAP is not present, don't load the pointers
     if self.has_cmap:
         self.pointers['CMAP'] = self.parm_data['CHARMM_CMAP_COUNT'][0]
         self.pointers['CMAP_TYPES'] = self.parm_data['CHARMM_CMAP_COUNT'][1]
コード例 #6
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 def load_pointers(self):
     """
     Loads the data in POINTERS section into a pointers dictionary with each
     key being the pointer name according to http://ambermd.org/formats.html
     """
     AmberParm.load_pointers(self)
     # Other pointers
     nub, nubtypes = self.parm_data['CHARMM_UREY_BRADLEY_COUNT'][:2]
     self.pointers['NUB'] = nub
     self.pointers['NUBTYPES'] = nubtypes
     self.pointers['NIMPHI'] = self.parm_data['CHARMM_NUM_IMPROPERS'][0]
     self.pointers['NIMPRTYPES'] = self.parm_data['CHARMM_NUM_IMPR_TYPES'][0]
     # If CMAP is not present, don't load the pointers
     if self.has_cmap:
         self.pointers['CMAP'] = self.parm_data['CHARMM_CMAP_COUNT'][0]
         self.pointers['CMAP_TYPES'] = self.parm_data['CHARMM_CMAP_COUNT'][1]
コード例 #7
0
ファイル: _chamberparm.py プロジェクト: davidlmobley/ParmEd
 def recalculate_LJ(self):
     """
     Takes the values of the LJ_radius and LJ_depth arrays and recalculates
     the LENNARD_JONES_A/BCOEF topology sections from the canonical
     combining rules.
     """
     AmberParm.recalculate_LJ(self)
     ntypes = self.pointers['NTYPES']
     acoef = self.parm_data['LENNARD_JONES_14_ACOEF']
     bcoef = self.parm_data['LENNARD_JONES_14_BCOEF']
     for i in range(ntypes):
         for j in range(i, ntypes):
             index = self.parm_data['NONBONDED_PARM_INDEX'][ntypes*i+j] - 1
             rij = self.LJ_14_radius[i] + self.LJ_14_radius[j]
             wdij = sqrt(self.LJ_14_depth[i] * self.LJ_14_depth[j])
             acoef[index] = wdij * rij ** 12
             bcoef[index] = 2 * wdij * rij**6
コード例 #8
0
 def recalculate_LJ(self):
     """
     Takes the values of the LJ_radius and LJ_depth arrays and recalculates
     the LENNARD_JONES_A/BCOEF topology sections from the canonical
     combining rules.
     """
     AmberParm.recalculate_LJ(self)
     ntypes = self.pointers['NTYPES']
     acoef = self.parm_data['LENNARD_JONES_14_ACOEF']
     bcoef = self.parm_data['LENNARD_JONES_14_BCOEF']
     for i in xrange(ntypes):
         for j in xrange(i, ntypes):
             index = self.parm_data['NONBONDED_PARM_INDEX'][ntypes*i+j] - 1
             rij = self.LJ_14_radius[i] + self.LJ_14_radius[j]
             wdij = sqrt(self.LJ_14_depth[i] * self.LJ_14_depth[j])
             acoef[index] = wdij * rij ** 12
             bcoef[index] = 2 * wdij * rij**6