Updated copyright information.

Refactored ENM code and tests to reflect ModelBase.
Added CG topology and trajectory files to test data.

Signed-off-by: Timothy Click <tcthepoet@yahoo.com>

src/fluctmatch/models/__init__.py

@@ -1,19 +1,40 @@
-# -*- Mode: python; tab-width: 4; indent-tabs-mode:nil; coding: utf-8 -*-
-# vim: tabstop=4 expandtab shiftwidth=4 softtabstop=4
+# -*- coding: utf-8 -*-
 #
-# fluctmatch --- https://github.com/tclick/python-fluctmatch
-# Copyright (c) 2013-2017 The fluctmatch Development Team and contributors
-# (see the file AUTHORS for the full list of names)
+#  python-fluctmatch -
+#  Copyright (c) 2019 Timothy H. Click, Ph.D.
 #
-# Released under the New BSD license.
+#  All rights reserved.
 #
-# Please cite your use of fluctmatch in published work:
+#  Redistribution and use in source and binary forms, with or without
+#  modification, are permitted provided that the following conditions are met:
 #
-# Timothy H. Click, Nixon Raj, and Jhih-Wei Chu.
-# Calculation of Enzyme Fluctuograms from All-Atom Molecular Dynamics
-# Simulation. Meth Enzymology. 578 (2016), 327-342,
-# doi:10.1016/bs.mie.2016.05.024.
+#  Redistributions of source code must retain the above copyright notice, this
+#  list of conditions and the following disclaimer.
 #
+#  Redistributions in binary form must reproduce the above copyright notice,
+#  this list of conditions and the following disclaimer in the documentation
+#  and/or other materials provided with the distribution.
+#
+#  Neither the name of the author nor the names of its contributors may be used
+#  to endorse or promote products derived from this software without specific
+#  prior written permission.
+#
+#  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS”
+#  AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+#  IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+#  ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR
+#  ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+#  DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+#  SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+#  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+#  OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+#  OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+#
+#  Timothy H. Click, Nixon Raj, and Jhih-Wei Chu.
+#  Simulation. Meth Enzymology. 578 (2016), 327-342,
+#  Calculation of Enzyme Fluctuograms from All-Atom Molecular Dynamics
+#  doi:10.1016/bs.mie.2016.05.024.
+
 import logging
 
 from .enm import Enm

src/fluctmatch/models/enm.py

@@ -1,27 +1,49 @@
 # -*- coding: utf-8 -*-
-# vim: tabstop=4 expandtab shiftwidth=4 softtabstop=4
 #
-# fluctmatch --- https://github.com/tclick/python-fluctmatch
-# Copyright (c) 2013-2017 The fluctmatch Development Team and contributors
-# (see the file AUTHORS for the full list of names)
+#  python-fluctmatch -
+#  Copyright (c) 2019 Timothy H. Click, Ph.D.
 #
-# Released under the New BSD license.
+#  All rights reserved.
 #
-# Please cite your use of fluctmatch in published work:
+#  Redistribution and use in source and binary forms, with or without
+#  modification, are permitted provided that the following conditions are met:
 #
-# Timothy H. Click, Nixon Raj, and Jhih-Wei Chu.
-# Calculation of Enzyme Fluctuograms from All-Atom Molecular Dynamics
-# Simulation. Meth Enzymology. 578 (2016), 327-342,
-# doi:10.1016/bs.mie.2016.05.024.
+#  Redistributions of source code must retain the above copyright notice, this
+#  list of conditions and the following disclaimer.
 #
-import numpy as np
-from MDAnalysis.core import topologyattrs
-from MDAnalysis.lib.distances import distance_array, self_capped_distance
-from fluctmatch.fluctmatch import utils as fmutils
-from fluctmatch.models.base import (
-    ModelBase,
-    rename_universe,
-)
+#  Redistributions in binary form must reproduce the above copyright notice,
+#  this list of conditions and the following disclaimer in the documentation
+#  and/or other materials provided with the distribution.
+#
+#  Neither the name of the author nor the names of its contributors may be used
+#  to endorse or promote products derived from this software without specific
+#  prior written permission.
+#
+#  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS”
+#  AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+#  IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+#  ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR CONTRIBUTORS BE LIABLE FOR
+#  ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+#  DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+#  SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+#  CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+#  OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+#  OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+#
+#  Timothy H. Click, Nixon Raj, and Jhih-Wei Chu.
+#  Simulation. Meth Enzymology. 578 (2016), 327-342,
+#  Calculation of Enzyme Fluctuograms from All-Atom Molecular Dynamics
+#  doi:10.1016/bs.mie.2016.05.024.
+"""Class for elastic network model."""
+
+from typing import List, Optional, Tuple
+
+import MDAnalysis as mda
+from MDAnalysis.core.topologyattrs import Atomtypes, Charges, Bonds
+from MDAnalysis.lib import distances
+
+from .base import ModelBase, rename_universe
+from .selection import *
 
 
 class Enm(ModelBase):
@@ -30,96 +52,97 @@ class Enm(ModelBase):
     Determines the interactions between beads via distance cutoffs `rmin` and
     `rmax`. The atoms and residues are also renamed to prevent name collision
     when working with fluctuation matching.
-    """
-    model = "ENM"
-    describe = "Elastic network model"
 
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-        self._rmin: float = kwargs.get("rmin", 0.)
-        self._rmax: float = kwargs.get("rmax", 10.)
-        self._initialize(*args, **kwargs)
+        Parameters
+    ----------
+    extended : bool, optional
+        Renames the residues and atoms according to the extended CHARMM PSF
+        format. Standard CHARMM PSF limits the residue and atom names to four
+        characters, but the extended CHARMM PSF permits eight characters. The
+        residues and atoms are renamed according to the number of segments
+        (1: A, 2: B, etc.) and then the residue number or atom index number.
+    xplor : bool, optional
+        Assigns the atom type as either a numerical or an alphanumerical
+        designation. CHARMM normally assigns a numerical designation, but the
+        XPLOR version permits an alphanumerical designation with a maximum
+        size of 4. The numerical form corresponds to the atom index number plus
+        a factor of 100, and the alphanumerical form will be similar the
+        standard CHARMM atom name.
+    com : bool, optional
+        Calculates the bead coordinates using either the center of mass
+        (default) or center of geometry.
+    guess_angles : bool, optional
+        Once Universe has been created, attempt to guess the connectivity
+        between atoms.  This will populate the .angles, .dihedrals, and
+        .impropers attributes of the Universe.
+    cutoff : float, optional
+        Used as a bond distance cutoff for an elastic network model; otherwise,
+        ignored.
+    min_cutoff : float, optional
+        Used as a minimum bond distance cutoff for an elastic network model;
+        otherwise, ignored.
+    charges : bool, optional
+        If True, keeps the original charges; otherwise, sets the charges to 0.
+
+    Attributes
+    ----------
+    universe : :class:`~MDAnalysis.Universe`
+        The transformed universe
 
-    def __repr__(self) -> str:
-        message: str = f"<CG Universe with {self.atoms.n_atoms} beads"
-        try:
-            message += f" and {len(self._topology.bonds.values)} bonds"
-        except AttributeError as exc:
-            pass
-        finally:
-            message += ">"
-        return message
-
-    def _initialize(self, *args, **kwargs):
-        self.__dict__.update(self.atu.__dict__)
-
-        rename_universe(self)
-        charges: bool = kwargs.get("charges", False)
-        if not charges:
-            self._topology.add_TopologyAttr(
-                topologyattrs.Charges(np.zeros(self.atoms.n_atoms))
-            )
-        self._topology.add_TopologyAttr(
-            topologyattrs.Atomtypes(np.arange(self.atoms.n_atoms) + 1)
-        )
-        self._topology.add_TopologyAttr(topologyattrs.Angles([]))
-        self._topology.add_TopologyAttr(topologyattrs.Dihedrals([]))
-        self._topology.add_TopologyAttr(topologyattrs.Impropers([]))
-        self._generate_from_topology()
-
-        self._add_bonds()
-        if kwargs.get("guess_angles", False):
-            self._add_angles()
-            self._add_dihedrals()
-            self._add_impropers()
+    """
+    model: str = "ENM"
+    describe: str = "Elastic network model"
 
-    def _add_bonds(self):
-        positions: np.ndarray = fmutils.AverageStructure(self.atu.atoms).run().result
-        pairs, _ = self_capped_distance(
-            positions, self._rmax, min_cutoff=self._rmin
-        )
-        bonds = topologyattrs.Bonds(np.unique(pairs, axis=0))
-        self._topology.add_TopologyAttr(bonds)
-        self._generate_from_topology()
-
-    @property
-    def rmin(self) -> float:
-        """The minimum distance required to define a bond interaction.
-
-        Returns
-        -------
-        float
-        """
-        return self._rmin
+    def __init__(self,
+                 xplor: bool = True,
+                 extended: bool = True,
+                 com: bool = True,
+                 guess_angles: bool = False,
+                 cutoff: float = 10.0,
+                 min_cutoff: Optional[float] = None,
+                 charges: bool = False):
+        super().__init__(xplor, extended, com, guess_angles, cutoff)
+
+        self._min_cutoff: Optional[float] = min_cutoff
+        self._charges: bool = charges
 
-    @rmin.setter
-    def rmin(self, distance: float):
-        """Set the minimum distance required for a bond definition.
+    def create_topology(self, universe: mda.Universe):
+        """Deteremine the topology attributes and initialize the universe.
 
         Parameters
         ----------
-        distance : float
-            Minimum distance between beads
+        universe : :class:`~MDAnalysis.Universe`
+            An all-atom universe
         """
-        self._rmin: float = distance
+        try:
+            self.universe = universe.copy()
+        except TypeError:
+            self.universe = universe
 
-    @property
-    def rmax(self) -> float:
-        """The maximum distance required to define a bond interaction.
+        rename_universe(self.universe)
 
-        Returns
-        -------
-        float
-        """
-        return self._rmax
+        if not self._charges:
+            charges = np.zeros(self.universe.atoms.n_atoms)
+            self.universe.add_TopologyAttr(Charges(charges))
 
-    @rmax.setter
-    def rmax(self, distance: float):
-        """Set the maximum distance required for a bond definition.
+        atomtypes: np.ndarray = np.arange(self.universe.atoms.n_atoms) + 1
+        self.universe.add_TopologyAttr(Atomtypes(atomtypes))
 
-        Parameters
-        ----------
-        distance : float
-            Maximum distance between beads
-        """
-        self._rmax: float = distance
+    def add_trajectory(self, universe: mda.Universe):
+        pass
+
+    def _add_bonds(self):
+        positions: np.ndarray = np.zeros_like(self.universe.atoms.positions)
+        for _ in self.universe.trajectory:
+            positions += self.universe.atoms.positions
+        self.universe.trajectory.rewind()
+        positions /= self.universe.trajectory.n_frames
+
+        pairs, _ = distances.self_capped_distance(positions, self._cutoff,
+                                                  min_cutoff=self._min_cutoff)
+        pairs: List[Tuple[int, int]] = [
+            tuple(_)
+            for _ in np.unique(pairs, axis=0)
+        ]
+        bonds: Bonds = Bonds(pairs)
+        self.universe.add_TopologyAttr(bonds)