Exemple #1
0
def reduceModel(model, atoms, select):
    """Return reduced NMA model.  Reduces a :class:`~.NMA` model to a subset of 
    *atoms* matching *select*.  This function behaves differently depending on 
    the type of the *model* argument.  For :class:`.ANM` and :class:`.GNM` or 
    other :class:`.NMA` models, force constant matrix for system of interest 
    (specified by the *select*) is derived from the force constant matrix for 
    the *model* by assuming that for any given displacement of the system of 
    interest, other atoms move along in such a way as to minimize the potential
    energy.  This is based on the formulation in [KH00]_.  For :class:`.PCA` 
    models, this function simply takes the sub-covariance matrix for selection.

    :arg model: dynamics model
    :type model: :class:`.ANM`, :class:`.GNM`, or :class:`.PCA`
    
    :arg atoms: atoms that were used to build the model
    :type atoms: :class:`.Atomic`
    
    :arg select: an atom selection or a selection string 
    :type select: :class:`.Selection`, str 
    
    :returns: (:class:`.NMA`, :class:`.Selection`)"""
    
    linalg = importLA()

    if not isinstance(model, NMA):
        raise TypeError('model must be an NMA instance, not {0:s}'
                        .format(type(model)))
    if not isinstance(atoms, (AtomGroup, AtomSubset, AtomMap)):
        raise TypeError('atoms type is not valid')
    if len(atoms) <= 1:
        raise TypeError('atoms must contain more than 1 atoms')

    if isinstance(model, GNM):
        matrix = model._kirchhoff
    elif isinstance(model, ANM):
        matrix = model._hessian
    elif isinstance(model, PCA):
        matrix = model._cov
    else:
        raise TypeError('model does not have a valid type derived from NMA')
    if matrix is None:
        raise ValueError('model matrix (Hessian/Kirchhoff/Covariance) is not '
                         'built')

    if isinstance(select, str):
        system = SELECT.getBoolArray(atoms, select)
        n_sel = sum(system)
        if n_sel == 0:
            raise ValueError('select matches 0 atoms')
        if len(atoms) == n_sel:
            raise ValueError('select matches all atoms')

        if isinstance(atoms, AtomGroup):
            ag = atoms
            which = np.arange(len(atoms))[system]
        else:
            ag = atoms.getAtomGroup()
            which = atoms._getIndices()[system]
        sel = Selection(ag, which, select, atoms.getACSIndex())
        
    elif isinstance(select, AtomSubset):
        sel = select
        if isinstance(atoms, AtomGroup):
            if sel.getAtomGroup() != atoms:
                raise ValueError('select and atoms do not match')
            system = np.zeros(len(atoms), bool)
            system[sel._getIndices()] = True 
        else:
            if atoms.getAtomGroup() != sel.getAtomGroup():
                raise ValueError('select and atoms do not match')
            elif not sel in atoms:
                raise ValueError('select is not a subset of atoms')
            idxset = set(atoms._getIndices())
            system = np.array([idx in idxset for idx in sel._getIndices()])
    
    else:
        raise TypeError('select must be a string or a Selection instance')
    
    other = np.invert(system)

    if model.is3d():
        system = np.tile(system, (3,1)).transpose().flatten()
        other = np.tile(other, (3,1)).transpose().flatten()
    ss = matrix[system,:][:,system]
    if isinstance(model, PCA):
        eda = PCA(model.getTitle() + ' reduced')
        eda.setCovariance(ss)
        return eda, system
    so = matrix[system,:][:,other]
    os = matrix[other,:][:,system]
    oo = matrix[other,:][:,other]
    matrix = ss - np.dot(so, np.dot(linalg.inv(oo), os))
    
    if isinstance(model, GNM):
        gnm = GNM(model.getTitle() + ' reduced')
        gnm.setKirchhoff(matrix)
        return gnm, sel
    elif isinstance(model, ANM):
        anm = ANM(model.getTitle() + ' reduced')
        anm.setHessian(matrix)
        return anm, sel
    elif isinstance(model, PCA):
        eda = PCA(model.getTitle() + ' reduced')
        eda.setCovariance(matrix)
        return eda, sel
Exemple #2
0
def reduceModel(model, atoms, selstr):
    """Return reduced NMA model.
    
    Reduces a :class:`NMA` model to a subset of *atoms* matching a selection 
    *selstr*.  This function behaves differently depending on the type of the 
    *model* argument.  For ANM and GNM or other NMA models, this functions 
    derives the force constant matrix for system of interest (specified by the 
    *selstr*) from the force constant matrix for the *model* by assuming that 
    for any given displacement of the system of interest, the other atoms move 
    along in such a way as to minimize the potential energy.  This is based on 
    the formulation in in [KH00]_.  For PCA models, this function simply takes 
    the sub-covariance matrix for the selected atoms.

    :arg model: dynamics model
    :type model: :class:`ANM`, :class:`GNM`, or :class:`PCA`
    :arg atoms: atoms that were used to build the model
    :arg selstr: a selection string specifying subset of atoms"""

    linalg = importLA()

    if not isinstance(model, NMA):
        raise TypeError("model must be an NMA instance, not {0:s}".format(type(model)))
    if not isinstance(atoms, (AtomGroup, AtomSubset, AtomMap)):
        raise TypeError("atoms type is not valid")
    if len(atoms) <= 1:
        raise TypeError("atoms must contain more than 1 atoms")

    if isinstance(model, GNM):
        matrix = model._kirchhoff
    elif isinstance(model, ANM):
        matrix = model._hessian
    elif isinstance(model, PCA):
        matrix = model._cov
    else:
        raise TypeError("model does not have a valid type derived from NMA")
    if matrix is None:
        raise ValueError("model matrix (Hessian/Kirchhoff/Covariance) is not " "built")

    system = SELECT.getBoolArray(atoms, selstr)
    other = np.invert(system)
    n_sel = sum(system)
    if n_sel == 0:
        LOGGER.warning("selection has 0 atoms")
        return None
    if len(atoms) == n_sel:
        LOGGER.warning("selection results in same number of atoms, " "model is not reduced")
        return None

    if model.is3d():
        system = np.tile(system, (3, 1)).transpose().flatten()
        other = np.tile(other, (3, 1)).transpose().flatten()
    ss = matrix[system, :][:, system]
    if isinstance(model, PCA):
        eda = PCA(model.getTitle() + " reduced")
        eda.setCovariance(ss)
        return eda, system
    so = matrix[system, :][:, other]
    os = matrix[other, :][:, system]
    oo = matrix[other, :][:, other]
    matrix = ss - np.dot(so, np.dot(linalg.inv(oo), os))

    if isinstance(model, GNM):
        gnm = GNM(model.getTitle() + " reduced")
        gnm.setKirchhoff(matrix)
        return gnm, system
    elif isinstance(model, ANM):
        anm = ANM(model.getTitle() + " reduced")
        anm.setHessian(matrix)
        return anm, system
    elif isinstance(model, PCA):
        eda = PCA(model.getTitle() + " reduced")
        eda.setCovariance(matrix)
        return eda, system