def saveEnsemble(ensemble, filename=None, **kwargs):
"""Save *ensemble* model data as :file:`filename.ens.npz`. If *filename*
is ``None``, title of the *ensemble* will be used as the filename, after
white spaces in the title are replaced with underscores. Extension is
:file:`.ens.npz`. Upon successful completion of saving, filename is
returned. This function makes use of :func:`numpy.savez` function."""
if not isinstance(ensemble, Ensemble):
raise TypeError('invalid type for ensemble, {0:s}'
.format(type(ensemble)))
if len(ensemble) == 0:
raise ValueError('ensemble instance does not contain data')
dict_ = ensemble.__dict__
attr_list = ['_title', '_confs', '_weights', '_coords']
if isinstance(ensemble, PDBEnsemble):
attr_list.append('_labels')
if filename is None:
filename = ensemble.getTitle().replace(' ', '_')
attr_dict = {}
for attr in attr_list:
value = dict_[attr]
if value is not None:
attr_dict[attr] = value
filename += '.ens.npz'
ostream = openFile(filename, 'wb', **kwargs)
np.savez(ostream, **attr_dict)
ostream.close()
return filename
def saveModel(nma, filename=None, matrices=False, **kwargs):
"""Save *nma* model data as :file:`filename.nma.npz`. By default,
eigenvalues, eigenvectors, variances, trace of covariance matrix,
and name of the model will be saved. If *matrices* is ``True``,
covariance, Hessian or Kirchhoff matrices are saved too, whichever
are available. If *filename* is ``None``, name of the NMA instance
will be used as the filename, after ``" "`` (white spaces) in the name
are replaced with ``"_"`` (underscores). Extension may differ based
on the type of the NMA model. For ANM models, it is :file:`.anm.npz`.
Upon successful completion of saving, filename is returned. This
function makes use of :func:`numpy.savez` function."""
if not isinstance(nma, NMA):
raise TypeError('invalid type for nma, {0:s}'.format(type(nma)))
if len(nma) == 0:
raise ValueError('nma instance does not contain data')
dict_ = nma.__dict__
attr_list = ['_title', '_trace', '_array', '_eigvals', '_vars', '_n_atoms',
'_dof', '_n_modes']
if filename is None:
filename = nma.getTitle().replace(' ', '_')
if isinstance(nma, GNMBase):
attr_list.append('_cutoff')
attr_list.append('_gamma')
if matrices:
attr_list.append('_kirchhoff')
if isinstance(nma, ANM):
attr_list.append('_hessian')
if isinstance(nma, ANM):
type_ = 'ANM'
else:
type_ = 'GNM'
elif isinstance(nma, EDA):
type_ = 'EDA'
elif isinstance(nma, PCA):
type_ = 'PCA'
else:
type_ = 'NMA'
if matrices:
attr_list.append('_cov')
attr_dict = {'type': type_}
for attr in attr_list:
value = dict_[attr]
if value is not None:
attr_dict[attr] = value
filename += '.' + type_.lower() + '.npz'
ostream = openFile(filename, 'wb', **kwargs)
np.savez(ostream, **attr_dict)
ostream.close()
return filename
def saveAtoms(atoms, filename=None, **kwargs):
"""Save *atoms* in ProDy internal format. All atomic classes are accepted
as *atoms* argument. This function saves user set atomic data as well.
Note that title of the AtomGroup instance is used as the filename when
*atoms* is not an AtomGroup. To avoid overwriting an existing file with
the same name, specify a *filename*."""
if not isinstance(atoms, Atomic):
raise TypeError('atoms must be Atomic instance, not {0:s}'
.format(type(atoms)))
if isinstance(atoms, AtomGroup):
ag = atoms
title = ag.getTitle()
else:
ag = atoms.getAtomGroup()
title = str(atoms)
if filename is None:
filename = ag.getTitle().replace(' ', '_')
filename += '.ag.npz'
attr_dict = {'title': title}
attr_dict['n_atoms'] = atoms.numAtoms()
attr_dict['n_csets'] = atoms.numCoordsets()
attr_dict['cslabels'] = atoms.getCSLabels()
coords = atoms._getCoordsets()
if coords is not None:
attr_dict['coordinates'] = coords
bonds = ag._bonds
bmap = ag._bmap
if bonds is not None and bmap is not None:
if isinstance(atoms, AtomGroup):
attr_dict['bonds'] = bonds
attr_dict['bmap'] = bmap
attr_dict['numbonds'] = ag._data['numbonds']
else:
bonds = trimBonds(bonds, bmap, atoms._getIndices())
attr_dict['bonds'] = bonds
attr_dict['bmap'], attr_dict['numbonds'] = \
evalBonds(bonds, len(atoms))
for key, data in ag._data.iteritems():
if key == 'numbonds':
continue
if data is not None:
attr_dict[key] = data
ostream = openFile(filename, 'wb', **kwargs)
savez(ostream, **attr_dict)
ostream.close()
return filename
def saveVector(vector, filename, **kwargs):
"""Save *vector* data as :file:`filename.vec.npz`. Upon successful
completion of saving, filename is returned. This function makes use
of :func:`numpy.savez` function."""
if not isinstance(vector, Vector):
raise TypeError('invalid type for vector, {0:s}'.format(type(vector)))
attr_dict = {}
attr_dict['title'] = vector.getTitle()
attr_dict['array'] = vector._getArray()
attr_dict['is3d'] = vector.is3d()
filename += '.vec.npz'
ostream = openFile(filename, 'wb', **kwargs)
np.savez(ostream, **attr_dict)
ostream.close()
return filename
def writeNMD(filename, modes, atoms):
"""Writes an NMD file for given *modes* and includes applicable data from
*atoms*. Returns *filename*, if file is successfully written. NMD file
format is described at :ref:`nmd-format`.
.. note::
#. This function skips modes with zero eigenvalues.
#. If a :class:`Vector` instance is given, it will be normalized before
it is written. It's length before normalization will be written
as the scaling factor of the vector."""
if not isinstance(modes, (NMA, ModeSet, Mode, Vector)):
raise TypeError('modes must be NMA, ModeSet, Mode, or Vector, '
'not {0:s}'.format(type(modes)))
if modes.numAtoms() != atoms.numAtoms():
raise Exception('number of atoms do not match')
out = openFile(filename, 'w')
#out.write('#!{0:s} -e\n'.format(VMDPATH))
out.write('nmwiz_load {0:s}\n'.format(os.path.abspath(filename)))
name = modes.getTitle()
name = name.replace(' ', '_').replace('.', '_')
if not name.replace('_', '').isalnum() or len(name) > 30:
name = str(atoms)
name = name.replace(' ', '_').replace('.', '_')
if not name.replace('_', '').isalnum() or len(name) > 30:
name = os.path.splitext(os.path.split(filename)[1])[0]
out.write('name {0:s}\n'.format(name))
try:
coords = atoms.getCoords()
except:
raise ValueError('coordinates could not be retrieved from atoms')
if coords is None:
raise ValueError('atom coordinates are not set')
try:
data = atoms.getNames()
if data is not None:
out.write('atomnames {0:s}\n'.format(' '.join(data)))
except:
pass
try:
data = atoms.getResnames()
if data is not None:
out.write('resnames {0:s}\n'.format(' '.join(data)))
except:
pass
try:
data = atoms.getResnums()
if data is not None:
out.write('resids {0:s}\n'.format(' '.join(data.astype('|S5'))))
except:
pass
try:
data = atoms.getChids()
if data is not None:
out.write('chainids {0:s}\n'.format(' '.join(data)))
except:
pass
try:
data = atoms.getBetas()
if data is not None:
out.write('bfactors {0:s}\n'.format(' '.join(
['{0:.3f}'.format(x) for x in data.flatten()])))
except:
pass
out.write('coordinates {0:s}\n'.format(
' '.join(['{0:.3f}'.format(x) for x in coords.flatten()])))
count = 0
if isinstance(modes, Vector):
out.write('mode 1 {0:.2f} {1:s}\n'.format(abs(modes), ' '.join(
['{0:.3f}'.format(x) for x in modes.getNormed()._getArray()])))
count += 1
else:
if isinstance(modes, Mode):
modes = [modes]
for mode in modes:
if mode.getEigenvalue() < ZERO:
continue
out.write('mode {0:d} {1:.2f} {2:s}\n'.format(
mode.getIndex()+1, mode.getVariance()**0.5,
' '.join(
['{0:.3f}'.format(x) for x in mode._getArray()])))
count += 1
if count == 0:
LOGGER.warning('No normal mode data was written. '
'Given modes might have 0 eigenvalues.')
out.close()
return filename