def project(self, *args, **kwargs):
""" Project molecule.
Parameters
----------
mol : :class:`Molecule <htmd.molecule.molecule.Molecule>`
A :class:`Molecule <htmd.molecule.molecule.Molecule>` object to project.
Returns
-------
data : np.ndarray
An array containing the projected data.
"""
# -------------- DEPRECATION PATCH --------------
if isinstance(self, np.ndarray) or isinstance(self, Molecule):
from warnings import warn
warn('Static use of the project method will be deprecated in the next version of HTMD. '
'Please change your projection code according to the tutorials on www.htmd.org')
data = _MetricDistanceOld.project(self, *args, **kwargs)
logger.warning('Static use of the project method will be deprecated in the next version of HTMD. '
'Please change your projection code according to the tutorials on www.htmd.org')
return data
# ------------------ CUT HERE -------------------
mol = args[0]
(sel1, sel2) = self._getSelections(mol)
if np.ndim(sel1) == 1 and np.ndim(sel2) == 1: # normal distances
metric = pp_calcDistances(mol, sel1, sel2, self.metric, self.threshold, self.pbc, truncate=self.truncate)
else: # minimum distances by groups
metric = pp_calcMinDistances(mol, sel1, sel2)
return metric
def project(self, mol):
""" Project molecule.
Parameters
----------
mol : :class:`Molecule <htmd.molecule.molecule.Molecule>`
A :class:`Molecule <htmd.molecule.molecule.Molecule>` object to project.
Returns
-------
data : np.ndarray
An array containing the projected data.
"""
(sel1, sel2) = self._getSelections(mol)
if np.ndim(sel1) == 1 and np.ndim(sel2) == 1: # normal distances
metric = pp_calcDistances(mol,
sel1,
sel2,
self.metric,
self.threshold,
self.pbc,
truncate=self.truncate)
else: # minimum distances by groups
metric = pp_calcMinDistances(mol,
sel1,
sel2,
self.metric,
self.threshold,
pbc=self.pbc)
return metric
def _processTraj(self, mol):
(sel1, sel2) = self._getSelections(mol)
if np.ndim(sel1) == 1 and np.ndim(sel2) == 1: # normal distances
metric = pp_calcDistances(mol, sel1, sel2, self.metric, self.threshold, self.pbc, truncate=self.truncate)
else: # minimum distances by groups
metric = pp_calcMinDistances(mol, sel1, sel2)
#if not issparse(metric) and not metric.dtype == 'bool' and np.any(np.isreal(metric)) and self.precision != 0:
# metric = np.round(metric * (1 / self.precision)) * self.precision
return metric
def project(self, mol):
""" Project molecule.
Parameters
----------
mol : :class:`Molecule <htmd.molecule.molecule.Molecule>`
A :class:`Molecule <htmd.molecule.molecule.Molecule>` object to project.
Returns
-------
data : np.ndarray
An array containing the projected data.
"""
(sel1, sel2) = self._getSelections(mol)
if np.ndim(sel1) == 1 and np.ndim(sel2) == 1: # normal distances
metric = pp_calcDistances(mol, sel1, sel2, self.metric, self.threshold, self.pbc, truncate=self.truncate)
else: # minimum distances by groups
metric = pp_calcMinDistances(mol, sel1, sel2, self.metric, self.threshold, pbc=self.pbc)
return metric