def all_to_all(self, prepared_traj1, prepared_traj2):
"""Get a matrix of distances from all frames in one traj to all frames in
another
Parameters
----------
prepared_traj1 : ndarray
First prepared trajectory
prepared_traj2 : ndarray
Second prepared trajectory
Returns
-------
distances : ndarray
A 2D array of shape len(preprared_traj1) * len(preprared_traj2)"""
if prepared_traj1 is prepared_traj2:
warnings.warn('runtime', re.sub("\s+", " ", """it's not recommended to
use this method to calculate the full pairwise distance matrix for
one trajectory to itself (as you're doing). Use all_pairwise, which
will be more efficient if you reall need the results as a 2D matrix
(why?) then you can always use scipy.spatial.distance.squareform()
on the output of all_pairwise()""".replace('\n', ' ')))
out = cdist(prepared_traj1, prepared_traj2, metric=self.metric, p=self.p,
V=self.V, VI=self.VI)
return out
def one_to_all(self, prepared_traj1, prepared_traj2, index1):
"""Measure the distance from one frame to every frame in a trajectory
The distances calculated are from the `index1`th frame of `prepared_traj1`
to all the frames in `prepared_traj2` with indices `indices2`. Although
this is similar to one_to_many, it can often be computed faster
Parameters
----------
prepared_traj1 : ndarray
First prepared trajectory
prepared_traj2 : ndarray
Second prepared trajectory
index1 : int
index in `prepared_trajectory`
Returns
-------
distances : ndarray
A vector of distances of length len(prepared_traj2)"""
if not isinstance(index1, int):
raise TypeError('index1 must be of type int.')
out2 = cdist(prepared_traj2, prepared_traj1[[index1]], metric=self.metric,
p=self.p, V=self.V, VI=self.VI)
return out2[:, 0]
def many_to_many(self, prepared_traj1, prepared_traj2, indices1, indices2):
"""Get a matrix of distances from each frame in a set to each other frame
in a second set.
Calculate a MATRIX of distances from the frames in prepared_traj1 with
indices `indices1` to the frames in prepared_traj2 with indices `indices2`,
using supplied metric.
Parameters
----------
prepared_traj1 : ndarray
First prepared trajectory
prepared_traj2 : ndarray
Second prepared trajectory
indices1 : array_like
list of indices in `prepared_traj1` to calculate the distances from
indices2 : array_like
list of indices in `prepared_traj2` to calculate the distances to
Returns
-------
distances : ndarray
A 2D array of shape len(indices1) * len(indices2)"""
out = cdist(prepared_traj1[indices1], prepared_traj2[indices2], metric=self.metric,
p=self.p, V=self.V, VI=self.VI)
return out
def one_to_many(self, prepared_traj1, prepared_traj2, index1, indices2):
"""Calculate a vector of distances from one frame of the first trajectory
to many frames of the second trajectory
The distances calculated are from the `index1`th frame of `prepared_traj1`
to the frames in `prepared_traj2` with indices `indices2`
Parameters
----------
prepared_traj1 : ndarray
First prepared trajectory
prepared_traj2 : ndarray
Second prepared trajectory
index1 : int
index in `prepared_trajectory`
indices2 : ndarray
list of indices in `prepared_traj2` to calculate the distances to
Returns
-------
distances : ndarray
Vector of distances of length len(indices2)
"""
if not isinstance(index1, int):
raise TypeError('index1 must be of type int.')
out = cdist(prepared_traj2[indices2], prepared_traj1[[index1]],
metric=self.metric, p=self.p, V=self.V, VI=self.VI)
return out[:, 0]
def all_to_all(self, prepared_traj1, prepared_traj2):
"""Get a matrix of distances from all frames in one traj to all frames in
another
Parameters
----------
prepared_traj1 : ndarray
First prepared trajectory
prepared_traj2 : ndarray
Second prepared trajectory
Returns
-------
distances : ndarray
A 2D array of shape len(preprared_traj1) * len(preprared_traj2)"""
if prepared_traj1 is prepared_traj2:
warnings.warn(
'runtime',
re.sub(
"\s+", " ", """it's not recommended to
use this method to calculate the full pairwise distance matrix for
one trajectory to itself (as you're doing). Use all_pairwise, which
will be more efficient if you reall need the results as a 2D matrix
(why?) then you can always use scipy.spatial.distance.squareform()
on the output of all_pairwise()""".replace('\n', ' ')))
out = cdist(prepared_traj1,
prepared_traj2,
metric=self.metric,
p=self.p,
V=self.V,
VI=self.VI)
return out
def many_to_many(self, prepared_traj1, prepared_traj2, indices1, indices2):
"""Get a matrix of distances from each frame in a set to each other frame
in a second set.
Calculate a MATRIX of distances from the frames in prepared_traj1 with
indices `indices1` to the frames in prepared_traj2 with indices `indices2`,
using supplied metric.
Parameters
----------
prepared_traj1 : ndarray
First prepared trajectory
prepared_traj2 : ndarray
Second prepared trajectory
indices1 : array_like
list of indices in `prepared_traj1` to calculate the distances from
indices2 : array_like
list of indices in `prepared_traj2` to calculate the distances to
Returns
-------
distances : ndarray
A 2D array of shape len(indices1) * len(indices2)"""
out = cdist(prepared_traj1[indices1],
prepared_traj2[indices2],
metric=self.metric,
p=self.p,
V=self.V,
VI=self.VI)
return out
def one_to_all(self, prepared_traj1, prepared_traj2, index1):
"""Measure the distance from one frame to every frame in a trajectory
The distances calculated are from the `index1`th frame of `prepared_traj1`
to all the frames in `prepared_traj2` with indices `indices2`. Although
this is similar to one_to_many, it can often be computed faster
Parameters
----------
prepared_traj1 : ndarray
First prepared trajectory
prepared_traj2 : ndarray
Second prepared trajectory
index1 : int
index in `prepared_trajectory`
Returns
-------
distances : ndarray
A vector of distances of length len(prepared_traj2)"""
if not isinstance(index1, int):
raise TypeError('index1 must be of type int.')
out2 = cdist(prepared_traj2,
prepared_traj1[[index1]],
metric=self.metric,
p=self.p,
V=self.V,
VI=self.VI)
return out2[:, 0]
def one_to_many(self, prepared_traj1, prepared_traj2, index1, indices2):
"""Calculate a vector of distances from one frame of the first trajectory
to many frames of the second trajectory
The distances calculated are from the `index1`th frame of `prepared_traj1`
to the frames in `prepared_traj2` with indices `indices2`
Parameters
----------
prepared_traj1 : ndarray
First prepared trajectory
prepared_traj2 : ndarray
Second prepared trajectory
index1 : int
index in `prepared_trajectory`
indices2 : ndarray
list of indices in `prepared_traj2` to calculate the distances to
Returns
-------
distances : ndarray
Vector of distances of length len(indices2)
"""
if not isinstance(index1, int):
raise TypeError('index1 must be of type int.')
out = cdist(prepared_traj2[indices2],
prepared_traj1[[index1]],
metric=self.metric,
p=self.p,
V=self.V,
VI=self.VI)
return out[:, 0]
