distances.py 文件源码

def transform(self, traj):
        # All needed distances
        Dall = mdtraj.compute_distances(traj, self.distance_indexes, periodic=self.periodic)
        # Just the minimas
        Dmin = np.zeros((traj.n_frames,self.dimension))
        res = np.zeros_like(Dmin)
        # Compute the min groupwise
        for ii, (gi, gf) in enumerate(self.group_identifiers):
            Dmin[:, ii] = Dall[:,gi:gf].min(1)
        # Do we want binary?
        if self.threshold is not None:
            I = np.argwhere(Dmin <= self.threshold)
            res[I[:, 0], I[:, 1]] = 1.0
        else:
            res = Dmin

        return res