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# 3.4. Distance analysis — `MDAnalysis.distances`

This module provides functions to rapidly compute distances between atoms or groups of atoms.

`MDAnalysis.analysis.distances.``distance_array`()

  Calculate all distances between a reference set and another configuration.

  d = distance_array(ref,conf,box[,result=d])

  Arguments : | ref reference coordinate array conf configuration coordinate array box orthorhombic unit cell dimensions (minimum image convention is applied) or None [None] result optional preallocated result array which must have the shape (len(ref),len(conf)) and dtype=numpy.float64. Avoids creating the array which saves time when the function is called repeatedly. [None]
  Returns : | d (len(ref),len(conf)) numpy array with the distances d[i,j] between ref coordinates i and conf coordinates j

  Note

  This method is slower than it could be because internally we need to make copies of the ref and conf arrays.

`MDAnalysis.analysis.distances.``self_distance_array`()

  Calculate all distances d_ij between atoms i and j within a configuration ref.

  d = self_distance_array(ref,box[,result=d])

  Arguments : | ref reference coordinate array with N=len(ref) coordinates box orthorhombic unit cell dimensions (minimum image convention is applied) or None [None] result optional preallocated result array which must have the shape (N*(N-1)/2,) and dtype `numpy.float64`. Avoids creating the array which saves time when the function is called repeatedly. [None]
      Returns : | d N*(N-1)/2 numpy 1D array with the distances dist[i,j] between ref coordinates i and j at position d[k]. Loop through d:
          for i in xrange(N):
             for j in xrange(i+1, N):
                 k += 1
                 dist[i,j] = d[k]

  Note

  This method is slower than it could be because internally we need to make copies of the coordinate arrays.

`MDAnalysis.analysis.distances.``contact_matrix`(coord, cutoff=15.0, returntype='numpy', box=None, progress_meter_freq=100, suppress_progmet=False)

  Calculates a matrix of contacts between a list of coordinates. There is a fast, high-memory-usage version for small systems (returntype=’numpy’), and a slower, low-memory-usage version for larger systems (returntype=’sparse’).

  If box dimensions are passed, then periodic boundary conditions are applied.

  Change progress_meter_freq to alter frequency of progress meter updates. Or switch suppress_progmet to True to suppress it completely.

`MDAnalysis.analysis.distances.``dist`(A, B, offset=0)

  Return distance between atoms in two atom groups.

  The distance is calculated atom-wise. The residue ids are also returned because a typical use case is to look at CA distances before and after an alignment. Using the offset keyword one can also add a constant offset to the resids which facilitates comparison with PDB numbering.

  Arguments : | A, B `AtomGroup` with the same number of atoms
  Keywords : | offset : integer The offset is added to resids_A and resids_B (see below) in order to produce PDB numbers. The default is 0. offset : tuple offset[0] is added to resids_A and offset[1] to resids_B.
  Returns : | NumPy array([resids_A, resids_B, distances])

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