add tests and stuff

package/MDAnalysis/analysis/align.py

@@ -338,6 +338,7 @@ def _fit_to(mobile_coordinates, ref_coordinates, mobile_atoms,
     """
     R, min_rmsd = rotation_matrix(mobile_coordinates, ref_coordinates,
                                   weights=weights)
+
     mobile_atoms.translate(-mobile_com)
     mobile_atoms.rotate(R)
     mobile_atoms.translate(ref_com)
@@ -630,7 +631,7 @@ def __init__(self, mobile, reference, select='all', filename=None,
         select = rms.process_selection(select)
         self.ref_atoms = reference.select_atoms(*select['reference']).atoms
         self.mobile_atoms = mobile.select_atoms(*select['mobile']).atoms
-        if in_memory or not isinstance(mobile.trajectory, MemoryReader):
+        if in_memory or isinstance(mobile.trajectory, MemoryReader):
             mobile.transfer_to_memory()
             filename = None
             logger.info("Moved mobile trajectory to in-memory representation")

package/MDAnalysis/analysis/base.py

@@ -113,7 +113,7 @@ def __init__(self, trajectory, verbose=False, **kwargs):
         self._trajectory = trajectory
         self._verbose = verbose
 
-    def _setup_frames(self, trajectory, start=None, stop=None, step=None):
+    def _setup_frames(self, trajectory, start=None, stop=None, step=None, frames=None):
         """
         Pass a Reader object and define the desired iteration pattern
         through the trajectory
@@ -139,7 +139,9 @@ def _setup_frames(self, trajectory, start=None, stop=None, step=None):
         self.start = start
         self.stop = stop
         self.step = step
-        self.frame_indices = np.arange(start, stop, step)
+        if frames is None:
+            frames = np.arange(start, stop, step)
+        self.frame_indices = frames
         self.n_frames = len(self.frame_indices)
         self.frames = np.zeros(self.n_frames, dtype=int)
         self.times = np.zeros(self.n_frames)
@@ -162,7 +164,7 @@ def _conclude(self):
         """
         pass  # pylint: disable=unnecessary-pass
 
-    def run(self, start=None, stop=None, step=None, verbose=None):
+    def run(self, start=None, stop=None, step=None, frames=None, verbose=None):
         """Perform the calculation
 
         Parameters
@@ -181,7 +183,7 @@ def run(self, start=None, stop=None, step=None, verbose=None):
         verbose = getattr(self, '_verbose',
                           False) if verbose is None else verbose
 
-        self._setup_frames(self._trajectory, start, stop, step)
+        self._setup_frames(self._trajectory, start, stop, step, frames)
         logger.info("Starting preparation")
         self._prepare()
         for i, frame in enumerate(ProgressBar(self.frame_indices, verbose=verbose)):

package/MDAnalysis/analysis/clustering/__init__.py

@@ -1,2 +1,25 @@
+# -*- Mode: python; tab-width: 4; indent-tabs-mode:nil; coding:utf-8 -*-
+# vim: tabstop=4 expandtab shiftwidth=4 softtabstop=4
+#
+# MDAnalysis --- https://www.mdanalysis.org
+# Copyright (c) 2006-2017 The MDAnalysis Development Team and contributors
+# (see the file AUTHORS for the full list of names)
+#
+# Released under the GNU Public Licence, v2 or any higher version
+#
+# Please cite your use of MDAnalysis in published work:
+#
+# R. J. Gowers, M. Linke, J. Barnoud, T. J. E. Reddy, M. N. Melo, S. L. Seyler,
+# D. L. Dotson, J. Domanski, S. Buchoux, I. M. Kenney, and O. Beckstein.
+# MDAnalysis: A Python package for the rapid analysis of molecular dynamics
+# simulations. In S. Benthall and S. Rostrup editors, Proceedings of the 15th
+# Python in Science Conference, pages 102-109, Austin, TX, 2016. SciPy.
+# doi: 10.25080/majora-629e541a-00e
+#
+# N. Michaud-Agrawal, E. J. Denning, T. B. Woolf, and O. Beckstein.
+# MDAnalysis: A Toolkit for the Analysis of Molecular Dynamics Simulations.
+# J. Comput. Chem. 32 (2011), 2319--2327, doi:10.1002/jcc.21787
+#
+
 from .clusters import Clusters
 from . import methods

package/MDAnalysis/analysis/clustering/cluster_methods.pyx

@@ -22,9 +22,6 @@
 #
 """
 Cython wrapper for the C implementation of the Affinity Perturbation clustering algorithm.
-
-:Author: Matteo Tiberti, Wouter Boomsma, Tone Bengtsen
-
 """
 import warnings
 
@@ -83,10 +80,6 @@ def affinity_propagation(similarity, preference, float lam, int max_iter, int co
 
 
     cdef np.ndarray[np.float32_t, ndim=1] sim = np.ravel(similarity[indices]).astype(np.float32)
-    # sim = np.ascontiguousarray(sim)
-
-    print(sim)
-
     cdef np.ndarray[long, ndim=1] clusters = np.zeros((cn), dtype=long)
 
     # run C module Affinity Propagation

package/MDAnalysis/analysis/clustering/methods.py

@@ -1,3 +1,26 @@
+# -*- Mode: python; tab-width: 4; indent-tabs-mode:nil; coding:utf-8 -*-
+# vim: tabstop=4 expandtab shiftwidth=4 softtabstop=4
+#
+# MDAnalysis --- https://www.mdanalysis.org
+# Copyright (c) 2006-2017 The MDAnalysis Development Team and contributors
+# (see the file AUTHORS for the full list of names)
+#
+# Released under the GNU Public Licence, v2 or any higher version
+#
+# Please cite your use of MDAnalysis in published work:
+#
+# R. J. Gowers, M. Linke, J. Barnoud, T. J. E. Reddy, M. N. Melo, S. L. Seyler,
+# D. L. Dotson, J. Domanski, S. Buchoux, I. M. Kenney, and O. Beckstein.
+# MDAnalysis: A Python package for the rapid analysis of molecular dynamics
+# simulations. In S. Benthall and S. Rostrup editors, Proceedings of the 15th
+# Python in Science Conference, pages 102-109, Austin, TX, 2016. SciPy.
+# doi: 10.25080/majora-629e541a-00e
+#
+# N. Michaud-Agrawal, E. J. Denning, T. B. Woolf, and O. Beckstein.
+# MDAnalysis: A Toolkit for the Analysis of Molecular Dynamics Simulations.
+# J. Comput. Chem. 32 (2011), 2319--2327, doi:10.1002/jcc.21787
+#
+
 from . import cluster_methods
 
 class AffinityPropagation:

package/MDAnalysis/analysis/encore/clustering/ClusteringMethod.py

@@ -158,9 +158,9 @@ def __call__(self, distance_matrix):
             max_iterations = self.max_iter,
             convergence = self.convergence_iter,
             noise=int(self.add_noise))
-        print(clusters)
-        raise ValueError()
+
         return clusters
+
 if sklearn:
 
     class AffinityPropagation(ClusteringMethod):

package/MDAnalysis/analysis/encore/clustering/affinityprop.pyx

@@ -97,8 +97,6 @@ def AffinityPropagation(s, preference, float lam, int max_iterations, int conver
 
     # Prepare input and ouput arrays
     cdef numpy.ndarray[numpy.float32_t,  ndim=1] matndarray = numpy.ascontiguousarray(s._elements, dtype=numpy.float32)
-
-    print(matndarray)
     cdef numpy.ndarray[long,   ndim=1] clusters   = numpy.zeros((s.size),dtype=long)
 
     # run C module Affinity Propagation