run all linters and fix files

.coveragerc

@@ -15,6 +15,3 @@ exclude_lines =
     def __repr__
     raise NotImplementedError
     if __name__ == .__main__.:
-
-
-

.github/CONTRIBUTING.md

@@ -15,4 +15,3 @@ If your issue isn't a defect with the code and instead you require help using MD
 If you're contributing code, please check out [How to contribute](https://www.mdanalysis.org/UserGuide/contributing.html) in the User Guide and look at the [Style guide](https://github.com/MDAnalysis/mdanalysis/wiki/Style-Guide).
 
 MDAnalysis devs are most easily reached through the [development list](https://groups.google.com/forum/#!forum/mdnalysis-devel).
-

.github/ISSUE_TEMPLATE/questions.md

@@ -4,12 +4,12 @@ about: If you want to ask a question please use the mailing list!
 
 ---
 
-If you have a **QUESTION** such as 
+If you have a **QUESTION** such as
 
 - how to use MDAnalysis in general
 - how to accomplish something specific,
 - what output means
-- ... or similar questions related to *USING* MDAnalysis 
+- ... or similar questions related to *USING* MDAnalysis
 
 then please *ask this question on the user mailing list*
 

.github/PULL_REQUEST_TEMPLATE.md

@@ -1,7 +1,7 @@
 Fixes #
 
 Changes made in this Pull Request:
- - 
+ -
 
 
 PR Checklist

.github/workflows/deploy.yaml

@@ -151,7 +151,7 @@ jobs:
           packages_dir: testsuite/dist
           skip_existing: true
           repository_url: https://test.pypi.org/legacy/
- 
+
   upload_pypi:
     if: |
       github.repository == 'MDAnalysis/mdanalysis' &&

.github/workflows/gh-ci-cron.yaml

@@ -212,7 +212,7 @@ jobs:
     - name: run_tests
       run: |
         pytest --timeout=200 -n auto testsuite/MDAnalysisTests --disable-pytest-warnings --durations=50
-        
+
   # Issue 4208
   conda-latest-release:
     # A set of runner to check that the latest conda release works as expected
@@ -259,7 +259,7 @@ jobs:
     - name: run_tests
       run: |
           pytest --timeout=200 -n auto --pyargs MDAnalysisTests
-          
+
   pypi-latest-release:
     # A set of runner to check that the latest conda release works as expected
     if: "github.repository == 'MDAnalysis/mdanalysis'"

.github/workflows/gh-ci.yaml

@@ -124,7 +124,6 @@ jobs:
         fail_ci_if_error: True
         verbose: True
 
-
   build_docs:
     if: "github.repository == 'MDAnalysis/mdanalysis'"
     runs-on: ubuntu-latest

CITATION.bib

@@ -2,7 +2,7 @@
 %% Please see https://docs.mdanalysis.org/stable/documentation_pages/references.html
 %% for more details and citations for included methods.
 
-%% Saved with string encoding Unicode (UTF-8) 
+%% Saved with string encoding Unicode (UTF-8)
 
 
 

CODE_OF_CONDUCT.md

@@ -128,12 +128,12 @@ The online form gives you the option to keep your report anonymous or request
 that we follow up with you directly. While we cannot follow up on an anonymous
 report, we will take appropriate action.
 
-You may also follow [NumFOCUS’s Code of Conduct violation reporting][NF-conduct] 
-guidelines if you would like to contact a third-party outside of the MDAnalysis 
+You may also follow [NumFOCUS’s Code of Conduct violation reporting][NF-conduct]
+guidelines if you would like to contact a third-party outside of the MDAnalysis
 community.
 
 ### Reporting at MDAnalysis Events and Meetups
-If you are attending an MDAnalysis event or meetup and wish to [make a report](#reporting), you may contact the ombudspersons (who will identify themselves at the event) or other event staff/meetup organizers so that they can take any appropriate immediate response. If you would prefer not to do that, please [submit a report][conduct-form] to MDAnalysis. 
+If you are attending an MDAnalysis event or meetup and wish to [make a report](#reporting), you may contact the ombudspersons (who will identify themselves at the event) or other event staff/meetup organizers so that they can take any appropriate immediate response. If you would prefer not to do that, please [submit a report][conduct-form] to MDAnalysis.
 
 Ombudspeople and event staff/meetup organizers will be happy to help participants contact venue security or local law enforcement, provide escorts, or otherwise assist those experiencing harassment to feel safe for the duration of the event/meetup.
 
@@ -174,9 +174,8 @@ modified by MDAnalysis. We are grateful to those projects for contributing these
 materials under open licensing terms for us to easily reuse.
 
 All content on this page is licensed under a [*Creative Commons
-Attribution*](http://creativecommons.org/licenses/by/3.0/) license. 
+Attribution*](http://creativecommons.org/licenses/by/3.0/) license.
 
 [conduct-form]: https://forms.gle/r2SMU4XcwM814CpJ9
 
 [NF-conduct]: https://numfocus.org/code-of-conduct
-

LICENSE

@@ -1690,7 +1690,7 @@ pyqcprot (src/pyqcprot) is released under the following 'BSD 3-clause' licence:
 -----------------------------------------------------------------------------
 PyQCPROT
 
-    Author(s) of Original Implementation:     
+    Author(s) of Original Implementation:
                   Douglas L. Theobald
                   Department of Biochemistry
                   MS 009
@@ -1700,7 +1700,7 @@ PyQCPROT
                   USA
 
                   [email protected]
-                  
+
                   Pu Liu
                   Johnson & Johnson Pharmaceutical Research and Development, L.L.C.
                   665 Stockton Drive
@@ -1710,18 +1710,18 @@ PyQCPROT
                   [email protected]
 
                   For the original code written in C see:
-                  http://theobald.brandeis.edu/qcp/ 
+                  http://theobald.brandeis.edu/qcp/
 
 
     Author of Python Port:
                   Joshua L. Adelman
                   Department of Biological Sciences
                   University of Pittsburgh
                   Pittsburgh, PA 15260
-                   
+
                   [email protected]
 
- 
+
     If you use this QCP rotation calculation method in a publication, please
     reference:
 
@@ -1731,25 +1731,25 @@ PyQCPROT
       Acta Crystallographica A 61(4):478-480.
 
       Pu Liu, Dmitris K. Agrafiotis, and Douglas L. Theobald (2010)
-      "Fast determination of the optimal rotational matrix for macromolecular 
+      "Fast determination of the optimal rotational matrix for macromolecular
       superpositions."
-      J. Comput. Chem. 31, 1561-1563. 
+      J. Comput. Chem. 31, 1561-1563.
 
 
-    Copyright (c) 2009-2010, Pu Liu and Douglas L. Theobald 
+    Copyright (c) 2009-2010, Pu Liu and Douglas L. Theobald
     Copyright (c) 2011       Joshua L. Adelman
     All rights reserved.
 
-    Redistribution and use in source and binary forms, with or without modification, are permitted 
+    Redistribution and use in source and binary forms, with or without modification, are permitted
     provided that the following conditions are met:
 
-    * Redistributions of source code must retain the above copyright notice, this list of 
+    * Redistributions of source code must retain the above copyright notice, this list of
       conditions and the following disclaimer.
-    * Redistributions in binary form must reproduce the above copyright notice, this list 
-      of conditions and the following disclaimer in the documentation and/or other materials 
+    * Redistributions in binary form must reproduce the above copyright notice, this list
+      of conditions and the following disclaimer in the documentation and/or other materials
       provided with the distribution.
-    * Neither the name of the <ORGANIZATION> nor the names of its contributors may be used to 
-      endorse or promote products derived from this software without specific prior written 
+    * Neither the name of the <ORGANIZATION> nor the names of its contributors may be used to
+      endorse or promote products derived from this software without specific prior written
       permission.
 
     THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
@@ -1787,4 +1787,3 @@ inclusion in MDAnalysis and on websites related to MDAnalysis. They
 are distributed under the same license as the 'Atom' logo.
 
 ==========================================================================
-

README.rst

@@ -6,14 +6,14 @@
 
 |docs| |devdocs| |usergroup| |developergroup| |anaconda| |asv|
 
-MDAnalysis_ is a Python library for the analysis of computer simulations of many-body systems at the molecular scale, spanning use cases from interactions of drugs with proteins to novel materials. It is widely used in the scientific community and is written by scientists for scientists. 
+MDAnalysis_ is a Python library for the analysis of computer simulations of many-body systems at the molecular scale, spanning use cases from interactions of drugs with proteins to novel materials. It is widely used in the scientific community and is written by scientists for scientists.
 
 It works with a wide range of popular simulation packages including Gromacs, Amber, NAMD, CHARMM, DL_Poly, HooMD, LAMMPS and many others — see the lists of supported `trajectory formats`_ and `topology formats`_.
 MDAnalysis also includes widely used analysis algorithms in the `MDAnalysis.analysis`_ module.
 
 .. _numfocus-fiscal-sponsor-attribution:
 
-The MDAnalysis project uses an `open governance model`_ and is fiscally sponsored by `NumFOCUS`_. Consider making 
+The MDAnalysis project uses an `open governance model`_ and is fiscally sponsored by `NumFOCUS`_. Consider making
 a `tax-deductible donation`_ to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.
 
 .. image:: https://www.mdanalysis.org/public/images/numfocus-sponsored-small.png
@@ -105,7 +105,7 @@ two papers:
     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`_    
+    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
@@ -190,7 +190,7 @@ For citations of included algorithms and sub-modules please see the references_.
 .. |anaconda| image:: https://anaconda.org/conda-forge/mdanalysis/badges/version.svg
    :alt: Anaconda
    :target: https://anaconda.org/conda-forge/mdanalysis
-   
+
 .. |asv| image:: https://img.shields.io/badge/benchmarked%20by-asv-blue.svg
    :alt: ASV Benchmarks
    :target:  https://www.mdanalysis.org/benchmarks/

benchmarks/benchmarks/ag_methods.py

@@ -326,11 +326,11 @@ def time_bond(self, num_atoms):
 
 class CompoundSplitting(object):
     """Test how fast can we split compounds into masks and apply them
-    
+
     The benchmark used in Issue #3000. Parameterizes multiple compound number
     and size combinations.
     """
-    
+
     params = [(100, 10000, 1000000),  # n_atoms
               (1, 10, 100),           # n_compounds
               (True, False),          # homogeneous
@@ -345,7 +345,7 @@ def setup(self, n_atoms, n_compounds, homogeneous, contiguous):
 
         if n_compounds == 1 and not (homogeneous and contiguous):
             raise NotImplementedError
-            
+
         if n_compounds == n_atoms:
             if not (homogeneous and contiguous):
                 raise NotImplementedError
@@ -359,14 +359,14 @@ def setup(self, n_atoms, n_compounds, homogeneous, contiguous):
         else:
             compound_indices = np.sort(np.floor(rg.random(n_atoms)
                                                 * n_compounds).astype(np.int))
-                
+
         unique_indices = np.unique(compound_indices)
         if len(unique_indices) != n_compounds:
             raise RuntimeError
-        
+
         if not contiguous:
             rg.shuffle(compound_indices)
-        
+
         self.u = MDAnalysis.Universe.empty(n_atoms,
                                            n_residues=n_compounds,
                                            n_segments=1,
@@ -394,11 +394,11 @@ class FragmentFinding(object):
 
     def setup(self, universe_type):
         if universe_type == 'large_fragment_small_solvents':
-            univ = (TPR, XTC) 
+            univ = (TPR, XTC)
         elif universe_type == 'large_fragment':
             univ = (PSF, DCD)
         else:
-            univ = (TRZ_psf, TRZ) 
+            univ = (TRZ_psf, TRZ)
         self.u = MDAnalysis.Universe(*univ)
 
     def time_find_fragments(self, universe_type):

benchmarks/benchmarks/analysis/rdf.py

@@ -23,7 +23,7 @@ class SimpleRdfBench(object):
                    'natoms']
 
     def setup(self, nbins, range_val, natoms):
-        
+
         self.sel_str = 'name OW'
 
         self.u = MDAnalysis.Universe(TPR, XTC)

benchmarks/benchmarks/topology.py

@@ -14,7 +14,7 @@ class TopologyGuessBench(object):
     """
     params = (10, 100, 1000, 10000)
     param_names = ['num_atoms']
-    
+
     def setup(self, num_atoms):
         self.u = MDAnalysis.Universe(GRO)
         self.ag = self.u.atoms[:num_atoms]

maintainer/install_all.sh

@@ -34,7 +34,7 @@ setup_py () {
 command="install"
 options=""
 while getopts hdu OPT; do
-    case $OPT in 
+    case $OPT in
 	h) echo "$usage"; exit 0;;
 	d) command="develop";;
 	u) options="${options} --user";;
@@ -44,5 +44,3 @@ done
 
 setup_py $command package "${options}"
 setup_py $command testsuite "${options}"
-
-

mypy_requirements.txt

@@ -1,2 +1,2 @@
 mypy==0.960
-typing_extensions
+typing_extensions

package/AUTHORS

@@ -186,7 +186,7 @@ Chronological list of authors
   - Mingyi Xue
   - Meghan Osato
   - Anirvinya G
-  - Rishabh Shukla  
+  - Rishabh Shukla
   - Manish Kumar
   - Aditi Tripathi
   - Sukeerti T