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GuessBonds
AroundBenchmark.ipynb
Augment-and-Gridsearch.ipynb
Augment.ipynb
Augment_Functionality.ipynb
Augment_Guessbonds.ipynb
BM_CGMDA_Uniform_New.ipynb
BM_CappedNS.ipynb
BM_MDAKDTree_Uniform_New.ipynb
BM_NNcutoff_Uniform.ipynb
BM_PairContact.ipynb
BM_PairContact_MOD.ipynb
BM_Selection_Slab.ipynb
BM_Selection_SphProtein.ipynb
BM_build.ipynb
Capped_Distance.ipynb
CellGrid_CellsizeOptimize.ipynb
CellGrid_Optimization.ipynb
Comparison of Query_ball_tree and query_ball_point.ipynb
GuessBonds.ipynb
New_SingleQuery.ipynb
Octree.ipynb
OctreeComparison.ipynb
PBC_PairContact.ipynb
PBC_SingleQuery.ipynb
RDF_Comparison.ipynb
README.md
SingleQuery.ipynb
SingleQueryComparison.ipynb
SingleQuery_NoPBC.ipynb
SphericalParticleSelection.ipynb
big.gro
guessbonds_benchmark.ipynb
initialization.py
small.gro

README.md

Num File Content
  1.    | [SingleQuery_NoPBC](https://github.com/ayushsuhane/Benchmarks_Distance/blob/master/Notebooks/SingleQuery_NoPBC.ipynb)	     |Consists of benchmarks associated with single query for cell-list, different KDtree, Octree (not yet). It also contains the variation ofexecution time with respect to variation in particles per cell for the cell-list data structure for single queries.|
    
  2.  | [Octree](https://github.com/ayushsuhane/Benchmarks_Distance/blob/master/Notebooks/Octree.ipynb)			|Comparison of adhoc octree C++ code (Behley 2015), with KDtree (PBC and Non PBC structure).
    
  3.  |[CellGrid_Optimization](https://github.com/ayushsuhane/Benchmarks_Distance/blob/master/Notebooks/CellGrid_Optimization.ipynb)	|Optimization of cellgrid module to evaluate optimized particles per cell.
    
  4.  |[BM_Selection_SphProtein](https://github.com/ayushsuhane/Benchmarks_Distance/blob/master/Notebooks/BM_Selection_SphProtein.ipynb) |	Selection around spherical protein centred around the midpoint of the box. Two different groups of particles are treated as solvent and protein particles.
    
  5.  |[BM_Selection_Slab](https://github.com/ayushsuhane/Benchmarks_Distance/blob/master/Notebooks/BM_Selection_Slab.ipynb)	|Two slabs of particles and selection of group of particles around each other within a cutoff distance
    
  6.  |[BM_PairContact](https://github.com/ayushsuhane/Benchmarks_Distance/blob/master/Notebooks/BM_PairContact.ipynb)		|Selection of all particles within a cutoff distance and comparison between KDTree, Celllist, Brute Force
    
  7.  |[AroundBenchmark](https://github.com/ayushsuhane/Benchmarks_Distance/blob/master/Notebooks/AroundBenchmark.ipynb)    |Benchmarks for around selections with new ``capped_distance`` function
    
  8.  |[Augment-and-Gridsearch](https://github.com/ayushsuhane/Benchmarks_Distance/blob/master/Notebooks/Augment-and-Gridsearch.ipynb)    |Benchmarks for ``augment_coordinates+KDTree`` with cell-list algorithm ``nsgrid``
    
  9.  |[Augment](https://github.com/ayushsuhane/Benchmarks_Distance/blob/master/Notebooks/Augment.ipynb)    |Tests and performance testing of augment function
    
  10. |[Augment-Functionality](https://github.com/ayushsuhane/Benchmarks_Distance/blob/master/Notebooks/Augment_Functionality.ipynb)    |Performance test of augment for triclininc systems
    
  11. |[Augment_GuessBonds](https://github.com/ayushsuhane/Benchmarks_Distance/blob/master/Notebooks/Augment_Guessbonds.ipynb)     |Real Case scenario for guessing bonds with augment functionality
    
  12. |[BM_CappedNS](https://github.com/ayushsuhane/Benchmarks_Distance/blob/master/Notebooks/BM_CappedNS.ipynb)     |Final benchmarks for ``capped_distance`` function to determine the rules in ``lib.distances._determine_method`` and ``lib.distances_determine_method_self``
    
  13. |[BM_PairContact_MOD](https://github.com/ayushsuhane/Benchmarks_Distance/blob/master/Notebooks/BM_PairContact_MOD.ipynb)    |Comparison of Cellgrid, KDtree and brute force for contact maps
    
  14. |Comparison of Query_ball_tree and query_ball_point |Comparison between individual query and query by tree from scipy.spatial.cKDTree
  15. |New_SingleQuery |Comparison of single query performance for bruteforce, scipy KDtree + augment and previous implementation of PeriodicKDTree
  16. |OctreeComparison |Comparison of single query fixed radius search for Octree, KDtree, Cell-list and brute force
  17. |PBC_PairContact |Pair contact comparison between Octree, Cell-list, KDTree and brute force
  18. |PBC_SingleQuery |An extensive comparison of all the methods i.e. different variants of KDTree, cell-list, brute force and Octree for single queries and PBC aware distance calculations
  19. |RDF_Comparison |Comparison of RDF between previous and new implementation for a use case
  20. |guessbonds_benchmark |Usage of self_capped_distance in guess bonds and performance for a use case.
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