Using pip 21.3.1 from /home/jjerphan/.local/share/miniconda3/envs/kdtree/lib/python3.9/site-packages/pip (python 3.9)
Obtaining file:///home/jjerphan/dev/kdtree
  Running command python setup.py egg_info

  Error compiling Cython file:
  ------------------------------------------------------------
  ...
              # the asynchronous construction of the tree.
              active Counter counter = consume Counter()
              active QueryActor query_actor

          for idx_worker in range(n_workers):
              query_actor = consume QueryActor(
                                             ^
  ------------------------------------------------------------

  kdtree.pyx:785:44: Call with wrong number of arguments (expected 0, got 11)
  Traceback (most recent call last):
    File "<string>", line 1, in <module>
    File "/home/jjerphan/dev/kdtree/setup.py", line 20, in <module>
      ext_modules=cythonize(extensions),
    File "/home/jjerphan/dev/kdtree/src/cython/Cython/Build/Dependencies.py", line 1110, in cythonize
      cythonize_one(*args)
    File "/home/jjerphan/dev/kdtree/src/cython/Cython/Build/Dependencies.py", line 1277, in cythonize_one
      raise CompileError(None, pyx_file)
  Cython.Compiler.Errors.CompileError: kdtree.pyx
  Compiling kdtree.pyx because it changed.
  [1/1] Cythonizing kdtree.pyx
  Preparing metadata (setup.py) ... error

 → python debug.py
 TypeError: 'consume' operand is not isolated
 Exception ignored in: 'KDTree.query'
 Traceback (most recent call last):
   File "/home/jjerphan/dev/kdtree/debug.py", line 18, in <module>
       tree.query(Y, knn_indices, knn_distances)
       TypeError: 'consume' operand is not isolated

prange is not resolved when used in a cypclass.
Co-authored-by: Xavier Thompson <xavier.thompson@nexedi.com>

prange can't be resolved, yet it is imported.

This change the logic to query the tree for nearest neighbors.
Start with a simple sequential query for each point.

This change the logic to query the tree for nearest neighbors.
Start with a simple sequential query for each point.

This change the logic to query the tree for nearest neighbors.
Start with a simple sequential query for each point.

This change the logic to query the tree for nearest neighbors.
Start with a simple sequential query for each point.

This change the logic to query the tree for nearest neighbors.
Start with a simple sequential query for each point.

This change the logic to query the tree for nearest neighbors.
Start with a simple sequential query for each point.

This move the Node informations to dedicated datastructure
decoupling the actor hierarchy from the data allowing using
adapted pattern for both constructing and querying the tree.

This has been extracted from:
https://lab.nexedi.com/jjerphan/cython_plus_experiments/tree/queue-dispatch/kdtree

The runtime was written by Xavier T. and adapted by Julien J.

The experimentation KDTree was written by Julien J.
Co-authored-by: Xavier Thompson <xavier.thompson@nexedi.com>