v1.5.7

• Revised parallel Jaccard to support scipy==1.5.1 (previously failed with scipy=1.4.1 / #4)
• Updated leidenalg and scipy version requirements.
• Added PhenoGraph clustering tutorial with PBMC3K dataset from 10X Genomics.
• Created a test collection for use with pytest.

v1.5.6

• Fix the multiprocessing code that doesn't close/join the pool.

v1.5.5

Exposed parameter n_iterations for Leiden

v1.5.4

Fix to sort_by_size:
faster and efficient sorting by size of clusters

v1.5.3

Phenograph supports now Leiden algorithm for community detection.
The new feature can be called from phenograph.cluster, by choosing leiden as the clustering algorithm.
Few adjustments to the code including black formatting.

v1.5.2

• Include simple parallel implementation of brute force nearest neighbors search using scipy's cdist and multiprocessing. This may be more efficient than kdtree on very large high-dimensional data sets
  and avoids memory issues that arise in sklearn's implementation.
• Refactor parallel_jaccard_kernel to remove unnecessary use of ctypes and multiprocessing.Array.