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        "author": "Fabio Zanini",
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        "description": "k nearest neighbor (KNN) graphs via Pearson correlation distance and local sensitive hashing (LSH).\n\n- **Development**: https://github.com/iosonofabio/lshknn\n- **Authors**: Fabio Zanini and Paolo Carnevali\n- **License**: MIT\n- **Copyright**: Fabio Zanini and Chan Zuckerberg Initiative\n\n.. code-block:: python\n\n    import numpy as np\n    import lshknn\n\n    # Make mock data\n    # 2 features (rows), 4 samples (columns)\n    data = np.array(\n            [[1, 0, 1, 0],\n             [0, 1, 0, 1]],\n            dtype=np.float64)\n\n    # Instantiate class\n    c = lshknn.Lshknn(\n            data=data,\n            k=1,\n            threshold=0.2,\n            m=10,\n            slice_length=4)\n\n    # Call subroutine\n    knn, similarity, n_neighbors = c()\n\n    # Check result\n    assert (knn == [[2], [3], [0], [1]]).all()",
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