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Python framework for fast (approximated) nearest neighbour search in large, high-dimensional data sets using different locality-sensitive hashes.

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# Issue Type [x] Bug (Typo) # Steps to Replicate and Expected Behaviour - Examine nearpy/hashes/permutation/hashpermutationmapper.py, nearpy/hashes/permutation/hashpermutations.py and observe `separatly`, however expect to see `separately`. - Examine nearpy/filters/vectorfilter.py and observe...

There are small typos in: - README.md - nearpy/filters/uniquefilter.py - nearpy/filters/vectorfilter.py - nearpy/hashes/permutation/hashpermutationmapper.py - nearpy/hashes/permutation/hashpermutations.py - nearpy/hashes/permutation/permutedIndex.py - nearpy/hashes/randombinaryprojectiontree.py Fixes: - Should read `separately` rather than `separatly`. - Should read...

I have input samples as a sparse matrix of shape **(531990 samples, 85765 features)**. The size of this matrix in memory is **56KB**. The matrix as a numpy array is...

Please update the version in the repo.

This library does not work with sklearn Pipelines as it is now. I converted the RandomBinaryProjections this way, for a project I am working on in [this repo](https://github.com/glicerico/SGNN/blob/a327426671a2ad978e794a23aae8aa0405d95ecb/SGNN/core.py#L34)

For certain projections at least (RandomBinary for example), it doesn't seem to make a difference whether you normalize the elements for where they hash. But if you care about the...

Minor issue. The `redis_object` in the `_add_vector` function of the [storage_redis.py](https://github.com/pixelogik/NearPy/blob/master/nearpy/storage/storage_redis.py) is not being used since the `redis_object` is already associated with `self`, and it should not be passed as...

Because I found this method to be very useful on Redis storage, I've added it to the mongo storage as well. I haven't done a benchmark to compare what is...

I was going to compute recall rate using NearPy. But I found that the vectors I stored has been revised. The following is what I did. I stored a bunch...