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# skbio.diversity.block_beta_diversity

skbio.diversity.block_beta_diversity(metric, counts, ids, validate=True, k=64, reduce_f=None, map_f=None, **kwargs)

  Perform a block-decomposition beta diversity calculation

  State: Experimental as of 0.5.1.

  Parameters:

    - metric (str or callable) – The pairwise distance function to apply. If `metric` is a string, it must be resolvable by scikit-bio (e.g., UniFrac methods), or must be callable.

    - counts (2D array_like of ints or floats) – Matrix containing count/abundance data where each row contains counts of OTUs in a given sample.

    - ids (iterable of strs) – Identifiers for each sample in `counts`.

    - validate (bool, optional) – See `skbio.diversity.beta_diversity` for details.

    - reduce_f (function, optional) –

      A method to reduce PartialDistanceMatrix objects into a single DistanceMatrix. The expected signature is:

      > f(Iterable of DistanceMatrix) -> DistanceMatrix

      Note, this is the reduce within a map/reduce.

    - map_f (function, optional) –

      A method that accepts a _block_compute. The expected signature is:

      > f(**kwargs) -> DistanceMatrix

      NOTE: ipyparallel’s map_async will not work here as we need to be able to pass around **kwargs`.

    - k (int, optional) – The blocksize used when computing distances

    - kwargs (kwargs, optional) – Metric-specific parameters.

  Returns:

    A distance matrix relating all samples represented by counts to each other.

  Return type:

    DistanceMatrix

  Notes

  This method is designed to facilitate computing beta diversity in parallel. In general, if you are processing a few hundred samples or less, then it is likely the case that skbio.diversity.beta_diversity will be faster. The original need which motivated the development of this method was processing the Earth Microbiome Project [1] dataset which at the time spanned over 25,000 samples and 7.5 million open reference OTUs.

  See also

  `skbio.diversity.beta_diversity`, `skbio.diversity.partial_beta_diversity`

  References

  [1]

  http://www.earthmicrobiome.org/