skbio.diversity.block_beta_diversity¶

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

Perform a block-decomposition beta diversity calculation

State: Experimental as of 0.5.1.

Parameters:

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

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:

DistanceMatrix

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