skbio.diversity.beta_diversity#
- skbio.diversity.beta_diversity(metric, counts, ids=None, validate=True, pairwise_func=None, **kwargs)[source]#
Compute distances between all pairs of samples.
- Parameters:
- metricstr or callable
The beta diversity metric, i.e., a pairwise distance function to apply to the sample(s). See
beta
and SciPy’spdist
for available metrics. Passing metric as a string is preferable as this often results in an optimized version of the metric being used.- countstable_like of shape (n_samples, n_taxa) or (n_taxa,)
Vector or matrix containing count/abundance data of one or multiple samples. See supported formats.
- idsarray_like of shape (n_samples,), optional
Identifiers for each sample in
counts
. If not provided, will extract sample IDs fromcounts
, if available, or assign integer identifiers in the order that samples were provided.- validate: bool, optional
If True (default), validate the input data before applying the alpha diversity metric. See
skbio.diversity
for the details of validation.- pairwise_funccallable, optional
The function to use for computing pairwise distances. Must take
counts
andmetric
and return a square, hollow, 2-D float array of dissimilarities. Examples of functions that can be provided are SciPy’spdist
(default) and scikit-learn’spairwise_distances
.- kwargsdict, optional
Metric-specific parameters. Refer to the documentation of the chosen metric. A special parameter is
taxa
, needed by some phylogenetic metrics. If not provided, will extract taxa (feature IDs) fromcounts
, if available, and pass to the metric.
- Returns:
DistanceMatrix
Distances between all pairs of samples (i.e., rows). The number of rows and columns will be equal to the number of rows in
counts
.
- Raises:
- ValueError, MissingNodeError, DuplicateNodeError
If validation fails. Exact error will depend on what was invalid.
- Any Exception
If invalid method-specific parameters are provided.