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
State: Experimental as of 0.4.0.
- Parameters
metric (str, callable) – The pairwise distance function to apply. See the scipy
pdist
docs and the scikit-bio functions linked under See Also for available metrics. Passing metrics as a strings is preferable as this often results in an optimized version of the metric being used.counts (2D array_like of ints or floats or 2D pandas DataFrame) – Matrix containing count/abundance data where each row contains counts of OTUs in a given sample.
ids (iterable of strs, optional) – Identifiers for each sample in
counts
. By default, samples will be assigned integer identifiers in the order that they were provided (where the type of the identifiers will bestr
).validate (bool, optional) – If False, validation of the input won’t be performed. This step can be slow, so if validation is run elsewhere it can be disabled here. However, invalid input data can lead to invalid results or error messages that are hard to interpret, so this step should not be bypassed if you’re not certain that your input data are valid. See
skbio.diversity
for the description of what validation entails so you can determine if you can safely disable validation.pairwise_func (callable, optional) – The function to use for computing pairwise distances. This function must take
counts
andmetric
and return a square, hollow, 2-Dnumpy.ndarray
of dissimilarities (floats). Examples of functions that can be provided arescipy.spatial.distance.pdist
andsklearn.metrics.pairwise_distances
. By default,scipy.spatial.distance.pdist
will be used.kwargs (kwargs, optional) – Metric-specific parameters.
- Returns
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
.- Return type
skbio.DistanceMatrix
- Raises
ValueError, MissingNodeError, DuplicateNodeError – If validation fails. Exact error will depend on what was invalid.
TypeError – If invalid method-specific parameters are provided.
See also
skbio.diversity
,skbio.diversity.beta
,skbio.diversity.get_beta_diversity_metrics
,skbio.diversity.alpha_diversity
,scipy.spatial.distance.pdist
,sklearn.metrics.pairwise_distances