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.
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 be str
).
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
and metric
and return a square, hollow, 2-D
numpy.ndarray
of dissimilarities (floats). Examples of functions
that can be provided are scipy.spatial.distance.pdist
and
sklearn.metrics.pairwise_distances
. By default,
sklearn.metrics.pairwise_distances
will be used.
kwargs (kwargs, optional) – Metric-specific parameters.
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
.
skbio.DistanceMatrix
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()