skbio.stats.distance.DissimilarityMatrix¶
- class skbio.stats.distance.DissimilarityMatrix(data, ids=None, validate=True)[source]¶
Store dissimilarities between objects.
A DissimilarityMatrix instance stores a square, hollow, two-dimensional matrix of dissimilarities between objects. Objects could be, for example, samples or DNA sequences. A sequence of IDs accompanies the dissimilarities.
Methods are provided to load and save dissimilarity matrices from/to disk, as well as perform common operations such as extracting dissimilarities based on object ID.
- Parameters:
data (array_like or DissimilarityMatrix) – Square, hollow, two-dimensional
numpy.ndarray
of dissimilarities (floats), or a structure that can be converted to anumpy.ndarray
usingnumpy.asarray
or a one-dimensional vector of dissimilarities (floats), as defined by scipy.spatial.distance.squareform. Can instead be a DissimilarityMatrix (or subclass) instance, in which case the instance’s data will be used. Data will be converted to a floatdtype
if necessary. A copy will not be made if already anumpy.ndarray
with a floatdtype
.ids (sequence of str, optional) – Sequence of strings to be used as object IDs. Must match the number of rows/cols in data. If
None
(the default), IDs will be monotonically-increasing integers cast as strings, with numbering starting from zero, e.g.,('0', '1', '2', '3', ...)
.validate (bool, optional) – If validate is
True
(the default) and data is not a DissimilarityMatrix object, the input data will be validated.
See also
DistanceMatrix
,scipy.spatial.distance.squareform
Notes
The dissimilarities are stored in redundant (square-form) format [1].
The data are not checked for symmetry, nor guaranteed/assumed to be symmetric.
References
Attributes
T
Transpose of the dissimilarity matrix.
data
Array of dissimilarities.
default_write_format
dtype
Data type of the dissimilarities.
ids
Tuple of object IDs.
png
Display heatmap in IPython Notebook as PNG.
shape
Two-element tuple containing the dissimilarity matrix dimensions.
size
Total number of elements in the dissimilarity matrix.
svg
Display heatmap in IPython Notebook as SVG.
Built-ins
Check if the specified ID is in the dissimilarity matrix.
Compare this dissimilarity matrix to another for equality.
Slice into dissimilarity data by object ID or numpy indexing.
Helper for pickle.
Determine whether two dissimilarity matrices are not equal.
Return a string representation of the dissimilarity matrix.
Methods
between
(from_, to_[, allow_overlap])Obtain the distances between the two groups of IDs
copy
()Return a deep copy of the dissimilarity matrix.
filter
(ids[, strict])Filter the dissimilarity matrix by IDs.
from_iterable
(iterable, metric[, key, keys])Create DissimilarityMatrix from an iterable given a metric.
index
(lookup_id)Return the index of the specified ID.
plot
([cmap, title])Creates a heatmap of the dissimilarity matrix
read
(file[, format])Create a new
DissimilarityMatrix
instance from a file.Return an array of dissimilarities in redundant format.
Create a
pandas.DataFrame
from thisDissimilarityMatrix
.Return the transpose of the dissimilarity matrix.
within
(ids)Obtain all the distances among the set of IDs
write
(file[, format])Write an instance of
DissimilarityMatrix
to a file.