skbio.stats.distance.
DistanceMatrix
(data, ids=None)[source]¶Store distances between objects.
A DistanceMatrix is a DissimilarityMatrix with the additional requirement that the matrix data is symmetric. There are additional methods made available that take advantage of this symmetry.
See also
Notes
The distances are stored in redundant (square-form) format [1]. To facilitate use with other scientific Python routines (e.g., scipy), the distances can be retrieved in condensed (vector-form) format using condensed_form.
DistanceMatrix only requires that the distances it stores are symmetric. Checks are not performed to ensure the other three metric properties hold (non-negativity, identity of indiscernibles, and triangle inequality) [2]. Thus, a DistanceMatrix instance can store distances that are not metric.
References
[1] | http://docs.scipy.org/doc/scipy/reference/spatial.distance.html |
[2] | http://planetmath.org/metricspace |
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
x in dm |
Check if the specified ID is in the dissimilarity matrix. |
dm1 == dm2 |
Compare this dissimilarity matrix to another for equality. |
dm[x] |
Slice into dissimilarity data by object ID or numpy indexing. |
__init_subclass__ |
This method is called when a class is subclassed. |
dm1 != dm2 |
Determine whether two dissimilarity matrices are not equal. |
str(dm) |
Return a string representation of the dissimilarity matrix. |
Methods
condensed_form () |
Return an array of distances in condensed format. |
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 DistanceMatrix from all pairs in an iterable given a metric. |
index (lookup_id) |
Return the index of the specified ID. |
permute ([condensed]) |
Randomly permute both rows and columns in the matrix. |
plot ([cmap, title]) |
Creates a heatmap of the dissimilarity matrix |
read (file[, format]) |
Create a new DistanceMatrix instance from a file. |
redundant_form () |
Return an array of dissimilarities in redundant format. |
to_data_frame () |
Create a pandas.DataFrame from this DissimilarityMatrix . |
to_series () |
Create a pandas.Series from this DistanceMatrix . |
transpose () |
Return the transpose of the dissimilarity matrix. |
write (file[, format]) |
Write an instance of DistanceMatrix to a file. |