scipy.cluster.hierarchy.

num_obs_linkage#

scipy.cluster.hierarchy.num_obs_linkage(Z)[source]#

Return the number of original observations of the linkage matrix passed.

Parameters:

Zndarray: The linkage matrix on which to perform the operation.

Returns:

nint: The number of original observations in the linkage.

Notes

num_obs_linkage has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

Library	CPU	GPU
NumPy	✅	n/a
CuPy	n/a	✅
PyTorch	✅	✅
JAX	✅	✅
Dask	✅	n/a

See Support for the array API standard for more information.

Examples

>>> from scipy.cluster.hierarchy import ward, num_obs_linkage
>>> from scipy.spatial.distance import pdist

>>> X = [[0, 0], [0, 1], [1, 0],
...      [0, 4], [0, 3], [1, 4],
...      [4, 0], [3, 0], [4, 1],
...      [4, 4], [3, 4], [4, 3]]

>>> Z = ward(pdist(X))

Z is a linkage matrix obtained after using the Ward clustering method with X, a dataset with 12 data points.

>>> num_obs_linkage(Z)
12