scipy.cluster.hierarchy.to_mlab_linkage#
- scipy.cluster.hierarchy.to_mlab_linkage(Z)[source]#
Convert a linkage matrix to a MATLAB(TM) compatible one.
Converts a linkage matrix
Z
generated by the linkage function of this module to a MATLAB(TM) compatible one. The return linkage matrix has the last column removed and the cluster indices are converted to1..N
indexing.- Parameters:
- Zndarray
A linkage matrix generated by
scipy.cluster.hierarchy
.
- Returns:
- to_mlab_linkagendarray
A linkage matrix compatible with MATLAB(TM)’s hierarchical clustering functions.
The return linkage matrix has the last column removed and the cluster indices are converted to
1..N
indexing.
See also
linkage
for a description of what a linkage matrix is.
from_mlab_linkage
transform from Matlab to SciPy format.
Examples
>>> from scipy.cluster.hierarchy import ward, to_mlab_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 array([[ 0. , 1. , 1. , 2. ], [ 3. , 4. , 1. , 2. ], [ 6. , 7. , 1. , 2. ], [ 9. , 10. , 1. , 2. ], [ 2. , 12. , 1.29099445, 3. ], [ 5. , 13. , 1.29099445, 3. ], [ 8. , 14. , 1.29099445, 3. ], [11. , 15. , 1.29099445, 3. ], [16. , 17. , 5.77350269, 6. ], [18. , 19. , 5.77350269, 6. ], [20. , 21. , 8.16496581, 12. ]])
After a linkage matrix
Z
has been created, we can usescipy.cluster.hierarchy.to_mlab_linkage
to convert it into MATLAB format:>>> mZ = to_mlab_linkage(Z) >>> mZ array([[ 1. , 2. , 1. ], [ 4. , 5. , 1. ], [ 7. , 8. , 1. ], [ 10. , 11. , 1. ], [ 3. , 13. , 1.29099445], [ 6. , 14. , 1.29099445], [ 9. , 15. , 1.29099445], [ 12. , 16. , 1.29099445], [ 17. , 18. , 5.77350269], [ 19. , 20. , 5.77350269], [ 21. , 22. , 8.16496581]])
The new linkage matrix
mZ
uses 1-indexing for all the clusters (instead of 0-indexing). Also, the last column of the original linkage matrix has been dropped.