scipy.cluster.hierarchy.from_mlab_linkage¶
-
scipy.cluster.hierarchy.
from_mlab_linkage
(Z)[source]¶ Convert a linkage matrix generated by MATLAB(TM) to a new linkage matrix compatible with this module.
The conversion does two things:
- the indices are converted from
1..N
to0..(N-1)
form, and - a fourth column
Z[:,3]
is added whereZ[i,3]
represents the number of original observations (leaves) in the non-singleton clusteri
.
This function is useful when loading in linkages from legacy data files generated by MATLAB.
Parameters: - Z : ndarray
A linkage matrix generated by MATLAB(TM).
Returns: - ZS : ndarray
A linkage matrix compatible with
scipy.cluster.hierarchy
.
See also
linkage
- for a description of what a linkage matrix is.
to_mlab_linkage
- transform from Scipy to MATLAB format.
Examples
>>> import numpy as np >>> from scipy.cluster.hierarchy import ward, from_mlab_linkage
Given a linkage matrix in MATLAB format
mZ
, we can usescipy.cluster.hierarchy.from_mlab_linkage
to import it into Scipy format:>>> mZ = np.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]])
>>> Z = from_mlab_linkage(mZ) >>> 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. ]])
As expected, the linkage matrix
Z
returned includes an additional column counting the number of original samples in each cluster. Also, all cluster indexes are reduced by 1 (MATLAB format uses 1-indexing, whereas Scipy uses 0-indexing).- the indices are converted from