scipy.cluster.hierarchy.

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` to `0..(N-1)` form, and

• a fourth column `Z[:,3]` is added where `Z[i,3]` represents the number of original observations (leaves) in the non-singleton cluster `i`.

Parameters:
Zndarray

A linkage matrix generated by MATLAB(TM).

Returns:
ZSndarray

A linkage matrix compatible with `scipy.cluster.hierarchy`.

`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 use `scipy.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 indices are reduced by 1 (MATLAB format uses 1-indexing, whereas SciPy uses 0-indexing).