Scipy hierarchial clustering - clusterize new vector
Use the euclidean metric? I think the precomputed clusters have a center. So you can calculate the distanc between every center and the new vector.
I am clusterizing a bunch of feature vectors using scipy linkage with ward method. 
I want a predictive model that works in two steps:

Training data is clusterized
A new vector comes, the distance between the vector and each cluster is computed, the new vector is assigned the "nearest" cluster's label

How can I compute the distances between a new vector and precomputed clusters?