We propose in this paper an exploratory analysis algorithm for functional
data. The method partitions a set of functions into K clusters and represents
each cluster by a simple prototype (e.g., piecewise constant). The total number
of segments in the prototypes, P, is chosen by the user and optimally
distributed among the clusters via two dynamic programming algorithms. The
practical relevance of the method is shown on two real world datasets