I've implemented the blue (multi-round random election process), cobalt (greedy algorithm with random order), and independent selection (random selection of test set) algorithms for finding independent sets and bipartite independent pairs in graphs. The files esl_msa_iset.c and esl_iset.c are analogous to esl_msacluster.c and esl_cluster.c.
I also added a new distance function to esl_distance.c which computes a connectivity metric for sequences within a MSA. A user of profmark can elect for this metric to appear in the .tbl file of a profmark benchmark.
I've implemented the blue (multi-round random election process), cobalt (greedy algorithm with random order), and independent selection (random selection of test set) algorithms for finding independent sets and bipartite independent pairs in graphs. The files esl_msa_iset.c and esl_iset.c are analogous to esl_msacluster.c and esl_cluster.c.
I also added a new distance function to esl_distance.c which computes a connectivity metric for sequences within a MSA. A user of profmark can elect for this metric to appear in the .tbl file of a profmark benchmark.