def conformational_space_comparison(clustering, trajectoryHandler, matrixHandler,
clustering_parameters, refinement_parameters):
# clustering = Refiner(matrixHandler,
# trajectoryHandler,
# clustering_parameters,
# refinement_parameters,
# observer).run(clustering)
traj_ranges = {}
current = 0
for i, pdb_source in enumerate(trajectoryHandler.sources):
num_confs = pdb_source.get_info("number_of_conformations")
traj_ranges["traj_%d"%i] = (current, current + num_confs -1)
current = current + num_confs
decomposed_clusters = Separator.separate(clustering.clusters, traj_ranges)
analysis = Analyzer.run(decomposed_clusters, matrixHandler.distance_matrix)
return analysis
def conformational_space_comparison(clustering, trajectoryHandler,
matrixHandler, clustering_parameters,
refinement_parameters):
# clustering = Refiner(matrixHandler,
# trajectoryHandler,
# clustering_parameters,
# refinement_parameters,
# observer).run(clustering)
traj_ranges = {}
current = 0
for i, pdb_source in enumerate(trajectoryHandler.sources):
num_confs = pdb_source.get_info("number_of_conformations")
traj_ranges["traj_%d" % i] = (current, current + num_confs - 1)
current = current + num_confs
decomposed_clusters = Separator.separate(clustering.clusters, traj_ranges)
analysis = Analyzer.run(decomposed_clusters, matrixHandler.distance_matrix)
return analysis
def conformational_space_comparison(clustering, matrixHandler,
trajectoryHandler, clustering_parameters,
refinement_parameters, observer):
# clustering = Refiner(matrixHandler,
# trajectoryHandler,
# clustering_parameters,
# refinement_parameters,
# observer).run(clustering)
# TODO: testing
traj_ranges = {}
current = 0
for i, pdb in enumerate(trajectoryHandler.pdbs):
traj_ranges["traj_%d" % i] = (current,
current + pdb["conformations"] - 1)
current = current + pdb["conformations"]
decomposed_clusters = Separator.separate(clustering.clusters, traj_ranges)
analysis = Analyzer.run(decomposed_clusters, matrixHandler.distance_matrix)
return analysis
