""" Load data into a numpy matrix. (1) load function is used to load a .npy binary file, which can be generated from a .txt file (2) genfromtxt generates a numpy array from a raw text file """ print "Loading", sys.argv[1], "similarity matrix..." cost_mat = load(sys.argv[1]) #cost_mat = genfromtxt(data_path + '/cost-matrices/' + sys.argv[1]) """ Compute the bullseye score. Assuming MPEG-7 data is loaded """ e = Evaluation(cost_mat, 20, 70) print "Top 40 bullseye score: ", e.bullseye(40) """ Compute a new similarity matrix using dice coefficient as a population cue """ #Geometric mean, to ensure symmetry cost_mat = sqrt(cost_mat * cost_mat.transpose()) p = Population(cost_mat, 20, 70, verbose=True) #Not setting k will attempt to automatically find it! processed_matrix = p.generate_diff(k=13) e = Evaluation(processed_matrix, 20, 70) print "Top 40 bullseye score using dice: ", e.bullseye(40) """ Update the similarity matrix further using the previous matrix to build components