def test_fast_segmentation(self): n = 360 k = 3 epsilon = 1 generate_input_file(n) data = np.genfromtxt("input.csv", delimiter=" ") p = np.c_[np.mgrid[1:n + 1], data] D = Coreset.build_coreset(p, k, epsilon) print len(D) x = np.empty((0, 4)) for coreset in D: print "coreset range", coreset.e - coreset.b + 1 pts = utils.pt_on_line(xrange(int(coreset.b), int(coreset.e) + 1), coreset.g) # TODO: 2nd parameter should be epsilon w = Coreset.PiecewiseCoreset(len(pts[0]), epsilon) p_coreset = np.column_stack((pts[0], pts[1], pts[2], w)) p_coreset_filtered = p_coreset[p_coreset[:, 3] > 0] # print "weighted points", p_coreset_filtered x = np.append(x, p_coreset_filtered, axis=0) print "num of weighted points", len(x) dividers = ksegment.coreset_k_segment_fast_segmentation(x, k) print "dividers", dividers print "dividers-cost:", utils.calc_cost_dividers(p, dividers) utils.visualize_3d(p, dividers)
def test_bicritiria(self): n = 300 k = 8 data = example1(n) p = np.c_[np.mgrid[1:n + 1], data] bicritiria_cost = Coreset.bicriteria(p, k) print "Bicritiria estimate: ", bicritiria_cost real_cost = utils.calc_cost_dividers(p, ksegment.k_segment(p, k)) print "real cost: ", real_cost self.assertGreaterEqual(bicritiria_cost, real_cost)
def test_fast_segmentation(self): # generate points n = 600 k = 6 epsilon = 10 generate_input_file(n) data = np.genfromtxt("input.csv", delimiter=" ") p = np.c_[np.mgrid[1:n + 1], data] D = Coreset.build_coreset(p, k, epsilon) print D dividers = ksegment.coreset_k_segment_fast_segmentation(D, k, epsilon) print "dividers", dividers print "dividers-cost:", utils.calc_cost_dividers(p, dividers)