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)
