def test_best_fit_line_multiple_coresets(self):
# generate points
N = 1200
# for example1 choose N that divides by 6
data = example1(N)
P = np.c_[np.mgrid[1:N + 1], data]
P1 = P[:1000]
P2 = P[1000:]
C = Coreset.OneSegmentCorset(P)
C1 = Coreset.OneSegmentCorset(P1)
C2 = Coreset.OneSegmentCorset(P2)
best_fit_line_P = utils.calc_best_fit_line(P)
best_fit_line_C = utils.calc_best_fit_line(C.repPoints)
best_fit_line_P1 = utils.calc_best_fit_line(P1)
best_fit_line_C1 = utils.calc_best_fit_line(C1.repPoints)
original_cost_not_best_fit_line = utils.sqrd_dist_sum(P, best_fit_line_P)
single_coreset_cost = utils.sqrd_dist_sum(C.repPoints, best_fit_line_P) * C.weight
C1_cost = int(utils.sqrd_dist_sum(C1.repPoints, best_fit_line_P) * C1.weight)
P1_cost = int(utils.sqrd_dist_sum(P1, utils.calc_best_fit_line(P1)))
C2_cost = int(utils.sqrd_dist_sum(C2.repPoints, best_fit_line_P) * C2.weight)
dual_coreset_cost = C1_cost + C2_cost
self.assertEqual(int(original_cost_not_best_fit_line), int(single_coreset_cost))
self.assertEqual(C1_cost, P1_cost)
self.assertEqual(int(original_cost_not_best_fit_line), int(dual_coreset_cost))
res2 = utils.calc_best_fit_line_coreset(C1, C2)
self.assertEqual(best_fit_line_P, res2)
def test_OneSegmentCoreset_bestFitLineIdentical_diferrentWeights(self):
# generate points
N = 1200
# for example1 choose N that divides by 6
data = example1(N)
P = np.c_[np.mgrid[1:N + 1], data]
P1 = P[:5]
P2 = P[5:20]
P3 = P[20:30]
P4 = P[30:]
C = Coreset.OneSegmentCorset(P)
C1 = Coreset.OneSegmentCorset(P1)
C2 = Coreset.OneSegmentCorset(P2)
C3 = Coreset.OneSegmentCorset(P3)
C4 = Coreset.OneSegmentCorset(P4)
C1_C2 = [C1,C2]
C3_C4 = [C3,C4]
coreset_of_coresets1 = Coreset.OneSegmentCorset(C1_C2, True)
coreset_of_coresets2 = Coreset.OneSegmentCorset(C3_C4, True)
coreset_of_coresetrs = [coreset_of_coresets1, coreset_of_coresets2]
coreset_of_coresets3 = Coreset.OneSegmentCorset(coreset_of_coresetrs, True)
original_points_best_fit_line = utils.calc_best_fit_line(P)
single_coreset_best_fit_line = utils.calc_best_fit_line(C.repPoints)
coreset_of_coresetes_best_fit_line = utils.calc_best_fit_line(coreset_of_coresets3.repPoints)
np.testing.assert_allclose(original_points_best_fit_line, coreset_of_coresetes_best_fit_line)
np.testing.assert_allclose(coreset_of_coresetes_best_fit_line, single_coreset_best_fit_line)
def test_OneSegmentCoreset_Cost(self):
# generate points
n = 1200
data = example1(n)
P = np.c_[np.mgrid[1:n + 1], data]
P1 = P[:1000]
C1 = Coreset.OneSegmentCorset(P1)
best_fit_line_P = utils.calc_best_fit_line(P)
best_fit_line_P1 = utils.calc_best_fit_line(P1)
best_fit_line_C1 = utils.calc_best_fit_line(C1.repPoints)
self.assertEqual(best_fit_line_P1.all(), best_fit_line_C1.all())
original_cost_not_best_fit_line = utils.sqrd_dist_sum(P1, best_fit_line_P)
original_cost_best_fit_line = utils.sqrd_dist_sum(P1, best_fit_line_P1)
single_coreset_cost_not_best_fit_line = utils.sqrd_dist_sum(C1.repPoints, best_fit_line_P) * C1.weight
single_coreset_cost_best_fit_line = utils.sqrd_dist_sum(C1.repPoints, best_fit_line_C1) * C1.weight
self.assertEqual(int(original_cost_best_fit_line), int(single_coreset_cost_best_fit_line))
self.assertEqual(int(original_cost_not_best_fit_line), int(single_coreset_cost_not_best_fit_line))