def sample_combination(num_imgs):
if CHOOSE_UNIFORM:
return sample_convex_combinations.sample(num_imgs)
else:
result = [0] * num_imgs
result[random.randrange(num_imgs)] = 1
return result
def test_dimensions(self):
for d in [1, 2, 3, 5, 10, 12, 19, 30]:
with self.subTest(d=d):
actual = sample_convex_combinations.sample(d, rng=dummy_rng)
self.assertEqual(d, len(actual), actual)
self.assertTrue(all(0.0 <= e <= 1.0 for e in actual), actual)
self.assertAlmostEqual(1, sum(actual), actual)
def test_dimensions(self):
for d in [1, 2, 3, 5, 10, 12, 19, 30]:
with self.subTest(d=d):
actual = sample_convex_combinations.sample(d, span_origin=True)
self.assertEqual(d, len(actual), actual)
self.assertTrue(all(0.0 <= e <= 1.0 for e in actual), actual)
# The following will fail 0.0002% of the time for no reason.
# TODO: Find a better way to deal with it.
self.assertTrue(0.000001 <= sum(actual) <= 0.999999, actual)
def gather(d, span_origin, asserter):
actual = sample_convex_combinations.sample(d, span_origin=span_origin)
# Various sanity-checks:
asserter.assertEqual(d, len(actual), actual)
asserter.assertTrue(all(0.0 <= e <= 1.0 for e in actual), actual)
if span_origin:
# The following will fail 0.0002% of the time for no reason.
# TODO: Find a better way to deal with it.
asserter.assertTrue(
GATHER_FALSE_POSITIVE <= sum(actual) <= 1 - GATHER_FALSE_POSITIVE,
actual)
else:
asserter.assertAlmostEqual(1.0, sum(actual), actual)
return actual
def test_call(self):
self.assertEqual(3, len(sample_convex_combinations.sample(3)))
def test_call(self):
self.assertEqual(
3, len(sample_convex_combinations.sample(3, span_origin=True)))