def setUp(self):
self.merge_triples = ((
distribution.create_exponential(3, 2, 0.1),
distribution.create_exponential(3, 2, 0.1),
distribution.create_exponential(4, 2, 0.1),
), (distribution.create_linear(3, 0.2, 0.1),
distribution.create_linear(3, 0.2, 0.1),
distribution.create_linear(4, 0.2, 0.1)), (
distribution.create_explicit([0.1, 0.3]),
distribution.create_explicit([0.1, 0.3]),
distribution.create_explicit([0.1, 0.3, 0.5]),
))
for d1, d2, _ in self.merge_triples:
distribution.add_sample(_LOW_SAMPLE, d1)
distribution.add_sample(_HIGH_SAMPLE, d2)
def setUp(self):
self.merge_triples = (
(
distribution.create_exponential(3, 2, 0.1),
distribution.create_exponential(3, 2, 0.1),
distribution.create_exponential(4, 2, 0.1),
),(
distribution.create_linear(3, 0.2, 0.1),
distribution.create_linear(3, 0.2, 0.1),
distribution.create_linear(4, 0.2, 0.1)
),(
distribution.create_explicit([0.1, 0.3]),
distribution.create_explicit([0.1, 0.3]),
distribution.create_explicit([0.1, 0.3, 0.5]),
)
)
for d1, d2, _ in self.merge_triples:
distribution.add_sample(_LOW_SAMPLE, d1)
distribution.add_sample(_HIGH_SAMPLE, d2)
def _make_linear_dist():
return distribution.create_linear(3, 0.2, 0.1)
def test_should_succeed_if_inputs_are_ok(self):
num_finite_buckets = 1
got = distribution.create_linear(num_finite_buckets, 0.1, 0.1)
expect(len(got.bucketCounts)).to(equal(num_finite_buckets + 2))
def test_should_fail_if_growth_factor_is_bad(self):
testf = lambda: distribution.create_linear(1, -0.1, 0.1)
expect(testf).to(raise_error(ValueError))
def test_should_fail_if_num_finite_buckets_is_bad(self):
testf = lambda: distribution.create_linear(0, 1.1, 0.1)
expect(testf).to(raise_error(ValueError))
def _make_linear_dist():
return distribution.create_linear(3, 0.2, 0.1)
def test_should_succeed_if_inputs_are_ok(self):
num_finite_buckets = 1
got = distribution.create_linear(num_finite_buckets, 0.1, 0.1)
expect(len(got.bucketCounts)).to(equal(num_finite_buckets + 2))
def test_should_fail_if_growth_factor_is_bad(self):
testf = lambda: distribution.create_linear(1, -0.1, 0.1)
expect(testf).to(raise_error(ValueError))
def test_should_fail_if_num_finite_buckets_is_bad(self):
testf = lambda: distribution.create_linear(0, 1.1, 0.1)
expect(testf).to(raise_error(ValueError))