def test_should_merge_bucket_counts_correctly(self):
for d1, d2, _ in self.merge_triples:
d1_start = list(d1.bucketCounts)
d2_start = list(d2.bucketCounts)
want = [x + y for (x,y) in zip(d1_start, d2_start)]
distribution.merge(d1, d2)
expect(d2.bucketCounts).to(equal(want))
def test_should_merge_bucket_counts_correctly(self):
for d1, d2, _ in self.merge_triples:
d1_start = list(d1.bucketCounts)
d2_start = list(d2.bucketCounts)
want = [x + y for (x, y) in zip(d1_start, d2_start)]
distribution.merge(d1, d2)
expect(d2.bucketCounts).to(equal(want))
def test_should_merge_stats_correctly(self):
# TODO(add a check of the variance)
for d1, d2, _ in self.merge_triples:
distribution.merge(d1, d2)
expect(d2.count).to(equal(2))
expect(d2.mean).to(equal((_HIGH_SAMPLE + _LOW_SAMPLE) / 2))
expect(d2.maximum).to(equal(_HIGH_SAMPLE))
expect(d2.minimum).to(equal(_LOW_SAMPLE))
def test_should_merge_stats_correctly(self):
# TODO(add a check of the variance)
for d1, d2, _ in self.merge_triples:
distribution.merge(d1, d2)
expect(d2.count).to(equal(2))
expect(d2.mean).to(equal(old_div((_HIGH_SAMPLE + _LOW_SAMPLE), 2)))
expect(d2.maximum).to(equal(_HIGH_SAMPLE))
expect(d2.minimum).to(equal(_LOW_SAMPLE))
def test_should_fail_on_dissimilar_bucket_options(self):
explicit = _make_explicit_dist()
linear = _make_linear_dist()
exponential = _make_exponential_dist()
pairs = ((explicit, linear), (explicit, exponential), (linear,
exponential))
for p in pairs:
testf = lambda: distribution.merge(*p)
expect(testf).to(raise_error(ValueError))
def test_should_fail_on_dissimilar_bucket_options(self):
explicit = _make_explicit_dist()
linear = _make_linear_dist()
exponential = _make_exponential_dist()
pairs = (
(explicit, linear),
(explicit, exponential),
(linear, exponential)
)
for p in pairs:
testf = lambda: distribution.merge(*p)
expect(testf).to(raise_error(ValueError))
def test_should_fail_on_dissimilar_bucket_counts(self):
for _, d2, d3 in self.merge_triples:
testf = lambda: distribution.merge(d2, d3)
expect(testf).to(raise_error(ValueError))
def test_should_fail_on_dissimilar_bucket_counts(self):
for _, d2, d3 in self.merge_triples:
testf = lambda: distribution.merge(d2, d3)
expect(testf).to(raise_error(ValueError))