def test_populate_buckets_underflow(self):
pb = metrics_pb2.MetricsData()
m = metrics.DistributionMetric('test')
d = distribution.Distribution(
distribution.FixedWidthBucketer(10, num_finite_buckets=10))
d.add(-5)
d.add(-1000000)
m._populate_value(pb, d, 1234)
self.assertEquals([], pb.distribution.bucket)
self.assertEquals(2, pb.distribution.underflow)
self.assertEquals(0, pb.distribution.overflow)
self.assertEquals(-500002.5, pb.distribution.mean)
def test_populate_custom(self):
pb = metrics_pb2.MetricsData()
m = metrics.DistributionMetric('test')
m._populate_value(
pb, distribution.Distribution(distribution.GeometricBucketer(4)),
1234)
self.assertEquals(
pb.distribution.spec_type,
metrics_pb2.PrecomputedDistribution.CUSTOM_PARAMETERIZED)
self.assertEquals(0, pb.distribution.width)
self.assertEquals(4, pb.distribution.growth_factor)
self.assertEquals(100, pb.distribution.num_buckets)
m._populate_value(
pb, distribution.Distribution(distribution.FixedWidthBucketer(10)),
1234)
self.assertEquals(
pb.distribution.spec_type,
metrics_pb2.PrecomputedDistribution.CUSTOM_PARAMETERIZED)
self.assertEquals(10, pb.distribution.width)
self.assertEquals(0, pb.distribution.growth_factor)
self.assertEquals(100, pb.distribution.num_buckets)
def test_populate_canonical(self):
pb = metrics_pb2.MetricsData()
m = metrics.DistributionMetric('test')
m._populate_value(
pb, distribution.Distribution(distribution.GeometricBucketer()),
1234)
self.assertEquals(
pb.distribution.spec_type,
metrics_pb2.PrecomputedDistribution.CANONICAL_POWERS_OF_10_P_0_2)
m._populate_value(
pb, distribution.Distribution(distribution.GeometricBucketer(2)),
1234)
self.assertEquals(
pb.distribution.spec_type,
metrics_pb2.PrecomputedDistribution.CANONICAL_POWERS_OF_2)
m._populate_value(
pb, distribution.Distribution(distribution.GeometricBucketer(10)),
1234)
self.assertEquals(
pb.distribution.spec_type,
metrics_pb2.PrecomputedDistribution.CANONICAL_POWERS_OF_10)