def to_point(self, timestamp):
"""Get a Point conversion of this aggregation.
This method creates a :class: `opencensus.metrics.export.point.Point`
with a :class: `opencensus.metrics.export.value.ValueDistribution`
value, and creates buckets and exemplars for that distribution from the
appropriate classes in the `metrics` package.
:type timestamp: :class: `datetime.datetime`
:param timestamp: The time to report the point as having been recorded.
:rtype: :class: `opencensus.metrics.export.point.Point`
:return: a :class: `opencensus.metrics.export.value.ValueDistribution`
-valued Point.
"""
buckets = [None] * len(self.counts_per_bucket)
for ii, count in enumerate(self.counts_per_bucket):
stat_ex = self.exemplars.get(ii, None)
if stat_ex is not None:
metric_ex = value.Exemplar(stat_ex.value, stat_ex.timestamp,
copy.copy(stat_ex.attachments))
buckets[ii] = value.Bucket(count, metric_ex)
else:
buckets[ii] = value.Bucket(count)
bucket_options = value.BucketOptions(value.Explicit(self.bounds))
return point.Point(
value.ValueDistribution(
count=self.count_data,
sum_=self.sum,
sum_of_squared_deviation=self.sum_of_sqd_deviations,
bucket_options=bucket_options,
buckets=buckets), timestamp)
def _create_distribution_value(count=1,
sum_=0,
sum_of_squared_deviation=0,
bounds=[],
buckets=[]):
return value.ValueDistribution(
count=count,
sum_=sum_,
sum_of_squared_deviation=sum_of_squared_deviation,
bucket_options=value.BucketOptions(type_=value.Explicit(
bounds=bounds)),
buckets=buckets)
def setUp(self):
self.double_value = value_module.ValueDouble(55.5)
self.long_value = value_module.ValueLong(9876543210)
self.timestamp = '2018-10-06T17:57:57.936475Z'
value_at_percentile = [summary_module.ValueAtPercentile(99.5, 10.2)]
snapshot = summary_module.Snapshot(10, 87.07, value_at_percentile)
self.summary = summary_module.Summary(10, 6.6, snapshot)
self.summary_value = value_module.ValueSummary(self.summary)
self.distribution_value = value_module.ValueDistribution(
100,
1000.0,
10.0,
value_module.BucketOptions(
value_module.Explicit(list(range(1, 10)))),
[value_module.Bucket(10, None) for ii in range(10)],
)
def test_bad_init(self):
with self.assertRaises(ValueError):
value_module.Explicit(None)
with self.assertRaises(ValueError):
value_module.Explicit([])
with self.assertRaises(ValueError):
value_module.Explicit([-1, 1, 2])
with self.assertRaises(ValueError):
value_module.Explicit([0, 1, 2])
with self.assertRaises(ValueError):
value_module.Explicit([1, 1])
with self.assertRaises(ValueError):
value_module.Explicit([2, 1])
def test_init(self):
bounds = [1, 2]
explicit = value_module.Explicit(bounds)
self.assertEqual(explicit.bounds, bounds)
value_at_percentile = [summary_module.ValueAtPercentile(99.5, 10.2)]
snapshot = summary_module.Snapshot(10, 87.07, value_at_percentile)
summary = summary_module.Summary(10, 6.6, snapshot)
summary_value = value_module.Value.summary_value(summary)
self.assertIsNotNone(summary_value)
self.assertIsInstance(summary_value, value_module.ValueSummary)
self.assertEqual(summary_value.value, summary)
VD_COUNT = 100
VD_SUM = 1000.0
VD_SUM_OF_SQUARED_DEVIATION = 10.0
BOUNDS = list(range(1, 10))
BUCKET_OPTIONS = value_module.BucketOptions(value_module.Explicit(BOUNDS))
BUCKETS = [value_module.Bucket(10, None) for ii in range(10)]
class TestValueDistribution(unittest.TestCase):
def test_init(self):
distribution = value_module.ValueDistribution(
VD_COUNT, VD_SUM, VD_SUM_OF_SQUARED_DEVIATION, BUCKET_OPTIONS,
BUCKETS)
self.assertEqual(distribution.count, VD_COUNT)
self.assertEqual(distribution.sum, VD_SUM)
self.assertEqual(distribution.sum_of_squared_deviation,
VD_SUM_OF_SQUARED_DEVIATION)
self.assertEqual(distribution.bucket_options, BUCKET_OPTIONS)
self.assertEqual(distribution.bucket_options.type_.bounds, BOUNDS)
self.assertEqual(distribution.buckets, BUCKETS)