class Google::Apis::ServicecontrolV1::Distribution

Distribution represents a frequency distribution of double-valued sample points. It contains the size of the population of sample points plus additional optional information: - the arithmetic mean of the samples - the minimum and maximum of the samples - the sum-squared-deviation of the samples, used to compute variance - a histogram of the values of the sample points

Attributes

bucket_counts[RW]

The number of samples in each histogram bucket. `bucket_counts` are optional. If present, they must sum to the `count` value. The buckets are defined below in `bucket_option`. There are N buckets. `bucket_counts` is the number of samples in the underflow bucket. `bucket_counts` to `bucket_counts` are the numbers of samples in each of the finite buckets. And `bucket_counts is the number of samples in the overflow bucket. See the comments of ` bucket_option` below for more details. Any suffix of trailing zeros may be omitted. Corresponds to the JSON property `bucketCounts` @return [Array<Fixnum>]

count[RW]

The total number of samples in the distribution. Must be >= 0. Corresponds to the JSON property `count` @return [Fixnum]

exemplars[RW]

Example points. Must be in increasing order of `value` field. Corresponds to the JSON property `exemplars` @return [Array<Google::Apis::ServicecontrolV1::Exemplar>]

explicit_buckets[RW]

Describing buckets with arbitrary user-provided width. Corresponds to the JSON property `explicitBuckets` @return [Google::Apis::ServicecontrolV1::ExplicitBuckets]

exponential_buckets[RW]

Describing buckets with exponentially growing width. Corresponds to the JSON property `exponentialBuckets` @return [Google::Apis::ServicecontrolV1::ExponentialBuckets]

linear_buckets[RW]

Describing buckets with constant width. Corresponds to the JSON property `linearBuckets` @return [Google::Apis::ServicecontrolV1::LinearBuckets]

maximum[RW]

The maximum of the population of values. Ignored if `count` is zero. Corresponds to the JSON property `maximum` @return [Float]

mean[RW]

The arithmetic mean of the samples in the distribution. If `count` is zero then this field must be zero. Corresponds to the JSON property `mean` @return [Float]

minimum[RW]

The minimum of the population of values. Ignored if `count` is zero. Corresponds to the JSON property `minimum` @return [Float]

sum_of_squared_deviation[RW]

The sum of squared deviations from the mean: Sum((x_i - mean)^2) where each x_i is a sample values. If `count` is zero then this field must be zero, otherwise validation of the request fails. Corresponds to the JSON property `sumOfSquaredDeviation` @return [Float]

Public Class Methods

new(**args) click to toggle source
# File lib/google/apis/servicecontrol_v1/classes.rb, line 759
def initialize(**args)
   update!(**args)
end

Public Instance Methods

update!(**args) click to toggle source

Update properties of this object

# File lib/google/apis/servicecontrol_v1/classes.rb, line 764
def update!(**args)
  @bucket_counts = args[:bucket_counts] if args.key?(:bucket_counts)
  @count = args[:count] if args.key?(:count)
  @exemplars = args[:exemplars] if args.key?(:exemplars)
  @explicit_buckets = args[:explicit_buckets] if args.key?(:explicit_buckets)
  @exponential_buckets = args[:exponential_buckets] if args.key?(:exponential_buckets)
  @linear_buckets = args[:linear_buckets] if args.key?(:linear_buckets)
  @maximum = args[:maximum] if args.key?(:maximum)
  @mean = args[:mean] if args.key?(:mean)
  @minimum = args[:minimum] if args.key?(:minimum)
  @sum_of_squared_deviation = args[:sum_of_squared_deviation] if args.key?(:sum_of_squared_deviation)
end