type Aggregation interface {
	// contains filtered or unexported methods
}

type DataPoint[N int64 | float64] struct {
	// Attributes is the set of key value pairs that uniquely identify the
	// timeseries.
	Attributes attribute.Set
	// StartTime is when the timeseries was started. (optional)
	StartTime time.Time `json:",omitempty"`
	// Time is the time when the timeseries was recorded. (optional)
	Time time.Time `json:",omitempty"`
	// Value is the value of this data point.
	Value N

	// Exemplars is the sampled Exemplars collected during the timeseries.
	Exemplars []Exemplar[N] `json:",omitempty"`
}

type Exemplar[N int64 | float64] struct {
	// FilteredAttributes are the attributes recorded with the measurement but
	// filtered out of the timeseries' aggregated data.
	FilteredAttributes []attribute.KeyValue
	// Time is the time when the measurement was recorded.
	Time time.Time
	// Value is the measured value.
	Value N
	// SpanID is the ID of the span that was active during the measurement. If
	// no span was active or the span was not sampled this will be empty.
	SpanID []byte `json:",omitempty"`
	// TraceID is the ID of the trace the active span belonged to during the
	// measurement. If no span was active or the span was not sampled this will
	// be empty.
	TraceID []byte `json:",omitempty"`
}

type ExponentialBucket struct {
	// Offset is the bucket index of the first entry in the Counts slice.
	Offset int32
	// Counts is an slice where Counts[i] carries the count of the bucket at
	// index (Offset+i). Counts[i] is the count of values greater than
	// base^(Offset+i) and less than or equal to base^(Offset+i+1).
	Counts []uint64
}

type ExponentialHistogram[N int64 | float64] struct {
	// DataPoints are the individual aggregated measurements with unique
	// attributes.
	DataPoints []ExponentialHistogramDataPoint[N]
	// Temporality describes if the aggregation is reported as the change from the
	// last report time, or the cumulative changes since a fixed start time.
	Temporality Temporality
}

type ExponentialHistogramDataPoint[N int64 | float64] struct {
	// Attributes is the set of key value pairs that uniquely identify the
	// timeseries.
	Attributes attribute.Set
	// StartTime is when the timeseries was started.
	StartTime time.Time
	// Time is the time when the timeseries was recorded.
	Time time.Time

	// Count is the number of updates this histogram has been calculated with.
	Count uint64
	// Min is the minimum value recorded. (optional)
	Min Extrema[N]
	// Max is the maximum value recorded. (optional)
	Max Extrema[N]
	// Sum is the sum of the values recorded.
	Sum N

	// Scale describes the resolution of the histogram. Boundaries are
	// located at powers of the base, where:
	//
	//   base = 2 ^ (2 ^ -Scale)
	Scale int32
	// ZeroCount is the number of values whose absolute value
	// is less than or equal to [ZeroThreshold].
	// When ZeroThreshold is 0, this is the number of values that
	// cannot be expressed using the standard exponential formula
	// as well as values that have been rounded to zero.
	// ZeroCount represents the special zero count bucket.
	ZeroCount uint64

	// PositiveBucket is range of positive value bucket counts.
	PositiveBucket ExponentialBucket
	// NegativeBucket is range of negative value bucket counts.
	NegativeBucket ExponentialBucket

	// ZeroThreshold is the width of the zero region. Where the zero region is
	// defined as the closed interval [-ZeroThreshold, ZeroThreshold].
	ZeroThreshold float64

	// Exemplars is the sampled Exemplars collected during the timeseries.
	Exemplars []Exemplar[N] `json:",omitempty"`
}

type Extrema[N int64 | float64] struct {
	// contains filtered or unexported fields
}

type Gauge[N int64 | float64] struct {
	// DataPoints are the individual aggregated measurements with unique
	// Attributes.
	DataPoints []DataPoint[N]
}

type Histogram[N int64 | float64] struct {
	// DataPoints are the individual aggregated measurements with unique
	// Attributes.
	DataPoints []HistogramDataPoint[N]
	// Temporality describes if the aggregation is reported as the change from the
	// last report time, or the cumulative changes since a fixed start time.
	Temporality Temporality
}

type HistogramDataPoint[N int64 | float64] struct {
	// Attributes is the set of key value pairs that uniquely identify the
	// timeseries.
	Attributes attribute.Set
	// StartTime is when the timeseries was started.
	StartTime time.Time
	// Time is the time when the timeseries was recorded.
	Time time.Time

	// Count is the number of updates this histogram has been calculated with.
	Count uint64
	// Bounds are the upper bounds of the buckets of the histogram. Because the
	// last boundary is +infinity this one is implied.
	Bounds []float64
	// BucketCounts is the count of each of the buckets.
	BucketCounts []uint64

	// Min is the minimum value recorded. (optional)
	Min Extrema[N]
	// Max is the maximum value recorded. (optional)
	Max Extrema[N]
	// Sum is the sum of the values recorded.
	Sum N

	// Exemplars is the sampled Exemplars collected during the timeseries.
	Exemplars []Exemplar[N] `json:",omitempty"`
}

type Metrics struct {
	// Name is the name of the Instrument that created this data.
	Name string
	// Description is the description of the Instrument, which can be used in documentation.
	Description string
	// Unit is the unit in which the Instrument reports.
	Unit string
	// Data is the aggregated data from an Instrument.
	Data Aggregation
}

type QuantileValue struct {
	// Quantile is the quantile of this value.
	//
	// Must be in the interval [0.0, 1.0].
	Quantile float64

	// Value is the value at the given quantile of a summary.
	//
	// Quantile values must NOT be negative.
	Value float64
}

type ResourceMetrics struct {
	// Resource represents the entity that collected the metrics.
	Resource *resource.Resource
	// ScopeMetrics are the collection of metrics with unique Scopes.
	ScopeMetrics []ScopeMetrics
}

type ScopeMetrics struct {
	// Scope is the Scope that the Meter was created with.
	Scope instrumentation.Scope
	// Metrics are a list of aggregations created by the Meter.
	Metrics []Metrics
}

type Sum[N int64 | float64] struct {
	// DataPoints are the individual aggregated measurements with unique
	// Attributes.
	DataPoints []DataPoint[N]
	// Temporality describes if the aggregation is reported as the change from the
	// last report time, or the cumulative changes since a fixed start time.
	Temporality Temporality
	// IsMonotonic represents if this aggregation only increases or decreases.
	IsMonotonic bool
}

type Summary struct {
	// DataPoints are the individual aggregated measurements with unique
	// attributes.
	DataPoints []SummaryDataPoint
}

type SummaryDataPoint struct {
	// Attributes is the set of key value pairs that uniquely identify the
	// timeseries.
	Attributes attribute.Set

	// StartTime is when the timeseries was started.
	StartTime time.Time
	// Time is the time when the timeseries was recorded.
	Time time.Time

	// Count is the number of updates this summary has been calculated with.
	Count uint64

	// Sum is the sum of the values recorded.
	Sum float64

	// (Optional) list of values at different quantiles of the distribution calculated
	// from the current snapshot. The quantiles must be strictly increasing.
	QuantileValues []QuantileValue
}

type Temporality uint8

const (

	// CumulativeTemporality defines a measurement interval that continues to
	// expand forward in time from a starting point. New measurements are
	// added to all previous measurements since a start time.
	CumulativeTemporality Temporality

	// DeltaTemporality defines a measurement interval that resets each cycle.
	// Measurements from one cycle are recorded independently, measurements
	// from other cycles do not affect them.
	DeltaTemporality
)