// this when we create the histogram.
func (d *metrics) toHistogramViews() []metric.Option {
	d.mu.Lock()
	defer d.mu.Unlock()
	d.started = true
	opts := []metric.Option{}
	for name, def := range d.known {
		if def.Bounds == nil {
			continue
		}
		// for each histogram metric (i.e. those with bounds), set up a view explicitly defining those buckets.

			return // Return early in the event of write failures
		}
		n = 0
	}
	w.nbytes = n
	w.writeCode(encoding[endBlockMarker])
}

// histogram accumulates a histogram of b in h.
//
// len(h) must be >= 256, and h's elements must be all zeroes.
func histogram(b []byte, h []int32) {
	h = h[:256]
	for _, t := range b {
		h[t]++
	}

	// trackSum >= trackMass, trackBucket must be recomputed.
	trackSum float64

	// hist is a hierarchical histogram of distribution mass.
	hist [mudDegree]float64
}

const (
	// mudDegree is the number of buckets in the MUD summary
	// histogram.
	mudDegree = 1024
)

type edge struct {
	// At x, the function increases by y.
	x, delta float64

import org.opensearch.search.aggregations.bucket.global.GlobalAggregationBuilder;
import org.opensearch.search.aggregations.bucket.histogram.DateHistogramAggregationBuilder;
import org.opensearch.search.aggregations.bucket.histogram.HistogramAggregationBuilder;
import org.opensearch.search.aggregations.bucket.missing.MissingAggregationBuilder;

import org.opensearch.search.aggregations.bucket.global.GlobalAggregationBuilder;
import org.opensearch.search.aggregations.bucket.histogram.DateHistogramAggregationBuilder;
import org.opensearch.search.aggregations.bucket.histogram.HistogramAggregationBuilder;
import org.opensearch.search.aggregations.bucket.missing.MissingAggregationBuilder;

  min_max_statistics_.set_global_max(std::numeric_limits<float>::lowest());
}

void CalibrationStatisticsCollectorMinMax::Collect(
    const float min, const float max, absl::Span<const int64_t> histogram) {
  min_max_statistics_.set_global_min(
      std::min(min_max_statistics_.global_min(), min));
  min_max_statistics_.set_global_max(
      std::max(min_max_statistics_.global_max(), max));
}

        # TYPE apiserver_authentication_jwt_authenticator_latency_seconds histogram
        apiserver_authentication_jwt_authenticator_latency_seconds_bucket{jwt_issuer_hash="sha256:29b34beedc55b972f2428f21bc588f9d38e5e8f7a7af825486e7bb4fd9caa2ad",result="success",le="0.001"} 1

    pass


class _HistogramCalibrationAlgorithmBase(_CalibrationAlgorithmBase):
  """Base class for histogram calibrators."""

  def __init__(
      self,
      statistics: calib_stats_pb2.CalibrationStatistics,
      calib_opts: stablehlo_quant_config_pb2.CalibrationOptions,
  ):
    """Builds histogram using statistics.histogram_statistics.

    lower_bound                                    hist_mid

  }

  message HistogramStatistics {
    // width of bin
    float bin_width = 1;

    // lower_bound is the first bin's min value.
    // lower_bound and bin_width can be used to restore the histogram.
    float lower_bound = 2;

    // hist_freq[i] saves frequency of range [bins[i], bins[i + 1]).
    // bins[i]     = lower_bound + bin_width * i
    // bins[i + 1] = lower_bound + bin_width * (i + 1)

			continue
		}
		metric := mf.GetMetric()[0]
		hist := metric.GetHistogram()
		if hist == nil {
			return 0, errors.New("dto.Metric has nil Histogram")
		}
		if hist.SampleCount == nil {
			return 0, errors.New("dto.Histogram has nil SampleCount")
		}
		return int64(*hist.SampleCount), nil
	}
	return 0, errMetricNotFound
}

func BenchmarkTimingRatioHistogram(b *testing.B) {