l.UpdatedAt = t // update to the latest time index

	if since >= 24 {
		l.Bins = [24]tierStats{}
		return
	}

	for lastIdx != idx {
		lastIdx = (lastIdx + 1) % 24
		l.Bins[lastIdx] = tierStats{}
	}
}

func (l *lastDayTierStats) clone() lastDayTierStats {
	clone := lastDayTierStats{
		UpdatedAt: l.UpdatedAt,
	}
	copy(clone.Bins[:], l.Bins[:])
	return clone
}

  std::pair<int32_t, int32_t> ExpandHistogramIfNeeded(float lower_bound,
                                                      float upper_bound);

  // 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)
  std::deque<float> hist_freq_;

  // Width of bin
  float bin_width_;

  // The first bin's left value. [left, right)

        def lib = new LibraryIdentifier("project", "lib")
        def bins = Stub(DomainObjectSet)

        when:
        def bins1 = locator.getBinaries(lib)
        def bins2 = locator.getBinaries(lib)

        then:
        bins1.is(bins)
        bins2.is(bins)

        and:
        1 * target.getBinaries(lib) >> bins
        0 * target._
    }

    def "caches null result"() {

	// map header, size 2
	// write "Bins"
	err = en.Append(0x82, 0xa4, 0x42, 0x69, 0x6e, 0x73)
	if err != nil {
		return
	}
	err = en.WriteArrayHeader(uint32(24))
	if err != nil {
		err = msgp.WrapError(err, "Bins")
		return
	}
	for za0001 := range z.Bins {
		err = z.Bins[za0001].EncodeMsg(en)
		if err != nil {
			err = msgp.WrapError(err, "Bins", za0001)
			return
		}
	}

  // Calculate the bin width with the actual num bins.
  float raw_bin_width = 256.0 / actual_num_bins;
  EXPECT_FLOAT_EQ(bin_width, raw_bin_width);
}

TEST(CalibrationParametersTest, CalculateNumBinsDivisible) {
  int32_t num_bins = CalculateActualNumBins(
      /*min_value=*/0.0, /*max_value=*/4.0, /*bin_width=*/2.0);

  // Expect 2 bins: [0, 2), [2, 4].
  EXPECT_EQ(num_bins, 2);
}

    // 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)
    repeated float hist_freq = 3;
  }

  MinMaxStatistics min_max_statistics = 1;
  AverageMinMaxStatistics average_min_max_statistics = 2;

namespace stablehlo::quantization {

// Calculates the bin width from the range and expected number of bins. The
// bin width is formalized to the form of 2^n. As a consequence, the actual
// number of bins might be smaller than the given `num_bins`.
inline float CalculateBinWidth(const float min_value, const float max_value,
                               const int32_t num_bins) {

set -o pipefail

KUBE_ROOT=$(dirname "${BASH_SOURCE[0]}")/..
source "${KUBE_ROOT}/hack/lib/init.sh"

kube::golang::setup_env
kube::util::ensure-temp-dir

BINS=(
	./cmd/gendocs
	./cmd/genkubedocs
	./cmd/genman
	./cmd/genyaml
)
GOPROXY=off go install "${BINS[@]}"

# Run all doc generators.
# $1 is the directory to put those generated documents
generate_docs() {
  local dest="$1"

    self._hist_freq = np.array(hist_stats.hist_freq)
    self._num_bins = len(self._hist_freq)
    self._num_bits = 8
    # i-th bin has a range [bins[i], bins[i + 1]).
    # bins[i] = lower_bound + i * bin_width
    # bins[i + 1] = lower_bound + (i + 1) * bin_width
    # So hist_mids[i] = (lower_bound + bin_width / 2) + bin_width * i
    first_mid = self._lower_bound + self._bin_width / 2

    // The unique id of this `CustomAggregator` op.
    StrAttr:$id,
    // The integer value of the enforcing `CalibrationMethod`.
    I32Attr:$calibration_method,
    // The number of histogram bins.
    I32Attr:$num_bins,
    // Min percentile to be included in the selected range, only used in the
    // `HISTOGRAM_PERCENTILE` method.
    F32Attr:$min_percentile,