cker-second").val(c),this.showMeridian&&this.$widget.find("input.bootstrap-timepicker-meridian").val(this.meridian)):(this.$widget.find("span.bootstrap-timepicker-hour").text(a),this.$widget.find("span.bootstrap-timepicker-minute").text(b),this.showSeconds&&this.$widget.find("span.bootstrap-timepicker-second").text(c),this.showMeridian&&this.$widget.find("span.bootstrap-timepicker-meridian").text(this.meridian))}},updateFromWidgetInputs:function(){if(this.$widget!==!1){var a=this.$widget.find("i...

				"application/vnd.marlin.drm.license+xml",
				"application/vnd.marlin.drm.mdcf",
				"application/vnd.mcd",
				"application/vnd.medcalcdata",
				"application/vnd.mediastation.cdkey",
				"application/vnd.meridian-slingshot",
				"application/vnd.mfer",
				"application/vnd.mfmp",
				"application/vnd.micrografx.flo",
				"application/vnd.micrografx.igx",
				"application/vnd.mif",
				"application/vnd.mindjet.mindmanager",

        return myTime && myTime.median < otherTime.median && differenceSignificantCheck.test(myTime, otherTime)
    }

    boolean significantlySlowerThan(MeasuredOperationList other, double minConfidence = MINIMUM_CONFIDENCE) {
        def myTime = results.totalTime
        def otherTime = other.totalTime
        myTime && myTime.median > otherTime.median && differenceIsSignificant(myTime, otherTime, minConfidence)
    }

    }

    String getSpeedStats() {
        format(totalTime)
    }

    private String format(DataSeries<?> measurement) {
        """  ${name} median: ${measurement.median.format()} min: ${measurement.min.format()}, max: ${measurement.max.format()}, se: ${measurement.standardError.format()}}
  > ${measurement.collect { it.format() }}
"""

    }

		*swaps++
		return b, a
	}
	return a, b
}

// median returns x where data[x] is the median of data[a],data[b],data[c], where x is a, b, or c.
func median(data Interface, a, b, c int, swaps *int) int {
	a, b = order2(data, a, b, swaps)
	b, c = order2(data, b, c, swaps)
	a, b = order2(data, a, b, swaps)
	return b
}

// medianAdjacent finds the median of data[a - 1], data[a], data[a + 1] and stores the index into a.

import java.util.stream.Collectors;

/**
 * A collection of measurements of some given units.
 */
public class DataSeries<Q> extends ArrayList<Amount<Q>> {
    private final Amount<Q> average;
    private final Amount<Q> median;
    private final Amount<Q> max;
    private final Amount<Q> min;
    // https://en.wikipedia.org/wiki/Standard_error
    private final Amount<Q> standardError;

        def v2 = DataAmount.kbytes(20)
        def v3 = DataAmount.kbytes(30)
        def series = new DataSeries([v1, v2, v3])

        expect:
        series.average == v2
        series.median == v2
        series.min == v1
        series.max == v3
        series.standardError == DataAmount.bytes(8360.92)
    }

    def "ignores null values"() {
        def v1 = DataAmount.kbytes(10)

	if {{Less "data" "b" "a"}} {
		*swaps++
		return b, a
	}
	return a, b
}

// median{{.FuncSuffix}} returns x where data[x] is the median of data[a],data[b],data[c], where x is a, b, or c.
func median{{.FuncSuffix}}{{.TypeParam}}(data {{.DataType}}, a, b, c int, swaps *int {{.ExtraParam}}) int {
	a, b = order2{{.FuncSuffix}}(data, a, b, swaps {{.ExtraArg}})

/**
 * Provides a fluent API for calculating <a
 * href="http://en.wikipedia.org/wiki/Quantile">quantiles</a>.
 *
 * <h3>Examples</h3>
 *
 * <p>To compute the median:
 *
 * <pre>{@code
 * double myMedian = median().compute(myDataset);
 * }</pre>
 *
 * where {@link #median()} has been statically imported.
 *
 * <p>To compute the 99th percentile:
 *
 * <pre>{@code

/**
 * Provides a fluent API for calculating <a
 * href="http://en.wikipedia.org/wiki/Quantile">quantiles</a>.
 *
 * <h3>Examples</h3>
 *
 * <p>To compute the median:
 *
 * <pre>{@code
 * double myMedian = median().compute(myDataset);
 * }</pre>
 *
 * where {@link #median()} has been statically imported.
 *
 * <p>To compute the 99th percentile:
 *
 * <pre>{@code