forked from golang/hotime
141 lines
4.6 KiB
Go
141 lines
4.6 KiB
Go
package stats
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// Float64Data is a named type for []float64 with helper methods
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type Float64Data []float64
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// Get item in slice
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func (f Float64Data) Get(i int) float64 { return f[i] }
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// Len returns length of slice
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func (f Float64Data) Len() int { return len(f) }
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// Less returns if one number is less than another
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func (f Float64Data) Less(i, j int) bool { return f[i] < f[j] }
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// Swap switches out two numbers in slice
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func (f Float64Data) Swap(i, j int) { f[i], f[j] = f[j], f[i] }
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// Min returns the minimum number in the data
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func (f Float64Data) Min() (float64, error) { return Min(f) }
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// Max returns the maximum number in the data
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func (f Float64Data) Max() (float64, error) { return Max(f) }
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// Sum returns the total of all the numbers in the data
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func (f Float64Data) Sum() (float64, error) { return Sum(f) }
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// Mean returns the mean of the data
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func (f Float64Data) Mean() (float64, error) { return Mean(f) }
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// Median returns the median of the data
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func (f Float64Data) Median() (float64, error) { return Median(f) }
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// Mode returns the mode of the data
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func (f Float64Data) Mode() ([]float64, error) { return Mode(f) }
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// GeometricMean returns the median of the data
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func (f Float64Data) GeometricMean() (float64, error) { return GeometricMean(f) }
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// HarmonicMean returns the mode of the data
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func (f Float64Data) HarmonicMean() (float64, error) { return HarmonicMean(f) }
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// MedianAbsoluteDeviation the median of the absolute deviations from the dataset median
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func (f Float64Data) MedianAbsoluteDeviation() (float64, error) {
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return MedianAbsoluteDeviation(f)
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}
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// MedianAbsoluteDeviationPopulation finds the median of the absolute deviations from the population median
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func (f Float64Data) MedianAbsoluteDeviationPopulation() (float64, error) {
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return MedianAbsoluteDeviationPopulation(f)
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}
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// StandardDeviation the amount of variation in the dataset
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func (f Float64Data) StandardDeviation() (float64, error) {
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return StandardDeviation(f)
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}
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// StandardDeviationPopulation finds the amount of variation from the population
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func (f Float64Data) StandardDeviationPopulation() (float64, error) {
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return StandardDeviationPopulation(f)
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}
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// StandardDeviationSample finds the amount of variation from a sample
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func (f Float64Data) StandardDeviationSample() (float64, error) {
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return StandardDeviationSample(f)
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}
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// QuartileOutliers finds the mild and extreme outliers
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func (f Float64Data) QuartileOutliers() (Outliers, error) {
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return QuartileOutliers(f)
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}
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// Percentile finds the relative standing in a slice of floats
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func (f Float64Data) Percentile(p float64) (float64, error) {
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return Percentile(f, p)
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}
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// PercentileNearestRank finds the relative standing using the Nearest Rank method
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func (f Float64Data) PercentileNearestRank(p float64) (float64, error) {
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return PercentileNearestRank(f, p)
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}
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// Correlation describes the degree of relationship between two sets of data
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func (f Float64Data) Correlation(d Float64Data) (float64, error) {
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return Correlation(f, d)
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}
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// Pearson calculates the Pearson product-moment correlation coefficient between two variables.
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func (f Float64Data) Pearson(d Float64Data) (float64, error) {
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return Pearson(f, d)
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}
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// Quartile returns the three quartile points from a slice of data
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func (f Float64Data) Quartile(d Float64Data) (Quartiles, error) {
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return Quartile(d)
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}
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// InterQuartileRange finds the range between Q1 and Q3
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func (f Float64Data) InterQuartileRange() (float64, error) {
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return InterQuartileRange(f)
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}
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// Midhinge finds the average of the first and third quartiles
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func (f Float64Data) Midhinge(d Float64Data) (float64, error) {
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return Midhinge(d)
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}
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// Trimean finds the average of the median and the midhinge
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func (f Float64Data) Trimean(d Float64Data) (float64, error) {
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return Trimean(d)
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}
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// Sample returns sample from input with replacement or without
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func (f Float64Data) Sample(n int, r bool) ([]float64, error) {
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return Sample(f, n, r)
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}
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// Variance the amount of variation in the dataset
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func (f Float64Data) Variance() (float64, error) {
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return Variance(f)
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}
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// PopulationVariance finds the amount of variance within a population
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func (f Float64Data) PopulationVariance() (float64, error) {
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return PopulationVariance(f)
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}
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// SampleVariance finds the amount of variance within a sample
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func (f Float64Data) SampleVariance() (float64, error) {
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return SampleVariance(f)
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}
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// Covariance is a measure of how much two sets of data change
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func (f Float64Data) Covariance(d Float64Data) (float64, error) {
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return Covariance(f, d)
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}
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// CovariancePopulation computes covariance for entire population between two variables.
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func (f Float64Data) CovariancePopulation(d Float64Data) (float64, error) {
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return CovariancePopulation(f, d)
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}
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