service/vendor/github.com/montanaflynn/stats/data.go

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2023-12-21 22:17:40 +08:00
package stats
// Float64Data is a named type for []float64 with helper methods
type Float64Data []float64
// Get item in slice
func (f Float64Data) Get(i int) float64 { return f[i] }
// Len returns length of slice
func (f Float64Data) Len() int { return len(f) }
// Less returns if one number is less than another
func (f Float64Data) Less(i, j int) bool { return f[i] < f[j] }
// Swap switches out two numbers in slice
func (f Float64Data) Swap(i, j int) { f[i], f[j] = f[j], f[i] }
// Min returns the minimum number in the data
func (f Float64Data) Min() (float64, error) { return Min(f) }
// Max returns the maximum number in the data
func (f Float64Data) Max() (float64, error) { return Max(f) }
// Sum returns the total of all the numbers in the data
func (f Float64Data) Sum() (float64, error) { return Sum(f) }
// Mean returns the mean of the data
func (f Float64Data) Mean() (float64, error) { return Mean(f) }
// Median returns the median of the data
func (f Float64Data) Median() (float64, error) { return Median(f) }
// Mode returns the mode of the data
func (f Float64Data) Mode() ([]float64, error) { return Mode(f) }
// GeometricMean returns the median of the data
func (f Float64Data) GeometricMean() (float64, error) { return GeometricMean(f) }
// HarmonicMean returns the mode of the data
func (f Float64Data) HarmonicMean() (float64, error) { return HarmonicMean(f) }
// MedianAbsoluteDeviation the median of the absolute deviations from the dataset median
func (f Float64Data) MedianAbsoluteDeviation() (float64, error) {
return MedianAbsoluteDeviation(f)
}
// MedianAbsoluteDeviationPopulation finds the median of the absolute deviations from the population median
func (f Float64Data) MedianAbsoluteDeviationPopulation() (float64, error) {
return MedianAbsoluteDeviationPopulation(f)
}
// StandardDeviation the amount of variation in the dataset
func (f Float64Data) StandardDeviation() (float64, error) {
return StandardDeviation(f)
}
// StandardDeviationPopulation finds the amount of variation from the population
func (f Float64Data) StandardDeviationPopulation() (float64, error) {
return StandardDeviationPopulation(f)
}
// StandardDeviationSample finds the amount of variation from a sample
func (f Float64Data) StandardDeviationSample() (float64, error) {
return StandardDeviationSample(f)
}
// QuartileOutliers finds the mild and extreme outliers
func (f Float64Data) QuartileOutliers() (Outliers, error) {
return QuartileOutliers(f)
}
// Percentile finds the relative standing in a slice of floats
func (f Float64Data) Percentile(p float64) (float64, error) {
return Percentile(f, p)
}
// PercentileNearestRank finds the relative standing using the Nearest Rank method
func (f Float64Data) PercentileNearestRank(p float64) (float64, error) {
return PercentileNearestRank(f, p)
}
// Correlation describes the degree of relationship between two sets of data
func (f Float64Data) Correlation(d Float64Data) (float64, error) {
return Correlation(f, d)
}
// Pearson calculates the Pearson product-moment correlation coefficient between two variables.
func (f Float64Data) Pearson(d Float64Data) (float64, error) {
return Pearson(f, d)
}
// Quartile returns the three quartile points from a slice of data
func (f Float64Data) Quartile(d Float64Data) (Quartiles, error) {
return Quartile(d)
}
// InterQuartileRange finds the range between Q1 and Q3
func (f Float64Data) InterQuartileRange() (float64, error) {
return InterQuartileRange(f)
}
// Midhinge finds the average of the first and third quartiles
func (f Float64Data) Midhinge(d Float64Data) (float64, error) {
return Midhinge(d)
}
// Trimean finds the average of the median and the midhinge
func (f Float64Data) Trimean(d Float64Data) (float64, error) {
return Trimean(d)
}
// Sample returns sample from input with replacement or without
func (f Float64Data) Sample(n int, r bool) ([]float64, error) {
return Sample(f, n, r)
}
// Variance the amount of variation in the dataset
func (f Float64Data) Variance() (float64, error) {
return Variance(f)
}
// PopulationVariance finds the amount of variance within a population
func (f Float64Data) PopulationVariance() (float64, error) {
return PopulationVariance(f)
}
// SampleVariance finds the amount of variance within a sample
func (f Float64Data) SampleVariance() (float64, error) {
return SampleVariance(f)
}
// Covariance is a measure of how much two sets of data change
func (f Float64Data) Covariance(d Float64Data) (float64, error) {
return Covariance(f, d)
}
// CovariancePopulation computes covariance for entire population between two variables.
func (f Float64Data) CovariancePopulation(d Float64Data) (float64, error) {
return CovariancePopulation(f, d)
}