Trait rstats::Medianf64

pub trait Medianf64 {
    // Required methods
    fn median(self) -> Result<f64, MedError<String>>;
    fn zeromedian(self) -> Result<Vec<f64, Global>, MedError<String>>;
    fn mediancorr(self, v: &[f64]) -> Result<f64, MedError<String>>;
    fn mad(self, med: f64) -> Result<f64, MedError<String>>;
    fn medstats(self) -> Result<MStats, MedError<String>>;
}

Fast 1D f64 medians and associated information and tasks

Required Methods

fn median(self) -> Result<f64, MedError<String>>

Finds the median, fast.

fn zeromedian(self) -> Result<Vec<f64, Global>, MedError<String>>

Zero median data produced by finding and subtracting the median.

fn mediancorr(self, v: &[f64]) -> Result<f64, MedError<String>>

Median correlation = cosine of an angle between two zero median vecs

fn mad(self, med: f64) -> Result<f64, MedError<String>>

Median of absolute differences (MAD).

fn medstats(self) -> Result<MStats, MedError<String>>

Median and MAD.

Implementations on Foreign Types

impl Medianf64 for &[f64]

fn median(self) -> Result<f64, MedError<String>>

Returns single f64 number even for even medians. Non destructive.

fn zeromedian(self) -> Result<Vec<f64, Global>, MedError<String>>

Zero median data produced by subtracting the median. Analogous to zero mean data when subtracting the mean.

fn mediancorr(self, v: &[f64]) -> Result<f64, MedError<String>>

We define median based correlation as cosine of an angle between two zero median vectors (analogously to Pearson’s zero mean vectors)

Example

use medians::Medianf64;
let v1 = vec![1_f64,2.,3.,4.,5.,6.,7.,8.,9.,10.,11.,12.,13.,14.];
let v2 = vec![14_f64,1.,13.,2.,12.,3.,11.,4.,10.,5.,9.,6.,8.,7.];
assert_eq!(v1.mediancorr(&v2).unwrap(),-0.1076923076923077);

fn mad(self, med: f64) -> Result<f64, MedError<String>>

Data dispersion estimator MAD (Median of Absolute Differences). MAD is more stable than standard deviation and more general than quartiles. When argument med is the median, it is the most stable measure of data dispersion.

fn medstats(self) -> Result<MStats, MedError<String>>

Centre and dispersion defined by median

Implementors