1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117

// pub mod tests;
pub mod i64impls;
pub mod f64impls;
pub mod vimpls;

use std::cmp::Ordering::Equal;
use anyhow::Result;

/// Median and quartiles
#[derive(Default)]
pub struct Med {
    pub lquartile: f64,
    pub median: f64,
    pub uquartile: f64
}
impl std::fmt::Display for Med {
    fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
        write!(f, "(LQ: {}, M: {}, UQ: {})", self.lquartile, self.median, self.uquartile)
    }
}

/// Mean and standard deviation (or std ratio for geometric mean).
#[derive(Default)]
pub struct MStats {
    pub mean: f64,
    pub std: f64
}
impl std::fmt::Display for MStats {
   fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
      write!(f, "Mean:\t{}\nStd:\t{}", self.mean, self.std)
   }
}
/// Implementing basic statistical measures.
pub trait RStats { 

   fn amean(&self) -> Result<f64>;
   fn ameanstd(&self) -> Result<MStats>;
   fn awmean(&self) -> Result<f64>;
   fn awmeanstd(&self) -> Result<MStats>;
   fn hmean(&self) -> Result<f64>;
   fn hwmean(&self) -> Result<f64>;
   fn gmean(&self) -> Result<f64>;
   fn gwmean(&self) -> Result<f64>;
   fn gmeanstd(&self) -> Result<MStats>;
   fn gwmeanstd(&self) -> Result<MStats>;
   fn median(&self) -> Result<Med>;
   fn icorrelation(&self, v:&[i64]) -> Result<f64>;
   fn correlation(&self, v:&[f64]) -> Result<f64>;
   fn autocorr(&self) -> Result<f64>;
  
}

/// Mutable primitive vector operations (for efficiency).
pub trait MutVectors {

   fn mutsmult(&mut self, s:f64);
   fn mutvsub(&mut self, v:&[f64]);
   fn mutvadd(&mut self, v:&[f64]);
   fn mutvunit(&mut self);
   fn mutvmag(&mut self) -> f64;

   }

/// Implementing basic vector algebra and safe geometric median.
pub trait Vectors {

   fn dotp(&self, v:&[f64]) -> f64;
   fn vsub(&self, v:&[f64]) -> Vec<f64>;
   fn vadd(&self, v:&[f64]) -> Vec<f64>;
   fn vmag(&self) -> f64;
   fn vdist(&self, v:&[f64]) -> f64;
   fn smult(&self, s:f64) -> Vec<f64>;
   fn vunit(&self) -> Vec<f64>;
   fn arcentroid(&self, d:usize) -> Vec<f64>;
   fn medoid(&self, d:usize) -> Result<(f64,usize)>;
   fn distsum(&self, d:usize, v:&[f64] ) -> f64;

   fn nextpoint(&self, d:usize, eps:f64, v:&[f64]) -> Result<(bool,Vec<f64>)>;
   fn betterpoint(&self, d:usize, eps:f64, v:&[f64] ) -> Result<(bool,Vec<f64>)>;
   fn firstpoint(&self, d:usize, indx:usize, v:&[f64]) -> Result<Vec<f64>>;
   fn gmedian(&self, d:usize, eps:f64) -> Result<(f64,Vec<f64>)>;   
   fn nmedian(&self, d:usize, eps:f64) -> Result<(f64,Vec<f64>)>;
   fn pmedian(&self, d:usize, eps:f64) -> Result<(f64,Vec<f64>)>;
   
}

/// Private helper function for formatting error messages
fn emsg(file:&'static str, line:u32, msg:&'static str)-> String {
   format!("{}:{} rstats {}",file,line,msg)
}

/// Private sum of linear weights 
fn wsum(n: usize) -> f64 { (n*(n+1)) as f64/2. }

/// Sorts a mutable `Vec<f64>` in place.  
/// It is the responsibility of the user to ensure that there are no NaNs etc.
pub fn sortf(v: &mut [f64]) { 
   v.sort_by(|a, b| a.partial_cmp(b).unwrap_or(Equal))
}

/// Generates a random f64 vector of size d x n suitable for testing. It needs two seeds.  
/// Uses local closure `rand` to generate random numbers (avoids dependencies).  
/// Random numbers are in the open interval 0..1 with uniform distribution.  
pub fn genvec(d:usize, n:usize, s1:u32, s2:u32 ) -> Vec<f64> {
   let size = d*n;
   // change the seeds as desired
   let mut m_z = s1 as u32;
   let mut m_w = s2 as u32;
   let mut rand = || {
      m_z = 36969 * (m_z & 65535) + (m_z >> 16);
      m_w = 18000 * (m_w & 65535) + (m_w >> 16);
      (((m_z << 16) & m_w) as f64 + 1.0)*2.328306435454494e-10
   };
   let mut v = Vec::with_capacity(size); 
   for _i in 0..size { v.push(rand()) }; // fills the lot with random numbers
   return v
}