Fix and simplify Pearson coefficient

src/covariance.rs

@@ -54,13 +54,14 @@ impl Covariance {
  let n = self.n.to_f64().unwrap();
 
  let delta_x = x - self.avg_x;
- let delta_y = y - self.avg_y;
+ let delta_x_n = delta_x / n;
+ let delta_y_n = (y - self.avg_y) / n;
 
- self.avg_x += delta_x / n;
- self.sum_x_2 += delta_x * delta_x * n * (n - 1.);
+ self.avg_x += delta_x_n;
+ self.sum_x_2 += delta_x_n * delta_x_n * n * (n - 1.);
 
- self.avg_y += delta_y / n;
- self.sum_y_2 += delta_y * delta_y * n * (n - 1.);
+ self.avg_y += delta_y_n;
+ self.sum_y_2 += delta_y_n * delta_y_n * n * (n - 1.);
 
  self.sum_prod += delta_x * (y - self.avg_y);
  }
@@ -91,30 +92,17 @@ impl Covariance {
  self.sum_prod / (self.n - 1).to_f64().unwrap()
  }
 
- /// Calculate the population Pearson correlation coefficient of the sample.
+ /// Calculate the population Pearson correlation coefficient.
  ///
  /// Returns NaN for an empty sample.
  #[cfg(any(feature = "std", feature = "libm"))]
  #[cfg_attr(doc_cfg, doc(cfg(any(feature = "std", feature = "libm"))))]
  #[inline]
- pub fn population_pearson(&self) -> f64 {
- let cov = self.population_covariance();
- let var_x = self.population_variance_x();
- let var_y = self.population_variance_y();
- cov / num_traits::Float::sqrt(var_x * var_y)
- }
-
- /// Calculate the sample Pearson correlation coefficient.
- ///
- /// Returns NaN for an empty sample.
- #[cfg(any(feature = "std", feature = "libm"))]
- #[cfg_attr(doc_cfg, doc(cfg(any(feature = "std", feature = "libm"))))]
- #[inline]
- pub fn sample_pearson(&self) -> f64 {
- let cov = self.sample_covariance();
- let var_x = self.sample_variance_x();
- let var_y = self.sample_variance_y();
- cov / num_traits::Float::sqrt(var_x * var_y)
+ pub fn pearson(&self) -> f64 {
+ if self.n < 2 {
+ return f64::NAN;
+ }
+ self.sum_prod / num_traits::Float::sqrt(self.sum_x_2 * self.sum_y_2)
  }
 
  /// Return the sample size.

tests/integration/covariance.rs

@@ -5,39 +5,66 @@ fn simple() {
  let mut cov = Covariance::new();
  assert!(cov.mean_x().is_nan());
  assert!(cov.mean_y().is_nan());
+ assert!(cov.population_variance_x().is_nan());
+ assert!(cov.population_variance_y().is_nan());
+ assert!(cov.sample_variance_x().is_nan());
+ assert!(cov.sample_variance_y().is_nan());
  assert!(cov.population_covariance().is_nan());
  assert!(cov.sample_covariance().is_nan());
- assert!(cov.population_pearson().is_nan());
- assert!(cov.sample_pearson().is_nan());
+ assert!(cov.pearson().is_nan());
 
  cov.add(1., 5.);
  assert_eq!(cov.mean_x(), 1.);
  assert_eq!(cov.mean_y(), 5.);
+ assert_eq!(cov.population_variance_x(), 0.);
+ assert_eq!(cov.population_variance_y(), 0.);
+ assert!(cov.sample_variance_x().is_nan());
+ assert!(cov.sample_variance_y().is_nan());
  assert_eq!(cov.population_covariance(), 0.);
  assert!(cov.sample_covariance().is_nan());
- // TODO: pearson
+ assert!(cov.pearson().is_nan());
 
  cov.add(2., 4.);
  assert_eq!(cov.mean_x(), 1.5);
  assert_eq!(cov.mean_y(), 4.5);
+ assert_eq!(cov.population_variance_x(), 0.25);
+ assert_eq!(cov.population_variance_y(), 0.25);
+ assert_eq!(cov.sample_variance_x(), 0.5);
+ assert_eq!(cov.sample_variance_y(), 0.5);
  assert_eq!(cov.population_covariance(), -0.25);
  assert_eq!(cov.sample_covariance(), -0.5);
+ assert_eq!(cov.pearson(), -1.);
 
  cov.add(3., 3.);
  assert_eq!(cov.mean_x(), 2.);
  assert_eq!(cov.mean_y(), 4.);
+ assert_eq!(cov.population_variance_x(), 2./3.);
+ assert_eq!(cov.population_variance_y(), 2./3.);
+ assert_eq!(cov.sample_variance_x(), 1.);
+ assert_eq!(cov.sample_variance_y(), 1.);
  assert_eq!(cov.population_covariance(), -2./3.);
  assert_eq!(cov.sample_covariance(), -1.);
+ assert_eq!(cov.pearson(), -1.);
 
  cov.add(4., 2.);
  assert_eq!(cov.mean_x(), 2.5);
  assert_eq!(cov.mean_y(), 3.5);
+ assert_eq!(cov.population_variance_x(), 1.25);
+ assert_eq!(cov.population_variance_y(), 1.25);
+ assert_eq!(cov.sample_variance_x(), 5./3.);
+ assert_eq!(cov.sample_variance_y(), 5./3.);
  assert_eq!(cov.population_covariance(), -1.25);
  assert_eq!(cov.sample_covariance(), -5./3.);
+ assert_eq!(cov.pearson(), -1.);
 
  cov.add(5., 1.);
  assert_eq!(cov.mean_x(), 3.);
  assert_eq!(cov.mean_y(), 3.);
+ assert_eq!(cov.population_variance_x(), 2.);
+ assert_eq!(cov.population_variance_y(), 2.);
+ assert_eq!(cov.sample_variance_x(), 2.5);
+ assert_eq!(cov.sample_variance_y(), 2.5);
  assert_eq!(cov.population_covariance(), -2.0);
  assert_eq!(cov.sample_covariance(), -2.5);
+ assert_eq!(cov.pearson(), -1.);
 }