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Refactor variance functions to distinguish between population and sample variance

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This commit is contained in:
Palash Tyagi 2025-07-15 01:00:03 +01:00
parent 64722914bd
commit 285147d52b
1 changed files with 37 additions and 16 deletions
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53
src/compute/stats/descriptive.rs
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@ -14,17 +14,29 @@ pub fn mean_horizontal(x: &Matrix<f64>) -> Matrix<f64> {
Matrix::from_vec(x.sum_horizontal(), x.rows(), 1) / n
}
pub fn variance(x: &Matrix<f64>) -> f64 {
fn population_or_sample_variance(x: &Matrix<f64>, population: bool) -> f64 {
let m = (x.rows() * x.cols()) as f64;
let mean_val = mean(x);
x.data()
.iter()
.map(|&v| (v - mean_val).powi(2))
.sum::<f64>()
/ m
/ if population { m } else { m - 1.0 }
}
fn _variance_axis(x: &Matrix<f64>, axis: Axis) -> Matrix<f64> {
pub fn population_variance(x: &Matrix<f64>) -> f64 {
population_or_sample_variance(x, true)
}
pub fn sample_variance(x: &Matrix<f64>) -> f64 {
population_or_sample_variance(x, false)
}
fn _population_or_sample_variance_axis(
x: &Matrix<f64>,
axis: Axis,
population: bool,
) -> Matrix<f64> {
match axis {
Axis::Row => {
// Calculate variance for each column (vertical variance)
@ -39,7 +51,7 @@ fn _variance_axis(x: &Matrix<f64>, axis: Axis) -> Matrix<f64> {
let diff = x.get(r, c) - mean_val;
sum_sq_diff += diff * diff;
}
result_data[c] = sum_sq_diff / num_rows;
result_data[c] = sum_sq_diff / (if population { num_rows } else { num_rows - 1.0 });
}
Matrix::from_vec(result_data, 1, x.cols())
}
@ -56,30 +68,39 @@ fn _variance_axis(x: &Matrix<f64>, axis: Axis) -> Matrix<f64> {
let diff = x.get(r, c) - mean_val;
sum_sq_diff += diff * diff;
}
result_data[r] = sum_sq_diff / num_cols;
result_data[r] = sum_sq_diff / (if population { num_cols } else { num_cols - 1.0 });
}
Matrix::from_vec(result_data, x.rows(), 1)
}
}
}
pub fn variance_vertical(x: &Matrix<f64>) -> Matrix<f64> {
_variance_axis(x, Axis::Row)
pub fn population_variance_vertical(x: &Matrix<f64>) -> Matrix<f64> {
_population_or_sample_variance_axis(x, Axis::Row, true)
}
pub fn variance_horizontal(x: &Matrix<f64>) -> Matrix<f64> {
_variance_axis(x, Axis::Col)
pub fn population_variance_horizontal(x: &Matrix<f64>) -> Matrix<f64> {
_population_or_sample_variance_axis(x, Axis::Col, true)
}
pub fn sample_variance_vertical(x: &Matrix<f64>) -> Matrix<f64> {
_population_or_sample_variance_axis(x, Axis::Row, false)
}
pub fn sample_variance_horizontal(x: &Matrix<f64>) -> Matrix<f64> {
_population_or_sample_variance_axis(x, Axis::Col, false)
}
pub fn stddev(x: &Matrix<f64>) -> f64 {
variance(x).sqrt()
population_variance(x).sqrt()
}
pub fn stddev_vertical(x: &Matrix<f64>) -> Matrix<f64> {
variance_vertical(x).map(|v| v.sqrt())
population_variance_vertical(x).map(|v| v.sqrt())
}
pub fn stddev_horizontal(x: &Matrix<f64>) -> Matrix<f64> {
variance_horizontal(x).map(|v| v.sqrt())
population_variance_horizontal(x).map(|v| v.sqrt())
}
pub fn median(x: &Matrix<f64>) -> f64 {
@ -180,7 +201,7 @@ mod tests {
assert!((mean(&x) - 3.0).abs() < EPSILON);
// Variance
assert!((variance(&x) - 2.0).abs() < EPSILON);
assert!((population_variance(&x) - 2.0).abs() < EPSILON);
// Standard Deviation
assert!((stddev(&x) - 1.4142135623730951).abs() < EPSILON);
@ -209,7 +230,7 @@ mod tests {
assert!((mean(&x) - 22.0).abs() < EPSILON);
// Variance should be heavily affected by outlier
assert!((variance(&x) - 1522.0).abs() < EPSILON);
assert!((population_variance(&x) - 1522.0).abs() < EPSILON);
// Standard Deviation should be heavily affected by outlier
assert!((stddev(&x) - 39.0128183970461).abs() < EPSILON);
@ -258,12 +279,12 @@ mod tests {
let x = Matrix::from_vec(data, 2, 3);
// cols: {1,4}, {2,5}, {3,6} all give 2.25
let vv = variance_vertical(&x);
let vv = population_variance_vertical(&x);
for c in 0..3 {
assert!((vv.get(0, c) - 2.25).abs() < EPSILON);
}
let vh = variance_horizontal(&x);
let vh = population_variance_horizontal(&x);
assert!((vh.get(0, 0) - (2.0 / 3.0)).abs() < EPSILON);
assert!((vh.get(1, 0) - (2.0 / 3.0)).abs() < EPSILON);
}