Refactor median and percentile functions to handle vertical and horizontal calculations correctly; add corresponding tests for validation

This commit is contained in:
Palash Tyagi 2025-07-08 21:00:19 +01:00
parent a2fcaf1d52
commit 5779c6b82d

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@ -94,33 +94,35 @@ pub fn median(x: &Matrix<f64>) -> f64 {
} }
fn _median_axis(x: &Matrix<f64>, axis: Axis) -> Matrix<f64> { fn _median_axis(x: &Matrix<f64>, axis: Axis) -> Matrix<f64> {
let mut data = match axis { let mx = match axis {
Axis::Row => x.sum_vertical(), Axis::Col => x.clone(),
Axis::Col => x.sum_horizontal(), Axis::Row => x.transpose(),
}; };
data.sort_by(|a, b| a.partial_cmp(b).unwrap());
let mid = data.len() / 2; let mut result = Vec::with_capacity(mx.cols());
if data.len() % 2 == 0 { for c in 0..mx.cols() {
Matrix::from_vec( let mut col = mx.column(c).to_vec();
vec![(data[mid - 1] + data[mid]) / 2.0], col.sort_by(|a, b| a.partial_cmp(b).unwrap());
if axis == Axis::Row { 1 } else { x.rows() }, let mid = col.len() / 2;
if axis == Axis::Row { x.cols() } else { 1 }, if col.len() % 2 == 0 {
) result.push((col[mid - 1] + col[mid]) / 2.0);
} else { } else {
Matrix::from_vec( result.push(col[mid]);
vec![data[mid]],
if axis == Axis::Row { 1 } else { x.rows() },
if axis == Axis::Row { x.cols() } else { 1 },
)
} }
} }
let (r, c) = match axis {
Axis::Col => (1, mx.cols()),
Axis::Row => (mx.cols(), 1),
};
Matrix::from_vec(result, r, c)
}
pub fn median_vertical(x: &Matrix<f64>) -> Matrix<f64> { pub fn median_vertical(x: &Matrix<f64>) -> Matrix<f64> {
_median_axis(x, Axis::Row) _median_axis(x, Axis::Col)
} }
pub fn median_horizontal(x: &Matrix<f64>) -> Matrix<f64> { pub fn median_horizontal(x: &Matrix<f64>) -> Matrix<f64> {
_median_axis(x, Axis::Col) _median_axis(x, Axis::Row)
} }
pub fn percentile(x: &Matrix<f64>, p: f64) -> f64 { pub fn percentile(x: &Matrix<f64>, p: f64) -> f64 {
@ -137,24 +139,29 @@ fn _percentile_axis(x: &Matrix<f64>, p: f64, axis: Axis) -> Matrix<f64> {
if p < 0.0 || p > 100.0 { if p < 0.0 || p > 100.0 {
panic!("Percentile must be between 0 and 100"); panic!("Percentile must be between 0 and 100");
} }
let mut data = match axis { let mx: Matrix<f64> = match axis {
Axis::Row => x.sum_vertical(), Axis::Col => x.clone(),
Axis::Col => x.sum_horizontal(), Axis::Row => x.transpose(),
}; };
data.sort_by(|a, b| a.partial_cmp(b).unwrap()); let mut result = Vec::with_capacity(mx.cols());
let index = ((p / 100.0) * (data.len() as f64 - 1.0)).round() as usize; for c in 0..mx.cols() {
Matrix::from_vec( let mut col = mx.column(c).to_vec();
vec![data[index]], col.sort_by(|a, b| a.partial_cmp(b).unwrap());
if axis == Axis::Row { 1 } else { x.rows() }, let index = ((p / 100.0) * (col.len() as f64 - 1.0)).round() as usize;
if axis == Axis::Row { x.cols() } else { 1 }, result.push(col[index]);
) }
let (r, c) = match axis {
Axis::Col => (1, mx.cols()),
Axis::Row => (mx.cols(), 1),
};
Matrix::from_vec(result, r, c)
} }
pub fn percentile_vertical(x: &Matrix<f64>, p: f64) -> Matrix<f64> { pub fn percentile_vertical(x: &Matrix<f64>, p: f64) -> Matrix<f64> {
_percentile_axis(x, p, Axis::Row) _percentile_axis(x, p, Axis::Col)
} }
pub fn percentile_horizontal(x: &Matrix<f64>, p: f64) -> Matrix<f64> { pub fn percentile_horizontal(x: &Matrix<f64>, p: f64) -> Matrix<f64> {
_percentile_axis(x, p, Axis::Col) _percentile_axis(x, p, Axis::Row)
} }
#[cfg(test)] #[cfg(test)]
@ -250,14 +257,12 @@ mod tests {
let data = vec![1.0, 4.0, 2.0, 5.0, 3.0, 6.0]; let data = vec![1.0, 4.0, 2.0, 5.0, 3.0, 6.0];
let x = Matrix::from_vec(data, 2, 3); let x = Matrix::from_vec(data, 2, 3);
// Vertical variances (per column): each is ((v - mean)^2 summed / 2)
// cols: {1,4}, {2,5}, {3,6} all give 2.25 // cols: {1,4}, {2,5}, {3,6} all give 2.25
let vv = variance_vertical(&x); let vv = variance_vertical(&x);
for c in 0..3 { for c in 0..3 {
assert!((vv.get(0, c) - 2.25).abs() < EPSILON); assert!((vv.get(0, c) - 2.25).abs() < EPSILON);
} }
// Horizontal variances (per row): rows [1,2,3] and [4,5,6] both give 2/3
let vh = variance_horizontal(&x); let vh = variance_horizontal(&x);
assert!((vh.get(0, 0) - (2.0 / 3.0)).abs() < EPSILON); assert!((vh.get(0, 0) - (2.0 / 3.0)).abs() < EPSILON);
assert!((vh.get(1, 0) - (2.0 / 3.0)).abs() < EPSILON); assert!((vh.get(1, 0) - (2.0 / 3.0)).abs() < EPSILON);
@ -280,4 +285,59 @@ mod tests {
assert!((sh.get(0, 0) - expected).abs() < EPSILON); assert!((sh.get(0, 0) - expected).abs() < EPSILON);
assert!((sh.get(1, 0) - expected).abs() < EPSILON); assert!((sh.get(1, 0) - expected).abs() < EPSILON);
} }
#[test]
fn test_median_vertical_horizontal() {
let data = vec![1.0, 4.0, 2.0, 5.0, 3.0, 6.0];
let x = Matrix::from_vec(data, 2, 3);
let mv = median_vertical(&x).row(0);
let expected_v = vec![2.5, 3.5, 4.5];
assert_eq!(mv, expected_v, "{:?} expected: {:?}", expected_v, mv);
}
#[test]
fn test_percentile_vertical_horizontal() {
// vec of f64 values 1..24 as a 4x6 matrix
let data: Vec<f64> = (1..=24).map(|x| x as f64).collect();
let x = Matrix::from_vec(data, 4, 6);
// columns:
// 1, 5, 9, 13, 17, 21
// 2, 6, 10, 14, 18, 22
// 3, 7, 11, 15, 19, 23
// 4, 8, 12, 16, 20, 24
let er0 = vec![1., 5., 9., 13., 17., 21.];
let er50 = vec![3., 7., 11., 15., 19., 23.];
let er100 = vec![4., 8., 12., 16., 20., 24.];
assert_eq!(percentile_vertical(&x, 0.0).data(), er0);
assert_eq!(percentile_vertical(&x, 50.0).data(), er50);
assert_eq!(percentile_vertical(&x, 100.0).data(), er100);
let eh0 = vec![1., 2., 3., 4.];
let eh50 = vec![13., 14., 15., 16.];
let eh100 = vec![21., 22., 23., 24.];
assert_eq!(percentile_horizontal(&x, 0.0).data(), eh0);
assert_eq!(percentile_horizontal(&x, 50.0).data(), eh50);
assert_eq!(percentile_horizontal(&x, 100.0).data(), eh100);
}
#[test]
#[should_panic(expected = "Percentile must be between 0 and 100")]
fn test_percentile_out_of_bounds() {
let data = vec![1.0, 2.0, 3.0];
let x = Matrix::from_vec(data, 1, 3);
percentile(&x, -10.0); // Should panic
}
#[test]
#[should_panic(expected = "Percentile must be between 0 and 100")]
fn test_percentile_vertical_out_of_bounds() {
let m = Matrix::from_vec(vec![1.0, 2.0, 3.0], 1, 3);
let _ = percentile_vertical(&m, -0.1);
}
} }