mirror of
https://github.com/storytold/gridcraft.git
synced 2026-11-09 02:34:11 +00:00
perf: select instead of sort in MEDIAN, PERCENTILE, QUARTILE, LARGE, SMALL
Read the needed order statistics with select_nth_unstable_by(total_cmp) instead of a full sort. Results are bit-identical; a test compares them against the previous full-sort code on randomised data. Fixes #2679 Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
This commit is contained in:
co-authored by
Claude Sonnet 5.5
parent
d8c5f5885f
commit
890870cd57
+132
-17
@@ -51,10 +51,11 @@ fn median(v: Vec<f64>) -> R<f64> {
|
||||
if v.is_empty() {
|
||||
return Err(CellError::Num);
|
||||
}
|
||||
let s = sorted(v);
|
||||
let n = s.len();
|
||||
let hi = s.get(n / 2).copied().unwrap_or(0.0);
|
||||
if n % 2 == 1 { Ok(hi) } else { Ok(s.get(n / 2 - 1).copied().unwrap_or(0.0).midpoint(hi)) }
|
||||
let mut v = v;
|
||||
let n = v.len();
|
||||
let (lower, hi, _) = v.select_nth_unstable_by(n / 2, f64::total_cmp);
|
||||
let hi = *hi;
|
||||
if n % 2 == 1 { Ok(hi) } else { Ok(lower.iter().copied().max_by(f64::total_cmp).unwrap_or(0.0).midpoint(hi)) }
|
||||
}
|
||||
|
||||
/// Values occurring at least twice, ordered by first occurrence, with their (equal, maximal) count.
|
||||
@@ -125,29 +126,38 @@ fn kth(v: Vec<f64>, k: f64, largest: bool) -> R<f64> {
|
||||
if k.is_nan() || k < 1.0 || k > v.len() as f64 {
|
||||
return Err(CellError::Num);
|
||||
}
|
||||
let s = sorted(v);
|
||||
let mut v = v;
|
||||
let k = k as usize;
|
||||
let idx = if largest { s.len() - k } else { k - 1 };
|
||||
s.get(idx).copied().ok_or(CellError::Num)
|
||||
let idx = if largest { v.len() - k } else { k - 1 };
|
||||
// Selection instead of a full sort; same total order, so the same bit pattern as `sorted(v)[idx]`.
|
||||
Ok(*v.select_nth_unstable_by(idx, f64::total_cmp).1)
|
||||
}
|
||||
|
||||
fn interp(s: &[f64], pos: f64) -> R<f64> {
|
||||
/// Value at fractional rank `pos` of the sorted data, linearly interpolated, found by selection.
|
||||
fn interp(mut v: Vec<f64>, pos: f64) -> R<f64> {
|
||||
let i = pos.floor();
|
||||
let frac = pos - i;
|
||||
let i = i as usize;
|
||||
let lo = *s.get(i).ok_or(CellError::Num)?;
|
||||
match s.get(i + 1) {
|
||||
Some(hi) if frac > 0.0 => Ok(lo + frac * (hi - lo)),
|
||||
_ => Ok(lo),
|
||||
if i >= v.len() {
|
||||
return Err(CellError::Num);
|
||||
}
|
||||
let (_, lo, upper) = v.select_nth_unstable_by(i, f64::total_cmp);
|
||||
let lo = *lo;
|
||||
// The next order statistic is the minimum of the upper partition.
|
||||
if frac > 0.0
|
||||
&& let Some(hi) = upper.iter().copied().min_by(f64::total_cmp)
|
||||
{
|
||||
return Ok(lo + frac * (hi - lo));
|
||||
}
|
||||
Ok(lo)
|
||||
}
|
||||
|
||||
fn percentile_inc(v: Vec<f64>, k: f64) -> R<f64> {
|
||||
if v.is_empty() || !(0.0..=1.0).contains(&k) {
|
||||
return Err(CellError::Num);
|
||||
}
|
||||
let s = sorted(v);
|
||||
interp(&s, k * (s.len() - 1) as f64)
|
||||
let pos = k * (v.len() - 1) as f64;
|
||||
interp(v, pos)
|
||||
}
|
||||
|
||||
fn percentile_exc(v: Vec<f64>, k: f64) -> R<f64> {
|
||||
@@ -159,8 +169,7 @@ fn percentile_exc(v: Vec<f64>, k: f64) -> R<f64> {
|
||||
if pos < 1.0 || pos > n {
|
||||
return Err(CellError::Num);
|
||||
}
|
||||
let s = sorted(v);
|
||||
interp(&s, pos - 1.0)
|
||||
interp(v, pos - 1.0)
|
||||
}
|
||||
|
||||
fn quartile_inc(v: Vec<f64>, q: f64) -> R<f64> {
|
||||
@@ -2274,7 +2283,9 @@ pub(crate) fn specs() -> Vec<FnSpec> {
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::{MAX_REGRESSORS, aggregate_values, aggregate_values_k, check_regression_size};
|
||||
use super::{
|
||||
MAX_REGRESSORS, R, aggregate_values, aggregate_values_k, check_regression_size, kth, median, percentile_exc, percentile_inc, sorted,
|
||||
};
|
||||
use crate::util::testutil::*;
|
||||
use gridcraft_core::{CellError, Value};
|
||||
|
||||
@@ -2463,6 +2474,110 @@ mod tests {
|
||||
close(ev("RANK.AVG", vec![n(3.5), r2, n(1.0)]), 3.5);
|
||||
}
|
||||
|
||||
// Reference implementations: the previous full-sort versions, as the oracle for the selection ones.
|
||||
fn old_interp(s: &[f64], pos: f64) -> R<f64> {
|
||||
let i = pos.floor();
|
||||
let frac = pos - i;
|
||||
let i = i as usize;
|
||||
let lo = *s.get(i).ok_or(CellError::Num)?;
|
||||
match s.get(i + 1) {
|
||||
Some(hi) if frac > 0.0 => Ok(lo + frac * (hi - lo)),
|
||||
_ => Ok(lo),
|
||||
}
|
||||
}
|
||||
|
||||
fn old_median(v: Vec<f64>) -> R<f64> {
|
||||
if v.is_empty() {
|
||||
return Err(CellError::Num);
|
||||
}
|
||||
let s = sorted(v);
|
||||
let n = s.len();
|
||||
let hi = s.get(n / 2).copied().unwrap_or(0.0);
|
||||
if n % 2 == 1 { Ok(hi) } else { Ok(s.get(n / 2 - 1).copied().unwrap_or(0.0).midpoint(hi)) }
|
||||
}
|
||||
|
||||
fn old_kth(v: Vec<f64>, k: f64, largest: bool) -> R<f64> {
|
||||
let k = k.ceil();
|
||||
if k.is_nan() || k < 1.0 || k > v.len() as f64 {
|
||||
return Err(CellError::Num);
|
||||
}
|
||||
let s = sorted(v);
|
||||
let k = k as usize;
|
||||
let idx = if largest { s.len() - k } else { k - 1 };
|
||||
s.get(idx).copied().ok_or(CellError::Num)
|
||||
}
|
||||
|
||||
fn old_percentile_inc(v: Vec<f64>, k: f64) -> R<f64> {
|
||||
if v.is_empty() || !(0.0..=1.0).contains(&k) {
|
||||
return Err(CellError::Num);
|
||||
}
|
||||
let s = sorted(v);
|
||||
old_interp(&s, k * (s.len() - 1) as f64)
|
||||
}
|
||||
|
||||
fn old_percentile_exc(v: Vec<f64>, k: f64) -> R<f64> {
|
||||
let n = v.len() as f64;
|
||||
if v.is_empty() || !(k > 0.0 && k < 1.0) {
|
||||
return Err(CellError::Num);
|
||||
}
|
||||
let pos = k * (n + 1.0);
|
||||
if pos < 1.0 || pos > n {
|
||||
return Err(CellError::Num);
|
||||
}
|
||||
let s = sorted(v);
|
||||
old_interp(&s, pos - 1.0)
|
||||
}
|
||||
|
||||
/// Same Ok bit pattern or same error.
|
||||
fn same(a: R<f64>, b: R<f64>) -> bool {
|
||||
match (a, b) {
|
||||
(Ok(x), Ok(y)) => x.to_bits() == y.to_bits(),
|
||||
(Err(x), Err(y)) => x == y,
|
||||
_ => false,
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn selection_matches_full_sort_bit_for_bit() {
|
||||
let mut state = 0x9E37_79B9_7F4A_7C15_u64;
|
||||
let mut next = move || {
|
||||
state ^= state << 13;
|
||||
state ^= state >> 7;
|
||||
state ^= state << 17;
|
||||
state
|
||||
};
|
||||
let specials = [0.0, -0.0, f64::INFINITY, f64::NEG_INFINITY, f64::NAN, -f64::NAN, f64::MAX, f64::MIN_POSITIVE, 1.0, -1.0];
|
||||
for len in (0..=40).chain([63, 64, 65, 100, 257, 1000, 4096]) {
|
||||
for round in 0..12 {
|
||||
let v: Vec<f64> = (0..len)
|
||||
.map(|_| match (round % 4, next() % 8) {
|
||||
// Few distinct values: many ties.
|
||||
(0, r) => (r % 3) as f64,
|
||||
// Specials, including both zeros and NaNs.
|
||||
(1, r) => specials[(next() as usize + r as usize) % specials.len()],
|
||||
// Wide random range.
|
||||
(2, _) => (next() as i64 as f64) / 1e3,
|
||||
// Integers with some specials mixed in.
|
||||
(_, 0) => specials[next() as usize % specials.len()],
|
||||
_ => (next() % 50) as f64,
|
||||
})
|
||||
.collect();
|
||||
assert!(same(median(v.clone()), old_median(v.clone())), "median len={len}");
|
||||
let ks = [-1.0, 0.0, 0.2, 1.0, 1.5, 2.0, len as f64 / 2.0, len as f64 - 0.5, len as f64, len as f64 + 1.0, f64::NAN];
|
||||
for &k in &ks {
|
||||
for largest in [true, false] {
|
||||
assert!(same(kth(v.clone(), k, largest), old_kth(v.clone(), k, largest)), "kth len={len} k={k}");
|
||||
}
|
||||
}
|
||||
let ps = [-0.1, 0.0, 0.01, 0.1, 0.25, 0.3, 0.5, 0.75, 0.9, 0.99, 1.0, 1.1, f64::NAN, (next() % 1001) as f64 / 1000.0];
|
||||
for &p in &ps {
|
||||
assert!(same(percentile_inc(v.clone(), p), old_percentile_inc(v.clone(), p)), "pinc len={len} p={p}");
|
||||
assert!(same(percentile_exc(v.clone(), p), old_percentile_exc(v.clone(), p)), "pexc len={len} p={p}");
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn percentiles() {
|
||||
close(ev("PERCENTILE.INC", vec![c(&[1.0, 3.0, 2.0, 4.0]), n(0.3)]), 1.9);
|
||||
|
||||
Reference in New Issue
Block a user