use super::{Arg, C, CellError, R, Value, arg, array_numbers, array_val, as_array, has, num, num_val, opt_num}; // --------------------------------------------------------------------------------------------- // Basic helpers over number lists // --------------------------------------------------------------------------------------------- pub(super) fn mean(x: &[f64]) -> R { if x.is_empty() { return Err(CellError::Div0); } Ok(x.iter().sum::() / x.len() as f64) } pub(super) fn devsq(x: &[f64]) -> f64 { if x.is_empty() { return 0.0; } let m = x.iter().sum::() / x.len() as f64; x.iter().map(|v| (v - m) * (v - m)).sum() } pub(super) fn var_s(x: &[f64]) -> R { if x.len() < 2 { return Err(CellError::Div0); } Ok(devsq(x) / (x.len() - 1) as f64) } pub(super) fn var_p(x: &[f64]) -> R { if x.is_empty() { return Err(CellError::Div0); } Ok(devsq(x) / x.len() as f64) } fn sorted(mut v: Vec) -> Vec { v.sort_by(f64::total_cmp); v } pub(super) fn median(v: Vec) -> R { 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)) } } /// Values occurring at least twice, ordered by first occurrence, with their (equal, maximal) count. fn modes(v: &[f64]) -> Vec { let mut counts: Vec<(f64, usize)> = Vec::new(); for &x in v { if let Some(e) = counts.iter_mut().find(|e| e.0 == x) { e.1 += 1; } else { counts.push((x, 1)); } } let best = counts.iter().map(|e| e.1).max().unwrap_or(0); if best < 2 { return Vec::new(); } counts.into_iter().filter(|e| e.1 == best).map(|e| e.0).collect() } pub(super) fn mode_sngl(v: &[f64]) -> R { modes(v).first().copied().ok_or(CellError::NA) } /// Numbers for MODE / MODE.SNGL / MODE.MULT. Inside multi-cell ranges and arrays only numbers /// count, like [`numbers`]. Scalar arguments differ from SUM: in Excel 365, text and logical /// values are skipped whether typed or referenced (even numeric text such as `"1"`, so /// `MODE(1,"1",2,3)` is `#N/A`, and `MODE(1,TRUE,TRUE,2)` is `#N/A`), but a single-cell reference /// to a blank cell is `#VALUE!` (`MODE(B9,2,D7)` with D7 blank). Arguments are processed left to /// right, so the first error wins. The results cached in POI's FormulaEvalTestData come from an /// older Excel that answered `#VALUE!` for typed text; they are not the reference here. pub(super) fn mode_numbers(args: &[Arg]) -> R> { let mut out = Vec::new(); for a in args { match &a.value { Value::Array(arr) => { for v in arr.iter() { match v { Value::Number(n) => out.push(*n), Value::Error(e) => return Err(*e), _ => {} } } } Value::Number(n) => out.push(*n), Value::Error(e) => return Err(*e), Value::Text(_) | Value::Bool(_) => {} Value::Empty => return Err(CellError::Value), } } Ok(out) } fn product(v: &[f64]) -> f64 { if v.is_empty() { 0.0 } else { v.iter().product() } } pub(super) fn min_of(v: &[f64]) -> f64 { if v.is_empty() { 0.0 } else { v.iter().copied().fold(f64::INFINITY, f64::min) } } pub(super) fn max_of(v: &[f64]) -> f64 { if v.is_empty() { 0.0 } else { v.iter().copied().fold(f64::NEG_INFINITY, f64::max) } } /// k-th largest (k is rounded up like Excel). fn kth(v: Vec, k: f64, largest: bool) -> R { 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 interp(s: &[f64], pos: f64) -> R { 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), } } pub(super) fn percentile_inc(v: Vec, k: f64) -> R { 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) } pub(super) fn percentile_exc(v: Vec, k: f64) -> R { 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); interp(&s, pos - 1.0) } pub(super) fn quartile_inc(v: Vec, q: f64) -> R { let q = q.trunc(); if !(0.0..=4.0).contains(&q) { return Err(CellError::Num); } percentile_inc(v, q / 4.0) } pub(super) fn quartile_exc(v: Vec, q: f64) -> R { let q = q.trunc(); if !(1.0..=3.0).contains(&q) { return Err(CellError::Num); } percentile_exc(v, q / 4.0) } pub(super) fn arg_nums(a: &[Arg], i: usize) -> R> { array_numbers(&arg(a, i)?.value) } /// Pairs of numbers at matching positions of two arrays (pairs with a non-number skipped). /// Different sizes give `#N/A`; errors propagate. fn pairs(x: &Value, y: &Value) -> R<(Vec, Vec)> { let xa = as_array(x); let ya = as_array(y); if xa.data.len() != ya.data.len() { return Err(CellError::NA); } let mut xs = Vec::new(); let mut ys = Vec::new(); for (a, b) in xa.data.iter().zip(ya.data.iter()) { if let Value::Error(e) = a { return Err(*e); } if let Value::Error(e) = b { return Err(*e); } if let (Value::Number(p), Value::Number(q)) = (a, b) { xs.push(*p); ys.push(*q); } } Ok((xs, ys)) } pub(super) fn arg_pairs(a: &[Arg], i: usize, j: usize) -> R<(Vec, Vec)> { pairs(&arg(a, i)?.value, &arg(a, j)?.value) } /// (sum of cross deviations, devsq x, devsq y, mean x, mean y). pub(super) fn moments(x: &[f64], y: &[f64]) -> R<(f64, f64, f64, f64, f64)> { let mx = mean(x)?; let my = mean(y)?; let mut sxy = 0.0; let mut sxx = 0.0; let mut syy = 0.0; for (a, b) in x.iter().zip(y) { sxy += (a - mx) * (b - my); sxx += (a - mx) * (a - mx); syy += (b - my) * (b - my); } Ok((sxy, sxx, syy, mx, my)) } pub(super) fn correl(x: &[f64], y: &[f64]) -> R { if x.len() < 2 { return Err(CellError::Div0); } let (sxy, sxx, syy, _, _) = moments(x, y)?; if sxx == 0.0 || syy == 0.0 { return Err(CellError::Div0); } Ok(sxy / (sxx * syy).sqrt()) } pub(super) fn slope(y: &[f64], x: &[f64]) -> R { let (sxy, sxx, _, _, _) = moments(x, y)?; if sxx == 0.0 { return Err(CellError::Div0); } Ok(sxy / sxx) } pub(super) fn intercept(y: &[f64], x: &[f64]) -> R { let (sxy, sxx, _, mx, my) = moments(x, y)?; if sxx == 0.0 { return Err(CellError::Div0); } Ok(my - sxy / sxx * mx) } fn trunc_digits(r: f64, sig: f64) -> f64 { let f = 10f64.powi(sig as i32); if !f.is_finite() { return r; } ((r * f) + 1e-9).floor() / f } fn col_value(v: Vec) -> R { let n = v.len(); array_val(n, 1, v.into_iter().map(Value::Number).collect()) } // --------------------------------------------------------------------------------------------- // Aggregates // --------------------------------------------------------------------------------------------- pub(super) fn count_impl(a: &[Arg]) -> f64 { let mut c = 0usize; for x in a { match &x.value { Value::Array(arr) => c += arr.iter().filter(|v| v.is_number()).count(), Value::Number(_) => c += 1, _ if x.from_ref => {} Value::Bool(_) => c += 1, Value::Text(t) if gridcraft_core::parse::parse_number_text(t).is_some() => c += 1, _ => {} } } c as f64 } pub(super) fn counta_impl(a: &[Arg]) -> f64 { let mut c = 0usize; for x in a { match &x.value { Value::Array(arr) => c += arr.iter().filter(|v| !v.is_empty()).count(), Value::Empty if x.from_ref => {} _ => c += 1, } } c as f64 } pub(super) fn countblank(a: &[Arg], _: C) -> R { let v = &arg(a, 0)?.value; let blank = |x: &Value| matches!(x, Value::Empty) || matches!(x, Value::Text(t) if t.is_empty()); let c = match v { Value::Array(arr) => arr.iter().filter(|x| blank(x)).count(), x => usize::from(blank(x)), }; num_val(c as f64) } pub(super) fn mode_mult(a: &[Arg], _: C) -> R { let v = mode_numbers(a)?; let m = modes(&v); if m.is_empty() { return Err(CellError::NA); } col_value(m) } pub(super) fn large(a: &[Arg], _: C) -> R { num_val(kth(arg_nums(a, 0)?, num(a, 1)?, true)?) } pub(super) fn small(a: &[Arg], _: C) -> R { num_val(kth(arg_nums(a, 0)?, num(a, 1)?, false)?) } pub(super) fn rank_impl(a: &[Arg], avg: bool) -> R { let x = num(a, 0)?; let v = arg_nums(a, 1)?; let asc = opt_num(a, 2, 0.0)? != 0.0; let eq = v.iter().filter(|&&y| y == x).count(); if eq == 0 { return Err(CellError::NA); } let before = v.iter().filter(|&&y| if asc { y < x } else { y > x }).count(); let r = before as f64 + 1.0; num_val(if avg { r + (eq as f64 - 1.0) / 2.0 } else { r }) } pub(super) fn percentrank_impl(a: &[Arg], exc: bool) -> R { let s = sorted(arg_nums(a, 0)?); let x = num(a, 1)?; let sig = opt_num(a, 2, 3.0)?.trunc(); if sig < 1.0 || s.is_empty() { return Err(CellError::Num); } // Excel: 10^significance overflows from 309 up. if sig >= 309.0 { return Err(CellError::Div0); } let (first, last) = (s.first().copied().unwrap_or(0.0), s.last().copied().unwrap_or(0.0)); if x < first || x > last { return Err(CellError::NA); } let n = s.len() as f64; let rank_of = |v: f64| -> f64 { let less = s.iter().filter(|&&y| y < v).count() as f64; if exc { (less + 1.0) / (n + 1.0) } else if n <= 1.0 { 1.0 } else { less / (n - 1.0) } }; let r = if s.contains(&x) { rank_of(x) } else { let lo = s.iter().copied().filter(|&y| y < x).fold(f64::NEG_INFINITY, f64::max); let hi = s.iter().copied().filter(|&y| y > x).fold(f64::INFINITY, f64::min); let (rl, rh) = (rank_of(lo), rank_of(hi)); rl + (x - lo) / (hi - lo) * (rh - rl) }; // From significance 15 up Excel returns 15 significant digits, rounded. if sig >= 15.0 { return num_val(format!("{r:.14e}").parse().unwrap_or(r)); } num_val(trunc_digits(r, sig)) } pub(super) fn trimmean(a: &[Arg], _: C) -> R { let v = arg_nums(a, 0)?; let p = num(a, 1)?; if !(0.0..1.0).contains(&p) || v.is_empty() { return Err(CellError::Num); } let n = v.len(); let per_side = ((n as f64 * p) / 2.0).floor() as usize; let s = sorted(v); let kept = s.get(per_side..n - per_side).unwrap_or(&[]); num_val(mean(kept)?) } pub(super) fn kurt(v: &[f64]) -> R { let n = v.len() as f64; if v.len() < 4 { return Err(CellError::Div0); } let m = mean(v)?; let s = var_s(v)?.sqrt(); if s == 0.0 { return Err(CellError::Div0); } let sum4: f64 = v.iter().map(|x| ((x - m) / s).powi(4)).sum(); Ok(n * (n + 1.0) / ((n - 1.0) * (n - 2.0) * (n - 3.0)) * sum4 - 3.0 * (n - 1.0).powi(2) / ((n - 2.0) * (n - 3.0))) } pub(super) fn skew(v: &[f64]) -> R { let n = v.len() as f64; if v.len() < 3 { return Err(CellError::Div0); } let m = mean(v)?; let s = var_s(v)?.sqrt(); if s == 0.0 { return Err(CellError::Div0); } let sum3: f64 = v.iter().map(|x| ((x - m) / s).powi(3)).sum(); Ok(n / ((n - 1.0) * (n - 2.0)) * sum3) } pub(super) fn skew_p(v: &[f64]) -> R { let m = mean(v)?; let s = var_p(v)?.sqrt(); if s == 0.0 { return Err(CellError::Div0); } Ok(v.iter().map(|x| ((x - m) / s).powi(3)).sum::() / v.len() as f64) } pub(super) fn geomean(v: &[f64]) -> R { if v.is_empty() || v.iter().any(|&x| x <= 0.0) { return Err(CellError::Num); } Ok((v.iter().map(|x| x.ln()).sum::() / v.len() as f64).exp()) } pub(super) fn harmean(v: &[f64]) -> R { if v.is_empty() { return Err(CellError::NA); } if v.iter().any(|&x| x <= 0.0) { return Err(CellError::Num); } Ok(v.len() as f64 / v.iter().map(|x| 1.0 / x).sum::()) } pub(super) fn avedev(v: &[f64]) -> R { if v.is_empty() { return Err(CellError::Num); } let m = mean(v)?; Ok(v.iter().map(|x| (x - m).abs()).sum::() / v.len() as f64) } pub(super) fn frequency(a: &[Arg], _: C) -> R { let data = arg_nums(a, 0)?; let bins = arg_nums(a, 1)?; if bins.is_empty() { return col_value(vec![data.len() as f64]); } let mut order: Vec = (0..bins.len()).collect(); order.sort_by(|&i, &j| bins.get(i).copied().unwrap_or(0.0).total_cmp(&bins.get(j).copied().unwrap_or(0.0))); let mut counts = vec![0.0; bins.len() + 1]; for x in data { let slot = order.iter().find(|&&i| x <= bins.get(i).copied().unwrap_or(f64::INFINITY)).copied().unwrap_or(bins.len()); if let Some(c) = counts.get_mut(slot) { *c += 1.0; } } col_value(counts) } pub(super) fn prob(a: &[Arg], _: C) -> R { let (xs, ps) = arg_pairs(a, 0, 1)?; let lo = num(a, 2)?; let hi = if has(a, 3) { num(a, 3)? } else { lo }; if ps.iter().any(|&p| p <= 0.0 || p > 1.0) { return Err(CellError::Num); } let total: f64 = ps.iter().sum(); if (total - 1.0).abs() > 1e-7 { return Err(CellError::Num); } num_val(xs.iter().zip(&ps).filter(|(x, _)| **x >= lo && **x <= hi).map(|(_, p)| p).sum()) } pub(super) fn standardize(a: &[Arg], _: C) -> R { let (x, m, sd) = (num(a, 0)?, num(a, 1)?, num(a, 2)?); if sd <= 0.0 { return Err(CellError::Num); } num_val((x - m) / sd) } // --------------------------------------------------------------------------------------------- // SUBTOTAL / AGGREGATE support // --------------------------------------------------------------------------------------------- /// Evaluates SUBTOTAL/AGGREGATE function `function_num` over already-filtered cell values. /// /// Codes 1–11 (and 101–111) are AVERAGE, COUNT, COUNTA, MAX, MIN, PRODUCT, STDEV.S, STDEV.P, /// SUM, VAR.S, VAR.P; 12 = MEDIAN, 13 = MODE.SNGL. Codes 14–19 need `k`: use /// [`aggregate_values_k`] (they give `#VALUE!` here). Values that are not numbers are ignored /// (COUNTA counts non-empty values); the first error value present is returned. pub fn aggregate_values(function_num: u32, values: &[Value]) -> Value { crate::util::finish(aggregate_impl(function_num, values, None)) } /// AGGREGATE codes 14 = LARGE, 15 = SMALL, 16 = PERCENTILE.INC, 17 = QUARTILE.INC, /// 18 = PERCENTILE.EXC, 19 = QUARTILE.EXC with their `k` argument; codes 1–13 delegate to /// [`aggregate_values`]. pub fn aggregate_values_k(function_num: u32, values: &[Value], k: &Value) -> Value { crate::util::finish(aggregate_impl(function_num, values, Some(k))) } fn aggregate_impl(function_num: u32, values: &[Value], k: Option<&Value>) -> R { let code = if (101..=111).contains(&function_num) { function_num - 100 } else { function_num }; let mut xs = Vec::new(); let mut nonempty = 0usize; let mut push = |v: &Value| -> R<()> { match v { Value::Number(n) => xs.push(*n), Value::Error(e) => return Err(*e), _ => {} } if !v.is_empty() { nonempty += 1; } Ok(()) }; for v in values { match v { Value::Array(arr) => arr.iter().try_for_each(&mut push)?, other => push(other)?, } } let k = match (code, k) { (14..=19, Some(k)) => k.scalar().to_number()?, (14..=19, None) => return Err(CellError::Value), _ => 0.0, }; let r = match code { 1 => mean(&xs)?, 2 => xs.len() as f64, 3 => nonempty as f64, 4 => max_of(&xs), 5 => min_of(&xs), 6 => product(&xs), 7 => var_s(&xs)?.sqrt(), 8 => var_p(&xs)?.sqrt(), 9 => xs.iter().sum(), 10 => var_s(&xs)?, 11 => var_p(&xs)?, 12 => median(xs)?, 13 => mode_sngl(&xs)?, 14 => kth(xs, k, true)?, 15 => kth(xs, k, false)?, 16 => percentile_inc(xs, k)?, 17 => quartile_inc(xs, k)?, 18 => percentile_exc(xs, k)?, 19 => quartile_exc(xs, k)?, _ => return Err(CellError::Value), }; num_val(r) }