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refactor(engine): move cmd/solver tests to src/cmd/solver/tests.rs
This commit is contained in:
aiongg
@@ -2127,482 +2127,4 @@ fn run(s: &mut Session, p: &Json) -> Result<Json> {
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}
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#[cfg(test)]
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mod tests {
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use gridcraft_core::{CellRef, Value};
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use serde_json::json;
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use crate::Session;
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fn s() -> Session {
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let mut s = Session::new();
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s.new_workbook();
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s
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}
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fn n(s: &Session, a: &str) -> f64 {
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let d = s.doc().unwrap();
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d.wb.active().unwrap().value(CellRef::parse(a).unwrap()).as_f64().unwrap_or(f64::NAN)
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}
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/// The first saved-model name scoped to the active sheet.
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fn saved(s: &Session) -> String {
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let d = s.doc().unwrap();
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d.wb.names.iter().find(|n| n.scope == Some(d.wb.active_sheet())).map(|n| n.name.clone()).unwrap_or_default()
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}
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fn set(s: &mut Session, cells: &[(&str, &str)]) {
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for (c, v) in cells {
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s.execute("cell.set", json!({"cell": c, "input": v})).unwrap();
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}
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}
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#[test]
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fn simplex_solves_the_wyndor_glass_lp() {
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// Hillier & Lieberman's Wyndor Glass problem: max 3x + 5y, x ≤ 4, 2y ≤ 12, 3x + 2y ≤ 18
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// → x = 2, y = 6, Z = 36.
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let mut s = s();
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set(&mut s, &[("A1", "0"), ("A2", "0"), ("B1", "=3*A1+5*A2"), ("B2", "=2*A2"), ("B3", "=3*A1+2*A2")]);
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let r = s
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.execute(
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"data.solver",
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json!({"objective": "B1", "goal": "max", "variables": "A1:A2", "constraints": ["A1 <= 4", "B2 <= 12", {"lhs": "B3", "op": "<=", "rhs": 18}], "method": "simplex"}),
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)
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.unwrap();
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assert_eq!(r["status"], "optimal", "{r}");
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assert!((n(&s, "A1") - 2.0).abs() < 1e-9 && (n(&s, "A2") - 6.0).abs() < 1e-9);
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assert!((n(&s, "B1") - 36.0).abs() < 1e-9);
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// The model is saved as hidden names, survives XLSX and solves again from them.
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let names: Vec<String> = s.doc().unwrap().wb.names.iter().map(|n| n.name.clone()).collect();
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assert!(names.iter().any(|n| n == "solver_opt") && names.iter().any(|n| n == "solver_lhs3"));
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let b64 = s.execute("file.saveBytes", json!({"format": "xlsx"})).unwrap()["base64"].as_str().unwrap().to_string();
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s.execute("file.open", json!({"name": "m.xlsx", "base64": b64})).unwrap();
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set(&mut s, &[("A1", "0"), ("A2", "0")]);
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let m = s.execute("data.solver", json!({})).unwrap();
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assert_eq!(m["model"]["objective"], "B1");
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assert_eq!(m["model"]["method"], "simplex");
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let r = s.execute("data.solver", json!({"saved": true})).unwrap();
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assert_eq!(r["status"], "optimal");
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assert!((n(&s, "B1") - 36.0).abs() < 1e-9);
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// Minimise with keep: false leaves the cells alone.
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set(&mut s, &[("A1", "1"), ("A2", "1")]);
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let r = s.execute("data.solver", json!({"saved": true, "goal": "min", "keep": false})).unwrap();
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assert_eq!(r["objective"], 0.0);
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assert_eq!((n(&s, "A1"), n(&s, "A2")), (1.0, 1.0));
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}
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#[test]
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fn integer_and_binary_constraints_use_branch_and_bound() {
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// max 5x + 4y, 6x + 4y ≤ 24, x + 2y ≤ 6: the LP optimum (3, 1.5) = 21; integers give
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// (4, 0) = 20.
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let mut s = s();
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set(&mut s, &[("B1", "=5*A1+4*A2"), ("B2", "=6*A1+4*A2"), ("B3", "=A1+2*A2")]);
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let base = json!({"objective": "B1", "variables": "A1:A2", "constraints": ["B2 <= 24", "B3 <= 6"], "method": "simplex"});
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let r = s.execute("data.solver", base.clone()).unwrap();
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assert!((r["objective"].as_f64().unwrap() - 21.0).abs() < 1e-9);
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let mut p = base.clone();
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p["constraints"].as_array_mut().unwrap().push(json!("A1:A2 int"));
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let r = s.execute("data.solver", p).unwrap();
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assert_eq!(r["status"], "optimal");
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assert_eq!((n(&s, "A1"), n(&s, "A2"), n(&s, "B1")), (4.0, 0.0, 20.0));
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// 0/1 knapsack: values 10, 13, 7, weights 5, 6, 4, capacity 10 → items 2 and 3 (20).
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set(&mut s, &[("D1", "=10*C1+13*C2+7*C3"), ("D2", "=5*C1+6*C2+4*C3")]);
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let r = s
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.execute("data.solver", json!({"objective": "D1", "variables": "C1:C3", "constraints": ["D2 <= 10", "C1:C3 bin"], "method": "simplex"}))
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.unwrap();
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assert_eq!(r["status"], "optimal");
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assert_eq!((n(&s, "C1"), n(&s, "C2"), n(&s, "C3"), n(&s, "D1")), (0.0, 1.0, 1.0, 20.0));
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}
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#[test]
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fn grg_finds_smooth_optima() {
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// Largest rectangle with perimeter at most 20: a 5 × 5 square, area 25.
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let mut s = s();
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set(&mut s, &[("A1", "1"), ("A2", "1"), ("B1", "=A1*A2"), ("B2", "=2*A1+2*A2")]);
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let r = s.execute("data.solver", json!({"objective": "B1", "variables": "A1:A2", "constraints": ["B2 <= 20"]})).unwrap();
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assert_eq!(r["status"], "converged", "{r}");
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assert!((n(&s, "A1") - 5.0).abs() < 1e-3 && (n(&s, "A2") - 5.0).abs() < 1e-3, "{r}");
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// Unconstrained minimum of (x − 3)² + (y + 1)² at (3, −1) once negatives are allowed.
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set(&mut s, &[("C1", "0"), ("C2", "0"), ("D1", "=(C1-3)^2+(C2+1)^2")]);
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s.execute("data.solver", json!({"objective": "D1", "goal": "min", "variables": "C1:C2", "nonNegative": false})).unwrap();
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assert!((n(&s, "C1") - 3.0).abs() < 1e-4 && (n(&s, "C2") + 1.0).abs() < 1e-4);
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// Value Of: x³ = 8 → x = 2.
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set(&mut s, &[("E1", "1"), ("F1", "=E1^3")]);
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s.execute("data.solver", json!({"objective": "F1", "goal": "value", "value": 8, "variables": "E1"})).unwrap();
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assert!((n(&s, "E1") - 2.0).abs() < 1e-4);
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}
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#[test]
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fn evolutionary_finds_the_global_minimum_of_non_smooth_and_multimodal_models() {
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let mut s = s();
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// |x − 3| + |y + 2| has a kink at its minimum (3, −2).
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set(&mut s, &[("A1", "0"), ("A2", "0"), ("B1", "=ABS(A1-3)+ABS(A2+2)")]);
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let p =
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json!({"objective": "B1", "goal": "min", "variables": "A1:A2", "constraints": ["A1:A2 >= -10", "A1:A2 <= 10"], "method": "evolutionary"});
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let r = s.execute("data.solver", p.clone()).unwrap();
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assert!(r["status"] == "converged" || r["status"] == "cannotImprove", "{r}");
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assert!((n(&s, "A1") - 3.0).abs() < 1e-6 && (n(&s, "A2") + 2.0).abs() < 1e-6, "{r}");
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// The same seed repeats the run exactly.
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set(&mut s, &[("A1", "0"), ("A2", "0")]);
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let again = s.execute("data.solver", p).unwrap();
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assert_eq!(again["values"], r["values"]);
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assert_eq!(again["evaluations"], r["evaluations"]);
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// Rastrigin's function 20 + Σ (x² − 10 cos 2πx) on [−5.12, 5.12]² has its global minimum 0
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// at the origin among many local minima; GRG from (3.3, −2.7) stops at a local one.
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set(&mut s, &[("C1", "3.3"), ("C2", "-2.7"), ("D1", "=20+C1^2-10*COS(2*PI()*C1)+C2^2-10*COS(2*PI()*C2)")]);
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let base = json!({"objective": "D1", "goal": "min", "variables": "C1:C2", "constraints": ["C1:C2 >= -5.12", "C1:C2 <= 5.12"]});
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s.execute("data.solver", base.clone()).unwrap();
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assert!(n(&s, "D1") > 0.5, "GRG is local: {}", n(&s, "D1"));
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set(&mut s, &[("C1", "3.3"), ("C2", "-2.7")]);
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let mut p = base.clone();
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p["method"] = json!("evolutionary");
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let r = s.execute("data.solver", p).unwrap();
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assert!(n(&s, "D1") < 1e-8 && n(&s, "C1").abs() < 1e-5 && n(&s, "C2").abs() < 1e-5, "{r}");
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// A stepped model: ROUND makes it flat almost everywhere; the minimum is at 7.2.
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set(&mut s, &[("E1", "0"), ("F1", "=ABS(ROUND(E1,0)-7)+ABS(E1-7.2)/100")]);
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s.execute("data.solver", json!({"objective": "F1", "goal": "min", "variables": "E1", "constraints": ["E1 <= 20"], "method": "evolutionary"}))
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.unwrap();
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assert!((n(&s, "E1") - 7.2).abs() < 1e-6, "{}", n(&s, "E1"));
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}
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#[test]
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fn evolutionary_handles_integers_bounds_and_the_saved_model() {
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let mut s = s();
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// The 0/1 knapsack of the branch-and-bound test: items 2 and 3, value 20.
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set(&mut s, &[("D1", "=10*C1+13*C2+7*C3"), ("D2", "=5*C1+6*C2+4*C3")]);
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let p = json!({"objective": "D1", "variables": "C1:C3", "constraints": ["D2 <= 10", "C1:C3 bin"], "method": "evolutionary", "populationSize": 30, "randomSeed": 7});
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let r = s.execute("data.solver", p).unwrap();
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assert!(r["status"] == "converged" || r["status"] == "cannotImprove", "{r}");
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assert_eq!((n(&s, "C1"), n(&s, "C2"), n(&s, "C3"), n(&s, "D1")), (0.0, 1.0, 1.0, 20.0));
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// The method and its options are saved, survive XLSX and solve again.
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let b64 = s.execute("file.saveBytes", json!({"format": "xlsx"})).unwrap()["base64"].as_str().unwrap().to_string();
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s.execute("file.open", json!({"name": "e.xlsx", "base64": b64})).unwrap();
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let m = s.execute("data.solver", json!({})).unwrap();
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assert_eq!(m["model"]["method"], "evolutionary");
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assert_eq!((m["model"]["populationSize"].as_f64(), m["model"]["randomSeed"].as_f64()), (Some(30.0), Some(7.0)));
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set(&mut s, &[("C1", "0"), ("C2", "0"), ("C3", "0")]);
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s.execute("data.solver", json!({"saved": true})).unwrap();
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assert_eq!(n(&s, "D1"), 20.0);
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// Integer constraints: max x + y with x + 2y ≤ 7 on integers in [0, 10] → (7, 0).
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set(&mut s, &[("A1", "0"), ("A2", "0"), ("B1", "=A1+A2"), ("B2", "=A1+2*A2")]);
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let r = s
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.execute(
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"data.solver",
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json!({"objective": "B1", "variables": "A1:A2", "constraints": ["B2 <= 7", "A1:A2 <= 10", "A1:A2 int"], "method": "evolutionary"}),
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)
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.unwrap();
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assert_eq!((n(&s, "A1"), n(&s, "A2")), (7.0, 0.0), "{r}");
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// Every variable needs bounds unless requireBounds is off; then it searches around the start.
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set(&mut s, &[("E1", "1"), ("F1", "=ABS(E1-4)")]);
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let p = json!({"objective": "F1", "goal": "min", "variables": "E1", "method": "evolutionary"});
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assert!(s.execute("data.solver", p.clone()).is_err());
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let mut p = p;
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p["requireBounds"] = json!(false);
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s.execute("data.solver", p).unwrap();
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assert!((n(&s, "E1") - 4.0).abs() < 1e-6);
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// Infeasible constraints and a tiny budget are reported without changing the cells.
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set(&mut s, &[("E1", "1")]);
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let r = s
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.execute("data.solver", json!({"objective": "F1", "variables": "E1", "constraints": ["E1 <= 3", "F1 >= 10"], "method": "evolutionary"}))
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.unwrap();
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assert_eq!(r["status"], "infeasible", "{r}");
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let r = s
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.execute(
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"data.solver",
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json!({"objective": "F1", "variables": "E1", "constraints": ["E1 <= 3"], "method": "evolutionary", "maxEvaluations": 3}),
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)
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.unwrap();
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assert_eq!(r["status"], "iterationLimit", "{r}");
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assert_eq!(n(&s, "E1"), 1.0);
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}
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/// Text or number at `a1` on sheet `name`.
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fn at(s: &Session, name: &str, a1: &str) -> Value {
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let d = s.doc().unwrap();
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d.wb.sheet(d.wb.sheet_index(name).unwrap()).unwrap().value(CellRef::parse(a1).unwrap())
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}
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/// The row of the first cell holding `text` on sheet `name`.
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fn row_of(s: &Session, name: &str, text: &str) -> u32 {
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let d = s.doc().unwrap();
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let sh = d.wb.sheet(d.wb.sheet_index(name).unwrap()).unwrap();
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(0..60).find(|r| (0..8).any(|c| sh.value(CellRef::new(*r, c)) == Value::text(text))).unwrap()
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}
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#[test]
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fn answer_and_limits_reports_describe_the_wyndor_glass_solution() {
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// Wyndor Glass with labels: doors and windows across, the three plants' hours down.
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let mut s = s();
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s.execute(
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"range.setValues",
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json!({"range": "A1", "values": [[null, "Doors", "Windows", "Used", "Available"], ["Batches", 0, 0, null, null], ["Plant 1", 1, 0, null, 4], ["Plant 2", 0, 2, null, 12], ["Plant 3", 3, 2, null, 18], ["Profit", 3, 5, null, null]]}),
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)
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.unwrap();
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for r in 3..=6 {
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set(&mut s, &[(&format!("D{r}"), &format!("=SUMPRODUCT(B{r}:C{r},$B$2:$C$2)"))]);
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}
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let solved = s
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.execute(
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"data.solver",
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json!({"objective": "D6", "variables": "B2:C2", "constraints": ["D3:D5 <= E3:E5"], "method": "simplex", "reports": ["answer", "limits"]}),
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)
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.unwrap();
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assert_eq!(solved["status"], "optimal", "{solved}");
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assert_eq!(solved["reports"], json!(["Answer Report 1", "Limits Report 1"]));
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assert_eq!(solved["original"], json!({"B2": 0.0, "C2": 0.0}));
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let d = s.doc().unwrap();
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let names: Vec<&str> = d.wb.sheets.iter().map(|x| x.name.as_str()).collect();
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assert_eq!(names, ["Answer Report 1", "Limits Report 1", "Sheet1"]);
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assert_eq!(d.wb.active().unwrap().name, "Sheet1", "the model's sheet stays active");
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assert_eq!(saved(&s), "solver_opt", "the saved model follows its sheet");
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let a = "Answer Report 1";
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assert_eq!(at(&s, a, "A1"), Value::text("GridCraft Answer Report"));
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// Objective: $D$6 "Profit Used", from 0 to 36.
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let r = row_of(&s, a, "$D$6");
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assert_eq!(at(&s, a, &format!("C{}", r + 1)), Value::text("Profit Used"));
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assert_eq!((at(&s, a, &format!("D{}", r + 1)), at(&s, a, &format!("E{}", r + 1))), (Value::number(0.0), Value::number(36.0)));
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// Variables: doors 0 → 2, windows 0 → 6, continuous.
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let r = row_of(&s, a, "$B$2") + 1;
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assert_eq!(at(&s, a, &format!("C{r}")), Value::text("Batches Doors"));
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assert_eq!(at(&s, a, &format!("E{r}")), Value::number(2.0));
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assert_eq!(at(&s, a, &format!("F{r}")), Value::text("Contin"));
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assert_eq!(at(&s, a, &format!("E{}", r + 1)), Value::number(6.0));
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// Constraints: plant 1 has 2 hours to spare; plants 2 and 3 are binding.
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let r = row_of(&s, a, "$D$3") + 1;
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assert_eq!(at(&s, a, &format!("E{r}")), Value::text("$D$3<=$E$3"));
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assert_eq!((at(&s, a, &format!("F{r}")), at(&s, a, &format!("G{r}"))), (Value::text("Not Binding"), Value::number(2.0)));
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for k in 1..=2 {
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assert_eq!((at(&s, a, &format!("F{}", r + k)), at(&s, a, &format!("G{}", r + k))), (Value::text("Binding"), Value::number(0.0)));
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}
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// Limits with the other variable held: doors 0..2 (profit 30..36), windows 0..6 (6..36).
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let l = "Limits Report 1";
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let r = row_of(&s, l, "$B$2") + 1;
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let row = |r: u32| ["D", "E", "F", "G", "H"].map(|c| at(&s, l, &format!("{c}{r}")).as_f64().unwrap());
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assert_eq!(row(r), [2.0, 0.0, 30.0, 2.0, 36.0]);
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assert_eq!(row(r + 1), [6.0, 0.0, 6.0, 6.0, 36.0]);
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// data.solverReport writes reports from the saved model and a given solution.
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let out =
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s.execute("data.solverReport", json!({"reports": ["answer"], "values": {"B2": 2, "C2": 6}, "original": {"B2": 1, "C2": 1}})).unwrap();
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assert_eq!(out["sheets"], json!(["Answer Report 2"]));
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let r = row_of(&s, "Answer Report 2", "$D$6") + 1;
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assert_eq!(at(&s, "Answer Report 2", &format!("D{r}")), Value::number(8.0));
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// Undo removes the reports and keeps the solution; refused requests write nothing.
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s.execute("edit.undo", json!({})).unwrap();
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assert_eq!(s.doc().unwrap().wb.sheets.len(), 3);
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for p in [
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json!({}),
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json!({"reports": []}),
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json!({"reports": "answer"}),
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json!({"reports": ["population"]}),
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json!({"reports": ["answer"], "values": {"Z9": 1}}),
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json!({"reports": ["answer"], "values": {"B2": "x"}}),
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json!({"reports": ["limits"], "constraints": ["D3:D5 <= E3:E5", "B2:C2 int"]}),
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json!({"reports": ["limits"], "method": "evolutionary", "constraints": ["D3:D5 <= E3:E5", "B2:C2 <= 10"]}),
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] {
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assert!(s.execute("data.solverReport", p.clone()).is_err(), "{p}");
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}
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assert_eq!(s.doc().unwrap().wb.sheets.len(), 3);
|
||||
// With the solve, its reports and the saved model undone (one step), the result still
|
||||
// describes the solution.
|
||||
s.execute("edit.undo", json!({})).unwrap();
|
||||
assert_eq!((s.doc().unwrap().wb.sheets.len(), n(&s, "B2")), (1, 0.0));
|
||||
let mut p = solved.clone();
|
||||
p["reports"] = json!(["answer"]);
|
||||
assert_eq!(s.execute("data.solverReport", p).unwrap()["sheets"], json!(["Answer Report 1"]));
|
||||
let r = row_of(&s, "Answer Report 1", "$B$2") + 1;
|
||||
assert_eq!(at(&s, "Answer Report 1", &format!("E{r}")), Value::number(2.0));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn refused_solver_reports_preserve_the_document_and_history() {
|
||||
for (protected, method, constraints, reports, error) in [
|
||||
(true, "simplex", json!(["A1 <= 4"]), json!(["answer"]), "workbook is protected"),
|
||||
(false, "simplex", json!(["A1 <= 4", "A1 int"]), json!(["answer", "limits"]), "integer or binary"),
|
||||
(false, "evolutionary", json!(["A1 <= 4"]), json!(["answer", "limits"]), "Simplex LP and GRG"),
|
||||
] {
|
||||
for (keep, save) in [(true, true), (false, true), (true, false), (false, false)] {
|
||||
let mut s = s();
|
||||
set(&mut s, &[("A1", "1"), ("B1", "=2*A1")]);
|
||||
s.execute(
|
||||
"data.solver",
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": ["A1 <= 2"], "method": "simplex", "keep": false}),
|
||||
)
|
||||
.unwrap();
|
||||
set(&mut s, &[("C1", "redo")]);
|
||||
s.execute("edit.undo", json!({})).unwrap();
|
||||
let d = s.doc_mut().unwrap();
|
||||
std::sync::Arc::make_mut(&mut d.wb).protected_structure = protected;
|
||||
d.saved = d.wb.clone();
|
||||
let before = d.clone();
|
||||
let journal = s.journal.clone();
|
||||
let err = s
|
||||
.execute(
|
||||
"data.solver",
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": constraints, "method": method,
|
||||
"reports": reports, "keep": keep, "saveModel": save}),
|
||||
)
|
||||
.unwrap_err();
|
||||
assert!(err.to_string().contains(error), "{err}");
|
||||
let d = s.doc().unwrap();
|
||||
assert!(std::sync::Arc::ptr_eq(&d.wb, &before.wb), "{method}: keep={keep}, save={save}: {err}");
|
||||
assert!(!d.is_dirty());
|
||||
assert_eq!(d.revision, before.revision);
|
||||
assert_eq!(d.selection, before.selection);
|
||||
assert_eq!(d.sheet_selections, before.sheet_selections);
|
||||
for (after, before) in [(&d.undo, &before.undo), (&d.redo, &before.redo)] {
|
||||
assert_eq!(after.len(), before.len());
|
||||
for (a, b) in after.iter().zip(before) {
|
||||
assert!(std::sync::Arc::ptr_eq(&a.wb, &b.wb));
|
||||
assert_eq!((&a.label, &a.selection), (&b.label, &b.selection));
|
||||
}
|
||||
}
|
||||
assert_eq!(s.journal, journal);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn solver_reports_and_optional_solution_and_model_share_one_undo() {
|
||||
for (keep, save) in [(true, true), (false, true), (true, false), (false, false)] {
|
||||
let mut s = s();
|
||||
set(&mut s, &[("A1", "1"), ("B1", "=2*A1")]);
|
||||
let before = s.doc().unwrap().clone();
|
||||
let out = s
|
||||
.execute(
|
||||
"data.solver",
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": ["A1 <= 4"], "method": "simplex",
|
||||
"reports": ["answer"], "keep": keep, "saveModel": save}),
|
||||
)
|
||||
.unwrap();
|
||||
assert_eq!(out["status"], "optimal");
|
||||
assert_eq!(out["reports"], json!(["Answer Report 1"]));
|
||||
assert_eq!(out["model"]["objective"], "Sheet1!B1");
|
||||
assert_eq!(n(&s, "A1"), if keep { 4.0 } else { 1.0 });
|
||||
assert_eq!(saved(&s), if save { "solver_opt" } else { "" });
|
||||
assert_eq!(s.doc().unwrap().undo.len(), before.undo.len() + 1);
|
||||
assert_eq!(s.doc().unwrap().wb.active().unwrap().name, "Sheet1");
|
||||
let r = row_of(&s, "Answer Report 1", "$A$1") + 1;
|
||||
assert_eq!(at(&s, "Answer Report 1", &format!("E{r}")), Value::number(4.0));
|
||||
s.execute("edit.undo", json!({})).unwrap();
|
||||
assert!(std::sync::Arc::ptr_eq(&s.doc().unwrap().wb, &before.wb));
|
||||
s.execute("edit.redo", json!({})).unwrap();
|
||||
assert_eq!(s.doc().unwrap().wb.sheets.len(), 2);
|
||||
assert_eq!(n(&s, "A1"), if keep { 4.0 } else { 1.0 });
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn solver_reports_keep_row_autofit_on_the_model_sheet() {
|
||||
let mut s = s();
|
||||
set(&mut s, &[("A1", "1"), ("B1", "=2*A1")]);
|
||||
s.execute("home.columnWidth", json!({"cols": "A:A", "width": 30})).unwrap();
|
||||
s.execute("home.wrapText", json!({"range": "A1", "on": true})).unwrap();
|
||||
let before = s.doc().unwrap().wb.active().unwrap().row_height(0);
|
||||
s.execute(
|
||||
"data.solver",
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": ["A1 <= 1000000"], "method": "simplex", "reports": ["answer"]}),
|
||||
)
|
||||
.unwrap();
|
||||
let sh = s.doc().unwrap().wb.active().unwrap();
|
||||
assert_eq!(sh.name, "Sheet1");
|
||||
assert_eq!(sh.value(CellRef::new(0, 0)), Value::number(1_000_000.0));
|
||||
assert!(sh.row_height(0) > before, "the solved wrapped number must re-fit its row after the report shifts its sheet");
|
||||
s.execute("edit.undo", json!({})).unwrap();
|
||||
assert_eq!(s.doc().unwrap().wb.active().unwrap().row_height(0), before);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn solver_report_insertion_keeps_variable_edit_guards() {
|
||||
for array in [false, true] {
|
||||
let mut s = s();
|
||||
set(&mut s, &[("A2", "1"), ("B1", "=2*A2")]);
|
||||
let error = if array {
|
||||
s.execute("selection.set", json!({"range": "A1:A2"})).unwrap();
|
||||
s.execute("cell.set", json!({"input": "=1", "array": true})).unwrap();
|
||||
"part of an array"
|
||||
} else {
|
||||
s.execute("review.protectSheet", json!({})).unwrap();
|
||||
"protected sheet"
|
||||
};
|
||||
let before = s.doc().unwrap().clone();
|
||||
let err = s
|
||||
.execute(
|
||||
"data.solver",
|
||||
json!({"objective": "B1", "variables": "A2", "constraints": ["A2 <= 4"], "method": "simplex", "reports": ["answer"]}),
|
||||
)
|
||||
.unwrap_err();
|
||||
assert!(err.to_string().contains(error), "{err}");
|
||||
let d = s.doc().unwrap();
|
||||
assert!(std::sync::Arc::ptr_eq(&d.wb, &before.wb));
|
||||
assert_eq!(d.undo.len(), before.undo.len());
|
||||
assert_eq!(d.sheet_selections, before.sheet_selections);
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn limits_report_of_a_nonlinear_model() {
|
||||
// The largest rectangle with perimeter at most 20 (5 × 5): with the height held at 5, the
|
||||
// width ranges over 0..5, the area over 0..25.
|
||||
let mut s = s();
|
||||
set(&mut s, &[("A1", "1"), ("A2", "1"), ("B1", "=A1*A2"), ("B2", "=2*A1+2*A2")]);
|
||||
let r =
|
||||
s.execute("data.solver", json!({"objective": "B1", "variables": "A1:A2", "constraints": ["B2 <= 20"], "reports": ["limits"]})).unwrap();
|
||||
assert_eq!(r["reports"], json!(["Limits Report 1"]), "{r}");
|
||||
let l = "Limits Report 1";
|
||||
let r = row_of(&s, l, "$A$1") + 1;
|
||||
let got: Vec<f64> = ["E", "F", "G", "H"].iter().map(|c| at(&s, l, &format!("{c}{r}")).as_f64().unwrap()).collect();
|
||||
for (g, want) in got.iter().zip([0.0, 0.0, 5.0, 25.0]) {
|
||||
assert!((g - want).abs() < 1e-3, "{got:?}");
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn infeasible_unbounded_and_nonlinear_models_are_reported() {
|
||||
let mut s = s();
|
||||
set(&mut s, &[("A1", "1"), ("B1", "=2*A1")]);
|
||||
for method in ["simplex", "grg"] {
|
||||
let r = s
|
||||
.execute("data.solver", json!({"objective": "B1", "variables": "A1", "constraints": ["A1 >= 5", "B1 <= 6"], "method": method}))
|
||||
.unwrap();
|
||||
assert_eq!(r["status"], "infeasible", "{method}: {r}");
|
||||
assert_eq!(r["changed"], false);
|
||||
assert_eq!(n(&s, "A1"), 1.0, "an infeasible model leaves the cells alone");
|
||||
}
|
||||
let r = s.execute("data.solver", json!({"objective": "B1", "variables": "A1", "method": "simplex"})).unwrap();
|
||||
assert_eq!(r["status"], "unbounded");
|
||||
let r = s.execute("data.solver", json!({"objective": "B1", "variables": "A1", "method": "grg", "maxEvaluations": 5000})).unwrap();
|
||||
assert!(r["status"] == "unbounded" || r["status"] == "iterationLimit", "{r}");
|
||||
set(&mut s, &[("A1", "1"), ("C1", "=A1^2")]);
|
||||
let r = s.execute("data.solver", json!({"objective": "C1", "goal": "min", "variables": "A1", "method": "simplex"})).unwrap();
|
||||
assert_eq!(r["status"], "notLinear");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn hostile_models_are_refused_without_panicking() {
|
||||
let mut s = s();
|
||||
let r = s.execute("data.solver", json!({})).unwrap();
|
||||
assert!(r["model"].is_null());
|
||||
assert!(s.take_ui_requests().iter().any(|q| matches!(q, crate::UiRequest::Dialog(n, _) if n == "solver")));
|
||||
set(&mut s, &[("B1", "=SUM(A1:A1000)"), ("C1", "5")]);
|
||||
for p in [
|
||||
json!({"objective": "B1", "variables": "A1:A1000"}),
|
||||
json!({"objective": "B1", "variables": "A1:XFD1048576"}),
|
||||
json!({"objective": "C1", "variables": "A1"}),
|
||||
json!({"objective": "B1:B2", "variables": "A1"}),
|
||||
json!({"objective": "B1", "variables": "B1"}),
|
||||
json!({"objective": "B1", "variables": "A1", "goal": "sideways"}),
|
||||
json!({"objective": "B1", "variables": "A1", "goal": "value"}),
|
||||
json!({"objective": "B1", "variables": "A1", "method": "evolutionary"}),
|
||||
json!({"objective": "B1", "variables": "A1", "method": "annealing"}),
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": ["A1 ?? 3"]}),
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": "A1 <= 3"}),
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": ["A1:A3 <= C1:C2"]}),
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": ["C1 int"]}),
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": ["A1:A1048576 <= 1"]}),
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": vec![json!("A1 <= 1"); 1001]}),
|
||||
json!({"objective": "Nope!B1", "variables": "A1"}),
|
||||
] {
|
||||
assert!(s.execute("data.solver", p.clone()).is_err(), "{p}");
|
||||
}
|
||||
// Huge evaluation requests are capped, and a model erroring everywhere doesn't panic.
|
||||
set(&mut s, &[("D1", "=1/0+A1")]);
|
||||
let r = s.execute("data.solver", json!({"objective": "D1", "variables": "A1", "maxEvaluations": 1e300})).unwrap();
|
||||
assert_ne!(r["status"], "converged");
|
||||
}
|
||||
}
|
||||
mod tests;
|
||||
|
||||
@@ -0,0 +1,477 @@
|
||||
use gridcraft_core::{CellRef, Value};
|
||||
use serde_json::json;
|
||||
|
||||
use crate::Session;
|
||||
|
||||
fn s() -> Session {
|
||||
let mut s = Session::new();
|
||||
s.new_workbook();
|
||||
s
|
||||
}
|
||||
fn n(s: &Session, a: &str) -> f64 {
|
||||
let d = s.doc().unwrap();
|
||||
d.wb.active().unwrap().value(CellRef::parse(a).unwrap()).as_f64().unwrap_or(f64::NAN)
|
||||
}
|
||||
/// The first saved-model name scoped to the active sheet.
|
||||
fn saved(s: &Session) -> String {
|
||||
let d = s.doc().unwrap();
|
||||
d.wb.names.iter().find(|n| n.scope == Some(d.wb.active_sheet())).map(|n| n.name.clone()).unwrap_or_default()
|
||||
}
|
||||
fn set(s: &mut Session, cells: &[(&str, &str)]) {
|
||||
for (c, v) in cells {
|
||||
s.execute("cell.set", json!({"cell": c, "input": v})).unwrap();
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn simplex_solves_the_wyndor_glass_lp() {
|
||||
// Hillier & Lieberman's Wyndor Glass problem: max 3x + 5y, x ≤ 4, 2y ≤ 12, 3x + 2y ≤ 18
|
||||
// → x = 2, y = 6, Z = 36.
|
||||
let mut s = s();
|
||||
set(&mut s, &[("A1", "0"), ("A2", "0"), ("B1", "=3*A1+5*A2"), ("B2", "=2*A2"), ("B3", "=3*A1+2*A2")]);
|
||||
let r = s
|
||||
.execute(
|
||||
"data.solver",
|
||||
json!({"objective": "B1", "goal": "max", "variables": "A1:A2", "constraints": ["A1 <= 4", "B2 <= 12", {"lhs": "B3", "op": "<=", "rhs": 18}], "method": "simplex"}),
|
||||
)
|
||||
.unwrap();
|
||||
assert_eq!(r["status"], "optimal", "{r}");
|
||||
assert!((n(&s, "A1") - 2.0).abs() < 1e-9 && (n(&s, "A2") - 6.0).abs() < 1e-9);
|
||||
assert!((n(&s, "B1") - 36.0).abs() < 1e-9);
|
||||
// The model is saved as hidden names, survives XLSX and solves again from them.
|
||||
let names: Vec<String> = s.doc().unwrap().wb.names.iter().map(|n| n.name.clone()).collect();
|
||||
assert!(names.iter().any(|n| n == "solver_opt") && names.iter().any(|n| n == "solver_lhs3"));
|
||||
let b64 = s.execute("file.saveBytes", json!({"format": "xlsx"})).unwrap()["base64"].as_str().unwrap().to_string();
|
||||
s.execute("file.open", json!({"name": "m.xlsx", "base64": b64})).unwrap();
|
||||
set(&mut s, &[("A1", "0"), ("A2", "0")]);
|
||||
let m = s.execute("data.solver", json!({})).unwrap();
|
||||
assert_eq!(m["model"]["objective"], "B1");
|
||||
assert_eq!(m["model"]["method"], "simplex");
|
||||
let r = s.execute("data.solver", json!({"saved": true})).unwrap();
|
||||
assert_eq!(r["status"], "optimal");
|
||||
assert!((n(&s, "B1") - 36.0).abs() < 1e-9);
|
||||
// Minimise with keep: false leaves the cells alone.
|
||||
set(&mut s, &[("A1", "1"), ("A2", "1")]);
|
||||
let r = s.execute("data.solver", json!({"saved": true, "goal": "min", "keep": false})).unwrap();
|
||||
assert_eq!(r["objective"], 0.0);
|
||||
assert_eq!((n(&s, "A1"), n(&s, "A2")), (1.0, 1.0));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn integer_and_binary_constraints_use_branch_and_bound() {
|
||||
// max 5x + 4y, 6x + 4y ≤ 24, x + 2y ≤ 6: the LP optimum (3, 1.5) = 21; integers give
|
||||
// (4, 0) = 20.
|
||||
let mut s = s();
|
||||
set(&mut s, &[("B1", "=5*A1+4*A2"), ("B2", "=6*A1+4*A2"), ("B3", "=A1+2*A2")]);
|
||||
let base = json!({"objective": "B1", "variables": "A1:A2", "constraints": ["B2 <= 24", "B3 <= 6"], "method": "simplex"});
|
||||
let r = s.execute("data.solver", base.clone()).unwrap();
|
||||
assert!((r["objective"].as_f64().unwrap() - 21.0).abs() < 1e-9);
|
||||
let mut p = base.clone();
|
||||
p["constraints"].as_array_mut().unwrap().push(json!("A1:A2 int"));
|
||||
let r = s.execute("data.solver", p).unwrap();
|
||||
assert_eq!(r["status"], "optimal");
|
||||
assert_eq!((n(&s, "A1"), n(&s, "A2"), n(&s, "B1")), (4.0, 0.0, 20.0));
|
||||
// 0/1 knapsack: values 10, 13, 7, weights 5, 6, 4, capacity 10 → items 2 and 3 (20).
|
||||
set(&mut s, &[("D1", "=10*C1+13*C2+7*C3"), ("D2", "=5*C1+6*C2+4*C3")]);
|
||||
let r = s
|
||||
.execute("data.solver", json!({"objective": "D1", "variables": "C1:C3", "constraints": ["D2 <= 10", "C1:C3 bin"], "method": "simplex"}))
|
||||
.unwrap();
|
||||
assert_eq!(r["status"], "optimal");
|
||||
assert_eq!((n(&s, "C1"), n(&s, "C2"), n(&s, "C3"), n(&s, "D1")), (0.0, 1.0, 1.0, 20.0));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn grg_finds_smooth_optima() {
|
||||
// Largest rectangle with perimeter at most 20: a 5 × 5 square, area 25.
|
||||
let mut s = s();
|
||||
set(&mut s, &[("A1", "1"), ("A2", "1"), ("B1", "=A1*A2"), ("B2", "=2*A1+2*A2")]);
|
||||
let r = s.execute("data.solver", json!({"objective": "B1", "variables": "A1:A2", "constraints": ["B2 <= 20"]})).unwrap();
|
||||
assert_eq!(r["status"], "converged", "{r}");
|
||||
assert!((n(&s, "A1") - 5.0).abs() < 1e-3 && (n(&s, "A2") - 5.0).abs() < 1e-3, "{r}");
|
||||
// Unconstrained minimum of (x − 3)² + (y + 1)² at (3, −1) once negatives are allowed.
|
||||
set(&mut s, &[("C1", "0"), ("C2", "0"), ("D1", "=(C1-3)^2+(C2+1)^2")]);
|
||||
s.execute("data.solver", json!({"objective": "D1", "goal": "min", "variables": "C1:C2", "nonNegative": false})).unwrap();
|
||||
assert!((n(&s, "C1") - 3.0).abs() < 1e-4 && (n(&s, "C2") + 1.0).abs() < 1e-4);
|
||||
// Value Of: x³ = 8 → x = 2.
|
||||
set(&mut s, &[("E1", "1"), ("F1", "=E1^3")]);
|
||||
s.execute("data.solver", json!({"objective": "F1", "goal": "value", "value": 8, "variables": "E1"})).unwrap();
|
||||
assert!((n(&s, "E1") - 2.0).abs() < 1e-4);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn evolutionary_finds_the_global_minimum_of_non_smooth_and_multimodal_models() {
|
||||
let mut s = s();
|
||||
// |x − 3| + |y + 2| has a kink at its minimum (3, −2).
|
||||
set(&mut s, &[("A1", "0"), ("A2", "0"), ("B1", "=ABS(A1-3)+ABS(A2+2)")]);
|
||||
let p =
|
||||
json!({"objective": "B1", "goal": "min", "variables": "A1:A2", "constraints": ["A1:A2 >= -10", "A1:A2 <= 10"], "method": "evolutionary"});
|
||||
let r = s.execute("data.solver", p.clone()).unwrap();
|
||||
assert!(r["status"] == "converged" || r["status"] == "cannotImprove", "{r}");
|
||||
assert!((n(&s, "A1") - 3.0).abs() < 1e-6 && (n(&s, "A2") + 2.0).abs() < 1e-6, "{r}");
|
||||
// The same seed repeats the run exactly.
|
||||
set(&mut s, &[("A1", "0"), ("A2", "0")]);
|
||||
let again = s.execute("data.solver", p).unwrap();
|
||||
assert_eq!(again["values"], r["values"]);
|
||||
assert_eq!(again["evaluations"], r["evaluations"]);
|
||||
// Rastrigin's function 20 + Σ (x² − 10 cos 2πx) on [−5.12, 5.12]² has its global minimum 0
|
||||
// at the origin among many local minima; GRG from (3.3, −2.7) stops at a local one.
|
||||
set(&mut s, &[("C1", "3.3"), ("C2", "-2.7"), ("D1", "=20+C1^2-10*COS(2*PI()*C1)+C2^2-10*COS(2*PI()*C2)")]);
|
||||
let base = json!({"objective": "D1", "goal": "min", "variables": "C1:C2", "constraints": ["C1:C2 >= -5.12", "C1:C2 <= 5.12"]});
|
||||
s.execute("data.solver", base.clone()).unwrap();
|
||||
assert!(n(&s, "D1") > 0.5, "GRG is local: {}", n(&s, "D1"));
|
||||
set(&mut s, &[("C1", "3.3"), ("C2", "-2.7")]);
|
||||
let mut p = base.clone();
|
||||
p["method"] = json!("evolutionary");
|
||||
let r = s.execute("data.solver", p).unwrap();
|
||||
assert!(n(&s, "D1") < 1e-8 && n(&s, "C1").abs() < 1e-5 && n(&s, "C2").abs() < 1e-5, "{r}");
|
||||
// A stepped model: ROUND makes it flat almost everywhere; the minimum is at 7.2.
|
||||
set(&mut s, &[("E1", "0"), ("F1", "=ABS(ROUND(E1,0)-7)+ABS(E1-7.2)/100")]);
|
||||
s.execute("data.solver", json!({"objective": "F1", "goal": "min", "variables": "E1", "constraints": ["E1 <= 20"], "method": "evolutionary"}))
|
||||
.unwrap();
|
||||
assert!((n(&s, "E1") - 7.2).abs() < 1e-6, "{}", n(&s, "E1"));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn evolutionary_handles_integers_bounds_and_the_saved_model() {
|
||||
let mut s = s();
|
||||
// The 0/1 knapsack of the branch-and-bound test: items 2 and 3, value 20.
|
||||
set(&mut s, &[("D1", "=10*C1+13*C2+7*C3"), ("D2", "=5*C1+6*C2+4*C3")]);
|
||||
let p = json!({"objective": "D1", "variables": "C1:C3", "constraints": ["D2 <= 10", "C1:C3 bin"], "method": "evolutionary", "populationSize": 30, "randomSeed": 7});
|
||||
let r = s.execute("data.solver", p).unwrap();
|
||||
assert!(r["status"] == "converged" || r["status"] == "cannotImprove", "{r}");
|
||||
assert_eq!((n(&s, "C1"), n(&s, "C2"), n(&s, "C3"), n(&s, "D1")), (0.0, 1.0, 1.0, 20.0));
|
||||
// The method and its options are saved, survive XLSX and solve again.
|
||||
let b64 = s.execute("file.saveBytes", json!({"format": "xlsx"})).unwrap()["base64"].as_str().unwrap().to_string();
|
||||
s.execute("file.open", json!({"name": "e.xlsx", "base64": b64})).unwrap();
|
||||
let m = s.execute("data.solver", json!({})).unwrap();
|
||||
assert_eq!(m["model"]["method"], "evolutionary");
|
||||
assert_eq!((m["model"]["populationSize"].as_f64(), m["model"]["randomSeed"].as_f64()), (Some(30.0), Some(7.0)));
|
||||
set(&mut s, &[("C1", "0"), ("C2", "0"), ("C3", "0")]);
|
||||
s.execute("data.solver", json!({"saved": true})).unwrap();
|
||||
assert_eq!(n(&s, "D1"), 20.0);
|
||||
// Integer constraints: max x + y with x + 2y ≤ 7 on integers in [0, 10] → (7, 0).
|
||||
set(&mut s, &[("A1", "0"), ("A2", "0"), ("B1", "=A1+A2"), ("B2", "=A1+2*A2")]);
|
||||
let r = s
|
||||
.execute(
|
||||
"data.solver",
|
||||
json!({"objective": "B1", "variables": "A1:A2", "constraints": ["B2 <= 7", "A1:A2 <= 10", "A1:A2 int"], "method": "evolutionary"}),
|
||||
)
|
||||
.unwrap();
|
||||
assert_eq!((n(&s, "A1"), n(&s, "A2")), (7.0, 0.0), "{r}");
|
||||
// Every variable needs bounds unless requireBounds is off; then it searches around the start.
|
||||
set(&mut s, &[("E1", "1"), ("F1", "=ABS(E1-4)")]);
|
||||
let p = json!({"objective": "F1", "goal": "min", "variables": "E1", "method": "evolutionary"});
|
||||
assert!(s.execute("data.solver", p.clone()).is_err());
|
||||
let mut p = p;
|
||||
p["requireBounds"] = json!(false);
|
||||
s.execute("data.solver", p).unwrap();
|
||||
assert!((n(&s, "E1") - 4.0).abs() < 1e-6);
|
||||
// Infeasible constraints and a tiny budget are reported without changing the cells.
|
||||
set(&mut s, &[("E1", "1")]);
|
||||
let r = s
|
||||
.execute("data.solver", json!({"objective": "F1", "variables": "E1", "constraints": ["E1 <= 3", "F1 >= 10"], "method": "evolutionary"}))
|
||||
.unwrap();
|
||||
assert_eq!(r["status"], "infeasible", "{r}");
|
||||
let r = s
|
||||
.execute(
|
||||
"data.solver",
|
||||
json!({"objective": "F1", "variables": "E1", "constraints": ["E1 <= 3"], "method": "evolutionary", "maxEvaluations": 3}),
|
||||
)
|
||||
.unwrap();
|
||||
assert_eq!(r["status"], "iterationLimit", "{r}");
|
||||
assert_eq!(n(&s, "E1"), 1.0);
|
||||
}
|
||||
|
||||
/// Text or number at `a1` on sheet `name`.
|
||||
fn at(s: &Session, name: &str, a1: &str) -> Value {
|
||||
let d = s.doc().unwrap();
|
||||
d.wb.sheet(d.wb.sheet_index(name).unwrap()).unwrap().value(CellRef::parse(a1).unwrap())
|
||||
}
|
||||
|
||||
/// The row of the first cell holding `text` on sheet `name`.
|
||||
fn row_of(s: &Session, name: &str, text: &str) -> u32 {
|
||||
let d = s.doc().unwrap();
|
||||
let sh = d.wb.sheet(d.wb.sheet_index(name).unwrap()).unwrap();
|
||||
(0..60).find(|r| (0..8).any(|c| sh.value(CellRef::new(*r, c)) == Value::text(text))).unwrap()
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn answer_and_limits_reports_describe_the_wyndor_glass_solution() {
|
||||
// Wyndor Glass with labels: doors and windows across, the three plants' hours down.
|
||||
let mut s = s();
|
||||
s.execute(
|
||||
"range.setValues",
|
||||
json!({"range": "A1", "values": [[null, "Doors", "Windows", "Used", "Available"], ["Batches", 0, 0, null, null], ["Plant 1", 1, 0, null, 4], ["Plant 2", 0, 2, null, 12], ["Plant 3", 3, 2, null, 18], ["Profit", 3, 5, null, null]]}),
|
||||
)
|
||||
.unwrap();
|
||||
for r in 3..=6 {
|
||||
set(&mut s, &[(&format!("D{r}"), &format!("=SUMPRODUCT(B{r}:C{r},$B$2:$C$2)"))]);
|
||||
}
|
||||
let solved = s
|
||||
.execute(
|
||||
"data.solver",
|
||||
json!({"objective": "D6", "variables": "B2:C2", "constraints": ["D3:D5 <= E3:E5"], "method": "simplex", "reports": ["answer", "limits"]}),
|
||||
)
|
||||
.unwrap();
|
||||
assert_eq!(solved["status"], "optimal", "{solved}");
|
||||
assert_eq!(solved["reports"], json!(["Answer Report 1", "Limits Report 1"]));
|
||||
assert_eq!(solved["original"], json!({"B2": 0.0, "C2": 0.0}));
|
||||
let d = s.doc().unwrap();
|
||||
let names: Vec<&str> = d.wb.sheets.iter().map(|x| x.name.as_str()).collect();
|
||||
assert_eq!(names, ["Answer Report 1", "Limits Report 1", "Sheet1"]);
|
||||
assert_eq!(d.wb.active().unwrap().name, "Sheet1", "the model's sheet stays active");
|
||||
assert_eq!(saved(&s), "solver_opt", "the saved model follows its sheet");
|
||||
let a = "Answer Report 1";
|
||||
assert_eq!(at(&s, a, "A1"), Value::text("GridCraft Answer Report"));
|
||||
// Objective: $D$6 "Profit Used", from 0 to 36.
|
||||
let r = row_of(&s, a, "$D$6");
|
||||
assert_eq!(at(&s, a, &format!("C{}", r + 1)), Value::text("Profit Used"));
|
||||
assert_eq!((at(&s, a, &format!("D{}", r + 1)), at(&s, a, &format!("E{}", r + 1))), (Value::number(0.0), Value::number(36.0)));
|
||||
// Variables: doors 0 → 2, windows 0 → 6, continuous.
|
||||
let r = row_of(&s, a, "$B$2") + 1;
|
||||
assert_eq!(at(&s, a, &format!("C{r}")), Value::text("Batches Doors"));
|
||||
assert_eq!(at(&s, a, &format!("E{r}")), Value::number(2.0));
|
||||
assert_eq!(at(&s, a, &format!("F{r}")), Value::text("Contin"));
|
||||
assert_eq!(at(&s, a, &format!("E{}", r + 1)), Value::number(6.0));
|
||||
// Constraints: plant 1 has 2 hours to spare; plants 2 and 3 are binding.
|
||||
let r = row_of(&s, a, "$D$3") + 1;
|
||||
assert_eq!(at(&s, a, &format!("E{r}")), Value::text("$D$3<=$E$3"));
|
||||
assert_eq!((at(&s, a, &format!("F{r}")), at(&s, a, &format!("G{r}"))), (Value::text("Not Binding"), Value::number(2.0)));
|
||||
for k in 1..=2 {
|
||||
assert_eq!((at(&s, a, &format!("F{}", r + k)), at(&s, a, &format!("G{}", r + k))), (Value::text("Binding"), Value::number(0.0)));
|
||||
}
|
||||
// Limits with the other variable held: doors 0..2 (profit 30..36), windows 0..6 (6..36).
|
||||
let l = "Limits Report 1";
|
||||
let r = row_of(&s, l, "$B$2") + 1;
|
||||
let row = |r: u32| ["D", "E", "F", "G", "H"].map(|c| at(&s, l, &format!("{c}{r}")).as_f64().unwrap());
|
||||
assert_eq!(row(r), [2.0, 0.0, 30.0, 2.0, 36.0]);
|
||||
assert_eq!(row(r + 1), [6.0, 0.0, 6.0, 6.0, 36.0]);
|
||||
// data.solverReport writes reports from the saved model and a given solution.
|
||||
let out =
|
||||
s.execute("data.solverReport", json!({"reports": ["answer"], "values": {"B2": 2, "C2": 6}, "original": {"B2": 1, "C2": 1}})).unwrap();
|
||||
assert_eq!(out["sheets"], json!(["Answer Report 2"]));
|
||||
let r = row_of(&s, "Answer Report 2", "$D$6") + 1;
|
||||
assert_eq!(at(&s, "Answer Report 2", &format!("D{r}")), Value::number(8.0));
|
||||
// Undo removes the reports and keeps the solution; refused requests write nothing.
|
||||
s.execute("edit.undo", json!({})).unwrap();
|
||||
assert_eq!(s.doc().unwrap().wb.sheets.len(), 3);
|
||||
for p in [
|
||||
json!({}),
|
||||
json!({"reports": []}),
|
||||
json!({"reports": "answer"}),
|
||||
json!({"reports": ["population"]}),
|
||||
json!({"reports": ["answer"], "values": {"Z9": 1}}),
|
||||
json!({"reports": ["answer"], "values": {"B2": "x"}}),
|
||||
json!({"reports": ["limits"], "constraints": ["D3:D5 <= E3:E5", "B2:C2 int"]}),
|
||||
json!({"reports": ["limits"], "method": "evolutionary", "constraints": ["D3:D5 <= E3:E5", "B2:C2 <= 10"]}),
|
||||
] {
|
||||
assert!(s.execute("data.solverReport", p.clone()).is_err(), "{p}");
|
||||
}
|
||||
assert_eq!(s.doc().unwrap().wb.sheets.len(), 3);
|
||||
// With the solve, its reports and the saved model undone (one step), the result still
|
||||
// describes the solution.
|
||||
s.execute("edit.undo", json!({})).unwrap();
|
||||
assert_eq!((s.doc().unwrap().wb.sheets.len(), n(&s, "B2")), (1, 0.0));
|
||||
let mut p = solved.clone();
|
||||
p["reports"] = json!(["answer"]);
|
||||
assert_eq!(s.execute("data.solverReport", p).unwrap()["sheets"], json!(["Answer Report 1"]));
|
||||
let r = row_of(&s, "Answer Report 1", "$B$2") + 1;
|
||||
assert_eq!(at(&s, "Answer Report 1", &format!("E{r}")), Value::number(2.0));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn refused_solver_reports_preserve_the_document_and_history() {
|
||||
for (protected, method, constraints, reports, error) in [
|
||||
(true, "simplex", json!(["A1 <= 4"]), json!(["answer"]), "workbook is protected"),
|
||||
(false, "simplex", json!(["A1 <= 4", "A1 int"]), json!(["answer", "limits"]), "integer or binary"),
|
||||
(false, "evolutionary", json!(["A1 <= 4"]), json!(["answer", "limits"]), "Simplex LP and GRG"),
|
||||
] {
|
||||
for (keep, save) in [(true, true), (false, true), (true, false), (false, false)] {
|
||||
let mut s = s();
|
||||
set(&mut s, &[("A1", "1"), ("B1", "=2*A1")]);
|
||||
s.execute(
|
||||
"data.solver",
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": ["A1 <= 2"], "method": "simplex", "keep": false}),
|
||||
)
|
||||
.unwrap();
|
||||
set(&mut s, &[("C1", "redo")]);
|
||||
s.execute("edit.undo", json!({})).unwrap();
|
||||
let d = s.doc_mut().unwrap();
|
||||
std::sync::Arc::make_mut(&mut d.wb).protected_structure = protected;
|
||||
d.saved = d.wb.clone();
|
||||
let before = d.clone();
|
||||
let journal = s.journal.clone();
|
||||
let err = s
|
||||
.execute(
|
||||
"data.solver",
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": constraints, "method": method,
|
||||
"reports": reports, "keep": keep, "saveModel": save}),
|
||||
)
|
||||
.unwrap_err();
|
||||
assert!(err.to_string().contains(error), "{err}");
|
||||
let d = s.doc().unwrap();
|
||||
assert!(std::sync::Arc::ptr_eq(&d.wb, &before.wb), "{method}: keep={keep}, save={save}: {err}");
|
||||
assert!(!d.is_dirty());
|
||||
assert_eq!(d.revision, before.revision);
|
||||
assert_eq!(d.selection, before.selection);
|
||||
assert_eq!(d.sheet_selections, before.sheet_selections);
|
||||
for (after, before) in [(&d.undo, &before.undo), (&d.redo, &before.redo)] {
|
||||
assert_eq!(after.len(), before.len());
|
||||
for (a, b) in after.iter().zip(before) {
|
||||
assert!(std::sync::Arc::ptr_eq(&a.wb, &b.wb));
|
||||
assert_eq!((&a.label, &a.selection), (&b.label, &b.selection));
|
||||
}
|
||||
}
|
||||
assert_eq!(s.journal, journal);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn solver_reports_and_optional_solution_and_model_share_one_undo() {
|
||||
for (keep, save) in [(true, true), (false, true), (true, false), (false, false)] {
|
||||
let mut s = s();
|
||||
set(&mut s, &[("A1", "1"), ("B1", "=2*A1")]);
|
||||
let before = s.doc().unwrap().clone();
|
||||
let out = s
|
||||
.execute(
|
||||
"data.solver",
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": ["A1 <= 4"], "method": "simplex",
|
||||
"reports": ["answer"], "keep": keep, "saveModel": save}),
|
||||
)
|
||||
.unwrap();
|
||||
assert_eq!(out["status"], "optimal");
|
||||
assert_eq!(out["reports"], json!(["Answer Report 1"]));
|
||||
assert_eq!(out["model"]["objective"], "Sheet1!B1");
|
||||
assert_eq!(n(&s, "A1"), if keep { 4.0 } else { 1.0 });
|
||||
assert_eq!(saved(&s), if save { "solver_opt" } else { "" });
|
||||
assert_eq!(s.doc().unwrap().undo.len(), before.undo.len() + 1);
|
||||
assert_eq!(s.doc().unwrap().wb.active().unwrap().name, "Sheet1");
|
||||
let r = row_of(&s, "Answer Report 1", "$A$1") + 1;
|
||||
assert_eq!(at(&s, "Answer Report 1", &format!("E{r}")), Value::number(4.0));
|
||||
s.execute("edit.undo", json!({})).unwrap();
|
||||
assert!(std::sync::Arc::ptr_eq(&s.doc().unwrap().wb, &before.wb));
|
||||
s.execute("edit.redo", json!({})).unwrap();
|
||||
assert_eq!(s.doc().unwrap().wb.sheets.len(), 2);
|
||||
assert_eq!(n(&s, "A1"), if keep { 4.0 } else { 1.0 });
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn solver_reports_keep_row_autofit_on_the_model_sheet() {
|
||||
let mut s = s();
|
||||
set(&mut s, &[("A1", "1"), ("B1", "=2*A1")]);
|
||||
s.execute("home.columnWidth", json!({"cols": "A:A", "width": 30})).unwrap();
|
||||
s.execute("home.wrapText", json!({"range": "A1", "on": true})).unwrap();
|
||||
let before = s.doc().unwrap().wb.active().unwrap().row_height(0);
|
||||
s.execute(
|
||||
"data.solver",
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": ["A1 <= 1000000"], "method": "simplex", "reports": ["answer"]}),
|
||||
)
|
||||
.unwrap();
|
||||
let sh = s.doc().unwrap().wb.active().unwrap();
|
||||
assert_eq!(sh.name, "Sheet1");
|
||||
assert_eq!(sh.value(CellRef::new(0, 0)), Value::number(1_000_000.0));
|
||||
assert!(sh.row_height(0) > before, "the solved wrapped number must re-fit its row after the report shifts its sheet");
|
||||
s.execute("edit.undo", json!({})).unwrap();
|
||||
assert_eq!(s.doc().unwrap().wb.active().unwrap().row_height(0), before);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn solver_report_insertion_keeps_variable_edit_guards() {
|
||||
for array in [false, true] {
|
||||
let mut s = s();
|
||||
set(&mut s, &[("A2", "1"), ("B1", "=2*A2")]);
|
||||
let error = if array {
|
||||
s.execute("selection.set", json!({"range": "A1:A2"})).unwrap();
|
||||
s.execute("cell.set", json!({"input": "=1", "array": true})).unwrap();
|
||||
"part of an array"
|
||||
} else {
|
||||
s.execute("review.protectSheet", json!({})).unwrap();
|
||||
"protected sheet"
|
||||
};
|
||||
let before = s.doc().unwrap().clone();
|
||||
let err = s
|
||||
.execute(
|
||||
"data.solver",
|
||||
json!({"objective": "B1", "variables": "A2", "constraints": ["A2 <= 4"], "method": "simplex", "reports": ["answer"]}),
|
||||
)
|
||||
.unwrap_err();
|
||||
assert!(err.to_string().contains(error), "{err}");
|
||||
let d = s.doc().unwrap();
|
||||
assert!(std::sync::Arc::ptr_eq(&d.wb, &before.wb));
|
||||
assert_eq!(d.undo.len(), before.undo.len());
|
||||
assert_eq!(d.sheet_selections, before.sheet_selections);
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn limits_report_of_a_nonlinear_model() {
|
||||
// The largest rectangle with perimeter at most 20 (5 × 5): with the height held at 5, the
|
||||
// width ranges over 0..5, the area over 0..25.
|
||||
let mut s = s();
|
||||
set(&mut s, &[("A1", "1"), ("A2", "1"), ("B1", "=A1*A2"), ("B2", "=2*A1+2*A2")]);
|
||||
let r =
|
||||
s.execute("data.solver", json!({"objective": "B1", "variables": "A1:A2", "constraints": ["B2 <= 20"], "reports": ["limits"]})).unwrap();
|
||||
assert_eq!(r["reports"], json!(["Limits Report 1"]), "{r}");
|
||||
let l = "Limits Report 1";
|
||||
let r = row_of(&s, l, "$A$1") + 1;
|
||||
let got: Vec<f64> = ["E", "F", "G", "H"].iter().map(|c| at(&s, l, &format!("{c}{r}")).as_f64().unwrap()).collect();
|
||||
for (g, want) in got.iter().zip([0.0, 0.0, 5.0, 25.0]) {
|
||||
assert!((g - want).abs() < 1e-3, "{got:?}");
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn infeasible_unbounded_and_nonlinear_models_are_reported() {
|
||||
let mut s = s();
|
||||
set(&mut s, &[("A1", "1"), ("B1", "=2*A1")]);
|
||||
for method in ["simplex", "grg"] {
|
||||
let r = s
|
||||
.execute("data.solver", json!({"objective": "B1", "variables": "A1", "constraints": ["A1 >= 5", "B1 <= 6"], "method": method}))
|
||||
.unwrap();
|
||||
assert_eq!(r["status"], "infeasible", "{method}: {r}");
|
||||
assert_eq!(r["changed"], false);
|
||||
assert_eq!(n(&s, "A1"), 1.0, "an infeasible model leaves the cells alone");
|
||||
}
|
||||
let r = s.execute("data.solver", json!({"objective": "B1", "variables": "A1", "method": "simplex"})).unwrap();
|
||||
assert_eq!(r["status"], "unbounded");
|
||||
let r = s.execute("data.solver", json!({"objective": "B1", "variables": "A1", "method": "grg", "maxEvaluations": 5000})).unwrap();
|
||||
assert!(r["status"] == "unbounded" || r["status"] == "iterationLimit", "{r}");
|
||||
set(&mut s, &[("A1", "1"), ("C1", "=A1^2")]);
|
||||
let r = s.execute("data.solver", json!({"objective": "C1", "goal": "min", "variables": "A1", "method": "simplex"})).unwrap();
|
||||
assert_eq!(r["status"], "notLinear");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn hostile_models_are_refused_without_panicking() {
|
||||
let mut s = s();
|
||||
let r = s.execute("data.solver", json!({})).unwrap();
|
||||
assert!(r["model"].is_null());
|
||||
assert!(s.take_ui_requests().iter().any(|q| matches!(q, crate::UiRequest::Dialog(n, _) if n == "solver")));
|
||||
set(&mut s, &[("B1", "=SUM(A1:A1000)"), ("C1", "5")]);
|
||||
for p in [
|
||||
json!({"objective": "B1", "variables": "A1:A1000"}),
|
||||
json!({"objective": "B1", "variables": "A1:XFD1048576"}),
|
||||
json!({"objective": "C1", "variables": "A1"}),
|
||||
json!({"objective": "B1:B2", "variables": "A1"}),
|
||||
json!({"objective": "B1", "variables": "B1"}),
|
||||
json!({"objective": "B1", "variables": "A1", "goal": "sideways"}),
|
||||
json!({"objective": "B1", "variables": "A1", "goal": "value"}),
|
||||
json!({"objective": "B1", "variables": "A1", "method": "evolutionary"}),
|
||||
json!({"objective": "B1", "variables": "A1", "method": "annealing"}),
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": ["A1 ?? 3"]}),
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": "A1 <= 3"}),
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": ["A1:A3 <= C1:C2"]}),
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": ["C1 int"]}),
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": ["A1:A1048576 <= 1"]}),
|
||||
json!({"objective": "B1", "variables": "A1", "constraints": vec![json!("A1 <= 1"); 1001]}),
|
||||
json!({"objective": "Nope!B1", "variables": "A1"}),
|
||||
] {
|
||||
assert!(s.execute("data.solver", p.clone()).is_err(), "{p}");
|
||||
}
|
||||
// Huge evaluation requests are capped, and a model erroring everywhere doesn't panic.
|
||||
set(&mut s, &[("D1", "=1/0+A1")]);
|
||||
let r = s.execute("data.solver", json!({"objective": "D1", "variables": "A1", "maxEvaluations": 1e300})).unwrap();
|
||||
assert_ne!(r["status"], "converged");
|
||||
}
|
||||
Reference in New Issue
Block a user