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PranavandFredApps
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* Data: Solver Load/Save Model and Reset All
data.solverSaveModel writes a model (the sheet's saved model, or one
given as data.solver params) down a column of its sheet as formulas:
the objective and goal (=MAX(...), =MIN(...) or =cell=value), the
variable cells (=COUNT(...)), one =AND(relation) per constraint, which
shows TRUE while the constraint holds, and the method and its options
as an array constant. It refuses a range that overlaps the model's
cells or runs off the sheet.
data.solverLoadModel reads such a range (or reads down from its first
cell), checks the model and makes it the active sheet's model.
data.solverReset (Reset All) removes the active sheet's model. Each is
one undo step.
The Solver Parameters dialog has Reset All and Load/Save buttons; the
dialog can also be opened with fields that go over the saved model.
* Data: Solver Reset All also clears a model read from workbook-level names
A sheet's Solver model can come from workbook-level names, which every
sheet without a model of its own reads. Reset All removed only the
sheet-level names, so such a model stayed and the dialog showed it
again.
Removing the workbook-level names would change every other sheet that
reads them. Reset All instead leaves them in place and writes an empty
sheet-level solver_opt over them on the active sheet only; the result
says masked: true. saved_model now reads a sheet's own names when the
sheet has a solver_opt, and the workbook-level names only otherwise,
never a mix of both, and treats an empty solver_opt as no model. The
mask survives XLSX and is replaced when a model is saved on the sheet.
* Data: Solver Save Model clears the rest of a longer model saved at the same cell
Saving a model over a longer one saved at the same cell left the old
model's last rows on the sheet, so Load Model from that cell read the new
options row followed by stale constraint rows and refused the range.
Save Model now clears what is left of a model saved there before (only
when those cells hold a complete model written by Save Model, and never
the new model's own cells), keeping the cells' formatting, in the same
undo step. Load Model reading down from one cell also stops at the
options row, so formulas just below a saved model no longer break it.
* Data: Solver Load Model keeps the Evolutionary convergence and generations
Save Model writes Convergence and the generations without improvement in
its options row and Load Model reads them, but the sheet's saved model
(hidden names) did not hold them, so after Load Model, or any solve,
they fell back to their defaults. The saved model now keeps them for the
Evolutionary method: Convergence as solver_cvg, which means the same in
Excel, and the generations as gridcraft_solver_stall, because Excel's
solver_mni is a time in seconds. Saving a model again and Reset All
remove the GridCraft name with the solver_* names.
* Data: Solver Load Model refuses a range with a gap
Load Model from a range of several cells kept only the cells that hold a
formula, so the rows below a cell without one moved up. A constraint cell
overwritten by a constant gave a model without that constraint, and an
empty cell before the options row gave the default options, both without
an error. Load Model now refuses a range in which a cell before the last
formula holds no formula, and names that cell. Empty cells after the
model are still allowed.
* Data: Solver removes only its own names when it saves or resets a model
Saving a model (by a solve or Load Model) and Reset All removed every
name of the sheet that starts with solver_, so a user's own name such as
solver_budget was deleted with the model. They now remove only the
Solver's names: the ones Excel's Solver writes (solver_opt, solver_adj,
solver_lhs1, solver_rel1, solver_rhs1 and so on) and GridCraft's own.
The names are matched by name rather than by the hidden flag, so a model
whose names lost that flag is still replaced in full.
* Data: Solver Save Model refuses a place where the options cannot spill
The options row that Save Model writes is an array constant of eight
values, which spills into the seven cells to the right of its first
cell. Content in any of those cells blocked the spill and the options
cell showed #SPILL!. Save Model now checks the whole spill range before
it writes anything and refuses, naming the cell, when a cell there holds
content or another formula's spilled values or is a cell of the model,
when merged cells or a table meet the row (a dynamic array cannot spill
into a table), or when the range runs past the last column. It also
refuses a place where the model's column would cover another formula's
spilled values, which that formula would lose to #SPILL!. The options of
a model saved at the same cell before may be replaced, as before.
* Data: Solver Reset All and Load Model drop the old model's options
Reset All cleared the model fields of the Solver Parameters form but
kept the Evolutionary options (Convergence, Mutation Rate, Population
Size, Random Seed, generations without improvement and Require Bounds),
and Load Model kept any of them that the loaded model omits, such as all
of them for a GRG Nonlinear or Simplex LP model. A new Evolutionary model
then solved with the old options, for example with Require Bounds off.
Both now remove the model's options from the form first (one list of
their keys), so an option the model doesn't set takes its default.
* Data: Solver Save Model asks before it replaces data
Save Model wrote its formulas over whatever the model range held.
It is now refused, with the sheet unchanged, when a cell of the
range holds a value or a formula (a model saved there before
included), unless `overwrite: true` is passed. The message names
the first such cell and carries the same "already holds data"
phrase as Data Analysis, so the Solver Parameters dialog asks
"Replace it with the model?" with Replace and Don't Replace. The
question belongs to the range it asked about: editing the range,
Load or Reset All drops it. The check runs after the spill checks,
so the question is asked only when replacing would succeed. A save
remains one undo step.
Tests: the engine test refuses a value, a formula and an earlier
model, accepts only a true boolean, and undoes and redoes the
replacing save in one step; the dialog test covers Don't Replace,
an edited range and Replace. Both fail without the change.
* Data: Solver Load Model and Reset All tests for limits and undo
Tests for behaviour already in place: reading down from one cell of
a column of 5,000 formulas stops after the most rows a model takes,
a range larger than a model is refused before any cell is read, and
malformed or hostile cells and ranges (unbalanced brackets, an
overflowing number, an unknown sheet, 10,000 nested brackets, a
non-text `from`) each give an error and leave no model. Undoing
Reset All brings the model back with its options (the population
size).
* Data: Solver Load Model refuses a model without its options row
Load Model from one cell read down to the first cell without a
formula, and a range dropped its trailing cells without formulas.
A constraint cleared in the middle of a saved model, or its options
row cleared or replaced by a constant, therefore left a prefix of
the model, which was loaded as the whole model with default options
and replaced the sheet's model. Every load now requires the model's
last row to be the options row ({...}) that Save Model writes last;
otherwise it is refused, naming the cell without a formula when
reading down from one cell, and the sheet's model stays as it was.
The test clears a middle constraint, clears the options row and
replaces it by a constant, loads from the first cell and as two
ranges, and checks after each refusal that the old model (three
constraints, Simplex LP) is unchanged. It fails without the change.
* Data: Solver Options
The Solver Parameters dialog's Options button shows the Solver Options
in the same window: Max Evaluations and Integer Optimality for all
methods, and Convergence, Mutation Rate, Population Size, Random Seed,
Maximum Generations without Improvement and Require Bounds on Variables
for Evolutionary. OK keeps the changes for the next solve; Cancel
restores them.
The evaluation limit and Integer Optimality are now part of the model:
they are saved in the hidden names (solver_itr, which counts evaluations
in place of iterations, and solver_tol) and in the options row of Save
Model. Both accept numbers or text, as the other options do.
* Data: Solver keeps its own limits out of Excel's Solver names
The evaluation limit was saved as solver_itr. Excel uses that name for
its iteration limit (100 by default), so a workbook saved by Excel would
give GridCraft 100 evaluations and stop its search early. GridCraft now
saves the evaluation limit as gridcraft_solver_evals, which Excel
ignores, and no longer reads solver_itr. Saving a model again and Reset
All remove it with the other model names. Integer Optimality
(solver_tol) keeps Excel's name, as its meaning is the same.
* Data: Solver Reset All also resets the Solver Options
Reset All removes the model's options from the Solver Parameters form,
the Solver Options fields (the evaluation limit, Integer Optimality and
the Evolutionary options) and Require Bounds, so the next Solve uses the
defaults. It now also removes the copy of the options that Options keeps
for Cancel. A test checks that the options are gone after Reset All and
that Options then shows the defaults.
* Data: Solver reads Integer Optimality with a percent sign as percent
Integer Optimality is given in percent, but text such as "5%" was read
by the number parser as 0.05 and then divided by 100 again, so the
solver used 0.05 % instead of 5 %. A trailing percent sign is now
dropped before the number is read, so "5", "5%" and 5 all mean 5 %.
* Data: Solver Options closes with Escape back to the Solver Parameters
Escape in the Solver Options view went to the shared dialog handler,
which closed the whole Solver dialog: the options were not restored and
parameter edits made before opening Options were lost. Escape (and
closing the window) in Solver Options now does what Cancel does: it
restores the options and returns to the Solver Parameters. Escape in the
parameters still closes the dialog.
* Data: Solver keeps the Evolutionary options when another method solves
Solver Options sets the Evolutionary options whatever the solving
method, but the saved model and the model in data.solver's result held
them only for the Evolutionary method. A GRG Nonlinear or Simplex LP
solve (which saves the model by default) dropped them, and switching
back to Evolutionary brought back the defaults. They are now saved and
returned for every method. Two tests that expected them to be absent
for other methods now check their values.
* Data: Solver Options keeps its OK and Cancel row at button height
The Solver Options' OK and Cancel row was a right-to-left layout placed
straight in the window, which takes all the height it is offered, so
the buttons sat well below the last option and the window was taller
than its content. The row is now wrapped in a horizontal row as tall as
the buttons, as the other form dialogs do (ok_cancel).
The window's height now changes when it switches between the parameters
and the options, and the window re-centres over the next frames, so the
test that switches back and forth lets a few frames pass after each
switch before it clicks.
* Data: Solver Parameters keeps its Solve and Close row at button height
The Solve and Close row was a right-to-left layout placed straight in
the window. The window keeps its size when its content gets shorter, as
it does when the Load/Save area or a note is hidden again, and that
layout then filled the space left over, so Solve moved further below
the last row. The row is now a horizontal row as tall as the buttons,
as ok_cancel and the Solver Options do.
* Data: Solver dialog opened in its options sets them up as the Options button does
Opening the Solver dialog straight in the Solver Options (optionsView:
true) only changed the title. It skipped what the Options button does:
filling each option the form lacks with its default and keeping the
current values for Cancel. With no saved model the fields were blank,
and Cancel or Escape found nothing to restore, so the edits stayed and
the next Solve used them. The button and the dialog now share one
function for this.
* Data: Solver reads Integer Optimality back without floating-point noise
Integer Optimality is stored as a fraction, and the product with 100 is not exact for many percents (0.07 * 100 is 7.000000000000001). The percent is now rounded to 1E-10 % wherever it is read back: the saved model, the solve's model params and Save Model's options row.
* Data: Solver reads whole-number options back as integers
The model's numeric options were returned as floating-point JSON, so after a solve the Solver Options showed 20000.0, 100.0, 0.0 and 50.0. Values read from the hidden names, and Integer Optimality in the solve's result, are now JSON integers where they are whole, and the dialog shows 20000, 100, 0 and 50.
* Data: Solver test checks the model saved by the second solve
The test of Excel's iteration and time limits ignored the result of
its second `data.solver` call and checked only names the first call
had already created. It now reads the saved model afterwards and
checks the values the second call changed (Simplex LP and an
evaluation limit of 700). The call itself still fails, as Simplex LP
refuses the nonlinear model, after the model is saved.
* Data: Solver Load Model refuses an options row cut short
The options row of a saved model was read leniently: a missing value
or one that isn't a number took its default, and values after the
sixteenth were not read at all. A row cut short or edited by hand,
such as ={1}, therefore loaded the model with default options in
place of the saved ones (here: GRG Nonlinear in place of Simplex
LP). The row must now hold at least the eight numbers Save Model
writes (method, non-negative, population size, mutation rate, random
seed, require bounds, convergence, generations without improvement),
and every value in it, however many, must be a number; otherwise
Load Model is refused and the sheet's model stays as it was. Only
the first sixteen values are kept. More numbers than eight are still
read, so a row with options a later version adds loads too.
The test loads rows of one value, seven values, a text value among
the eight, after them and after the sixteenth, and a TRUE, from the
first cell and as a range, checking the old model after each
refusal, and a row of ten numbers, which loads. It fails without the
change.
---------
Co-authored-by: FredApps <FredApps@users.noreply.github.com>
1003 lines
55 KiB
Rust
1003 lines
55 KiB
Rust
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 = 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();
|
||
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);
|
||
}
|
||
}
|
||
|
||
fn formula(s: &Session, a1: &str) -> String {
|
||
let d = s.doc().unwrap();
|
||
d.wb.active().unwrap().cell(CellRef::parse(a1).unwrap()).and_then(|c| c.formula.as_ref()).map(|f| f.text.clone()).unwrap_or_default()
|
||
}
|
||
|
||
#[test]
|
||
fn save_and_load_model_round_trip_through_cells() {
|
||
let mut s = s();
|
||
set(&mut s, &[("B1", "=5*A1+4*A2"), ("B2", "=6*A1+4*A2"), ("B3", "=A1+2*A2"), ("C2", "24")]);
|
||
let model = json!({"objective": "B1", "variables": "A1:A2", "constraints": ["B2 <= C2", "B3 <= 6", "A1:A2 int", "A2 bin", "A1 >= 1"], "method": "simplex"});
|
||
s.execute("data.solver", model.clone()).unwrap();
|
||
let out = s.execute("data.solverSaveModel", json!({"to": "H1"})).unwrap();
|
||
assert_eq!(out["range"], "H1:H8");
|
||
let rows: Vec<String> = (1..=8).map(|r| formula(&s, &format!("H{r}"))).collect();
|
||
assert_eq!(
|
||
rows,
|
||
[
|
||
"MAX($B$1)",
|
||
"COUNT($A$1:$A$2)",
|
||
"AND($B$2<=$C$2)",
|
||
"AND($B$3<=6)",
|
||
"AND($A$1:$A$2=INT($A$1:$A$2))",
|
||
"AND(($A$2=0)+($A$2=1))",
|
||
"AND($A$1>=1)",
|
||
"{2,1,100,0.075,0,1,0.0001,50,20000,0}",
|
||
]
|
||
);
|
||
// The constraint cells show whether each constraint holds at the solution (4, 0).
|
||
assert_eq!(at(&s, "Sheet1", "H3"), Value::Bool(true));
|
||
assert_eq!(at(&s, "Sheet1", "H2"), Value::number(2.0));
|
||
// Reset All removes the model; Load Model restores it from the range or its first cell.
|
||
assert_eq!(s.execute("data.solverReset", json!({})).unwrap()["removed"].as_u64().map(|n| n > 0), Some(true));
|
||
assert!(s.execute("data.solver", json!({})).unwrap()["model"].is_null());
|
||
assert_eq!(s.execute("data.solverReset", json!({})).unwrap()["removed"], 0);
|
||
for from in ["H1:H8", "H1"] {
|
||
let loaded = s.execute("data.solverLoadModel", json!({"from": from})).unwrap();
|
||
assert_eq!(loaded["model"]["objective"], "B1", "{loaded}");
|
||
assert_eq!(loaded["model"]["constraints"], json!(["B2 <= C2", "B3 <= 6", "A1:A2 int", "A2 bin", "A1 >= 1"]));
|
||
assert_eq!(loaded["model"]["method"], "simplex");
|
||
}
|
||
set(&mut s, &[("A1", "0"), ("A2", "0")]);
|
||
let r = s.execute("data.solver", json!({"saved": true})).unwrap();
|
||
assert_eq!((r["status"].as_str(), n(&s, "A1"), n(&s, "A2")), (Some("optimal"), 4.0, 0.0), "{r}");
|
||
// A Value Of goal and the Evolutionary options survive too; an explicit model is saved
|
||
// as given.
|
||
let evo = json!({"objective": "B1", "goal": "value", "value": -2.5, "variables": "A1:A2", "constraints": ["A1:A2 <= 10"], "nonNegative": false, "method": "evolutionary", "populationSize": 40, "randomSeed": 3, "requireBounds": false});
|
||
assert_eq!(s.execute("data.solverSaveModel", json!({"to": "J10", "model": evo})).unwrap()["range"], "J10:J13");
|
||
assert_eq!(formula(&s, "J10"), "$B$1=-2.5");
|
||
let m = s.execute("data.solverLoadModel", json!({"from": "J10:J13"})).unwrap()["model"].clone();
|
||
assert_eq!((m["goal"].as_str(), m["value"].as_f64(), m["nonNegative"].as_bool()), (Some("value"), Some(-2.5), Some(false)), "{m}");
|
||
assert_eq!((m["method"].as_str(), m["populationSize"].as_f64(), m["randomSeed"].as_f64()), (Some("evolutionary"), Some(40.0), Some(3.0)));
|
||
assert_eq!(m["requireBounds"], false);
|
||
// Each command is one undo step.
|
||
s.execute("edit.undo", json!({})).unwrap();
|
||
assert_eq!(s.execute("data.solver", json!({})).unwrap()["model"]["method"], "simplex");
|
||
// Refused: no model or no target, overlapping the model, off the sheet, ranges that
|
||
// hold no model, other sheets and oversized ranges.
|
||
set(&mut s, &[("L1", "=1+1"), ("L2", "=SUM(A1:A2)")]);
|
||
for (cmd, p) in [
|
||
("data.solverSaveModel", json!({})),
|
||
("data.solverSaveModel", json!({"to": "A1"})),
|
||
("data.solverSaveModel", json!({"to": "B3"})),
|
||
("data.solverSaveModel", json!({"to": "A1048575"})),
|
||
("data.solverSaveModel", json!({"to": "H1", "model": {"objective": "B1", "variables": "A1,A2", "constraints": ["A1,A2 <= 3"]}})),
|
||
("data.solverSaveModel", json!({"to": "H1", "model": "B1"})),
|
||
("data.solverLoadModel", json!({})),
|
||
("data.solverLoadModel", json!({"from": "L1:L2"})),
|
||
("data.solverLoadModel", json!({"from": "Z1"})),
|
||
("data.solverLoadModel", json!({"from": "H2:H8"})),
|
||
("data.solverLoadModel", json!({"from": "H1:H1048576"})),
|
||
("data.solverLoadModel", json!({"from": "Nope!H1"})),
|
||
] {
|
||
assert!(s.execute(cmd, p.clone()).is_err(), "{cmd} {p}");
|
||
}
|
||
s.execute("data.solverReset", json!({})).unwrap();
|
||
assert!(s.execute("data.solverSaveModel", json!({"to": "H1"})).is_err(), "no model to save");
|
||
}
|
||
|
||
#[test]
|
||
fn reset_all_masks_a_workbook_level_model_and_keeps_other_sheets_models() {
|
||
let mut s = s();
|
||
set(&mut s, &[("A1", "1"), ("B1", "=2*A1")]);
|
||
s.execute("home.insertSheet", json!({"name": "Two"})).unwrap();
|
||
s.execute("sheet.activate", json!({"sheet": "Sheet1"})).unwrap();
|
||
let (one, two) = {
|
||
let wb = &s.doc().unwrap().wb;
|
||
(wb.sheet_index("Sheet1").unwrap(), wb.sheet_index("Two").unwrap())
|
||
};
|
||
// A model saved as workbook-level names, which every sheet reads.
|
||
{
|
||
let d = s.doc_mut().unwrap();
|
||
let wb = std::sync::Arc::make_mut(&mut d.wb);
|
||
for (name, formula) in [
|
||
("solver_opt", "Sheet1!$B$1"),
|
||
("solver_adj", "Sheet1!$A$1"),
|
||
("solver_typ", "1"),
|
||
("solver_num", "0"),
|
||
("solver_eng", "2"),
|
||
("solver_ssz", "500"),
|
||
] {
|
||
wb.names.push(gridcraft_model::DefinedName {
|
||
name: name.into(),
|
||
scope: None,
|
||
formula: formula.into(),
|
||
comment: String::new(),
|
||
hidden: true,
|
||
});
|
||
}
|
||
}
|
||
let model = |s: &Session, sheet: usize| super::saved_model(&s.doc().unwrap().wb, sheet);
|
||
assert_eq!(model(&s, one).map(|m| m["objective"].clone()), Some(json!("B1")));
|
||
// Reset All empties this sheet's model, which the dialog then shows, and no other sheet's.
|
||
let r = s.execute("data.solverReset", json!({})).unwrap();
|
||
assert_eq!(model(&s, one), None, "{r}");
|
||
assert_eq!(r["masked"], true, "{r}");
|
||
assert!(s.execute("data.solver", json!({})).unwrap()["model"].is_null());
|
||
assert_eq!(model(&s, two).map(|m| m["objective"].clone()), Some(json!("B1")));
|
||
assert_eq!(s.doc().unwrap().wb.names.iter().filter(|n| n.scope.is_none()).count(), 6);
|
||
// Undo brings the model back with its options; the mask survives XLSX.
|
||
s.execute("edit.undo", json!({})).unwrap();
|
||
assert_eq!(model(&s, one).and_then(|m| m["populationSize"].as_f64()), Some(500.0));
|
||
s.execute("edit.redo", json!({})).unwrap();
|
||
assert_eq!(model(&s, one), None);
|
||
let b64 = s.execute("file.saveBytes", json!({"format": "xlsx"})).unwrap()["base64"].as_str().unwrap().to_string();
|
||
s.execute("file.open", json!({"name": "r.xlsx", "base64": b64})).unwrap();
|
||
s.execute("sheet.activate", json!({"sheet": "Sheet1"})).unwrap();
|
||
assert_eq!(model(&s, one), None);
|
||
assert!(model(&s, two).is_some());
|
||
// A model saved on the sheet replaces the mask and is read alone: the workbook-level
|
||
// population size doesn't leak into it.
|
||
s.execute("data.solver", json!({"objective": "B1", "variables": "A1", "constraints": ["A1 <= 3"], "method": "simplex"})).unwrap();
|
||
let m = model(&s, one).unwrap();
|
||
assert_eq!((m["objective"].as_str(), m["populationSize"].as_f64()), (Some("B1"), Some(100.0)), "{m}");
|
||
assert_eq!(s.execute("data.solverReset", json!({})).unwrap()["masked"], true);
|
||
assert_eq!(model(&s, one), None);
|
||
}
|
||
|
||
#[test]
|
||
fn saving_a_shorter_model_over_a_longer_one_clears_the_rest() {
|
||
let mut s = s();
|
||
set(&mut s, &[("B1", "=5*A1+4*A2"), ("B2", "=6*A1+4*A2"), ("B3", "=A1+2*A2"), ("H9", "=1+1")]);
|
||
let long = json!({"objective": "B1", "variables": "A1:A2", "constraints": ["B2 <= 24", "B3 <= 6", "A1 <= 3", "A2 <= 3"]});
|
||
let short = json!({"objective": "B1", "variables": "A1:A2", "constraints": ["B2 <= 24"]});
|
||
assert_eq!(s.execute("data.solverSaveModel", json!({"to": "H1", "model": long})).unwrap()["range"], "H1:H7");
|
||
assert_eq!(s.execute("data.solverSaveModel", json!({"to": "H1", "model": short, "overwrite": true})).unwrap()["range"], "H1:H4");
|
||
// The old model's last rows are cleared; a formula below it stays.
|
||
for r in 5..=7 {
|
||
assert_eq!(formula(&s, &format!("H{r}")), "", "H{r}");
|
||
}
|
||
assert_eq!(formula(&s, "H9"), "1+1");
|
||
let loaded = s.execute("data.solverLoadModel", json!({"from": "H1"})).unwrap();
|
||
assert_eq!(loaded["model"]["constraints"], json!(["B2 <= 24"]), "{loaded}");
|
||
// Reading down from one cell stops at the options row even with formulas right below it.
|
||
set(&mut s, &[("H5", "=2+2")]);
|
||
let loaded = s.execute("data.solverLoadModel", json!({"from": "H1"})).unwrap();
|
||
assert_eq!(loaded["model"]["constraints"], json!(["B2 <= 24"]), "{loaded}");
|
||
// Saving over cells that hold no model leaves the cells below them as they are.
|
||
assert_eq!(s.execute("data.solverSaveModel", json!({"to": "H8", "model": short, "overwrite": true})).unwrap()["range"], "H8:H11");
|
||
assert_eq!(formula(&s, "H5"), "2+2");
|
||
}
|
||
|
||
#[test]
|
||
fn save_model_asks_before_it_replaces_data_and_is_one_undo_step() {
|
||
let mut s = s();
|
||
set(&mut s, &[("B1", "=5*A1+4*A2"), ("B2", "=6*A1+4*A2"), ("H2", "kept"), ("H3", "=1+1")]);
|
||
let model = json!({"objective": "B1", "variables": "A1:A2", "constraints": ["B2 <= 24"]});
|
||
// A value or a formula in the column: refused, the sheet unchanged, the cell named.
|
||
let e = s.execute("data.solverSaveModel", json!({"to": "H1", "model": model.clone()})).unwrap_err().to_string();
|
||
assert!(e.contains(crate::cmd::analysis::OVERWRITE_ERROR) && e.contains("H1:H4") && e.contains("H2"), "{e}");
|
||
assert_eq!((at(&s, "Sheet1", "H2"), formula(&s, "H3"), formula(&s, "H1")), (Value::text("kept"), "1+1".into(), String::new()));
|
||
// So is a model saved there before, and `overwrite` only as a true boolean.
|
||
assert!(s.execute("data.solverSaveModel", json!({"to": "J10", "model": model.clone()})).is_ok());
|
||
for overwrite in [json!(null), json!(false), json!("true"), json!(1)] {
|
||
let e = s.execute("data.solverSaveModel", json!({"to": "J10", "model": model.clone(), "overwrite": overwrite})).unwrap_err();
|
||
assert!(e.to_string().contains(crate::cmd::analysis::OVERWRITE_ERROR), "{overwrite}: {e}");
|
||
}
|
||
// overwrite: true replaces the data in one undo step, which brings it all back.
|
||
let out = s.execute("data.solverSaveModel", json!({"to": "H1", "model": model, "overwrite": true})).unwrap();
|
||
assert_eq!(out["range"], "H1:H4");
|
||
assert_eq!((formula(&s, "H1"), formula(&s, "H2"), formula(&s, "H3")), ("MAX($B$1)".into(), "COUNT($A$1:$A$2)".into(), "AND($B$2<=24)".into()));
|
||
s.execute("edit.undo", json!({})).unwrap();
|
||
assert_eq!(
|
||
(at(&s, "Sheet1", "H2"), formula(&s, "H3"), formula(&s, "H1"), formula(&s, "H4")),
|
||
(Value::text("kept"), "1+1".into(), String::new(), String::new())
|
||
);
|
||
assert_eq!(formula(&s, "J10"), "MAX($B$1)");
|
||
s.execute("edit.redo", json!({})).unwrap();
|
||
assert_eq!(formula(&s, "H2"), "COUNT($A$1:$A$2)");
|
||
}
|
||
|
||
#[test]
|
||
fn saving_and_resetting_a_model_keep_the_users_own_solver_names() {
|
||
let mut s = s();
|
||
set(&mut s, &[("A1", "0"), ("B1", "=ABS(A1-3)"), ("C1", "100")]);
|
||
let name = |name: &str, scope: Option<usize>, formula: &str, hidden: bool| gridcraft_model::DefinedName {
|
||
name: name.into(),
|
||
scope,
|
||
formula: formula.into(),
|
||
comment: String::new(),
|
||
hidden,
|
||
};
|
||
{
|
||
let d = s.doc_mut().unwrap();
|
||
let wb = std::sync::Arc::make_mut(&mut d.wb);
|
||
// The user's own names, on the sheet and the workbook, and Excel's Solver names the
|
||
// model replaces.
|
||
wb.names.push(name("solver_budget", Some(0), "Sheet1!$C$1", false));
|
||
wb.names.push(name("Solver_Lhs_Total", Some(0), "Sheet1!$C$1", false));
|
||
wb.names.push(name("solver_budget", None, "Sheet1!$C$1", false));
|
||
wb.names.push(name("solver_lin", Some(0), "2", true));
|
||
wb.names.push(name("solver_lhs12", Some(0), "Sheet1!$A$1", true));
|
||
}
|
||
let names = |s: &Session| -> Vec<String> {
|
||
let mut v: Vec<String> = s.doc().unwrap().wb.names.iter().map(|n| format!("{}@{:?}", n.name, n.scope)).collect();
|
||
v.sort();
|
||
v
|
||
};
|
||
let mine = ["Solver_Lhs_Total@Some(0)", "solver_budget@None", "solver_budget@Some(0)"];
|
||
let model = json!({"objective": "B1", "goal": "min", "variables": "A1", "constraints": ["A1 <= 4"], "method": "simplex"});
|
||
s.execute("data.solver", model.clone()).unwrap();
|
||
let after = names(&s);
|
||
assert!(mine.iter().all(|n| after.contains(&n.to_string())), "{after:?}");
|
||
assert!(!after.iter().any(|n| n.starts_with("solver_lin") || n.starts_with("solver_lhs12")), "{after:?}");
|
||
// Load Model saves the model again; Reset All removes it and nothing else.
|
||
s.execute("data.solverSaveModel", json!({"to": "H1"})).unwrap();
|
||
s.execute("data.solverLoadModel", json!({"from": "H1"})).unwrap();
|
||
assert!(mine.iter().all(|n| names(&s).contains(&n.to_string())), "{:?}", names(&s));
|
||
let model_names = names(&s).len() - mine.len();
|
||
let r = s.execute("data.solverReset", json!({})).unwrap();
|
||
assert_eq!((r["removed"].as_u64(), r["masked"].as_bool()), (Some(model_names as u64), Some(false)), "{r}");
|
||
assert_eq!(names(&s), mine);
|
||
assert!(s.execute("data.solver", json!({})).unwrap()["model"].is_null());
|
||
}
|
||
|
||
#[test]
|
||
fn save_model_refuses_a_place_where_the_options_cannot_spill() {
|
||
let mut s = s();
|
||
set(&mut s, &[("B1", "=ABS(A1-3)"), ("H24", "=SEQUENCE(1,3)"), ("K30", "=SEQUENCE(3)"), ("M50", "=SEQUENCE(3)")]);
|
||
// Tables whose empty data rows meet an options row: one in its way, one holding the
|
||
// options cell.
|
||
for range in ["T59:U62", "W69:W71"] {
|
||
s.execute("insert.table", json!({"range": range, "header": true})).unwrap();
|
||
}
|
||
let model = json!({"objective": "B1", "goal": "min", "variables": "A1", "constraints": ["F4 <= 5"]});
|
||
let save = |s: &mut Session, to: &str| s.execute("data.solverSaveModel", json!({"to": to, "model": model.clone()}));
|
||
// The options row (H4) spills into I4:Q4: a value in its last cell is in the way.
|
||
set(&mut s, &[("Q4", "x")]);
|
||
let e = save(&mut s, "H1").unwrap_err().to_string();
|
||
assert!(e.contains("I4:Q4") && e.contains("Q4 isn't empty"), "{e}");
|
||
assert_eq!((formula(&s, "H1"), formula(&s, "H4")), (String::new(), String::new()));
|
||
assert!(s.execute("data.solver", json!({})).unwrap()["model"].is_null());
|
||
// With the row clear the options spill, and saving again at the same cell replaces them.
|
||
set(&mut s, &[("Q4", "")]);
|
||
for overwrite in [false, true] {
|
||
let p = json!({"to": "H1", "model": model.clone(), "overwrite": overwrite});
|
||
assert_eq!(s.execute("data.solverSaveModel", p).unwrap()["range"], "H1:H4");
|
||
assert_eq!(
|
||
(at(&s, "Sheet1", "H4"), at(&s, "Sheet1", "I4"), at(&s, "Sheet1", "O4"), at(&s, "Sheet1", "Q4")),
|
||
(Value::number(1.0), Value::number(1.0), Value::number(50.0), Value::number(0.0))
|
||
);
|
||
}
|
||
// Refused: in the options row, a formula (H24), another formula's spilled values (K31,
|
||
// from K30), a cell of the model (F4), merged cells, a table and the sheet's last columns;
|
||
// a column over another formula's spilled values (I24 of H24:J24, M51 of M50:M52) or with
|
||
// its options cell in a table.
|
||
s.execute("home.mergeCells", json!({"range": "S8:T9"})).unwrap();
|
||
for (to, why) in [
|
||
("G21", "H24 isn't empty"),
|
||
("J28", "K31 holds the values of another formula"),
|
||
("E1", "F4 is a cell of the model"),
|
||
("R5", "merged"),
|
||
("S57", "T60:AB60, but a table is in the way"),
|
||
("XFA1", "need 10 cells"),
|
||
("I21", "cover I24, which holds the values of another formula"),
|
||
("M51", "cover M51, which holds the values of another formula"),
|
||
("W67", "X70:AF70, but a table is in the way"),
|
||
] {
|
||
let e = save(&mut s, to).unwrap_err().to_string();
|
||
assert!(e.contains(why), "{to}: {e}");
|
||
assert_eq!(formula(&s, to), "", "{to}");
|
||
}
|
||
assert_eq!(
|
||
(at(&s, "Sheet1", "J24"), at(&s, "Sheet1", "K32"), at(&s, "Sheet1", "M52")),
|
||
(Value::number(3.0), Value::number(3.0), Value::number(3.0))
|
||
);
|
||
}
|
||
|
||
#[test]
|
||
fn load_model_refuses_a_range_with_a_cell_without_a_formula() {
|
||
let mut s = s();
|
||
set(&mut s, &[("B1", "=5*A1+4*A2"), ("B2", "=6*A1+4*A2"), ("B3", "=A1+2*A2")]);
|
||
let model = json!({"objective": "B1", "variables": "A1:A2", "constraints": ["B2 <= 24", "B3 <= 6", "A1 <= 3"], "method": "simplex"});
|
||
assert_eq!(s.execute("data.solverSaveModel", json!({"to": "H1", "model": model})).unwrap()["range"], "H1:H6");
|
||
// A range with empty cells after the model loads it.
|
||
let loaded = s.execute("data.solverLoadModel", json!({"from": "H1:H9"})).unwrap();
|
||
assert_eq!(loaded["model"]["constraints"], json!(["B2 <= 24", "B3 <= 6", "A1 <= 3"]), "{loaded}");
|
||
s.execute("data.solverReset", json!({})).unwrap();
|
||
// A constraint overwritten by a constant would drop that constraint; a gap before the
|
||
// options row would drop the options. Both are refused, naming the cell.
|
||
for (cell, input) in [("H4", "7"), ("H5", "")] {
|
||
let before = formula(&s, cell);
|
||
set(&mut s, &[(cell, input)]);
|
||
let e = s.execute("data.solverLoadModel", json!({"from": "H1:H6"})).unwrap_err().to_string();
|
||
assert!(e.contains(cell), "{e}");
|
||
assert!(s.execute("data.solver", json!({})).unwrap()["model"].is_null(), "{cell}");
|
||
set(&mut s, &[(cell, &format!("={before}"))]);
|
||
}
|
||
assert!(s.execute("data.solverLoadModel", json!({"from": "H1:H6"})).is_ok());
|
||
}
|
||
|
||
#[test]
|
||
fn load_model_refuses_a_model_cut_short_and_keeps_the_old_one() {
|
||
let mut s = s();
|
||
set(&mut s, &[("B1", "=5*A1+4*A2"), ("B2", "=6*A1+4*A2"), ("B3", "=A1+2*A2")]);
|
||
let model = json!({"objective": "B1", "variables": "A1:A2", "constraints": ["B2 <= 24", "B3 <= 6", "A1 <= 3"], "method": "simplex"});
|
||
s.execute("data.solver", model).unwrap();
|
||
assert_eq!(s.execute("data.solverSaveModel", json!({"to": "H1"})).unwrap()["range"], "H1:H6");
|
||
let kept = |s: &mut Session| {
|
||
let m = s.execute("data.solver", json!({})).unwrap()["model"].clone();
|
||
assert_eq!((m["constraints"].clone(), m["method"].clone()), (json!(["B2 <= 24", "B3 <= 6", "A1 <= 3"]), json!("simplex")), "{m}");
|
||
};
|
||
// A constraint cleared (H4), the options row cleared (H6) or replaced by a constant: from
|
||
// the first cell or as a range, the rows above the gap are not loaded as the whole model.
|
||
for (cell, input) in [("H4", ""), ("H6", ""), ("H6", "7")] {
|
||
let before = formula(&s, cell);
|
||
set(&mut s, &[(cell, input)]);
|
||
for from in ["H1", "H1:H6", "H1:H9"] {
|
||
let e = s.execute("data.solverLoadModel", json!({"from": from})).unwrap_err().to_string();
|
||
assert!(e.contains("complete model") || e.contains(cell), "{cell} {from}: {e}");
|
||
kept(&mut s);
|
||
}
|
||
set(&mut s, &[(cell, &format!("={before}"))]);
|
||
}
|
||
// An options row cut short or edited by hand: fewer than the eight values Save Model
|
||
// writes, or a value that isn't a number (among the eight, after them or after the sixteenth).
|
||
let options = formula(&s, "H6");
|
||
for row in [
|
||
"={1}",
|
||
"={2,1,100,0.075,0,1,0.0001}",
|
||
"={2,1,100,0.075,0,1,\"x\",50}",
|
||
"={2,TRUE,100,0.075,0,1,0.0001,50}",
|
||
"={2,1,100,0.075,0,1,0.0001,50,\"x\"}",
|
||
"={2,1,100,0.075,0,1,0.0001,50,9,10,11,12,13,14,15,16,\"x\"}",
|
||
] {
|
||
set(&mut s, &[("H6", row)]);
|
||
for from in ["H1", "H1:H6"] {
|
||
let e = s.execute("data.solverLoadModel", json!({"from": from})).unwrap_err().to_string();
|
||
assert!(e.contains("complete model"), "{row} {from}: {e}");
|
||
kept(&mut s);
|
||
}
|
||
}
|
||
// More values than eight (as a later version may write) still load.
|
||
set(&mut s, &[("H6", &format!("={}", options.trim_end_matches('}').to_string() + ",7,8}"))]);
|
||
assert!(s.execute("data.solverLoadModel", json!({"from": "H1"})).is_ok());
|
||
kept(&mut s);
|
||
set(&mut s, &[("H6", &format!("={options}"))]);
|
||
// The gap is named when reading down from one cell.
|
||
set(&mut s, &[("H4", "")]);
|
||
let e = s.execute("data.solverLoadModel", json!({"from": "H1"})).unwrap_err().to_string();
|
||
assert!(e.contains("H4 holds no formula"), "{e}");
|
||
s.execute("edit.undo", json!({})).unwrap();
|
||
assert!(s.execute("data.solverLoadModel", json!({"from": "H1"})).is_ok());
|
||
kept(&mut s);
|
||
}
|
||
|
||
#[test]
|
||
fn load_model_reads_a_bounded_column_and_refuses_malformed_cells() {
|
||
let mut s = s();
|
||
set(&mut s, &[("B1", "=ABS(A1-3)")]);
|
||
let put = |s: &mut Session, col: u32, rows: std::ops::Range<u32>, f: &dyn Fn(u32) -> String| {
|
||
let d = s.doc_mut().unwrap();
|
||
let sh = std::sync::Arc::make_mut(&mut std::sync::Arc::make_mut(&mut d.wb).sheets[0]);
|
||
for r in rows {
|
||
sh.set_cell(CellRef::new(r, col), gridcraft_model::Cell::formula(gridcraft_model::Formula::new(&f(r))));
|
||
}
|
||
};
|
||
// A column of formulas far longer than any model: read from its first cell, the read stops
|
||
// after the most rows a model takes and the column is refused; as a range, it is refused
|
||
// before any cell is read.
|
||
put(&mut s, 15, 0..5_000, &|r| format!("{r}+1"));
|
||
for from in ["P1", "P1:P5000", "P1:P1048576", "A1:XFD1048576"] {
|
||
assert!(s.execute("data.solverLoadModel", json!({"from": from})).is_err(), "{from}");
|
||
}
|
||
// Malformed and hostile cells and ranges: an error each, never a panic, no model.
|
||
let bad = ["AND(", "{", "{1e400,2", "MAX(Nope!A1)", "COUNT($A$1:$A$2", "AND($B$1<=", "MAX($B$1)&\"x\""];
|
||
put(&mut s, 17, 0..bad.len() as u32, &|r| bad[r as usize].to_string());
|
||
put(&mut s, 18, 0..1, &|_| format!("AND({})", "(".repeat(10_000)));
|
||
for r in 1..=bad.len() {
|
||
assert!(s.execute("data.solverLoadModel", json!({"from": format!("R{r}")})).is_err(), "R{r}");
|
||
}
|
||
for from in ["S1", "", ":", "P1:", "H0", "Sheet9!H1", "'Sheet1'!R1:R7", "R7:R1"] {
|
||
assert!(s.execute("data.solverLoadModel", json!({"from": from})).is_err(), "{from}");
|
||
}
|
||
assert!(s.execute("data.solverLoadModel", json!({"from": 7})).is_err());
|
||
assert!(s.execute("data.solver", json!({})).unwrap()["model"].is_null());
|
||
}
|
||
|
||
#[test]
|
||
fn load_model_keeps_the_evolutionary_convergence_and_generations() {
|
||
let mut s = s();
|
||
set(&mut s, &[("B1", "=ABS(A1-3)")]);
|
||
let evo = json!({"objective": "B1", "goal": "min", "variables": "A1", "constraints": ["A1 <= 4"], "method": "evolutionary", "convergence": 0.001, "generationsWithoutImprovement": 20});
|
||
s.execute("data.solverSaveModel", json!({"to": "H1", "model": evo})).unwrap();
|
||
let m = s.execute("data.solverLoadModel", json!({"from": "H1"})).unwrap()["model"].clone();
|
||
assert_eq!((m["convergence"].as_f64(), m["generationsWithoutImprovement"].as_f64()), (Some(0.001), Some(20.0)), "{m}");
|
||
// They survive XLSX; Excel's time limit (solver_mni, in seconds) isn't written or read.
|
||
let b64 = s.execute("file.saveBytes", json!({"format": "xlsx"})).unwrap()["base64"].as_str().unwrap().to_string();
|
||
s.execute("file.open", json!({"name": "c.xlsx", "base64": b64})).unwrap();
|
||
let m = s.execute("data.solver", json!({})).unwrap()["model"].clone();
|
||
assert_eq!((m["convergence"].as_f64(), m["generationsWithoutImprovement"].as_f64()), (Some(0.001), Some(20.0)), "{m}");
|
||
assert!(!s.doc().unwrap().wb.names.iter().any(|n| n.name == "solver_mni"));
|
||
// Reset All removes the GridCraft name with the rest.
|
||
s.execute("data.solverReset", json!({})).unwrap();
|
||
assert!(s.doc().unwrap().wb.names.iter().all(|n| n.scope != Some(0)));
|
||
}
|
||
|
||
#[test]
|
||
fn solver_options_are_saved_with_the_model() {
|
||
let mut s = s();
|
||
set(&mut s, &[("B1", "=10*A1+13*A2"), ("B2", "=5*A1+6*A2")]);
|
||
let p = json!({"objective": "B1", "variables": "A1:A2", "constraints": ["B2 <= 10", "A1:A2 bin"], "method": "evolutionary", "maxEvaluations": "3000", "integerOptimality": 5, "convergence": 0.001, "generationsWithoutImprovement": 20, "mutationRate": "0.1"});
|
||
let r = s.execute("data.solver", p).unwrap();
|
||
assert!(r["evaluations"].as_u64().unwrap() <= 3001, "{r}");
|
||
// The solve's own result gives whole numbers as integers too.
|
||
for k in ["maxEvaluations", "integerOptimality", "generationsWithoutImprovement", "populationSize", "randomSeed"] {
|
||
assert!(r["model"][k].is_i64() || r["model"][k].is_u64(), "{k}: {r}");
|
||
}
|
||
// The options survive XLSX in the hidden names, as given or as text.
|
||
let b64 = s.execute("file.saveBytes", json!({"format": "xlsx"})).unwrap()["base64"].as_str().unwrap().to_string();
|
||
s.execute("file.open", json!({"name": "o.xlsx", "base64": b64})).unwrap();
|
||
let m = s.execute("data.solver", json!({})).unwrap()["model"].clone();
|
||
let f = |k: &str| m[k].as_f64();
|
||
assert_eq!((f("maxEvaluations"), f("integerOptimality"), f("convergence")), (Some(3000.0), Some(5.0), Some(0.001)), "{m}");
|
||
assert_eq!((f("generationsWithoutImprovement"), f("mutationRate")), (Some(20.0), Some(0.1)));
|
||
// Whole numbers read back as integers, so the Solver dialog shows 3000 and not 3000.0.
|
||
for k in ["maxEvaluations", "integerOptimality", "generationsWithoutImprovement", "populationSize", "randomSeed"] {
|
||
assert!(m[k].is_i64(), "{k}: {m}");
|
||
}
|
||
assert_eq!(m["maxEvaluations"].to_string(), "3000");
|
||
// Out-of-range options are clamped, not refused.
|
||
let r = s.execute("data.solver", json!({"saved": true, "maxEvaluations": "1e300", "integerOptimality": -4})).unwrap();
|
||
assert_eq!((r["model"]["maxEvaluations"].as_f64(), r["model"]["integerOptimality"].as_f64()), (Some(200_000.0), Some(0.0)));
|
||
}
|
||
|
||
#[test]
|
||
fn excel_iteration_and_time_limits_are_not_read_as_gridcraft_options() {
|
||
let mut s = s();
|
||
set(&mut s, &[("A1", "0"), ("B1", "=ABS(A1-3)")]);
|
||
let model = json!({"objective": "B1", "goal": "min", "variables": "A1", "constraints": ["A1 <= 4"], "method": "evolutionary"});
|
||
s.execute("data.solver", model.clone()).unwrap();
|
||
let names = |s: &Session| -> Vec<String> {
|
||
let d = s.doc().unwrap();
|
||
d.wb.names.iter().filter(|n| n.scope == Some(0)).map(|n| n.name.clone()).collect()
|
||
};
|
||
// GridCraft's evaluation limit and generations go under its own names, not Excel's.
|
||
let saved = names(&s);
|
||
assert!(saved.iter().all(|n| n != "solver_itr" && n != "solver_mni"), "{saved:?}");
|
||
assert!(saved.iter().any(|n| n == "gridcraft_solver_evals") && saved.iter().any(|n| n == "gridcraft_solver_stall"), "{saved:?}");
|
||
// Excel's own limits, as a workbook from Excel holds them: 100 iterations, 30 seconds.
|
||
{
|
||
let d = s.doc_mut().unwrap();
|
||
let wb = std::sync::Arc::make_mut(&mut d.wb);
|
||
wb.names.retain(|n| !n.name.starts_with("gridcraft_"));
|
||
for (name, formula) in [("solver_itr", "100"), ("solver_mni", "30")] {
|
||
wb.names.push(gridcraft_model::DefinedName {
|
||
name: name.into(),
|
||
scope: Some(0),
|
||
formula: formula.into(),
|
||
comment: String::new(),
|
||
hidden: true,
|
||
});
|
||
}
|
||
}
|
||
let m = s.execute("data.solver", json!({})).unwrap()["model"].clone();
|
||
assert!(m["maxEvaluations"].is_null() && m["generationsWithoutImprovement"].is_null(), "{m}");
|
||
set(&mut s, &[("A1", "0")]);
|
||
let r = s.execute("data.solver", json!({"saved": true})).unwrap();
|
||
assert!(r["evaluations"].as_u64().unwrap() > 100, "{r}");
|
||
assert!((n(&s, "A1") - 3.0).abs() < 1e-3, "{r}");
|
||
// Saving again replaces GridCraft's names; Reset All removes them with the rest. Simplex
|
||
// LP refuses the nonlinear ABS model, but the model is saved before the solve.
|
||
let r = s.execute(
|
||
"data.solver",
|
||
json!({"objective": "B1", "goal": "min", "variables": "A1", "constraints": ["A1 <= 4"], "method": "simplex", "maxEvaluations": 700, "keep": false}),
|
||
);
|
||
let m = super::saved_model(&s.doc().unwrap().wb, 0).unwrap();
|
||
assert_eq!((m["method"].as_str(), m["maxEvaluations"].as_f64()), (Some("simplex"), Some(700.0)), "{m} {r:?}");
|
||
let saved = names(&s);
|
||
assert_eq!(
|
||
saved.iter().filter(|n| n.starts_with("gridcraft_")).collect::<Vec<_>>(),
|
||
["gridcraft_solver_evals", "gridcraft_solver_stall"],
|
||
"{saved:?}"
|
||
);
|
||
s.execute("data.solver", model).unwrap();
|
||
s.execute("data.solverReset", json!({})).unwrap();
|
||
assert!(names(&s).is_empty(), "{:?}", names(&s));
|
||
}
|
||
|
||
#[test]
|
||
fn integer_optimality_reads_a_percent_sign_as_percent() {
|
||
let mut s = s();
|
||
set(&mut s, &[("B1", "=3*A1")]);
|
||
for (given, want) in [(json!("5%"), 5.0), (json!(" 2.5 % "), 2.5), (json!("5"), 5.0), (json!(5), 5.0), (json!("150%"), 100.0)] {
|
||
let p = json!({"objective": "B1", "variables": "A1", "constraints": ["A1 <= 4", "A1 int"], "method": "simplex", "integerOptimality": given});
|
||
let r = s.execute("data.solver", p).unwrap();
|
||
assert_eq!(r["model"]["integerOptimality"].as_f64(), Some(want), "{given}: {r}");
|
||
}
|
||
// Percents whose fraction is not exact in binary read back as given, from the solve's
|
||
// result and from the saved model.
|
||
for given in [7.0, 29.0, 0.1] {
|
||
let p = json!({"objective": "B1", "variables": "A1", "constraints": ["A1 <= 4", "A1 int"], "method": "simplex", "integerOptimality": given});
|
||
let r = s.execute("data.solver", p).unwrap();
|
||
assert_eq!(r["model"]["integerOptimality"].as_f64(), Some(given), "{r}");
|
||
let m = s.execute("data.solver", json!({})).unwrap()["model"].clone();
|
||
assert_eq!(m["integerOptimality"].as_f64(), Some(given), "{m}");
|
||
}
|
||
}
|
||
|
||
#[test]
|
||
fn evolutionary_options_survive_a_solve_with_another_method() {
|
||
let mut s = s();
|
||
set(&mut s, &[("B1", "=3*A1")]);
|
||
let p = json!({"objective": "B1", "variables": "A1", "constraints": ["A1 <= 4"], "method": "grg", "populationSize": 40, "mutationRate": 0.2, "randomSeed": 7, "convergence": 0.001, "generationsWithoutImprovement": 25, "requireBounds": false});
|
||
let r = s.execute("data.solver", p).unwrap();
|
||
assert_eq!(r["model"]["populationSize"].as_f64(), Some(40.0), "{r}");
|
||
// The saved model keeps them for the next time the method is Evolutionary.
|
||
let m = s.execute("data.solver", json!({})).unwrap()["model"].clone();
|
||
let f = |k: &str| m[k].as_f64();
|
||
assert_eq!((f("populationSize"), f("mutationRate"), f("randomSeed")), (Some(40.0), Some(0.2), Some(7.0)), "{m}");
|
||
assert_eq!((f("convergence"), f("generationsWithoutImprovement"), m["requireBounds"].as_bool()), (Some(0.001), Some(25.0), Some(false)));
|
||
}
|
||
|
||
#[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");
|
||
}
|