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refactor: remove dead code, replace sum_matching tests with evaluate()

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Removes unused methods (sum_matching, get_mut, item_by_name, item_index,
top_level_groups, is_group_collapsed, show_item) and unused constants
(LABEL_THRESHOLD, MIN_COL_WIDTH).

The sum_matching tests in model.rs were bypassing the formula evaluator
entirely. Replaced them with equivalent tests that call evaluate() against
the existing Total = SUM(Revenue) formula, exercising the real aggregation
code path.

Also fixes a compile error in view.rs prop_tests where View/Axis imports
and a doc comment were incorrectly commented out.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Edward Langley
2026-03-30 22:56:04 -07:00
parent 15f7fbe799
commit a1b17dc9af
7 changed files with 102 additions and 140 deletions
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88
src/model/category.rs
View File

@ -93,31 +93,31 @@ impl Category {
}
}
pub fn item_by_name(&self, name: &str) -> Option<&Item> {
self.items.get(name)
}
// pub fn item_by_name(&self, name: &str) -> Option<&Item> {
// self.items.get(name)
// }
pub fn item_index(&self, name: &str) -> Option<usize> {
self.items.get_index_of(name)
}
// pub fn item_index(&self, name: &str) -> Option<usize> {
// self.items.get_index_of(name)
// }
/// Returns item names in order, grouped hierarchically
pub fn ordered_item_names(&self) -> Vec<&str> {
self.items.keys().map(|s| s.as_str()).collect()
}
/// Returns unique group names at the top level
pub fn top_level_groups(&self) -> Vec<&str> {
let mut seen = Vec::new();
for item in self.items.values() {
if let Some(g) = &item.group {
if !seen.contains(&g.as_str()) {
seen.push(g.as_str());
}
}
}
seen
}
// /// Returns unique group names at the top level
// pub fn top_level_groups(&self) -> Vec<&str> {
// let mut seen = Vec::new();
// for item in self.items.values() {
// if let Some(g) = &item.group {
// if !seen.contains(&g.as_str()) {
// seen.push(g.as_str());
// }
// }
// }
// seen
// }
}
#[cfg(test)]
@ -146,13 +146,13 @@ mod tests {
assert_eq!(c.items.len(), 1);
}
#[test]
fn add_item_in_group_sets_group() {
let mut c = cat();
c.add_item_in_group("Jan", "Q1");
let item = c.item_by_name("Jan").unwrap();
assert_eq!(item.group.as_deref(), Some("Q1"));
}
// #[test]
// fn add_item_in_group_sets_group() {
// let mut c = cat();
// c.add_item_in_group("Jan", "Q1");
// let item = c.item_by_name("Jan").unwrap();
// assert_eq!(item.group.as_deref(), Some("Q1"));
// }
#[test]
fn add_item_in_group_duplicate_returns_same_id() {
@ -171,24 +171,24 @@ mod tests {
assert_eq!(c.groups.len(), 1);
}
#[test]
fn top_level_groups_returns_unique_groups_in_insertion_order() {
let mut c = cat();
c.add_item_in_group("Jan", "Q1");
c.add_item_in_group("Feb", "Q1");
c.add_item_in_group("Apr", "Q2");
let groups = c.top_level_groups();
assert_eq!(groups, vec!["Q1", "Q2"]);
}
// #[test]
// fn top_level_groups_returns_unique_groups_in_insertion_order() {
// let mut c = cat();
// c.add_item_in_group("Jan", "Q1");
// c.add_item_in_group("Feb", "Q1");
// c.add_item_in_group("Apr", "Q2");
// let groups = c.top_level_groups();
// assert_eq!(groups, vec!["Q1", "Q2"]);
// }
#[test]
fn item_index_reflects_insertion_order() {
let mut c = cat();
c.add_item("East");
c.add_item("West");
c.add_item("North");
assert_eq!(c.item_index("East"), Some(0));
assert_eq!(c.item_index("West"), Some(1));
assert_eq!(c.item_index("North"), Some(2));
}
// #[test]
// fn item_index_reflects_insertion_order() {
// let mut c = cat();
// c.add_item("East");
// c.add_item("West");
// c.add_item("North");
// assert_eq!(c.item_index("East"), Some(0));
// assert_eq!(c.item_index("West"), Some(1));
// assert_eq!(c.item_index("North"), Some(2));
// }
}

37
src/model/cell.rs
View File

@ -113,10 +113,6 @@ impl DataStore {
self.cells.get(key)
}
pub fn get_mut(&mut self, key: &CellKey) -> Option<&mut CellValue> {
self.cells.get_mut(key)
}
pub fn cells(&self) -> &HashMap<CellKey, CellValue> {
&self.cells
}
@ -125,14 +121,6 @@ impl DataStore {
self.cells.remove(key);
}
/// Sum all cells matching partial coordinates
pub fn sum_matching(&self, partial: &[(String, String)]) -> f64 {
self.cells.iter()
.filter(|(key, _)| key.matches_partial(partial))
.filter_map(|(_, v)| v.as_f64())
.sum()
}
/// All cells where partial coords match
pub fn matching_cells(&self, partial: &[(String, String)]) -> Vec<(&CellKey, &CellValue)> {
self.cells.iter()
@ -274,24 +262,6 @@ mod data_store {
assert!(store.cells().is_empty());
}
#[test]
fn sum_matching_sums_across_dimension() {
let mut store = DataStore::new();
store.set(key(&[("Measure", "Revenue"), ("Region", "East")]), CellValue::Number(100.0));
store.set(key(&[("Measure", "Revenue"), ("Region", "West")]), CellValue::Number(200.0));
store.set(key(&[("Measure", "Cost"), ("Region", "East")]), CellValue::Number(50.0));
let partial = vec![("Measure".to_string(), "Revenue".to_string())];
assert_eq!(store.sum_matching(&partial), 300.0);
}
#[test]
fn sum_matching_empty_partial_sums_everything() {
let mut store = DataStore::new();
store.set(key(&[("Region", "East")]), CellValue::Number(10.0));
store.set(key(&[("Region", "West")]), CellValue::Number(20.0));
assert_eq!(store.sum_matching(&[]), 30.0);
}
#[test]
fn matching_cells_returns_correct_subset() {
let mut store = DataStore::new();
@ -306,13 +276,6 @@ mod data_store {
assert!(values.contains(&200.0));
}
#[test]
fn text_values_excluded_from_sum() {
let mut store = DataStore::new();
store.set(key(&[("Cat", "A")]), CellValue::Number(10.0));
store.set(key(&[("Cat", "B")]), CellValue::Text("hello".into()));
assert_eq!(store.sum_matching(&[]), 10.0);
}
}
#[cfg(test)]

31
src/model/model.rs
View File

@ -933,11 +933,11 @@ mod five_category {
#[test]
fn sum_revenue_for_east_region() {
let m = build_model();
let partial = vec![
("Measure".to_string(), "Revenue".to_string()),
let key = CellKey::new(vec![
("Measure".to_string(), "Total".to_string()),
("Region".to_string(), "East".to_string()),
];
let total = m.data.sum_matching(&partial);
]);
let total = m.evaluate(&key).and_then(|v| v.as_f64()).unwrap();
let expected: f64 = DATA.iter().filter(|&&(r, _, _, _, _, _)| r == "East").map(|&(_, _, _, _, rev, _)| rev).sum();
assert!(approx(total, expected), "expected {expected}, got {total}");
}
@ -945,11 +945,11 @@ mod five_category {
#[test]
fn sum_revenue_for_online_channel() {
let m = build_model();
let partial = vec![
let key = CellKey::new(vec![
("Channel".to_string(), "Online".to_string()),
("Measure".to_string(), "Revenue".to_string()),
];
let total = m.data.sum_matching(&partial);
("Measure".to_string(), "Total".to_string()),
]);
let total = m.evaluate(&key).and_then(|v| v.as_f64()).unwrap();
let expected: f64 = DATA.iter().filter(|&&(_, _, ch, _, _, _)| ch == "Online").map(|&(_, _, _, _, rev, _)| rev).sum();
assert!(approx(total, expected), "expected {expected}, got {total}");
}
@ -957,12 +957,12 @@ mod five_category {
#[test]
fn sum_revenue_for_shirts_q1() {
let m = build_model();
let partial = vec![
("Measure".to_string(), "Revenue".to_string()),
let key = CellKey::new(vec![
("Measure".to_string(), "Total".to_string()),
("Product".to_string(), "Shirts".to_string()),
("Time".to_string(), "Q1".to_string()),
];
let total = m.data.sum_matching(&partial);
]);
let total = m.evaluate(&key).and_then(|v| v.as_f64()).unwrap();
let expected: f64 = DATA.iter().filter(|&&(_, p, _, t, _, _)| p == "Shirts" && t == "Q1").map(|&(_, _, _, _, rev, _)| rev).sum();
assert!(approx(total, expected), "expected {expected}, got {total}");
}
@ -970,8 +970,10 @@ mod five_category {
#[test]
fn sum_all_revenue_equals_grand_total() {
let m = build_model();
let partial = vec![("Measure".to_string(), "Revenue".to_string())];
let total = m.data.sum_matching(&partial);
let key = CellKey::new(vec![
("Measure".to_string(), "Total".to_string()),
]);
let total = m.evaluate(&key).and_then(|v| v.as_f64()).unwrap();
let expected: f64 = DATA.iter().map(|&(_, _, _, _, rev, _)| rev).sum();
assert!(approx(total, expected), "expected {expected}, got {total}");
}
@ -1193,4 +1195,3 @@ mod prop_tests {
}
}
}