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Andras Schmelczer 2026-03-11 20:44:34 +00:00
parent 80a5a2a774
commit 791bc6976b
24 changed files with 890 additions and 312 deletions
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86
server-rs/src/routes/hexagon_stats.rs
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@ -71,6 +71,10 @@ pub struct HexagonStatsParams {
/// Comma-separated feature names to include in stats response.
/// Only listed features are computed; if absent or empty, no features are returned.
pub fields: Option<String>,
/// When set (with journey_slug), pick central_postcode as the postcode with the
/// shortest travel time for this mode+slug (so it has journey data).
pub journey_mode: Option<String>,
pub journey_slug: Option<String>,
}
pub async fn get_hexagon_stats(
@ -107,6 +111,17 @@ pub async fn get_hexagon_stats(
let (fields_specified, field_set) = parse_field_set(params.fields.as_deref());
// Load travel time data for central_postcode selection (if requested)
let journey_travel_data = match (&params.journey_mode, &params.journey_slug) {
(Some(mode), Some(slug)) if state.travel_time_store.has_destination(mode, slug) => {
state
.travel_time_store
.get(mode, slug)
.ok()
}
_ => None,
};
let response = tokio::task::spawn_blocking(move || {
let start_time = std::time::Instant::now();
let precomputed = &state.h3_cells;
@ -138,27 +153,58 @@ pub async fn get_hexagon_stats(
let total_count = matching_rows.len();
// Find the postcode of the property closest to the hexagon center
// Pick central_postcode: prefer the postcode with the shortest travel time
// for the requested journey destination (so it has journey data). Fall back
// to geographic proximity to the hexagon center.
let central_postcode = if !matching_rows.is_empty() {
let center: h3o::LatLng = cell.into();
let center_lat = center.lat() as f32;
let center_lon = center.lng() as f32;
let closest_row = matching_rows
.iter()
.copied()
.min_by(|&a, &b| {
let da_lat = state.data.lat[a] - center_lat;
let da_lon = state.data.lon[a] - center_lon;
let db_lat = state.data.lat[b] - center_lat;
let db_lon = state.data.lon[b] - center_lon;
let dist_a = da_lat * da_lat + da_lon * da_lon;
let dist_b = db_lat * db_lat + db_lon * db_lon;
dist_a
.partial_cmp(&dist_b)
.unwrap_or(std::cmp::Ordering::Equal)
})
.expect("matching_rows is non-empty");
Some(state.data.postcode(closest_row).to_string())
if let Some(ref travel_data) = journey_travel_data {
// Find the row with the shortest travel time in the travel data
let best_row = matching_rows
.iter()
.copied()
.filter_map(|row| {
let pc = state.data.postcode(row);
travel_data.get(pc).map(|td| (row, td.minutes))
})
.min_by_key(|&(_, mins)| mins)
.map(|(row, _)| row);
// Fall back to geographic center if no row has travel data
let row = best_row.unwrap_or_else(|| {
let center: h3o::LatLng = cell.into();
let center_lat = center.lat() as f32;
let center_lon = center.lng() as f32;
matching_rows
.iter()
.copied()
.min_by(|&a, &b| {
let da = (state.data.lat[a] - center_lat).powi(2)
+ (state.data.lon[a] - center_lon).powi(2);
let db = (state.data.lat[b] - center_lat).powi(2)
+ (state.data.lon[b] - center_lon).powi(2);
da.partial_cmp(&db).unwrap_or(std::cmp::Ordering::Equal)
})
.expect("matching_rows is non-empty")
});
Some(state.data.postcode(row).to_string())
} else {
// No journey destination requested — use geographic center
let center: h3o::LatLng = cell.into();
let center_lat = center.lat() as f32;
let center_lon = center.lng() as f32;
let closest_row = matching_rows
.iter()
.copied()
.min_by(|&a, &b| {
let da = (state.data.lat[a] - center_lat).powi(2)
+ (state.data.lon[a] - center_lon).powi(2);
let db = (state.data.lat[b] - center_lat).powi(2)
+ (state.data.lon[b] - center_lon).powi(2);
da.partial_cmp(&db).unwrap_or(std::cmp::Ordering::Equal)
})
.expect("matching_rows is non-empty");
Some(state.data.postcode(closest_row).to_string())
}
} else {
None
};