Sort FSRSItems by RevlogId for training

Cargo.toml

@@ -35,7 +35,7 @@ git = "https://github.com/ankitects/linkcheck.git"
 rev = "184b2ca50ed39ca43da13f0b830a463861adb9ca"
 
 [workspace.dependencies.fsrs]
-version = "=1.4.7"
+version = "=1.5.0"
 # git = "https://github.com/open-spaced-repetition/fsrs-rs.git"
 # rev = "58ca25ed2bc4bb1dc376208bbcaed7f5a501b941"
 # path = "../open-spaced-repetition/fsrs-rs"

cargo/licenses.json

@@ -1225,7 +1225,7 @@
   },
   {
     "name": "fsrs",
-    "version": "1.4.7",
+    "version": "1.5.0",
     "authors": "Open Spaced Repetition",
     "repository": "https://github.com/open-spaced-repetition/fsrs-rs",
     "license": "BSD-3-Clause",

rslib/src/scheduler/fsrs/memory_state.rs

@@ -284,7 +284,7 @@ pub(crate) fn fsrs_item_for_memory_state(
         ease_factor: f32,
     }
     if let Some(mut output) = reviews_for_fsrs(entries, next_day_at, false, ignore_revlogs_before) {
-        let mut item = output.fsrs_items.pop().unwrap();
+        let mut item = output.fsrs_items.pop().unwrap().1;
         if output.revlogs_complete {
             Ok(Some(FsrsItemForMemoryState {
                 item,

rslib/src/scheduler/fsrs/params.rs

@@ -237,7 +237,10 @@ fn fsrs_items_for_training(
             i.fsrs_items
         })
         .collect_vec();
-    revlogs.sort_by_cached_key(|r| r.reviews.len());
+    // Sort by RevlogId
+    revlogs.sort_by_key(|(revlog_id, _)| revlog_id.0);
+    // Extract only the FSRSItems after sorting
+    let revlogs = revlogs.into_iter().map(|(_, item)| item).collect_vec();
     (revlogs, review_count)
 }
 
@@ -246,7 +249,7 @@ pub(crate) struct ReviewsForFsrs {
     /// review entries prior to a card being reset).
     pub filtered_revlogs: Vec<RevlogEntry>,
     /// FSRS items derived from the filtered revlogs.
-    pub fsrs_items: Vec<FSRSItem>,
+    pub fsrs_items: Vec<(RevlogId, FSRSItem)>,
     /// True if there is enough history to derive memory state from history
     /// alone. If false, memory state will be derived from SM2.
     pub revlogs_complete: bool,
@@ -360,11 +363,11 @@ pub(crate) fn reviews_for_fsrs(
     let skip = if training { 1 } else { 0 };
     // Convert the remaining entries into separate FSRSItems, where each item
     // contains all reviews done until then.
-    let items: Vec<FSRSItem> = entries
+    let items: Vec<(RevlogId, FSRSItem)> = entries
         .iter()
         .enumerate()
         .skip(skip)
-        .map(|(outer_idx, _)| {
+        .map(|(outer_idx, entry)| {
             let reviews = entries
                 .iter()
                 .take(outer_idx + 1)
@@ -374,9 +377,9 @@ pub(crate) fn reviews_for_fsrs(
                     delta_t: delta_ts[inner_idx],
                 })
                 .collect();
-            FSRSItem { reviews }
+            (entry.id, FSRSItem { reviews })
         })
-        .filter(|item| !training || item.reviews.last().unwrap().delta_t > 0)
+        .filter(|(_, item)| !training || item.reviews.last().unwrap().delta_t > 0)
         .collect_vec();
     if items.is_empty() {
         None
@@ -445,7 +448,7 @@ pub(crate) mod tests {
         ignore_before: TimestampMillis,
     ) -> Option<Vec<FSRSItem>> {
         reviews_for_fsrs(revlog.to_vec(), NEXT_DAY_AT, training, ignore_before)
-            .map(|i| i.fsrs_items)
+            .map(|i| i.fsrs_items.into_iter().map(|(_, item)| item).collect_vec())
     }
 
     pub(crate) fn convert(revlog: &[RevlogEntry], training: bool) -> Option<Vec<FSRSItem>> {