Introduction | Understanding FSRS | The Memory Model | Retrievability | Basic Usage | Creating a New Card | Checking Retrievability | Getting the Next Interval | Simulating a Review | Simulating Long-term Learning | FSRS Parameters | Summary
Package: rfsrs 0.3.2
rfsrs: R Bindings for FSRS Spaced Repetition Algorithm
R bindings for the fsrs-rs Rust library implementing the Free Spaced Repetition Scheduler (FSRS) algorithm. FSRS is a modern spaced repetition algorithm based on the DSR (Difficulty, Stability, Retrievability) model of memory. Includes parameter optimization to train custom parameters from your review history, achieving better scheduling accuracy than default parameters or traditional algorithms like SM-2.
Authors:
rfsrs_0.3.2.tar.gz
rfsrs_0.3.2.tgz(r-4.6-x86_64)rfsrs_0.3.2.tgz(r-4.6-arm64)rfsrs_0.3.2.tgz(r-4.5-x86_64)rfsrs_0.3.2.tgz(r-4.5-arm64)
rfsrs_0.3.2.tar.gz(r-4.7-arm64)rfsrs_0.3.2.tar.gz(r-4.7-x86_64)rfsrs_0.3.2.tar.gz(r-4.6-arm64)rfsrs_0.3.2.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
rfsrs/json (API)
| # Install 'rfsrs' in R: |
| install.packages('rfsrs', repos = c('https://chrislongros.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/open-spaced-repetition/r-fsrs/issues
Last updated from:0ab571e653 (on master). Checks:9 OK, 6 FAIL. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 159 | ||
| linux-devel-x86_64 | OK | 194 | ||
| source / vignettes | OK | 264 | ||
| linux-release-arm64 | OK | 143 | ||
| linux-release-x86_64 | OK | 194 | ||
| macos-release-arm64 | OK | 198 | ||
| macos-release-x86_64 | OK | 428 | ||
| macos-oldrel-arm64 | OK | 180 | ||
| macos-oldrel-x86_64 | OK | 466 | ||
| windows-devel-arm64 | FAIL | 486 | ||
| windows-devel-x86_64 | FAIL | 271 | ||
| windows-release-arm64 | FAIL | 451 | ||
| windows-release-x86_64 | FAIL | 279 | ||
| windows-oldrel-x86_64 | FAIL | 272 | ||
| wasm-release | FAIL | 143 |
Exports:CardCard_from_jsonfsrs_anki_to_reviewsfsrs_evaluatefsrs_intervalfsrs_memory_state_from_historyfsrs_migrate_sm2fsrs_new_card_statefsrs_next_memory_statefsrs_optimizefsrs_parametersfsrs_recall_probabilityfsrs_recall_probability_vecfsrs_simulatefsrs_versionRatingReviewLogSchedulerScheduler_from_jsonState
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| FSRS Card | Card |
| Create Card from JSON | Card_from_json |
| Convert Anki Review Log to FSRS Format | fsrs_anki_to_reviews |
| Evaluate FSRS Parameters | fsrs_evaluate |
| Next review interval | fsrs_interval |
| Memory state replayed from a rating history | fsrs_memory_state_from_history |
| Migrate an SM-2 card to FSRS | fsrs_migrate_sm2 |
| Initial memory state for a new card | fsrs_new_card_state |
| Memory state after a review | fsrs_next_memory_state |
| Optimize FSRS Parameters | fsrs_optimize |
| Default FSRS parameters | fsrs_parameters |
| Retrievability | fsrs_recall_probability |
| Vectorized retrievability | fsrs_recall_probability_vec |
| Simulate Learning a Card | fsrs_simulate |
| Get the FSRS algorithm version used by this package | fsrs_version |
| FSRS Rating | Rating |
| FSRS Review Log | ReviewLog |
| FSRS Scheduler | Scheduler |
| Create Scheduler from JSON | Scheduler_from_json |
| FSRS State | State |