Caused by using due instead of original_due when card was in learning.
I think the original goal of that code was to ignore the learning timestamp
and show the next review date instead, but it's both simpler and more
intuitive to show the learning date instead.
Will allow user to see a record of difficulty changes, and allows us
to identify reviews that have been done with FSRS vs SM-2, since the
valid range is different.
* Pack FSRS data into card.data
* Update FSRS card data when preset or weights change
+ Show FSRS stats in card stats
* Show a warning when there's a limited review history
* Add some translations; tweak UI
* Fix default requested retention
* Add browser columns, fix calculation of R
* Property searches
eg prop:d>0.1
* Integrate FSRS into reviewer
* Warn about long learning steps
* Hide minimum interval when FSRS is on
* Don't apply interval multiplier to FSRS intervals
* Expose memory state to Python
* Don't set memory state on new cards
* Port Jarret's new tests; add some helpers to make tests more compact
https://github.com/open-spaced-repetition/fsrs-rs/pull/64
* Fix learning cards not being given memory state
* Require update to v3 scheduler
* Don't exclude single learning step when calculating memory state
* Use relearning step when learning steps unavailable
* Update docstring
* fix single_card_revlog_to_items (#2656)
* not need check the review_kind for unique_dates
* add email address to CONTRIBUTORS
* fix last first learn & keep early review
* cargo fmt
* cargo clippy --fix
* Add Jarrett to about screen
* Fix fsrs_memory_state being initialized to default in get_card()
* Set initial memory state on graduate
* Update to latest FSRS
* Fix experiment.log being empty
* Fix broken colpkg imports
Introduced by "Update FSRS card data when preset or weights change"
* Update memory state during (re)learning; use FSRS for graduating intervals
* Reset memory state when cards are manually rescheduled as new
* Add difficulty graph; hide eases when FSRS enabled
* Add retrievability graph
* Derive memory_state from revlog when it's missing and shouldn't be
---------
Co-authored-by: Jarrett Ye <jarrett.ye@outlook.com>
Due to the orphan rule, this meant removing our usages of impl ProtoStruct,
or converting them to a trait when they were used commonly.
rslib now directly references anki_proto and anki_i18n, instead of
'pub use'-ing them, and we can put the generated files back in OUT_DIR.
* fix stats calendar daylight saving time offset bug
Previously, when computing counts for the calendar in the stats menu, it was assumed that days had 86,400 seconds. However, this assumption does not hold true on the day when daylight savings occurs.
* add self to CONTRIBUTORS and about.py
* fix stats calendar anki day to calendar day mapping
Since Anki days don't necessarily roll over at midnight, mapping an Anki day into a calendar day needs to have a linear shift applied. By providing the frontend with access to the scheduler's rollover hour, we can account for this offset.
The existing architecture serializes all cards and revlog entries in
the search range into a protobuf message, which the web frontend needs
to decode and then process. The thinking at the time was that this would
make it easier for add-ons to add extra graphs, but in the ~2.5 years
since the new graphs were introduced, no add-ons appear to have taken
advantage of it.
The cards and revlog entries can grow quite large on large collections -
on a collection I tested with approximately 2.5M reviews, the serialized
data is about 110MB, which is a lot to have to deserialize in JavaScript.
This commit shifts the preliminary processing of the data to the Rust end,
which means the data is able to be processed faster, and less needs to
be sent to the frontend. On the test collection above, this reduces the
serialized data from about 110MB to about 160KB, resulting in a more
than 2x performance improvement, and reducing frontend memory usage from
about 400MB to about 40MB.
This also makes #2043 more feasible - while it is still about 50-100%
slower than protobufjs, with the much smaller message size, the difference
is only about 10ms.
