Crate fsrs

Structs§

CMRRTargetFn
Card
CombinedProgressState
ComputeParametersInput: Input parameters for computing FSRS parameters
FSRS: This is the main structure provided by this crate. It can be used for both parameter training, and for reviews.
FSRSItem: Stores a list of reviews for a card, in chronological order. Each FSRSItem corresponds to a single review, but contains the previous reviews of the card as well, after the first one. When used during review, the last item should include the correct delta_t, but the provided rating is ignored as all four ratings are returned by .next_states()
FSRSReview
ItemProgress
ItemState
MemoryState
ModelEvaluation
NextStates
PostSchedulingContext: Context for post scheduling operations.
PostSchedulingFn: Function type for post scheduling operations that takes a scheduling context and returns a new interval.
ReviewPriorityFn: Function type for review priority calculation that takes a card reference and returns a priority value (lower value means higher priority)
RevlogEntry
SimulationResult
SimulatorConfig
TrainingConfig: Hyperparameters used when training FSRS parameters.

benchmark
check_and_fill_parameters
compute_parameters: Computes optimized parameters for the FSRS model based on training data.
current_retrievability: Calculate the current retrievability for a memory state.
evaluate_with_time_series_splits: Evaluates the model using time series cross-validation.
expected_workload
expected_workload_with_existing_cards: Evaluate expected workload when there are already in-flight cards.
extract_simulator_config
filter_outlier
optimal_retention: For the given simulator parameters and parameters, determine the suggested desired_retention value.
simulate