fmt

src/optimal_retention.rs

@@ -224,11 +224,10 @@ pub fn simulate(
  continue;
  }
  if (review_cnt_per_day[day_index] + learn_cnt_per_day[day_index] + 1 > review_limit)
- || (!not_learn && learn_cnt_per_day[day_index] + 1 > learn_limit)
+  || (!not_learn && learn_cnt_per_day[day_index] + 1 > learn_limit)
  {
-
  dbg!(&learn_cnt_per_day[day_index]);
- 
+
  card.due += 1.;
  card_priorities.change_priority(&card_index, card_priority(card, !not_learn));
  continue;
@@ -255,21 +254,18 @@ pub fn simulate(
  //dbg!(&card, &rating);
 
  // Update 'cost' based on 'forget' and 'rating'
- let cost = if not_learn { 
+ let cost = if not_learn {
  if forget {
  review_costs[0] * loss_aversion
  } else {
  review_costs[rating - 1]
  }
- }
- else {
+ } else {
  learn_costs[rating - 1]
  };
 
  // Wait until a day which is available
- while day_index < learn_span
- && cost_per_day[day_index] + cost > max_cost_perday
- {
+ while day_index < learn_span && cost_per_day[day_index] + cost > max_cost_perday {
  day_index += 1;
  }
  if day_index >= learn_span {
@@ -305,8 +301,7 @@ pub fn simulate(
 
  if not_learn {
  review_cnt_per_day[day_index] += 1;
- }
- else {
+ } else {
  learn_cnt_per_day[day_index] += 1
  }
  cost_per_day[day_index] += cost;
@@ -945,17 +940,19 @@ mod tests {
  learn_span: 3,
  ..Default::default()
  };
- 
+
  let cards = vec![
  Card {
  difficulty: 5.0,
  stability: 5.0,
  last_date: -5.0,
  due: 0.0,
- }; 9
+ };
+ 9
  ];
 
- let (_, _ ,learn_cnt_per_day, _) = simulate(&config, &DEFAULT_PARAMETERS, 0.9, None, Some(cards))?;
+ let (_, _, learn_cnt_per_day, _) =
+ simulate(&config, &DEFAULT_PARAMETERS, 0.9, None, Some(cards))?;
 
  assert_eq!(learn_cnt_per_day.to_vec(), vec![1, 3, 3]);