Amiibo drops

Drop tables

Idx	Name	Description
0	Normal
1	Normal2
2	SmallHit
3	SmallHit2
4	BigHit
5	BigHit2
6	GreatHit
7	GreatHit2

Notes on AmiiboMgr

• amiibo code (AIDef:Action/CreateEpona, AIDef:Action/ItemAmiiboSelectDropTable, AIDef:AI/WolfLinkAmiibo) call AmiiboMgr::updateHistoryFlags^{[unofficial name]} every time an amiibo is used.
  • First, AmiiboMgr determines if it should reset its daily amiibo use history (stored in the AmiiboTouchHistory flag).
    • If less than 86400 seconds (1 day) have elapsed since the game was launched, don't do anything.^[check]
    • AmiiboMgr then computes 10000 * now.year + 100 * now.month + now.day. If the value is different from AmiiboLastTouchDate (which would mean that a day has elapsed), the AmiiboTouchHistory array is cleared.
  • AmiiboTouchHistoryTotal (which stores the last 200 used amiibos) is updated too. Exactly what happens is currently unknown.
  • Finally, AmiiboLastTouchDate is set to 10000 * now.year + 100 * now.month + now.day.

Logic

AIDef:Action/ItemAmiiboCreateFromDropTable (the action that is responsible for determining the drop table and spawning the drops) follows the following process:

• Get the number of times the amiibo has been scanned for the current day (using AmiiboTouchHistory): $scanCount
• Get the number of times the amiibo has been scanned (using AmiiboTouchHistoryTotal): $$scanCountTotal

• Determine the drop table category to use.
  • Remain if Find_4Relic_1stClear is set
  • Parasail if IsGet_PlayerStole2 is set
  • Normal otherwise

• Calculate the "adjust rate"
  • When the amiibo has been scanned 0 to $HitRateAdjustStart times, the adjust rate is 0%.
  • This value increases linearly and reaches its maximum (100%) when the amiibo scan count is >= $HitRateAdjustEnd.
  • In practice, because HitRateAdjustStart and HitRateAdjustEnd are both set to the same value (5), the formula can be simplified: the rate is 100% if $$scanCountTotal >= $HitRateAdjustEnd and 0% otherwise.

• Determine if there should be a Great Hit (RNG)
  • If $scanCount is <2, use GreatHitRate1st as the probability of getting a Great Hit.
  • If $scanCount is 2, use GreatHitRate2nd.
  • If $scanCount is 3, use GreatHitRate3rd.
  • In these three cases, if the great hit rate is >0.0, add adjustRate * (100.0 - greatHitRate) to the great hit rate.
  • Otherwise, if $scanCount is >3, the great hit rate is 0%.

• If there was no Great Hit, determine if there should be a Big Hit (RNG)
  • If $scanCount <= 3, a Big Hit is guaranteed.
  • If $scanCount >= 4, a Big Hit will never happen.

• Determine if there should be a Small Hit (RNG)
  • If $scanCount is <2, use SmallHitRate1st.
  • If $scanCount is 2, use SmallHitRate2nd.
  • If $scanCount is 3, use SmallHitRate3rd.
  • Otherwise, if $scanCount is >3, the great hit rate is 0%.

• Determine the drop num rate
  • If $scanCount is <2, use DropNumRate1st.
  • If $scanCount is 2, use DropNumRate2nd.
  • If $scanCount is 3, use DropNumRate3rd.
  • Otherwise, if $scanCount is >3, the drop num rate is 0%.

• For each drop table ({Normal,SmallHit,BigHit,GreatHit}{,2}), calculate the actual drop num.
  • 0 if the table doesn't exist in the bdrop
  • max(1, (dropNumRate * repeatNum) / 100.0) otherwise
  • Note: For BigHit and GreatHit tables, (Remain), (Parasail) or (Normal) are appended to the table name.

• Fix the drop nums based on the RNG results