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- CLOCK TICKS, TURN COUNTS & SMOOTH TIME: timing in FFT |
- '''''''''''''''''''''''''''''''''''''''''''''''''''''''
- The way time actually flows in FFT is based on 'ticks'.
- Every tick of the clock adds a players speed to his charge
- meter. If the number passes 100, you take an 'observed turn'
- and reset your meter. If two players fill on the same tick,
- they both play. A likely sorting method is highest overshoot
- Goes first. Ex:
- Sp Charge Over
- 11 99->110 10
- 12 96->108 8
- If Sp_11 and Sp_12 fill on the same tick, 11 plays before 12.
- The problem is 12 will now fill before 11 because they both
- start at ZERO. Rule:
- For two characters, the higher speed will eventually play
- twice in a row.
- In the previous post we used the term '100/Sp' as our 'turn time'.
- This looks problematic as FFT doesnt actually use fractions. Lets
- Reformulate using turn counts. The math that tells you turns for a
- given player based on tick counts is as follows:
- T = TICKS, total clock ticks
- C = CYCLE COUNT = CEILING(100/Sp), this gives the ticks per turn
- N = TURN COUNT = FLOOR(T/C), this is played turns given TICKS
- Now we can calculate something interesting. Assume we have
- multiple players. At a large TICKS value, compute two new values:
- N_total = N_1 + N_2 + N_3 + ... , sum of all turn counts
- Sp_total = Sp_1 + Sp_2 + ... , sum of all speeds
- This gives us 'statistical speed' or 'Ss':
- Ss_j = N_j/N_total*Sp_total
- Close with a 3 player example:
- TICKS = 257
- Player 1 2 3
- Sp 6 9 13
- C 17 12 8
- N 15 21 32
- Ss 6.2 8.6 13.2
- This gives credence to the Sp/100 value used for computing power as it
- nearly equals a scaled probability derived from turn counts. They are
- Identical for 1 player. They likely converge at infinite player count.
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