TGM randomizer: Difference between revisions
Maybe TGM-ACE also never deals an S, Z or O as the first piece. |
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== References == | == References == | ||
*[http://www.tetrisconcept.com/forum/viewtopic.php?p=2038#2038 colour_thief's description of the TGM randomizer] | *[http://www.tetrisconcept.com/forum/viewtopic.php?p=2038#2038 colour_thief's description of the TGM randomizer] | ||
[[Category:Game Mechanics]] | |||
[[Category:Gameplay Components]] | |||
[[Category:Randomizers]] |
Revision as of 22:45, 22 March 2007
Most games in Arika's Tetris The Grand Master series randomize the order of tetrominoes using an algorithm that makes successive identical tetrominoes less common. It involves keeping a history of the four most recent tetrominoes and trying to choose a random tetromino not in the history. It "rolls the dice" a given number of times and takes the first tetromino that doesn't match any in the history. TGM1 uses 4 tries; subsequent games using the TGM randomizer use 6 tries.
The history is not a unique list. If the randomizer fails to generate a unique tetromino, which happens about 3.5 percent of the time in a 6-try system, then two or more of one tetromino may occupy elements of the history.
A few additional behaviors exist in the beginning of the game.
- The game never deals an S, Z or O as the first piece.
- The state of the history is initialized to a fixed state:
- In TGM1, the history begins filled with 4 Z pieces.
- In TGM2, the history begins with a Z,S,Z,S sequence.
Tetris The Grand Master Ace does not use the TGM randomizer; it uses TTC's Random Generator algorithm instead.
(But TGM-ACE also never deals an S, Z or O as the first piece.)
Pseudocode
The finite-tries variation used in TGM works as follows:
- Function tgmRandomize(history as list of 4 pieces by reference, numTries as integer by value) as piece:
- For try = 1 to numTries:
- candidatePiece = random element of set {I, J, L, O, S, T, Z}
- If candidatePiece is not in history:
- Exit loop
- Move all tetrominoes in history back by one position
- Put candidatePiece at front of history
- Return candidatePiece
- For try = 1 to numTries:
As numTries increases without bound, the algorithm's behavior approaches the following:
- Function tgmRandomizeInf(history as list of 4 pieces by reference) as piece:
- candidatePiece = random element of set {I, J, L, O, S, T, Z} minus those pieces that are in history
- Move all tetrominoes in history back by one position
- Put candidatePiece at front of history
- Return candidatePiece