# Setting a random seed¶

The library has a variety of strategies whose behaviour is stochastic. To ensure reproducible results a random seed should be set. The library abstracts away the propagation of seeds in matches and tournaments, so you typically only need to supply a seed to those objects.

## Matches¶

For a match, set a seed by passing a parameter to Match

>>> import axelrod as axl
>>> players = (axl.Random(), axl.MetaMixer())  # Two stochastic strategies
>>> match = axl.Match(players, turns=3, seed=101)
>>> results = match.play()


We obtain the same results if it is played with the same seed:

>>> match2 = axl.Match(players, turns=3, seed=101)
>>> result2 = match2.play()
>>> results == result2
True


For noisy matches, a seed also needs to be set for reproducibility, even if the players are deterministic.

>>> import axelrod as axl
>>> players = (axl.Cooperator(), axl.Defector())  # Two deterministic strategies
>>> match = axl.Match(players, turns=200, seed=101, noise=0.25)
>>> results = match.play()
>>> match2 = axl.Match(players, turns=200, seed=101, noise=0.25)
>>> results2 = match2.play()
>>> results == results2
True


## Tournaments¶

For tournaments, an initial seed is used to generate subsequent seeds for each match in a a manner that will yield identical results. Note that if the tournament is run with multiple processes, the order of the matches may be computed differently, but the seeds used for each match will be the same.

To seed a tournament we also pass a seed to the tournament at creation time:

>>> import axelrod as axl
>>> seed = 201
>>> players = (axl.Random(), axl.Cooperator(), axl.MetaMixer())
>>> tournament = axl.Tournament(players, turns=5, repetitions=5, seed=seed)
>>> results = tournament.play(processes=1)
>>> tournament2 = axl.Tournament(players, turns=5, repetitions=5, seed=seed)
>>> results2 = tournament.play(processes=1)
>>> results.ranked_names == results2.ranked_names
True


For parallel processing, the ordering of match results may differ, but the actual results, and the final rankings, will be the same.

>>> import axelrod as axl
>>> players = (axl.Random(), axl.Cooperator(), axl.MetaMixer())
>>> tournament = axl.Tournament(players, turns=5, repetitions=5, seed=201)
>>> results = tournament.play(processes=2)
>>> tournament2 = axl.Tournament(players, turns=5, repetitions=5, seed=201)
>>> results2 = tournament.play(processes=2)
>>> results.ranked_names == results2.ranked_names
True


## Moran Process¶

Similarly, a Moran process is essentially another type of tournament. The library’s implementation will propagate child seeds to each match to ensure reproducibility. See also the documentation on EvolvablePlayers.

## Fingerprints¶

Since fingerprint generation depends on tournaments, fingerprints can also be given a seed for reproducibility.