Random numbers: Difference between revisions
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Other implementations of Standard ML have their own random number generators. For example, Moscow ML has a <code>Random</code> structure that is different from the one from SML/NJ. |
Other implementations of Standard ML have their own random number generators. For example, Moscow ML has a <code>Random</code> structure that is different from the one from SML/NJ. |
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{{works with| |
{{works with|Poly/ML}} |
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The SML Basis Library does not provide a routine for uniform deviate generation, and PolyML does not have one. Using a routine from "Monte Carlo" by Fishman (Springer), in the function uniformdeviate, and avoiding the slow IntInf's: |
The SML Basis Library does not provide a routine for uniform deviate generation, and PolyML does not have one. Using a routine from "Monte Carlo" by Fishman (Springer), in the function uniformdeviate, and avoiding the slow IntInf's: |
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<syntaxhighlight lang=" |
<syntaxhighlight lang="sml"> |
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val urandomlist = fn seed => fn n => |
val urandomlist = fn seed => fn n => |
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let |
let |
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