From Jason Turner

[rand.util.canonical]

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  #### Function template `generate_canonical` <a id="rand.util.canonical">[[rand.util.canonical]]</a>
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- Each function instantiated from the template described in this section 
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- [[rand.util.canonical]] maps the result of one or more invocations of a
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- supplied uniform random bit generator `g` to one member of the specified
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- `RealType` such that, if the values gᵢ produced by `g` are uniformly
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- distributed, the instantiation’s results tⱼ, 0 ≤ tⱼ < 1, are distributed
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- as uniformly as possible as specified below.
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-
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- [*Note 1*: Obtaining a value in this way can be a useful step in the
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- process of transforming a value generated by a uniform random bit
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- generator into a value that can be delivered by a random number
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- distribution. — *end note*]
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-
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  ``` cpp
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  template<class RealType, size_t bits, class URBG>
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  RealType generate_canonical(URBG& g);
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  ```
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  $$S = \sum_{i=0}^{k-1} (g_i - \texttt{g.min()})
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  \cdot R^i$$ using arithmetic of type `RealType`.
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  *Returns:* S / Rᵏ.
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  *Throws:* What and when `g` throws.
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  #### Function template `generate_canonical` <a id="rand.util.canonical">[[rand.util.canonical]]</a>
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  ``` cpp
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  template<class RealType, size_t bits, class URBG>
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  RealType generate_canonical(URBG& g);
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  ```
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  $$S = \sum_{i=0}^{k-1} (g_i - \texttt{g.min()})
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  \cdot R^i$$ using arithmetic of type `RealType`.
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  *Returns:* S / Rᵏ.
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+ [*Note 1*: 0 ≤ S / Rᵏ < 1. — *end note*]
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+
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  *Throws:* What and when `g` throws.
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+ [*Note 2*: If the values gᵢ produced by `g` are uniformly distributed,
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+ the instantiation’s results are distributed as uniformly as possible.
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+ Obtaining a value in this way can be a useful step in the process of
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+ transforming a value generated by a uniform random bit generator into a
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+ value that can be delivered by a random number
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+ distribution. — *end note*]
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+