Add documentation to the BigRNG

doc/helpdb.jl

@@ -3885,7 +3885,8 @@ popdisplay(d::Display)
 
 ("Mathematical Functions","Base","gcd","gcd(x, y)
 
-   Greatest common (positive) divisor (or zero if x and y are both zero).
+   Greatest common (positive) divisor (or zero if x and y are both
+   zero).
 
 "),
 
@@ -3897,8 +3898,8 @@ popdisplay(d::Display)
 
 ("Mathematical Functions","Base","gcdx","gcdx(x, y)
 
-   Greatest common (positive) divisor, also returning integer coefficients \"u\"
-   and \"v\" that solve \"ux+vy == gcd(x,y)\"
+   Greatest common (positive) divisor, also returning integer
+   coefficients \"u\" and \"v\" that solve \"ux+vy == gcd(x,y)\"
 
 "),
 
@@ -4769,7 +4770,8 @@ popdisplay(d::Display)
    Seed the RNG with a \"seed\", which may be an unsigned integer or a
    vector of unsigned integers. \"seed\" can even be a filename, in
    which case the seed is read from a file. If the argument \"rng\" is
-   not provided, the default global RNG is seeded.
+   not provided, the default global RNG and the default BigRNG are
+   seeded.
 
 "),
 
@@ -4781,9 +4783,24 @@ popdisplay(d::Display)
 
 "),
 
+("Random Numbers","Base","BigRNG","BigRNG([seed])
+
+   Create a \"BigRNG\" RNG object, used exclusively to generate random
+   BigInts and BigFloats. Different RNG objects can have their own
+   seeds, which may be useful for generating different streams of
+   random numbers.
+
+"),
+
 ("Random Numbers","Base","rand","rand()
 
-   Generate a \"Float64\" random number uniformly in [0,1)
+   Generate a \"Float64\" random number uniformly in [0,1).
+
+"),
+
+("Random Numbers","Base","rand","rand(BigFloat)
+
+   Generate a \"BigFloat\" random number uniformly in [0,1).
 
 "),
 
@@ -4803,9 +4820,24 @@ popdisplay(d::Display)
 
 "),
 
+("Random Numbers","Base","rand","rand(BigFloat, rng::AbstractRNG[, dims...])
+
+   Generate a random \"BigFloat\" number or array of the size
+   specified by dims, using the specified RNG object. Currently,
+   \"BigRNG\" is the only available Random Number Generator (RNG) for
+   BigFloats, which may be seeded using srand.
+
+"),
+
 ("Random Numbers","Base","rand","rand(dims or [dims...])
 
-   Generate a random \"Float64\" array of the size specified by dims
+   Generate a random \"Float64\" array of the size specified by dims.
+
+"),
+
+("Random Numbers","Base","rand","rand(BigFloat, dims or [dims...])
+
+   Generate a random \"BigFloat\" array of the size specified by dims.
 
 "),
 
@@ -4846,13 +4878,28 @@ popdisplay(d::Display)
 
 "),
 
+("Random Numbers","Base","randn","randn(BigFloat, dims or [dims...])
+
+   Generate a normally-distributed random BigFloat with mean 0 and
+   standard deviation 1. Optionally generate an array of normally-
+   distributed random BigFloats.
+
+"),
+
 ("Random Numbers","Base","randn!","randn!(A::Array{Float64, N})
 
    Fill the array A with normally-distributed (mean 0, standard
    deviation 1) random numbers. Also see the rand function.
 
 "),
 
+("Random Numbers","Base","randn!","randn!(A::Array{BigFloat, N})
+
+   Fill the array A with normally-distributed (mean 0, standard
+   deviation 1) random BigFloats. Also see the rand function.
+
+"),
+
 ("Random Numbers","Base","randsym","randsym(n)
 
    Generate a \"nxn\" symmetric array of normally-distributed random

doc/stdlib/base.rst

@@ -3206,19 +3206,27 @@ The `BigFloat` type implements arbitrary-precision floating-point aritmetic usin
 Random Numbers
 --------------
 
-Random number generateion in Julia uses the `Mersenne Twister library <http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/SFMT/#dSFMT>`_. Julia has a global RNG, which is used by default. Multiple RNGs can be plugged in using the ``AbstractRNG`` object, which can then be used to have multiple streams of random numbers. Currently, only ``MersenneTwister`` is supported.
+Random number generation in Julia uses the `Mersenne Twister library <http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/SFMT/#dSFMT>`_. Julia has a global RNG, which is used by default. Multiple RNGs can be plugged in using the ``AbstractRNG`` object, which can then be used to have multiple streams of random numbers. Currently, only ``MersenneTwister`` is supported. For the generation of BigInts and BigFloats, GMP's own Mersenne Twister implementation is used instead.
 
 .. function:: srand([rng], seed)
 
-   Seed the RNG with a ``seed``, which may be an unsigned integer or a vector of unsigned integers. ``seed`` can even be a filename, in which case the seed is read from a file. If the argument ``rng`` is not provided, the default global RNG is seeded.
+   Seed the RNG with a ``seed``, which may be an unsigned integer or a vector of unsigned integers. ``seed`` can even be a filename, in which case the seed is read from a file. If the argument ``rng`` is not provided, the default global RNG and the default BigRNG are seeded.
 
 .. function:: MersenneTwister([seed])
 
    Create a ``MersenneTwister`` RNG object. Different RNG objects can have their own seeds, which may be useful for generating different streams of random numbers.
 
+.. function:: BigRNG([seed])
+
+   Create a ``BigRNG`` RNG object, used exclusively to generate random BigInts and BigFloats. Different RNG objects can have their own seeds, which may be useful for generating different streams of random numbers.
+
 .. function:: rand()
 
-   Generate a ``Float64`` random number uniformly in [0,1)
+   Generate a ``Float64`` random number uniformly in [0,1).
+
+.. function:: rand(BigFloat)
+
+   Generate a ``BigFloat`` random number uniformly in [0,1).
 
 .. function:: rand!([rng], A)
 
@@ -3228,9 +3236,17 @@ Random number generateion in Julia uses the `Mersenne Twister library <http://ww
 
    Generate a random ``Float64`` number or array of the size specified by dims, using the specified RNG object. Currently, ``MersenneTwister`` is the only available Random Number Generator (RNG), which may be seeded using srand.
 
+.. function:: rand(BigFloat, rng::AbstractRNG, [dims...])
+
+   Generate a random ``BigFloat`` number or array of the size specified by dims, using the specified RNG object. Currently, ``BigRNG`` is the only available Random Number Generator (RNG) for BigFloats, which may be seeded using srand.
+
 .. function:: rand(dims or [dims...])
 
-   Generate a random ``Float64`` array of the size specified by dims
+   Generate a random ``Float64`` array of the size specified by dims.
+
+.. function:: rand(BigFloat, dims or [dims...])
+
+   Generate a random ``BigFloat`` array of the size specified by dims.
 
 .. function:: rand(Int32|Uint32|Int64|Uint64|Int128|Uint128, [dims...])
 
@@ -3252,10 +3268,18 @@ Random number generateion in Julia uses the `Mersenne Twister library <http://ww
 
    Generate a normally-distributed random number with mean 0 and standard deviation 1. Optionally generate an array of normally-distributed random numbers.
 
+.. function:: randn(BigFloat, dims or [dims...])
+
+   Generate a normally-distributed random BigFloat with mean 0 and standard deviation 1. Optionally generate an array of normally-distributed random BigFloats.
+
 .. function:: randn!(A::Array{Float64,N})
 
    Fill the array A with normally-distributed (mean 0, standard deviation 1) random numbers. Also see the rand function.
 
+.. function:: randn!(A::Array{BigFloat,N})
+
+   Fill the array A with normally-distributed (mean 0, standard deviation 1) random BigFloats. Also see the rand function.
+
 .. function:: randsym(n)
 
    Generate a ``nxn`` symmetric array of normally-distributed random numbers with mean 0 and standard deviation 1.