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Revert "Merge branch 'bigrng' of github.com:andrioni/julia into andri…
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…oni-bigrng"

This reverts commit 4cc21ca, reversing
changes made to 4f9a2a9.
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@ViralBShah
ViralBShah committed Dec 25, 2013
1 parent ef3bece commit 1a8885b
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Showing 7 changed files with 11 additions and 232 deletions.
1 change: 0 additions & 1 deletion base/exports.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,6 @@ export
Bidiagonal,
BigFloat,
BigInt,
BigRNG,
BitArray,
BitMatrix,
BitVector,
Expand Down
87 changes: 2 additions & 85 deletions base/gmp.jl
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Original file line number Diff line number Diff line change
@@ -1,13 +1,13 @@
module GMP

export BigInt, BigRNG
export BigInt

import Base: *, +, -, /, <, <<, >>, >>>, <=, ==, >, >=, ^, (~), (&), (|), ($),
binomial, cmp, convert, div, divrem, factorial, fld, gcd, gcdx, lcm, mod,
ndigits, promote_rule, rem, show, isqrt, string, isprime, powermod,
widemul, sum, trailing_zeros, trailing_ones, count_ones, base, parseint,
serialize, deserialize, bin, oct, dec, hex, isequal, invmod,
prevpow2, nextpow2, ndigits0z, rand, rand!, srand
prevpow2, nextpow2, ndigits0z

type BigInt <: Integer
alloc::Cint
Expand Down Expand Up @@ -419,87 +419,4 @@ widemul{T<:Integer}(x::T, y::T) = BigInt(x)*BigInt(y)
prevpow2(x::BigInt) = x < 0 ? -prevpow2(-x) : (x <= 2 ? x : one(BigInt) << (ndigits(x, 2)-1))
nextpow2(x::BigInt) = x < 0 ? -nextpow2(-x) : (x <= 2 ? x : one(BigInt) << ndigits(x-1, 2))

# Random number generation
type BigRNG <: AbstractRNG
seed_alloc::Cint
seed_size::Cint
seed_d::Ptr{Void}
alg::Cint
alg_data::Ptr{Void}

function BigRNG()
randstate = new(zero(Cint), zero(Cint), C_NULL, zero(Cint), C_NULL)
# The default algorithm in GMP is currently MersenneTwister
ccall((:__gmp_randinit_default, :libgmp), Void, (Ptr{BigRNG},),
&randstate)
finalizer(randstate, BigRNG_clear)
randstate
end
end

# Initialize with seed
function BigRNG(seed::Uint64)
randstate = BigRNG()
ccall((:__gmp_randseed_ui, :libgmp), Void, (Ptr{BigRNG}, Culong),
&randstate, seed)
randstate
end
function BigRNG(seed::BigInt)
randstate = BigRNG()
ccall((:__gmp_randseed, :libgmp), Void, (Ptr{BigRNG}, Ptr{BigInt}),
&randstate, &seed)
randstate
end

function BigRNG_clear(x::BigRNG)
ccall((:__gmp_randclear, :libgmp), Void, (Ptr{BigRNG},), &x)
end

function rand(::Type{BigInt}, randstate::BigRNG, n::Integer)
m = convert(BigInt, n)
randu(randstate, m)
end

function rand(r::Range1{BigInt})
ulen = convert(BigInt, length(r))
convert(BigInt, first(r) + randu(ulen))
end

function rand!(r::Range1{BigInt}, A::Array{BigInt})
for i = 1:length(A)
A[i] = rand(r)
end
A
end

rand(r::Range1{BigInt}, dims::Dims) = rand!(r, Array(BigInt, dims))
rand(r::Range1{BigInt}, dims::Int...) = rand!(r, Array(BigInt, dims...))

function randu(randstate::BigRNG, k::BigInt)
z = BigInt()
ccall((:__gmpz_urandomm, :libgmp), Void,
(Ptr{BigInt}, Ptr{BigRNG}, Ptr{BigInt}), &z, &randstate, &k)
z
end
randu(k::BigInt) = randu(Base.Random.DEFAULT_BIGRNG, k)

srand(r::BigRNG, seed) = srand(r, convert(BigInt, seed))
function srand(randstate::BigRNG, seed::Vector{Uint32})
s = big(0)
for i in seed
s = s << 32 + i
end
srand(randstate, s)
end
function srand(randstate::BigRNG, seed::Uint64)
ccall((:__gmp_randseed_ui, :libgmp), Void, (Ptr{BigRNG}, Culong),
&randstate, seed)
return
end
function srand(randstate::BigRNG, seed::BigInt)
ccall((:__gmp_randseed, :libgmp), Void, (Ptr{BigRNG}, Ptr{BigInt}),
&randstate, &seed)
return
end

end # module
40 changes: 1 addition & 39 deletions base/mpfr.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -17,8 +17,7 @@ import
itrunc, eps, signbit, sin, cos, tan, sec, csc, cot, acos, asin, atan,
cosh, sinh, tanh, sech, csch, coth, acosh, asinh, atanh, atan2,
serialize, deserialize, inf, nan, hash, cbrt, typemax, typemin,
realmin, realmax, get_rounding, set_rounding,
rand, rand!, randn, randn!
realmin, realmax, get_rounding, set_rounding

import Base.Math.lgamma_r

Expand Down Expand Up @@ -733,41 +732,4 @@ function hash(x::BigFloat)
h
end

# RNG-related functions
function rand(::Type{BigFloat}, randstate::BigRNG)
z = BigFloat()
ccall((:mpfr_urandom,:libmpfr), Int32,
(Ptr{BigFloat}, Ptr{BigRNG}, Int32),
&z, &randstate, ROUNDING_MODE[end])
z
end
rand(::Type{BigFloat}) = rand(BigFloat, Base.Random.DEFAULT_BIGRNG)

function rand!(r::BigRNG, A::Array{BigFloat})
for i = 1:length(A)
A[i] = rand(BigFloat, r)
end
A
end
rand!(A::Array{BigFloat}) = rand!(Base.Random.DEFAULT_BIGRNG, A)

function randn(::Type{BigFloat}, randstate::BigRNG)
z = BigFloat()
ccall((:mpfr_grandom,:libmpfr), Int32,
(Ptr{BigFloat}, Ptr{BigFloat}, Ptr{BigRNG}, Int32),
&z, C_NULL, &randstate, ROUNDING_MODE[end])
z
end
randn(::Type{BigFloat}) = randn(BigFloat, Base.Random.DEFAULT_BIGRNG)
randn(::Type{BigFloat}, dims::Dims) = randn!(Array(BigFloat, dims))
randn(::Type{BigFloat}, dims::Int...) = randn!(Array(BigFloat, dims...))

function randn!(r::BigRNG, A::Array{BigFloat})
for i = 1:length(A)
A[i] = randn(BigFloat, r)
end
A
end
randn!(A::Array{BigFloat}) = randn!(Base.Random.DEFAULT_BIGRNG, A)

end #module
9 changes: 1 addition & 8 deletions base/random.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -54,8 +54,7 @@ function librandom_init()
seed = reinterpret(Uint64, time())
seed = bitmix(seed, uint64(getpid()))
try
@linux_only seed = bitmix(seed, parseint(Uint64, readall(`ifconfig` |> `sha1sum`)[1:40], 16))
@osx_only seed = bitmix(seed, parseint(Uint64, readall(`ifconfig` |> `shasum`)[1:40], 16))
seed = bitmix(seed, parseint(Uint64, readall(`ifconfig` |> `sha1sum`)[1:40], 16))
catch
# ignore
end
Expand All @@ -76,12 +75,6 @@ end
function srand(seed::Vector{Uint32})
global RANDOM_SEED = seed
dsfmt_gv_init_by_array(seed)
s = big(0)
for i in Base.Random.RANDOM_SEED
s = s << 32 + i
end
global DEFAULT_BIGRNG = BigRNG(s)
return
end
srand(n::Integer) = srand(make_seed(n))

Expand Down
52 changes: 3 additions & 49 deletions doc/helpdb.jl
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Expand Up @@ -4830,8 +4830,7 @@ 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 and the default BigRNG are
seeded.
not provided, the default global RNG is seeded.
"),

Expand All @@ -4843,24 +4842,9 @@ 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).
"),

("Random Numbers","Base","rand","rand(BigFloat)
Generate a \"BigFloat\" random number uniformly in [0,1).
Generate a \"Float64\" random number uniformly in [0,1)
"),

Expand All @@ -4880,24 +4864,9 @@ 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.
"),

("Random Numbers","Base","rand","rand(BigFloat, dims or [dims...])
Generate a random \"BigFloat\" array of the size specified by dims.
Generate a random \"Float64\" array of the size specified by dims
"),

Expand Down Expand Up @@ -4938,28 +4907,13 @@ 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
Expand Down
32 changes: 4 additions & 28 deletions doc/stdlib/base.rst
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Expand Up @@ -3263,27 +3263,19 @@ The `BigFloat` type implements arbitrary-precision floating-point aritmetic usin
Random Numbers
--------------

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.
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.

.. 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 and the default BigRNG are 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 is 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).

.. function:: rand(BigFloat)

Generate a ``BigFloat`` random number uniformly in [0,1).
Generate a ``Float64`` random number uniformly in [0,1)

.. function:: rand!([rng], A)

Expand All @@ -3293,17 +3285,9 @@ Random number generation in Julia uses the `Mersenne Twister library <http://www

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.

.. function:: rand(BigFloat, dims or [dims...])

Generate a random ``BigFloat`` array of the size specified by dims.
Generate a random ``Float64`` array of the size specified by dims

.. function:: rand(Int32|Uint32|Int64|Uint64|Int128|Uint128, [dims...])

Expand All @@ -3325,18 +3309,10 @@ Random number generation in Julia uses the `Mersenne Twister library <http://www

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.
Expand Down
22 changes: 0 additions & 22 deletions test/random.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -22,25 +22,3 @@ if sizeof(Int32) < sizeof(Int)
@test typeof(r) == Int32
@test -1 <= r <= typemax(Int32)
end

range = big(typemax(Int128)):(big(typemax(Int128)) + 10000)
@test rand(range) != rand(range)
@test big(typemax(Int128)) <= rand(range) <= big(typemax(Int128)) + 10000
r = rand(range, 1, 2)
@test size(r) == (1, 2)
@test typeof(r) == Matrix{BigInt}

srand(0)
r = rand(range)
f = rand(BigFloat)
srand(0)
@test rand(range) == r
@test rand(BigFloat) == f

@test rand(BigFloat) != rand(BigFloat)
@test 0.0 <= rand(BigFloat) < 1.0
@test typeof(rand(BigFloat)) == BigFloat

r = rand(BigFloat, 1, 3)
@test size(r) == (1, 3)
@test typeof(r) == Matrix{BigFloat}

3 comments on commit 1a8885b

@ViralBShah
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This worked once when I tried it on my mac, and works fine on linux. However, after seeing the travis failure, I tried it again on my mac, and could not get it to work. It fails while trying to build sys.ji. Reverting it restores the build.

@ViralBShah
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Cc: @andrioni

@andrioni
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Just got home, I'm going to check it now.

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