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Merge pull request fortran-lang#20 from fortran-lang/master
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‎README.md

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@@ -82,6 +82,12 @@ GCC Fortran (MSYS) | 10 | Windows Server 2019 | x86_64
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GCC Fortran (MinGW) | 10 | Windows Server 2019 | x86_64, i686
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Intel oneAPI classic | 2021.1 | Ubuntu 20.04 | x86_64
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The following combinations are known to work, but they are not tested in the CI:
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Name | Version | Platform | Architecture
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--- | --- | --- | ---
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GCC Fortran (MinGW) | 8.4.0, 9.3.0, 10.2.0 | Windows 10 | x86_64, i686
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We try to test as many available compilers and platforms as possible.
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A list of tested compilers which are currently not working and the respective issue are listed below.
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‎doc/specs/index.md

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@@ -19,6 +19,7 @@ This is and index/directory of the specifications (specs) for each new module/fe
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- [optval](./stdlib_optval.html) - Fallback value for optional arguments
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- [quadrature](./stdlib_quadrature.html) - Numerical integration
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- [stats](./stdlib_stats.html) - Descriptive Statistics
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- [stats_distribution_PRNG](./stdlib_stats_distribution_PRNG.html) - Probability Distributions random number generator
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## Missing specs
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‎doc/specs/stdlib_stats_distribution_PRNG.md

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---
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title: stats_distribution
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---
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# Statistical Distributions -- Pseudorandom Number Generator Module
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[TOC]
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## `random_seed` - set or get a value of seed to the probability distribution pseudorandom number generator
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### Status
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Experimental
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### Description
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Set or get the seed value before calling the probability distribution pseudorandom number generator for variates.
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### Syntax
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`call [[stdlib_stats_distribution_PRNG(module):random_seed(interface)]](put, get)`
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### Arguments
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`put`: argument has `intent(in)` and may be a scalar of type `integer`.
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`get`: argument has `intent(out)` and is a scalar of type `integer`.
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### Return value
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Return a scalar of type `integer`.
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### Example
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```fortran
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program demo_random_seed
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use stdlib_stats_distribution_PRNG, only : random_seed
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implicit none
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integer :: seed_put, seed_get
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seed_put = 1234567
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call random_seed(seed_put, seed_get) ! set and get current value of seed
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end program demo_random_seed
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```
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## `dist_rand` - Get a random integer with specified kind
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### Status
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Experimental
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### Description
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Generate an integer pseudorandom number in a specific range [-2^k, 2^k - 1] according to the input integer kind n. This pseudorandom number will be operated by bit opeartors instead of normal arithmetic operators.
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### Syntax
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`result = [[stdlib_stats_distribution_PRNG(module):dist_rand(interface)]](n)`
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### Arguments
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`n`: argument has `intent(in)` is a scalar of type `integer`.
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### Return value
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Return a scalar of type `integer`.
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### Example
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```fortran
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program demo_dist_rand
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use stdlib_stats_distribution_PRNG, only : dist_rand, random_seed
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implicit none
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integer :: put, get
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put = 135792468
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call random_seed(put, get) ! set and get current value of seed
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print *, dist_rand(1_int8) ! random integer in [-2^7, 2^7 - 1]
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! -90
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print *, dist_rand(1_int16) ! random integer in [-2^15, 2^15 - 1]
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! -32725
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print *, dist_rand(1_int32) ! random integer in [-2^31, 2^31 - 1]
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! -1601563881
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print *, dist_rand(1_int64) ! random integer in [-2^63, 2^63 - 1]
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! 180977695517992208
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end program demo_dist_rand
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```

‎src/CMakeLists.txt

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stdlib_quadrature.fypp
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stdlib_quadrature_trapz.fypp
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stdlib_quadrature_simps.fypp
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stdlib_stats_distribution_PRNG.fypp
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)
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‎src/Makefile.manual

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stdlib_stats_moment_all.fypp \
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stdlib_stats_moment_mask.fypp \
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stdlib_stats_moment_scalar.fypp \
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stdlib_stats_var.fypp
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stdlib_stats_var.fypp \
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stdlib_stats_distribution_PRNG.fypp
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SRC = f18estop.f90 \
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stdlib_ascii.f90 \
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stdlib_optval.o \
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stdlib_kinds.o \
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stdlib_stats.o
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stdlib_stats_distribution_PRNG.o: \
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stdlib_kinds.o \
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stdlib_error.o

‎src/stdlib_stats_distribution_PRNG.fypp

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#:include "common.fypp"
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module stdlib_stats_distribution_PRNG
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use stdlib_kinds, only: int8, int16, int32, int64
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use stdlib_error, only: error_stop
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implicit none
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private
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integer, parameter :: MAX_INT_BIT_SIZE = bit_size(1_int64)
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integer(int64) :: st(4) ! internal states for xoshiro256ss function
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integer(int64) :: si = 614872703977525537_int64 ! default seed value
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logical :: seed_initialized = .false.
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public :: random_seed
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public :: dist_rand
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interface dist_rand
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!! Version experimental
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!!
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!! Generation of random integers with different kinds
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!! ([Specification](../page/specs/stdlib_stats_distribution_PRNG.html#
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!! description))
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#:for k1, t1 in INT_KINDS_TYPES
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module procedure dist_rand_${t1[0]}$${k1}$
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#:endfor
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end interface dist_rand
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interface random_seed
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!! Version experimental
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!!
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!! Set seed value for random number generator
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!! ([Specification](../page/specs/stdlib_stats_distribution_PRNG.html#
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!! description))
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!!
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#:for k1, t1 in INT_KINDS_TYPES
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module procedure random_distribution_seed_${t1[0]}$${k1}$
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#:endfor
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end interface random_seed
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contains
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#:for k1, t1 in INT_KINDS_TYPES
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function dist_rand_${t1[0]}$${k1}$(n) result(res)
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!! Random integer generation for various kinds
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!! result = [-2^k, 2^k - 1], k = 7, 15, 31, 63, depending on input kind
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!! Result will be operated by bitwise operators to generate desired integer
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!! and real pseudorandom numbers
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!!
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${t1}$, intent(in) :: n
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${t1}$ :: res
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integer :: k
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k = MAX_INT_BIT_SIZE - bit_size(n)
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if(k < 0) call error_stop("Error(dist_rand): Integer bit size is" &
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//" greater than 64bit")
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res = shiftr(xoshiro256ss( ), k)
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end function dist_rand_${t1[0]}$${k1}$
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#:endfor
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function xoshiro256ss( ) result (res)
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! Generate random 64-bit integers
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! Written in 2018 by David Blackman and Sebastiano Vigna ([email protected])
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! http://prng.di.unimi.it/xoshiro256starstar.c
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!
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! This is xoshiro256** 1.0, one of our all-purpose, rock-solid
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! generators. It has excellent (sub-ns) speed, a state (256 bits) that is
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! large enough for any parallel application, and it passes all tests we
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! are aware of.
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!
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! The state must be seeded so that it is not everywhere zero. If you have
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! a 64-bit seed, we suggest to seed a splitmix64 generator and use its
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! output to fill st.
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!
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! Fortran 90 version translated from C by Jim-215-Fisher
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!
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integer(int64) :: res, t
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if(.not. seed_initialized) call random_distribution_seed_iint64(si,t)
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res = rol64(st(2) * 5, 7) * 9
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t = shiftl(st(2), 17)
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st(3) = ieor(st(3), st(1))
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st(4) = ieor(st(4), st(2))
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st(2) = ieor(st(2), st(3))
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st(1) = ieor(st(1), st(4))
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st(3) = ieor(st(3), t)
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st(4) = rol64(st(4), 45)
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end function xoshiro256ss
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pure function rol64(x, k) result(res)
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integer(int64), intent(in) :: x
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integer, intent(in) :: k
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integer(int64) :: t1, t2, res
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t1 = shiftr(x, (64 - k))
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t2 = shiftl(x, k)
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res = ior(t1, t2)
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end function rol64
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function splitmix64(s) result(res)
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! Written in 2015 by Sebastiano Vigna ([email protected])
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! This is a fixed-increment version of Java 8's SplittableRandom
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! generator.
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! See http://dx.doi.org/10.1145/2714064.2660195 and
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! http://docs.oracle.com/javase/8/docs/api/java/util/SplittableRandom.html
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!
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! It is a very fast generator passing BigCrush, and it can be useful if
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! for some reason you absolutely want 64 bits of state.
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!
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! Fortran 90 translated from C by Jim-215-Fisher
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!
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integer(int64) :: res
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integer(int64), intent(in), optional :: s
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integer(int64) :: int01 = -7046029254386353131_int64, &
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int02 = -4658895280553007687_int64, &
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int03 = -7723592293110705685_int64
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! Values are converted from C unsigned integer of 0x9e3779b97f4a7c15,
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! 0xbf58476d1ce4e5b9, 0x94d049bb133111eb
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if(present(s)) si = s
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res = si
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si = res + int01
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res = ieor(res, shiftr(res, 30)) * int02
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res = ieor(res, shiftr(res, 27)) * int03
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res = ieor(res, shiftr(res, 31))
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end function splitmix64
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#:for k1, t1 in INT_KINDS_TYPES
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subroutine random_distribution_seed_${t1[0]}$${k1}$(put, get)
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!! Set seed value for random number generator
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!!
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${t1}$, intent(in) :: put
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${t1}$, intent(out) :: get
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integer(int64) :: tmp
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integer :: i
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tmp = splitmix64(int(put, kind = int64))
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do i = 1, 10
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tmp = splitmix64( )
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end do
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do i = 1, 4
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tmp = splitmix64( )
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st(i) = tmp
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end do
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get = int(tmp, kind = ${k1}$)
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seed_initialized = .true.
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end subroutine random_distribution_seed_${t1[0]}$${k1}$
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#:endfor
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end module stdlib_stats_distribution_PRNG

‎src/tests/stats/CMakeLists.txt

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ADDTEST(rawmoment)
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ADDTEST(var)
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ADDTEST(varn)
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ADDTEST(distribution_PRNG)
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if(DEFINED CMAKE_MAXIMUM_RANK)
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if(${CMAKE_MAXIMUM_RANK} GREATER 7)

‎src/tests/stats/Makefile.manual

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PROGS_SRC = test_mean.f90 test_moment.f90 test_var.f90
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include ../Makefile.manual.test.mk
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PROGS_SRC = test_mean.f90 test_moment.f90 test_var.f90 \
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test_distribution_PRNG.f90
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include ../Makefile.manual.test.mk

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