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RandomPkg.vhd
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RandomPkg.vhd
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--
-- File Name : RandomPkg.vhd
-- Design Unit Name : RandomPkg
-- Revision : STANDARD VERSION
--
-- Maintainer : Jim Lewis email : [email protected]
-- Contributor(s) :
-- Jim Lewis email : [email protected]
-- *
--
-- * In writing procedures normal, poisson, the following sources were referenced :
-- Wikipedia
-- package rnd2 written by John Breen and Ken Christensen
-- package RNG written by Gnanasekaran Swaminathan
--
--
-- Description :
-- RandomPType, a protected type, defined to hold randomization RandomSeeds and
-- function methods to facilitate randomization with uniform and weighted
-- distributions
--
-- Developed for :
-- SynthWorks Design Inc.
-- VHDL Training Classes
-- 11898 SW 128th Ave. Tigard, Or 97223
-- http ://www.SynthWorks.com
--
-- Revision History :
-- Date Version Description
-- 12/2006 : 0.1 Initial revision
-- Numerous revisions for SynthWorks' Advanced VHDL Testbenches and Verification
-- 02/2009 : 1.0 First Public Released Version
-- 02/25/2009 1.1 Replaced reference to std_2008 with a reference to
-- ieee_proposed.standard_additions.all ;
-- 06/2010 1.2 Added Normal and Poisson distributions
-- 03/2011 2.0 Major clean-up. Moved RandomParmType and control to here
-- 07/2011 2.1 Bug fix to convenience functions for slv, unsigned, and signed.
-- 06/2012 2.2 Removed '_' in the name of subprograms FavorBig and FavorSmall
-- 04/2013 2013.04 Changed DistInt. Return array indices now match input
-- Better Min, Max error handling in Uniform, FavorBig, FavorSmall, Normal, Poisson
-- 5/2013 - Removed extra variable declaration in functions RandInt and RandReal
-- 5/2013 2013.05 Big vector randomization added overloading RandUnsigned, RandSlv, and RandSigned
-- Added NULL_RANGE_TYPE to minimize null range warnings
-- 1/2014 2014.01 Added RandTime, RandReal(set), RandIntV, RandRealV, RandTimeV
-- Made sort, revsort from SortListPkg_int visible via aliases
-- 1/2015 2015.01 Changed Assert/Report to Alert
-- 5/2015 2015.06 Revised Alerts to Alert(OSVVM_ALERTLOG_ID, ...) ;
--
-- Copyright (c) 2006 - 2015 by SynthWorks Design Inc. All rights reserved.
--
-- Verbatim copies of this source file may be used and
-- distributed without restriction.
--
-- This source file is free software ; you can redistribute it
-- and/or modify it under the terms of the ARTISTIC License
-- as published by The Perl Foundation ; either version 2.0 of
-- the License, or (at your option) any later version.
--
-- This source is distributed in the hope that it will be
-- useful, but WITHOUT ANY WARRANTY ; without even the implied
-- warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
-- PURPOSE. See the Artistic License for details.
--
-- You should have received a copy of the license with this source.
-- If not download it from,
-- http ://www.perlfoundation.org/artistic_license_2_0
--
use work.OsvvmGlobalPkg.all ;
use work.AlertLogPkg.all ;
use work.RandomBasePkg.all ;
use work.SortListPkg_int.all ;
use std.textio.all ;
library ieee ;
use ieee.std_logic_1164.all ;
use ieee.numeric_std.all ;
use ieee.numeric_std_unsigned.all ;
use ieee.math_real.all ;
-- comment out following 3 lines with VHDL-2008. Leave in for VHDL-2002
-- library ieee_proposed ; -- remove with VHDL-2008
-- use ieee_proposed.standard_additions.all ; -- remove with VHDL-2008
-- use ieee_proposed.standard_textio_additions.all ; -- remove with VHDL-2008
package RandomPkg is
-- Uncomment the following with VHDL-2008 package generics.
-- For now they are defined in the package RandomBasePkg.vhd
-- package RandomGenericPkg is
-- generic (
-- type RandomSeedType ; -- base type for randomization
-- procedure Uniform (Result : out real ; Seed : inout RandomSeedType) ;
-- function GenRandSeed(IV : integer_vector) return RandomSeedType ;
-- function GenRandSeed(I : integer) return RandomSeedType ;
-- function GenRandSeed(S : string) return RandomSeedType ;
-- ) ;
-- make things from SortListPkg_int visible
alias sort is work.SortListPkg_int.sort[integer_vector return integer_vector] ;
alias revsort is work.SortListPkg_int.revsort[integer_vector return integer_vector] ;
-- note NULL_RANGE_TYPE should probably be in std.standard
subtype NULL_RANGE_TYPE is integer range 0 downto 1 ;
constant NULL_INTV : integer_vector (NULL_RANGE_TYPE) := (others => 0) ;
-- Supports DistValInt functionality
type DistRecType is record
Value : integer ;
Weight : integer ;
end record ;
type DistType is array (natural range <>) of DistRecType ;
-- Parameters for randomization
-- RandomDistType specifies the distribution to use for randomize
type RandomDistType is (NONE, UNIFORM, FAVOR_SMALL, FAVOR_BIG, NORMAL, POISSON) ;
type RandomParmType is record
Distribution : RandomDistType ;
Mean : Real ; -- also used as probability of success
StdDeviation : Real ; -- also used as number of trials for binomial
end record ;
-- RandomParm IO
function to_string(A : RandomDistType) return string ;
procedure write(variable L : inout line ; A : RandomDistType ) ;
procedure read(variable L : inout line ; A : out RandomDistType ; good : out boolean ) ;
procedure read(variable L : inout line ; A : out RandomDistType ) ;
function to_string(A : RandomParmType) return string ;
procedure write(variable L : inout line ; A : RandomParmType ) ;
procedure read(variable L : inout line ; A : out RandomParmType ; good : out boolean ) ;
procedure read(variable L : inout line ; A : out RandomParmType ) ;
type RandomPType is protected
-- Seed Manipulation
-- Known ambiguity between InitSeed with string and integer_vector
-- Recommendation, use : RV.InitSeed(RV'instance_path) ;
-- For integer_vector use either : RV.InitSeed(IV => (1,5)) ;
-- or : RV.InitSeed(integer_vector'(1,5)) ;
procedure InitSeed (S : string ) ;
procedure InitSeed (I : integer ) ;
procedure InitSeed (IV : integer_vector ) ;
-- SetSeed & GetSeed : Used to save and restore seed values
procedure SetSeed (RandomSeedIn : RandomSeedType ) ;
impure function GetSeed return RandomSeedType ;
-- SeedRandom = SetSeed & GetSeed for SV compatibility
-- replace with aliases when they work in popular simulators
procedure SeedRandom (RandomSeedIn : RandomSeedType ) ;
impure function SeedRandom return RandomSeedType ;
-- alias SeedRandom is SetSeed [RandomSeedType] ;
-- alias SeedRandom is GetSeed [return RandomSeedType] ;
-- Setting Randomization Parameters
-- Allows RandInt to have distributions other than uniform
procedure SetRandomParm (RandomParmIn : RandomParmType) ;
procedure SetRandomParm (
Distribution : RandomDistType ;
Mean : Real := 0.0 ;
Deviation : Real := 0.0
) ;
impure function GetRandomParm return RandomParmType ;
impure function GetRandomParm return RandomDistType ;
-- For compatibility with previous version - replace with alias
procedure SetRandomMode (RandomDistIn : RandomDistType) ;
-- alias SetRandomMode is SetRandomParm [RandomDistType, Real, Real] ;
-- Base Randomization Distributions
-- Uniform : Generate a random number with a Uniform distribution
impure function Uniform (Min, Max : in real) return real ;
impure function Uniform (Min, Max : integer) return integer ;
impure function Uniform (Min, Max : integer ; Exclude : integer_vector) return integer ;
-- FavorSmall
-- Generate random numbers with a greater number of small
-- values than large values
impure function FavorSmall (Min, Max : real) return real ;
impure function FavorSmall (Min, Max : integer) return integer ;
impure function FavorSmall (Min, Max : integer ; Exclude : integer_vector) return integer ;
-- FavorBig
-- Generate random numbers with a greater number of large
-- values than small values
impure function FavorBig (Min, Max : real) return real ;
impure function FavorBig (Min, Max : integer) return integer ;
impure function FavorBig (Min, Max : integer ; Exclude : integer_vector) return integer ;
-- Normal : Generate a random number with a normal distribution
impure function Normal (Mean, StdDeviation : real) return real ;
-- Normal + RandomVal >= Min and RandomVal < Max
impure function Normal (Mean, StdDeviation, Min, Max : real) return real ;
impure function Normal (
Mean : real ;
StdDeviation : real ;
Min : integer ;
Max : integer ;
Exclude : integer_vector := NULL_INTV
) return integer ;
-- Poisson : Generate a random number with a poisson distribution
-- Discrete distribution = only generates integral values
impure function Poisson (Mean : real) return real ;
-- Poisson + RandomVal >= Min and RandomVal < Max
impure function Poisson (Mean, Min, Max : real) return real ;
impure function Poisson (
Mean : real ;
Min : integer ;
Max : integer ;
Exclude : integer_vector := NULL_INTV
) return integer ;
-- randomization with a range
impure function RandInt (Min, Max : integer) return integer ;
impure function RandReal(Min, Max : Real) return real ;
impure function RandTime (Min, Max : time ; Unit : time := ns) return time ;
impure function RandSlv (Min, Max, Size : natural) return std_logic_vector ;
impure function RandUnsigned (Min, Max, Size : natural) return Unsigned ;
impure function RandSigned (Min, Max : integer ; Size : natural ) return Signed ;
impure function RandIntV (Min, Max : integer ; Size : natural) return integer_vector ;
impure function RandIntV (Min, Max : integer ; Unique : natural ; Size : natural) return integer_vector ;
impure function RandRealV (Min, Max : real ; Size : natural) return real_vector ;
impure function RandTimeV (Min, Max : time ; Size : natural ; Unit : time := ns) return time_vector ;
impure function RandTimeV (Min, Max : time ; Unique : natural ; Size : natural ; Unit : time := ns) return time_vector ;
-- randomization with a range and exclude vector
impure function RandInt (Min, Max : integer ; Exclude : integer_vector ) return integer ;
impure function RandTime (Min, Max : time ; Exclude : time_vector ; Unit : time := ns) return time ;
impure function RandSlv (Min, Max : natural ; Exclude : integer_vector ; Size : natural ) return std_logic_vector ;
impure function RandUnsigned (Min, Max : natural ; Exclude : integer_vector ; Size : natural ) return Unsigned ;
impure function RandSigned (Min, Max : integer ; Exclude : integer_vector ; Size : natural ) return Signed ;
impure function RandIntV (Min, Max : integer ; Exclude : integer_vector ; Size : natural) return integer_vector ;
impure function RandIntV (Min, Max : integer ; Exclude : integer_vector ; Unique : natural ; Size : natural) return integer_vector ;
impure function RandTimeV (Min, Max : time ; Exclude : time_vector ; Size : natural ; Unit : in time := ns) return time_vector ;
impure function RandTimeV (Min, Max : time ; Exclude : time_vector ; Unique : natural ; Size : natural ; Unit : in time := ns) return time_vector ;
-- Randomly select a value within a set of values
impure function RandInt ( A : integer_vector ) return integer ;
impure function RandReal ( A : real_vector ) return real ;
impure function RandTime (A : time_vector) return time ;
impure function RandSlv (A : integer_vector ; Size : natural) return std_logic_vector ;
impure function RandUnsigned (A : integer_vector ; Size : natural) return Unsigned ;
impure function RandSigned (A : integer_vector ; Size : natural ) return Signed ;
impure function RandIntV (A : integer_vector ; Size : natural) return integer_vector ;
impure function RandIntV (A : integer_vector ; Unique : natural ; Size : natural) return integer_vector ;
impure function RandRealV (A : real_vector ; Size : natural) return real_vector ;
impure function RandRealV (A : real_vector ; Unique : natural ; Size : natural) return real_vector ;
impure function RandTimeV (A : time_vector ; Size : natural) return time_vector ;
impure function RandTimeV (A : time_vector ; Unique : natural ; Size : natural) return time_vector ;
-- Randomly select a value within a set of values with exclude values (so can skip last or last n)
impure function RandInt ( A, Exclude : integer_vector ) return integer ;
impure function RandReal ( A, Exclude : real_vector ) return real ;
impure function RandTime (A, Exclude : time_vector) return time ;
impure function RandSlv (A, Exclude : integer_vector ; Size : natural) return std_logic_vector ;
impure function RandUnsigned (A, Exclude : integer_vector ; Size : natural) return Unsigned ;
impure function RandSigned (A, Exclude : integer_vector ; Size : natural ) return Signed ;
impure function RandIntV (A, Exclude : integer_vector ; Size : natural) return integer_vector ;
impure function RandIntV (A, Exclude : integer_vector ; Unique : natural ; Size : natural) return integer_vector ;
impure function RandRealV (A, Exclude : real_vector ; Size : natural) return real_vector ;
impure function RandRealV (A, Exclude : real_vector ; Unique : natural ; Size : natural) return real_vector ;
impure function RandTimeV (A, Exclude : time_vector ; Size : natural) return time_vector ;
impure function RandTimeV (A, Exclude : time_vector ; Unique : natural ; Size : natural) return time_vector ;
-- Randomly select between 0 and N-1 based on the specified weight.
-- where N = number values in weight array
impure function DistInt ( Weight : integer_vector ) return integer ;
impure function DistSlv ( Weight : integer_vector ; Size : natural ) return std_logic_vector ;
impure function DistUnsigned ( Weight : integer_vector ; Size : natural ) return unsigned ;
impure function DistSigned ( Weight : integer_vector ; Size : natural ) return signed ;
-- Distribution with just weights and with exclude values
impure function DistInt ( Weight : integer_vector ; Exclude : integer_vector ) return integer ;
impure function DistSlv ( Weight : integer_vector ; Exclude : integer_vector ; Size : natural ) return std_logic_vector ;
impure function DistUnsigned ( Weight : integer_vector ; Exclude : integer_vector ; Size : natural ) return unsigned ;
impure function DistSigned ( Weight : integer_vector ; Exclude : integer_vector ; Size : natural ) return signed ;
-- Distribution with weight and value
impure function DistValInt ( A : DistType ) return integer ;
impure function DistValSlv ( A : DistType ; Size : natural) return std_logic_vector ;
impure function DistValUnsigned ( A : DistType ; Size : natural) return unsigned ;
impure function DistValSigned ( A : DistType ; Size : natural) return signed ;
-- Distribution with weight and value and with exclude values
impure function DistValInt ( A : DistType ; Exclude : integer_vector ) return integer ;
impure function DistValSlv ( A : DistType ; Exclude : integer_vector ; Size : natural) return std_logic_vector ;
impure function DistValUnsigned ( A : DistType ; Exclude : integer_vector ; Size : natural) return unsigned ;
impure function DistValSigned ( A : DistType ; Exclude : integer_vector ; Size : natural) return signed ;
-- Large vector handling.
impure function RandUnsigned (Size : natural) return unsigned ;
impure function RandSlv (Size : natural) return std_logic_vector ;
impure function RandSigned (Size : natural) return signed ;
impure function RandUnsigned (Max : Unsigned) return unsigned ;
impure function RandSlv (Max : std_logic_vector) return std_logic_vector ;
impure function RandSigned (Max : signed) return signed ;
impure function RandUnsigned (Min, Max : unsigned) return unsigned ;
impure function RandSlv (Min, Max : std_logic_vector) return std_logic_vector ;
impure function RandSigned (Min, Max : signed) return signed ;
-- Convenience Functions
impure function RandReal return real ; -- 0.0 to 1.0
impure function RandReal(Max : Real) return real ; -- 0.0 to Max
impure function RandInt (Max : integer) return integer ;
impure function RandSlv (Max, Size : natural) return std_logic_vector ;
impure function RandUnsigned (Max, Size : natural) return Unsigned ;
impure function RandSigned (Max : integer ; Size : natural ) return Signed ;
end protected RandomPType ;
end RandomPkg ;
--- ///////////////////////////////////////////////////////////////////////////
--- ///////////////////////////////////////////////////////////////////////////
--- ///////////////////////////////////////////////////////////////////////////
package body RandomPkg is
-----------------------------------------------------------------
-- Local Randomization Support
-----------------------------------------------------------------
constant NULL_SLV : std_logic_vector (NULL_RANGE_TYPE) := (others => '0') ;
constant NULL_UV : unsigned (NULL_RANGE_TYPE) := (others => '0') ;
constant NULL_SV : signed (NULL_RANGE_TYPE) := (others => '0') ;
-----------------------------------------------------------------
-- Scale -- Scale a value to be within a given range
--
function Scale (A, Min, Max : real) return real is
variable ValRange : Real ;
begin
if Max >= Min then
ValRange := Max - Min ;
return A * ValRange + Min ;
else
return real'left ;
end if ;
end function Scale ;
function Scale (A : real ; Min, Max : integer) return integer is
variable ValRange : real ;
variable rMin, rMax : real ;
begin
if Max >= Min then
rMin := real(Min) - 0.5 ;
rMax := real(Max) + 0.5 ;
ValRange := rMax - rMin ;
return integer(round(A * ValRange + rMin)) ;
else
return integer'left ;
end if ;
end function Scale ;
-- create more smaller values
function FavorSmall (A : real) return real is
begin
return 1.0 - sqrt(A) ;
end FavorSmall ;
-- create more larger values
-- alias FavorBig is sqrt[real return real] ;
function FavorBig (A : real) return real is
begin
return sqrt(A) ;
end FavorBig ;
-- local.
function to_time_vector (A : integer_vector ; Unit : time) return time_vector is
variable result : time_vector(A'range) ;
begin
for i in A'range loop
result(i) := A(i) * Unit ;
end loop ;
return result ;
end function to_time_vector ;
-- local
function to_integer_vector (A : time_vector ; Unit : time) return integer_vector is
variable result : integer_vector(A'range) ;
begin
for i in A'range loop
result(i) := A(i) / Unit ;
end loop ;
return result ;
end function to_integer_vector ;
-- Local. Remove the exclude list from the list - integer_vector
procedure RemoveExclude(A, Exclude : integer_vector ; variable NewA : out integer_vector ; variable NewALength : inout natural ) is
alias norm_NewA : integer_vector(1 to NewA'length) is NewA ;
begin
NewALength := 0 ;
for i in A'range loop
if not inside(A(i), Exclude) then
NewALength := NewALength + 1 ;
norm_NewA(NewALength) := A(i) ;
end if ;
end loop ;
end procedure RemoveExclude ;
-- Local. Inside - real_vector
function inside(A : real ; Exclude : real_vector) return boolean is
begin
for i in Exclude'range loop
if A = Exclude(i) then
return TRUE ;
end if ;
end loop ;
return FALSE ;
end function inside ;
-- Local. Remove the exclude list from the list - real_vector
procedure RemoveExclude(A, Exclude : real_vector ; variable NewA : out real_vector ; variable NewALength : inout natural ) is
alias norm_NewA : real_vector(1 to NewA'length) is NewA ;
begin
NewALength := 0 ;
for i in A'range loop
if not inside(A(i), Exclude) then
NewALength := NewALength + 1 ;
norm_NewA(NewALength) := A(i) ;
end if ;
end loop ;
end procedure RemoveExclude ;
-- Local. Inside - time_vector
function inside(A : time ; Exclude : time_vector) return boolean is
begin
for i in Exclude'range loop
if A = Exclude(i) then
return TRUE ;
end if ;
end loop ;
return FALSE ;
end function inside ;
-- Local. Remove the exclude list from the list - time_vector
procedure RemoveExclude(A, Exclude : time_vector ; variable NewA : out time_vector ; variable NewALength : inout natural ) is
alias norm_NewA : time_vector(1 to NewA'length) is NewA ;
begin
NewALength := 0 ;
for i in A'range loop
if not inside(A(i), Exclude) then
NewALength := NewALength + 1 ;
norm_NewA(NewALength) := A(i) ;
end if ;
end loop ;
end procedure RemoveExclude ;
-----------------------------------------------------------------
-- RandomParmType IO
-----------------------------------------------------------------
-----------------------------------------------------------------
function to_string(A : RandomDistType) return string is
begin
return RandomDistType'image(A) ;
end function to_string ;
-----------------------------------------------------------------
procedure write(variable L : inout line ; A : RandomDistType ) is
begin
write(L, to_string(A)) ;
end procedure write ;
-----------------------------------------------------------------
procedure read(variable L : inout line ; A : out RandomDistType ; good : out boolean ) is
variable strval : string(1 to 40) ;
variable len : natural ;
begin
-- procedure SREAD (L : inout LINE ; VALUE : out STRING ; STRLEN : out NATURAL) ;
sread(L, strval, len) ;
A := RandomDistType'value(strval(1 to len)) ;
good := len > 0 ;
end procedure read ;
-----------------------------------------------------------------
procedure read(variable L : inout line ; A : out RandomDistType ) is
variable ReadValid : boolean ;
begin
read(L, A, ReadValid) ;
AlertIfNot( OSVVM_ALERTLOG_ID, ReadValid, "RandomPkg.read[line, RandomDistType] failed", FAILURE) ;
end procedure read ;
-----------------------------------------------------------------
function to_string(A : RandomParmType) return string is
begin
return RandomDistType'image(A.Distribution) & " " &
to_string(A.Mean, 2) & " " & to_string(A.StdDeviation, 2) ;
end function to_string ;
-----------------------------------------------------------------
procedure write(variable L : inout line ; A : RandomParmType ) is
begin
write(L, to_string(A)) ;
end procedure write ;
-----------------------------------------------------------------
procedure read(variable L : inout line ; A : out RandomParmType ; good : out boolean ) is
variable strval : string(1 to 40) ;
variable len : natural ;
variable igood : boolean ;
begin
loop
-- procedure SREAD (L : inout LINE ; VALUE : out STRING ; STRLEN : out NATURAL) ;
sread(L, strval, len) ;
A.Distribution := RandomDistType'value(strval(1 to len)) ;
igood := len > 0 ;
exit when not igood ;
read(L, A.Mean, igood) ;
exit when not igood ;
read(L, A.StdDeviation, igood) ;
exit ;
end loop ;
good := igood ;
end procedure read ;
-----------------------------------------------------------------
procedure read(variable L : inout line ; A : out RandomParmType ) is
variable ReadValid : boolean ;
begin
read(L, A, ReadValid) ;
AlertIfNot( OSVVM_ALERTLOG_ID, ReadValid, "RandomPkg.read[line, RandomParmType] failed", FAILURE) ;
end procedure read ;
-----------------------------------------------------------------
-----------------------------------------------------------------
type RandomPType is protected body
--
-- RandomSeed manipulation
--
variable RandomSeed : RandomSeedType := GenRandSeed(integer_vector'(1,7)) ;
procedure InitSeed (S : string ) is
begin
RandomSeed := GenRandSeed(S) ;
end procedure InitSeed ;
procedure InitSeed (I : integer ) is
begin
RandomSeed := GenRandSeed(I) ;
end procedure InitSeed ;
procedure InitSeed (IV : integer_vector ) is
begin
RandomSeed := GenRandSeed(IV) ;
end procedure InitSeed ;
procedure SetSeed (RandomSeedIn : RandomSeedType ) is
begin
RandomSeed := RandomSeedIn ;
end procedure SetSeed ;
procedure SeedRandom (RandomSeedIn : RandomSeedType ) is
begin
RandomSeed := RandomSeedIn ;
end procedure SeedRandom ;
impure function GetSeed return RandomSeedType is
begin
return RandomSeed ;
end function GetSeed ;
impure function SeedRandom return RandomSeedType is
begin
return RandomSeed ;
end function SeedRandom ;
--
-- randomization mode
--
variable RandomParm : RandomParmType ; -- left most values ok for init
procedure SetRandomParm (RandomParmIn : RandomParmType) is
begin
RandomParm := RandomParmIn ;
end procedure SetRandomParm ;
procedure SetRandomParm (
Distribution : RandomDistType ;
Mean : Real := 0.0 ;
Deviation : Real := 0.0
) is
begin
RandomParm := RandomParmType'(Distribution, Mean, Deviation) ;
end procedure SetRandomParm ;
impure function GetRandomParm return RandomParmType is
begin
return RandomParm ;
end function GetRandomParm ;
impure function GetRandomParm return RandomDistType is
begin
return RandomParm.Distribution ;
end function GetRandomParm ;
-- For compatibility with previous version
procedure SetRandomMode (RandomDistIn : RandomDistType) is
begin
SetRandomParm(RandomDistIn) ;
end procedure SetRandomMode ;
--
-- Base Randomization Distributions
--
--
-- Uniform : Generate a random number with a Uniform distribution
--
impure function Uniform (Min, Max : in real) return real is
variable rRandomVal : real ;
begin
AlertIf (OSVVM_ALERTLOG_ID, Max < Min, "RandomPkg.Uniform: Max < Min", FAILURE) ;
Uniform(rRandomVal, RandomSeed) ;
return scale(rRandomVal, Min, Max) ;
end function Uniform ;
impure function Uniform (Min, Max : integer) return integer is
variable rRandomVal : real ;
begin
AlertIf (OSVVM_ALERTLOG_ID, Max < Min, "RandomPkg.Uniform: Max < Min", FAILURE) ;
Uniform(rRandomVal, RandomSeed) ;
return scale(rRandomVal, Min, Max) ;
end function Uniform ;
impure function Uniform (Min, Max : integer ; Exclude : integer_vector) return integer is
variable iRandomVal : integer ;
variable ExcludeList : SortListPType ;
variable count : integer ;
begin
ExcludeList.add(Exclude, Min, Max) ;
count := ExcludeList.count ;
iRandomVal := Uniform(Min, Max - count) ;
-- adjust count, note iRandomVal changes while checking.
for i in 1 to count loop
exit when iRandomVal < ExcludeList.Get(i) ;
iRandomVal := iRandomVal + 1 ;
end loop ;
ExcludeList.erase ;
return iRandomVal ;
end function Uniform ;
--
-- FavorSmall
-- Generate random numbers with a greater number of small
-- values than large values
--
impure function FavorSmall (Min, Max : real) return real is
variable rRandomVal : real ;
begin
AlertIf (OSVVM_ALERTLOG_ID, Max < Min, "RandomPkg.FavorSmall: Max < Min", FAILURE) ;
Uniform(rRandomVal, RandomSeed) ;
return scale(FavorSmall(rRandomVal), Min, Max) ; -- real
end function FavorSmall ;
impure function FavorSmall (Min, Max : integer) return integer is
variable rRandomVal : real ;
begin
AlertIf (OSVVM_ALERTLOG_ID, Max < Min, "RandomPkg.FavorSmall: Max < Min", FAILURE) ;
Uniform(rRandomVal, RandomSeed) ;
return scale(FavorSmall(rRandomVal), Min, Max) ; -- integer
end function FavorSmall ;
impure function FavorSmall (Min, Max : integer ; Exclude : integer_vector) return integer is
variable iRandomVal : integer ;
variable ExcludeList : SortListPType ;
variable count : integer ;
begin
ExcludeList.add(Exclude, Min, Max) ;
count := ExcludeList.count ;
iRandomVal := FavorSmall(Min, Max - count) ;
-- adjust count, note iRandomVal changes while checking.
for i in 1 to count loop
exit when iRandomVal < ExcludeList.Get(i) ;
iRandomVal := iRandomVal + 1 ;
end loop ;
ExcludeList.erase ;
return iRandomVal ;
end function FavorSmall ;
--
-- FavorBig
-- Generate random numbers with a greater number of large
-- values than small values
--
impure function FavorBig (Min, Max : real) return real is
variable rRandomVal : real ;
begin
AlertIf (OSVVM_ALERTLOG_ID, Max < Min, "RandomPkg.FavorBig: Max < Min", FAILURE) ;
Uniform(rRandomVal, RandomSeed) ;
return scale(FavorBig(rRandomVal), Min, Max) ; -- real
end function FavorBig ;
impure function FavorBig (Min, Max : integer) return integer is
variable rRandomVal : real ;
begin
AlertIf (OSVVM_ALERTLOG_ID, Max < Min, "RandomPkg.FavorBig: Max < Min", FAILURE) ;
Uniform(rRandomVal, RandomSeed) ;
return scale(FavorBig(rRandomVal), Min, Max) ; -- integer
end function FavorBig ;
impure function FavorBig (Min, Max : integer ; Exclude : integer_vector) return integer is
variable iRandomVal : integer ;
variable ExcludeList : SortListPType ;
variable count : integer ;
begin
ExcludeList.add(Exclude, Min, Max) ;
count := ExcludeList.count ;
iRandomVal := FavorBig(Min, Max - count) ;
-- adjust count, note iRandomVal changes while checking.
for i in 1 to count loop
exit when iRandomVal < ExcludeList.Get(i) ;
iRandomVal := iRandomVal + 1 ;
end loop ;
ExcludeList.erase ;
return iRandomVal ;
end function FavorBig ;
-----------------------------------------------------------------
-- Normal
-- Generate a random number with a normal distribution
--
-- Use Box Muller, per Wikipedia :
-- http ://en.wikipedia.org/wiki/Box%E2%80%93Muller_transform
--
-- Use polar method, per Wikipedia :
-- http ://en.wikipedia.org/wiki/Marsaglia_polar_method
--
impure function Normal (Mean, StdDeviation : real) return real is
variable x01, y01 : real ;
variable StdNormalDist : real ; -- mean 0, variance 1
begin
-- add this check to set parameters?
if StdDeviation < 0.0 then
Alert(OSVVM_ALERTLOG_ID, "RandomPkg.Normal: Standard deviation must be >= 0.0", FAILURE) ;
return -1.0 ;
end if ;
-- Box Muller
Uniform (x01, RandomSeed) ;
Uniform (y01, RandomSeed) ;
StdNormalDist := sqrt(-2.0 * log(x01)) * cos(math_2_pi*y01) ;
-- Polar form rejected due to mean 50.0, std deviation = 5 resulted
-- in a median of 49
-- -- find two Uniform distributed values with range -1 to 1
-- -- that satisify S = X **2 + Y**2 < 1.0
-- loop
-- Uniform (x01, RandomSeed) ;
-- Uniform (y01, RandomSeed) ;
-- x := 2.0 * x01 - 1.0 ; -- scale to -1 to 1
-- y := 2.0 * y01 - 1.0 ;
-- s := x*x + y*y ;
-- exit when s < 1.0 and s > 0.0 ;
-- end loop ;
-- -- Calculate Standard Normal Distribution
-- StdNormalDist := x * sqrt((-2.0 * log(s)) / s) ;
-- Convert to have Mean and StdDeviation
return StdDeviation * StdNormalDist + Mean ;
end function Normal ;
-- Normal + RandomVal >= Min and RandomVal <= Max
impure function Normal (Mean, StdDeviation, Min, Max : real) return real is
variable rRandomVal : real ;
begin
if Max < Min then
Alert(OSVVM_ALERTLOG_ID, "RandomPkg.Normal: Max < Min", FAILURE) ;
return Mean ;
else
loop
rRandomVal := Normal (Mean, StdDeviation) ;
exit when rRandomVal >= Min and rRandomVal <= Max ;
end loop ;
end if ;
return rRandomVal ;
end function Normal ;
-- Normal + RandomVal >= Min and RandomVal <= Max
impure function Normal (
Mean : real ;
StdDeviation : real ;
Min : integer ;
Max : integer ;
Exclude : integer_vector := NULL_INTV
) return integer is
variable iRandomVal : integer ;
begin
if Max < Min then
Alert(OSVVM_ALERTLOG_ID, "RandomPkg.Normal: Max < Min", FAILURE) ;
return integer(round(Mean)) ;
else
loop
iRandomVal := integer(round( Normal(Mean, StdDeviation) )) ;
exit when iRandomVal >= Min and iRandomVal <= Max and
not inside(iRandomVal, Exclude) ;
end loop ;
end if ;
return iRandomVal ;
end function Normal ;
-----------------------------------------------------------------
-- Poisson
-- Generate a random number with a poisson distribution
-- Discrete distribution = only generates integral values
--
-- Use knuth method, per Wikipedia :
-- http ://en.wikipedia.org/wiki/Poisson_distribution
--
impure function Poisson (Mean : real) return real is
variable Product : Real := 1.0 ;
variable Bound : Real := 0.0 ;
variable UniformRand : Real := 0.0 ;
variable PoissonRand : Real := 0.0 ;
begin
Bound := exp(-1.0 * Mean) ;
Product := 1.0 ;
-- add this check to set parameters?
if Mean <= 0.0 or Bound <= 0.0 then
Alert(OSVVM_ALERTLOG_ID, "RandomPkg.Poisson: Mean < 0 or too large. Mean = " & real'image(Mean), FAILURE) ;
return Mean ;
end if ;
while (Product >= Bound) loop
PoissonRand := PoissonRand + 1.0 ;
Uniform(UniformRand, RandomSeed) ;
Product := Product * UniformRand ;
end loop ;
return PoissonRand ;
end function Poisson ; -- no range
-- Poisson + RandomVal >= Min and RandomVal < Max
impure function Poisson (Mean, Min, Max : real) return real is
variable rRandomVal : real ;
begin
if Max < Min then
Alert(OSVVM_ALERTLOG_ID, "RandomPkg.Poisson: Max < Min", FAILURE) ;
return Mean ;
else
loop
rRandomVal := Poisson (Mean) ;
exit when rRandomVal >= Min and rRandomVal <= Max ;
end loop ;
end if ;
return rRandomVal ;
end function Poisson ;
impure function Poisson (
Mean : real ;
Min : integer ;
Max : integer ;
Exclude : integer_vector := NULL_INTV
) return integer is
variable iRandomVal : integer ;
begin
if Max < Min then
Alert(OSVVM_ALERTLOG_ID, "RandomPkg.Poisson: Max < Min", FAILURE) ;
return integer(round(Mean)) ;
else
loop
iRandomVal := integer(round( Poisson (Mean) )) ;
exit when iRandomVal >= Min and iRandomVal <= Max and
not inside(iRandomVal, Exclude) ;
end loop ;
end if ;
return iRandomVal ;
end function Poisson ;
--
-- integer randomization with a range
-- Distribution determined by RandomParm
--
impure function RandInt (Min, Max : integer) return integer is
begin
case RandomParm.Distribution is
when NONE | UNIFORM => return Uniform(Min, Max) ;
when FAVOR_SMALL => return FavorSmall(Min, Max) ;
when FAVOR_BIG => return FavorBig (Min, Max) ;
when NORMAL => return Normal(RandomParm.Mean, RandomParm.StdDeviation, Min, Max) ;
when POISSON => return Poisson(RandomParm.Mean, Min, Max) ;
when others =>
Alert(OSVVM_ALERTLOG_ID, "RandomPkg.RandInt: RandomParm.Distribution not implemented", FAILURE) ;
return integer'low ;
end case ;
end function RandInt ;
--
-- real randomization with a range
-- Distribution determined by RandomParm
--
impure function RandReal(Min, Max : Real) return real is
begin
case RandomParm.Distribution is
when NONE | UNIFORM => return Uniform(Min, Max) ;
when FAVOR_SMALL => return FavorSmall(Min, Max) ;
when FAVOR_BIG => return FavorBig (Min, Max) ;
when NORMAL => return Normal(RandomParm.Mean, RandomParm.StdDeviation, Min, Max) ;
when POISSON => return Poisson(RandomParm.Mean, Min, Max) ;
when others =>
Alert(OSVVM_ALERTLOG_ID, "RandomPkg.RandReal: Specified RandomParm.Distribution not implemented", FAILURE) ;
return real(integer'low) ;
end case ;
end function RandReal ;
impure function RandTime (Min, Max : time ; Unit :time := ns) return time is
variable IntVal : integer ;
begin
-- if Max - Min > 2**31 result will be out of range
IntVal := RandInt(0, (Max - Min)/Unit) ;
Return Min + Unit*IntVal ;
end function RandTime ;
impure function RandSlv (Min, Max, Size : natural) return std_logic_vector is
begin
return std_logic_vector(to_unsigned(RandInt(Min, Max), Size)) ;
end function RandSlv ;
impure function RandUnsigned (Min, Max, Size : natural) return Unsigned is
begin
return to_unsigned(RandInt(Min, Max), Size) ;
end function RandUnsigned ;
impure function RandSigned (Min, Max : integer ; Size : natural ) return Signed is
begin
return to_signed(RandInt(Min, Max), Size) ;
end function RandSigned ;
impure function RandIntV (Min, Max : integer ; Size : natural) return integer_vector is
variable result : integer_vector(1 to Size) ;
begin
for i in result'range loop
result(i) := RandInt(Min, Max) ;
end loop ;
return result ;
end function RandIntV ;
impure function RandIntV (Min, Max : integer ; Unique : natural ; Size : natural) return integer_vector is
variable result : integer_vector(1 to Size) ;
variable iUnique : natural ;
begin
-- if Unique = 0, it is more efficient to call RandIntV(Min, Max, Size)
iUnique := Unique ;
if Max-Min+1 < Unique then
Alert(OSVVM_ALERTLOG_ID, "RandomPkg.(RandIntV | RandRealV | RandTimeV): Unique > number of values available", FAILURE) ;
iUnique := Max-Min+1 ;
end if ;
for i in result'range loop
result(i) := RandInt(Min, Max, result(maximum(1, 1 + i - iUnique) to Size)) ;
end loop ;
return result ;
end function RandIntV ;
impure function RandRealV (Min, Max : real ; Size : natural) return real_vector is
variable result : real_vector(1 to Size) ;
begin
for i in result'range loop
result(i) := RandReal(Min, Max) ;
end loop ;
return result ;
end function RandRealV ;
impure function RandTimeV (Min, Max : time ; Size : natural ; Unit : time := ns) return time_vector is
variable result : time_vector(1 to Size) ;
begin
for i in result'range loop
result(i) := RandTime(Min, Max, Unit) ;
end loop ;
return result ;
end function RandTimeV ;
impure function RandTimeV (Min, Max : time ; Unique : natural ; Size : natural ; Unit : time := ns) return time_vector is
begin
-- if Unique = 0, it is more efficient to call RandTimeV(Min, Max, Size)
return to_time_vector(RandIntV(Min/Unit, Max/Unit, Unique, Size), Unit) ;
end function RandTimeV ;