Im using ncvhdl version 6.11. For some reason, the uniform function
suddenly does not work as required. The seed value does not change on
different calls to the uniform function. I have debugged my program to
find out the error but have not been successful. So, I have to write a
random generator function (that need not be synthesized). Could
somebody please tell me what algorithm to use for the same?
Thanks,
PS: This is not part of any homework/school work
> Im using ncvhdl version 6.11. For some reason, the uniform function
> suddenly does not work as required. The seed value does not change on
> different calls to the uniform function.
http://groups.google.com/groups/?q=vhdl+uniform+declare+variable
Im pasting a snippet of my code.
procedure random_vector(
variable seed1 :inout integer;
variable seed2 :inout integer;
variable vmax : in integer;
variable result : out integer ) is
variable x : real;
begin
UNIFORM(seed1,seed2,x);
i := integer(x) mod vmax;
result := i;
end procedure random_vector;
begin
xx: process is
...
...
variable seed1, seed2 : integer := 1;)
random_vector(seed1 => seed1, seed2 => seed2, vmax, x=>x);
...
end process
When I run this behavorial code, I see that the value of seed does not
change between calls. Am I doing something wrong here?
Thanks,
Your procedure is out of process scope.
Maybe test it without a procedure first.
-- Mike T
xx: process is
variable ...
-- <----procedure declaration goes here
-- other declarations
begin
-- ...
The seed values have to be possitive, but this should only throw an
error rather than not work at all, but you have a problem with the x
output from the UNIFORM function.
> UNIFORM(seed1,seed2,x);
> i := integer(x) mod vmax;
> result := i;
X is a real value that will be a value between 0 and 1. casting it to
and integer will then just result in 0 or 1, and overall your "result"
value will end up just being 0 or 1, regardless of VMAX. You need to
take the returned x value and use that the scale the return value to
something more meaningful. It is best to work with real types until
the very end.
In the words of blue peter: here's one I prepared earlier:
procedure rand_int( variable seed1, seed2 : inout positive;
min, max : in integer; --
boundaries for the random result (inclusive)
result : out integer) is
variable rand : real;
begin
uniform(seed1, seed2, rand);
result := integer(
real(min) --set the base
+ (rand * (real(max)-real(min)) ) -- add in the random
offset from the base, over a given range.
);
end procedure;
On Aug 26, 10:12 am, Tricky <Trickyh...@gmail.com> wrote:
> On 25 Aug, 20:29, indu <sangeethasn...@gmail.com> wrote:
>
>
>
> > Thanks. I have initialised it but the seed does not seem to be
> > changing.
>
> > Im pasting a snippet of my code.
>
> > procedure random_vector(
> > variableseed1 :inout integer;
> > variableseed2 :inout integer;
> > variablevmax : in integer;
> > variableresult : out integer ) is
>
> > variablex : real;
> > begin
> > UNIFORM(seed1,seed2,x);
> > i := integer(x) mod vmax;
> > result := i;
> > end procedure random_vector;
> > begin
> > xx: process is
> > ...
> > ...
> >variableseed1, seed2 : integer := 1;)
> > random_vector(seed1 => seed1, seed2 => seed2, vmax, x=>x);
>
> > ...
> > end process
>
> > When I run this behavorial code, I see that the value of seed does not
> > change between calls. Am I doing something wrong here?
>
> > Thanks,
>
> The seed values have to be possitive, but this should only throw an
> error rather than not work at all, but you have a problem with the x
> output from theUNIFORMfunction.
>
> > UNIFORM(seed1,seed2,x);
> > i := integer(x) mod vmax;
> > result := i;
>
> X is a real value that will be a value between 0 and 1. casting it to
> and integer will then just result in 0 or 1, and overall your "result"
> value will end up just being 0 or 1, regardless of VMAX. You need to
> take the returned x value and use that the scale the return value to
> something more meaningful. It is best to work with real types until
> the very end.
>
> In the words of blue peter: here's one I prepared earlier:
>
> procedure rand_int(variableseed1, seed2 : inout positive;
> min, max : in integer; --
> boundaries for the random result (inclusive)
> result : out integer) is
> variablerand : real;
On Aug 26, 10:12 am, Tricky <Trickyh...@gmail.com> wrote:
> On 25 Aug, 20:29, indu <sangeethasn...@gmail.com> wrote:
>
>
>
> > Thanks. I have initialised it but the seed does not seem to be
> > changing.
>
> > Im pasting a snippet of my code.
>
> > procedure random_vector(
> > variableseed1 :inout integer;
> > variableseed2 :inout integer;
> > variablevmax : in integer;
> > variableresult : out integer ) is
>
> > variablex : real;
> > begin
> > UNIFORM(seed1,seed2,x);
> > i := integer(x) mod vmax;
> > result := i;
> > end procedure random_vector;
> > begin
> > xx: process is
> > ...
> > ...
> >variableseed1, seed2 : integer := 1;)
> > random_vector(seed1 => seed1, seed2 => seed2, vmax, x=>x);
>
> > ...
> > end process
>
> > When I run this behavorial code, I see that the value of seed does not
> > change between calls. Am I doing something wrong here?
>
> > Thanks,
>
> The seed values have to be possitive, but this should only throw an
> error rather than not work at all, but you have a problem with the x
> output from theUNIFORMfunction.
>
> > UNIFORM(seed1,seed2,x);
> > i := integer(x) mod vmax;
> > result := i;
>
> X is a real value that will be a value between 0 and 1. casting it to
> and integer will then just result in 0 or 1, and overall your "result"
> value will end up just being 0 or 1, regardless of VMAX. You need to
> take the returned x value and use that the scale the return value to
> something more meaningful. It is best to work with real types until
> the very end.
>
> In the words of blue peter: here's one I prepared earlier:
>
> procedure rand_int(variableseed1, seed2 : inout positive;
> min, max : in integer; --
> boundaries for the random result (inclusive)
> result : out integer) is
> variablerand : real;
One thing I didnt realise till yesterday - MIN and MAX are inclusive
boundaries, but do not have the same distribution as the other values.
eg:
MIN = 0, MAX = 5
over 100 repetitions, mean distribution is:
0 = 10
1 = 20
2 = 20
3 = 20
4 = 20
5 = 10
To make it evenly distributed, you'll need to + or - 0.5 from the end
result before converting to an integer. This will make it exclusive of
min (+0.5) or max (-0.5). For most useful purposes, it shouldnt really
matter though.