[Numpy-discussion] numarray.random_array number generation in C code

Perry Greenfield perry at stsci.edu
Tue Oct 5 18:14:00 CDT 2004


Faheem Mitha wrote:

> Dear People,
>
> I want to write some C++ code to link with Python, using the
> Boost.Python interface. I need to generate random numbers in the C++
> code, and I was wondering as to the best way of doing this.
>
> Note that it is important that the random number generation interoperate
> seamlessly with Python, in the sense that the behavior of the calls to
> the RNG is the same whether calls are made at the C level or the Python
> level. I hope the reasons why this is important are obvious.
>
> I was thinking that the method should go like this.
>
> 1) When C/C++ code called, reads seed from python random state.
>
> 2) Does its stuff.
>
> 3) Writes seed back to python level when it exits.
>
> After doing a little investigation of the numarray.random_array python
> library and associated extension modules, it seems possible that the
> answer is simpler than I had supposed. However, I would appreciate it if
> someone would tell me if my understanding is incorrect in some places.
>
> Summary: It seems that I can just call all the C entry point routines
> defined in ranlib.h, without worrying about getting or setting seeds.
>
> Rationale:
>
> The structure of this random number facility has three parts, all
> files in
> Packages/RandomArray2/Src.
>
> 1) low-level C routines: Packages/RandomArray2/Src/com.c and
> Packages/RandomArray2/Src/ranlib.c.
>
> com.c: basic RNG stuff; getting and setting seeds etc.
> ranlib.c: Random number generator algorithms for different distributions
> etc.
>
> 2) Python to C interface: Packages/RandomArray2/Src/ranlibmodule.c.
>
> This interfaces the stuff in com.c and ranlib.c.
>
> 3) Python wrapper: Packages/RandomArray2/Lib/RandomArray2.py.
>
> This wraps the C interface. In most cases it does not do much
> else besides
> some basic argument error checking.
>
> From my perspective, the important thing is that the random
> number seed is
> only defined at C level as a static object, all the RNG stuff
> happens at C
> level, and the Python code just calls the C code as necessary. (I'm
> sketchy about the details of what is defined as the seed etc.)
>
> This is in contrast with the R RNG facility (the only other RNG
> facility I
> am familiar with), which uses macros SetRNGstate() and GetRNGstate() to
> read and write the seed, which is defined at R level.
>
> Therefore, the upshot is that the C routines in ranlib.h read and write
> the same seed as the python level functions do, so no special action is
> necessary with regard to the seed.
>
> Is this correct?
>
> In any case, it would be nice if something like the above was documented,
> so lost souls like myself don't have to go trawling through the source
> code to figure out what is going on. Of course it is nice that the source
> code is available, otherwise even that would be impossible.
>
> R documents this stuff in the "Writing R Extensions" manual, online at
> http://cran.r-project.org/doc/manuals/R-exts.pdf. Perhaps the Numarray
> manual could have a small section about this too.
>
>                                                          Regards, Faheem.
>
I'm not sure I understand what you want to do. Do you want to link
directly to the extension code from your C++ code? If so I'm wondering
why. It would make the most sense if the C++ code needed obtain
small numbers of random numbers in some iterative loop, and you wish
to use the same random number library that that numarray is using.
Otherwise, I would normally obtain the random number array
in python, then call the C++ extension. Perhaps I didn't read carefully
enough. Normally linking to an extension module involves some hacks
that I'm not sure were done for the randomarray module (the gory
details are in the python docs for extension modules), Todd can
check on that, I'm not sure I will have time (a superficial check
seems to indicate that it doesn't support direct linking, though
one could link to the underlying library I suppose).

As an aside, it is likely that a better module can be done as some
have suggested, we just took what Numeric had at the time. Doing that
is not a high priority with us at the moment (anyone else want to
tackle that?). Right now integration with scipy is our biggest
priority so things like this will have to take a back seat for
a while.

Furthermore, we did what we needed to to port these modules from
Numeric, but that didn't necessarily make us experts in how they
worked. I wish we were, but we've generally been directing our
energy elsewhere. I'd presume that the sensible way for the module
to work is to initialize its seed from a time-based seed in the
absence of any other seed initialization, and to keep the seed
state in the extension module, but I could be wrong.

Perry






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