On Wed, 2005-07-13 at 12:13 -0300, Flavio Coelho wrote:
2005/7/13, Bruce Southey <bsouthey@gmail.com>: Hi, What is the seed used?
I am not setting the seed.
It is really important that you set the seed?
No.
Did you build Python and numarray from source?
Yes, I use Gentoo. I build everything from source.
Can you reduce your code to a few lines that have the problem?
Not really, poisson and binomial are the only two functions from Numeric that I use but they are called inside a rather complex object oriented code environment (objects within objetcs, being called recursively...) Bellow is the function within which poisson is called:
def stepSEIR_s(self,inits=(0,0,0),par=(0.001,1,1,0.5,1,0,0,0),theta=0, npass=0,dist='poisson'): """ Defines an stochastic model SEIR: - inits = (E,I,S) - par = (Beta, alpha, E,r,delta,B,w,p) see docs. - theta = infectious individuals from neighbor sites """ E,I,S = inits N = self.parentSite.totpop beta,alpha,e,r,delta,B,w,p = par Lpos_esp = beta*S*((I+theta)/(N+npass))**alpha #Number of new cases
if dist == 'poisson': Lpos = poisson(Lpos_esp) ## if theta == 0 and Lpos_esp == 0 and Lpos > 0: ## print Lpos,Lpos_esp,S,I,theta,N,self.parentSite.sitename elif dist == 'negbin': prob = I/(I+Lpos_esp) #convertin between parameterizations Lpos = negative_binomial(I,prob) self.parentSite.totalcases += Lpos #update number of cases Epos = (1-e)*E + Lpos Ipos = e*E + (1-r)*I Spos = S + B - Lpos Rpos = N-(Spos+Epos+Ipos) #self.parentSite.totpop = Spos+Epos+Ipos+Rpos self.parentSite.incidence.append(Lpos) if not self.parentSite.infected: if Lpos > 0: self.parentSite.infected = self.parentSite.parentGraph.simstep self.parentSite.parentGraph.epipath.append ((self.parentSite.parentGraph.simstep,self.parentSite,self.parentSite.infector))
return [Epos,Ipos,Spos]
Having this code is a good start to solving the problem. I think the next step is to simplify your example to make it runnable and provide known inputs for all the parameters which lead to a failure for you. Being really literal (spelling out every single damn thing) cuts down on speculation and inefficiency on our end. It would also be good to express the condition (or it's inverse) you think is an error as an assertion, so something like this might be what we need: from numarray.random_array import poisson E, I, S = (0,0,0) beta,alpha,e,r,delta,B,w,p = (0.001,1,1,0.5,1,0,0,0) theta = 0 npass = 0 N = 100 # total guess here for me Lpos_esp = beta*S*((I+theta)/(N+npass))**alpha #Number of new cases Lpos = poisson(Lpos_esp) assert not (theta == 0 and Lpos_esp == 0 and Lpos > 0) The problem is, the above works for me. Make it sane and get it to expose the error for you and I'll look into this some more. Regards, Todd
I wonder if called by itself it would trigger the problem... The commented Lines Is where I catch the errors: when poisson returns a greater than zero number, when called with mean 0.
Ranlib uses static floats so it may relate to numerical precision (as well as the random uniform random number generator). Really the only way is for you to debug the ranlib.c file
I'll see what I can do.
Note that R provides a standalone math library in C that includes the random number generators so you could you those instead. SWIG handles it rather well.
I think thats what Rpy already does...is it not?
thanks Bruce,
Flávio
Regards Bruce
On 7/13/05, Flavio Coelho <fccoelho@gmail.com> wrote: > Well, > I am definetly glad that someone has also stumbled onto the same problem. > > But it is nevertheless intriguing, that you can run poisson a million times > with mean zero or negative(it assumes zero mean inthis case) without any > problems by itself. But when I call it within my code, the rate of error is > very high (I would say it returns a wrong result every time, but I haven't > checked every answer). > > Meanwhile, my solution will be: > > import rpy > > n = rpy.r.rpois(n,mean) > > I don't feel I can trust poisson while this "funny" behavior is still > there... > If someone has any Idea of how I could trace this bug please tell me, and > I'll hunt it down. At least I can reproduce it in a very specific context. > > thanks, > > Flávio > > 2005/7/12, Sebastian Haase <haase@msg.ucsf.edu>: > > Hi Flavio! > > I had reported this long time ago and this list (about numarray). > > Somehow this got more or less dismissed. If I recall correctly the > argument > > was that nobody could reproduce it (I ran this on Debian Woody , py2.2, > (with > > CVS numarray at the time). > > > > I ended up writting my own wrapper(s): > > def poissonArr(shape=defshape, mean=1): > > from numarray import random_array as ra > > if mean == 0: > > return zeroArrF(shape) > > elif mean < 0: > > raise "poisson not defined for mean < 0" > > else: > > return ra.poisson(mean, shape).astype (na.UInt16) > > > > def poissonize(arr): > > from numarray import random_array as ra > > return na.where(arr<=0, 0, ra.poisson(arr)).astype ( na.UInt16) > > > > (I use the astype( na.UInt16) because of some OpenGL code) > > > > Just last week had this problem on a windows98 computer (python2.4). > > > > This should get sorted out ... > > > > Thanks for reporting this problem. > > Sebastian Haase > > > > > > > > > > On Tuesday 12 July 2005 13:32, Flavio Coelho wrote: > > > Hi, > > > > > > I am having problems with the poisson random number generators of both > > > Numarray and Numeric. > > > I can't replicate it when calling the function from the python cosonle, > but > > > it has consistently malfunctioned when used within one of my scripts. > > > > > > What happens is that it frequently return a value greater than zero when > > > called with zero mean: poisson( 0.0) > > > > > > Unfortunately My program is too big to send attached but I have > confirmed > > > the malfunction by printing both the mean and the result whenever it > spits > > > out a wrong result. > > > > > > This is very weird indeed, I have run poisson millions of times by itsel > on > > > the python console, without any problems... > > > > > > I hope it is some stupid mistake, but when I replace the poisson > function > > > call within my program by the R equivalent command (rpois) via the rpy > > > wrapper, everything works just fine... > > > > > > any Ideas? > > > > > > -- > > Flávio Codeço Coelho > registered Linux user # 386432 > --------------------------- > Great spirits have always found violent opposition from mediocrities. The > latter cannot understand it when a man does not thoughtlessly submit to > hereditary prejudices but honestly and courageously uses his intelligence. > Albert Einstein >
-- Flávio Codeço Coelho registered Linux user # 386432 --------------------------- Great spirits have always found violent opposition from mediocrities. The latter cannot understand it when a man does not thoughtlessly submit to hereditary prejudices but honestly and courageously uses his intelligence. Albert Einstein