That is good to hear. If I have a look at the change you made on rpy2, do
you think there is any hope i will be able to patch rpy1? I do not know much
about rpy yet, but if you think that is do-able this would give me a good
pretext to learn.
Laurent
2008/7/21 Laurent Gautier <[EMAIL PROTECTED]>:
> I fixed a problem with rpy2 (the fix is in SVN)
> It does seem to fit happily a lot of linear models without problems now.
>
> For the moment rpy-1.x, calling R's gc() is the only known workaround, I
> think.
>
>
> ##---
>
>
> #
> # brutal and naive strategy for model selection:
> # fit all possible two-variable models
> #
> # The purpose is of this is code to try reproducing
> # an elusive bug when iteratively fitting a lot of models.
> #
> # Here, we are iterating nvariable * (nvariables-1) times.
> #
>
> import rpy2.robjects as ro
> import array
> import random
>
> # build pool of variables
> nvariables = 75
> variables = {}
> for v_i in range(nvariables):
> a_i = array.array('f', [random.random() for i in xrange(1000)])
> rv_i = ro.RVector(a_i)
> variables['v%i' %v_i] = rv_i
>
> # create a dummy response variable
> y = variables['v1'].r + variables['v2']
>
>
> # fit all pairwise combinations
> dataframe = ro.r['data.frame']
> lm = ro.r['lm']
>
> res = []
> for v1_i in range(nvariables):
> for v2_i in xrange(v1_i+1):
> subvarnames = ['v%i' %x for x in [v1_i, v2_i]]
> subvar = dict([(x, variables[x]) for x in subvarnames])
> subvar['y'] = y
> dataf = dataframe(**subvar)
> fit = lm('y ~ %s + %s' %(subvarnames[0], subvarnames[1]),
> data=dataf)
> sumfit = ro.r.summary(fit)
> rsq = sumfit.r['adj.r.squared'][0][0]
>
> res.append((v1_i, v2_i, rsq))
>
> ## check R2 == 1 for the pair (v1, v2)
> [x for x in res if x[2] == 1]
>
>
>
>
> L.
>
>
>
>
>
>
> 2008/7/18 Laurent Gautier <[EMAIL PROTECTED]>:
> > 2008/7/18 Laurent Gautier <[EMAIL PROTECTED]>:
> >> 2008/7/17 laurent oget <[EMAIL PROTECTED]>:
> >>>
> >>>
> >>> 2008/7/17 Laurent Gautier <[EMAIL PROTECTED]>:
> >>>>
> >
> >> It might not really be a race condition, but more an overzealous
> >> garbage collection.
> >> R does not have reference counting, and objects without an associated
> >> symbol/name
> >> in the R space can be flagged as "protected" from garbage collection.
> >> The removal of
> >> the protection is recursive, I think,
> >
> > Just a work of caution: I I might not be thinking right. After
> > checking R's source, I am
> > not sure that contained elements in a "preserved" container are
> > recursively unprotected.
> > There is more that I do not know about R's memory management than I
> thought...
> >
>
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