2009/3/24 Dan Yamins <dyam...@gmail.com> > Hi all, > > I'm having a seg fault error from numpy.rec.fromarrays. > > I have a python list > L = [Col1, Col2] > where Col1 and Col2 are python lists of short strings (the max length of > Col1 strings is 4 chars and max length of Col2 is 7 chars). The len of Col1 > and Col2 is about 11500. > > Then I attempt > >>> A = numpy.rec.fromarrays(L,names = ['Aggregates','__color__']) > > This should produce a numpy record array with two columns, one called > 'Aggregates', the other called '__color__'. > > In and of it self, this runs. But then when I attempt to look at the > contents of A, running the __getitem__ method, say by doing: > > >>> print A > or > >>> A.tolist() > or > >>> A[0] > > then I get a seg fault error. (Acutally, the segfault only occurs about > 80% of the time I run these commands.) > > However, the __getitem__ method does work to produce attribute arrays from > column names , e.g. > > >>> Ag = A['Aggregates'] > > or > > >>> col = A['__color__'] > > both produce (apparently) completely correct and working numpy arrays. > > Moreover, If I pickle the object A before looking at it, everything works > fine. E.g. if I execute: > > >>> Hold_A = A.dumps() > >>> A = numpy.loads(Hold_A) > > then A seems to work fine. > > (Also: pickling the list L = [Col1,Col2] first, before running the > numpy.rec.fromarrays method, does not always fix the segfault.) > > > Can someone explain why this might be happening, and how I can fix it > (without having to use the pickling hack)? >
What architecture/operating system is this? Chuck
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