For every matrix dimension there is a parent (MatrixSpace). You are most likely seeing those. Use @fork / @parallel.
On Monday, July 13, 2015 at 9:44:01 AM UTC+2, Jori Mäntysalo wrote: > > I was asked to make a code that iterates over all matrices of given type > and size. And once again I see a memory leak. Here's an example code > > n = 7 > m = Integer(n*(n-1)/2) > for i in IntegerRange(2^m): > d = i.digits(base=2, padto=m) > l = [[1]+[0]*(n-1)] > for j in range(n-1): > l.append( d[(j+1)*j/2:(j+1)*(j+2)/2]+ [1] + [0]*(n-j-2) ) > M = Matrix(l) > eig = sorted((M*M.transpose()).eigenvalues())[0] > if eig <= 0: > print "Foobar" > > These kind of codes, where I make millions of small objects, compute > something and discard the object, seems to eat memory. Not much, but so > much that otherwise reasonable computable thing - say, something to run > for two days - will be impossible to do directly. > > Is there anything I can do for these? (Other than running the code > part-by-part.) > > This was ran on newest beta version. > > -- > Jori Mäntysalo > -- You received this message because you are subscribed to the Google Groups "sage-devel" group. To unsubscribe from this group and stop receiving emails from it, send an email to sage-devel+unsubscr...@googlegroups.com. To post to this group, send email to sage-devel@googlegroups.com. Visit this group at http://groups.google.com/group/sage-devel. For more options, visit https://groups.google.com/d/optout.
