Hi, I just went through my mail archive and found these two minor outstanding issues. Thought I'd ask for comments before the new release:
""" From: "Charles R Harris" <[EMAIL PROTECTED]> Subject: Re: [Numpy-discussion] Assign NaN, get zero On 11/11/06, Lisandro Dalcin <[EMAIL PROTECTED]> wrote: > > On 11/11/06, Stefan van der Walt <[EMAIL PROTECTED]> wrote: > > NaN (or inf) is a floating point number, so seeing a zero in integer > > representation seems correct: > > > > In [2]: int(N.nan) > > Out[2]: 0L > > > > Just to learn myself: Why int(N.nan) should be 0? Is it C behavior? In [1]: int32(0)/int32(0) Warning: divide by zero encountered in long_scalars Out[1]: 0 In [2]: float32(0)/float32(0) Out[2]: nan In [3]: int(nan) Out[3]: 0L I think it was just a default for numpy. Hmmm, numpy now warns on integer division by zero, didn't used to. Looks like a warning should also be raised when casting nan to integer. It is probably a small bug not to. I also suspect int(nan) should return a normal python zero, not 0L. """ """ From: "Bill Baxter" <[EMAIL PROTECTED]> To: numpy-discussion@scipy.org Subject: [Numpy-discussion] linalg.lstsq for complex Is this code from linalg.lstsq for the complex case correct? lapack_routine = lapack_lite.zgelsd lwork = 1 rwork = zeros((lwork,), real_t) work = zeros((lwork,),t) results = lapack_routine(m, n, n_rhs, a, m, bstar, ldb, s, rcond, 0, work, -1, rwork, iwork, 0) lwork = int(abs(work[0])) rwork = zeros((lwork,),real_t) a_real = zeros((m,n),real_t) bstar_real = zeros((ldb,n_rhs,),real_t) results = lapack_lite.dgelsd(m, n, n_rhs, a_real, m, bstar_real, ldb, s, rcond, 0, rwork, -1, iwork, 0) lrwork = int(rwork[0]) work = zeros((lwork,), t) rwork = zeros((lrwork,), real_t) results = lapack_routine(m, n, n_rhs, a, m, bstar, ldb, s, rcond, The middle call to dgelsd looks unnecessary to me. At the very least, allocating astar_real and bstar_real shouldn't be necessary since they aren't referenced anywhere else in the lstsq function. The lapack documentation for zgelsd also doesn't mention any need to call dgelsd to compute the size of the work array. """ Cheers Stéfan _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion