On Mon, Apr 2, 2012 at 6:18 PM, Aronne Merrelli <aronne.merre...@gmail.com> wrote: > On Sun, Apr 1, 2012 at 8:28 AM, Kamesh Krishnamurthy <kames...@gmail.com> > wrote: >> Hello all, >> >> I profiled NumPy EIG and MATLAB EIG on the same Macbook pro, and both were >> linking to the Accelerate framework BLAS. NumPy turns out to be ~4x slower. >> I've posted details on Stackoverflow: >> http://stackoverflow.com/q/9955021/974568 > > If you just call eig() in MATLAB it only returns eigenvalues (not > vectors). I think there might be a "shortcut" algorithm if you only > want the eigenvalues - or maybe it is faster just due to the smaller > memory requirement. NumPy's eig always computes both. On my Mac OS X > machine I get this result, showing the two are basically equivalent > (this is EPD NumPy, so show_config() shows it is built on MKL): > > MATLAB: >>> tic; eig(r); toc > Elapsed time is 10.594226 seconds. >>> tic; [V,D] = eig(r); toc > Elapsed time is 23.767467 seconds. > > NumPy > In [4]: t0=datetime.now(); numpy.linalg.eig(r); print datetime.now()-t0 > 0:00:25.594435 > In [6]: t0=datetime.now(); v,V = numpy.linalg.eig(r); print datetime.now()-t0 > 0:00:25.485411 > > If you change the MATLAB call, how does it compare?
Or you could alternatively change the numpy call to np.linalg.eigvals(r), if you're only interested in the eigenvalues. - N _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
