On Friday, July 10, 2015 at 3:07:17 PM UTC-6, Ondřej Čertík wrote: > > Hi, > > On Fri, Jul 10, 2015 at 7:30 AM, 刘金国 <[email protected] <javascript:>> > wrote: > > 4 x 4 is needed ~~ > > mathematica runs extremely fast for 4 x 4 matrix as it should be, but > ... > > Can you post the Mathematica result? So that we know what you are > trying to get and we can then help you get it with SymPy. > > Ondrej > > > > > 在 2014年2月12日星期三 UTC+8上午5:40:19，Vinzent Steinberg写道： > >> > >> On Monday, February 10, 2014 11:27:09 PM UTC-5, monde wilson wrote: > >>> > >>> why eigenvectors very slow > >>> > >>> what is the difference between numpy and sympy when doing matrix > >>> calculation > >> > >> > >> Sympy calculates eigenvectors symbolically (thus exactly), numpy > >> calculates them numerically using floating point arithmetic. > >> In general you don't want to use sympy to calculate the eigenvectors > for > >> matrices larger than 2x2, because the symbolic results can be very > >> complicated. (IIRC, the eigenvalues are calculated by finding roots of > the > >> characteristic polynomial, which can lead to nasty expressions for > dimension > >> 3 and beyond.) > >> > >>> > >>> will numpy faster and more accurately > >> > >> > >> Numpy will be a lot faster, but not more accurate. If you only need > >> numerical results, you probably should use numpy for this. > >> > >> Vinzent > > > > -- > > You received this message because you are subscribed to the Google > Groups > > "sympy" group. > > To unsubscribe from this group and stop receiving emails from it, send > an > > email to [email protected] <javascript:>. > > To post to this group, send email to [email protected] > <javascript:>. > > Visit this group at http://groups.google.com/group/sympy. > > To view this discussion on the web visit > > > https://groups.google.com/d/msgid/sympy/62a17328-bcd2-4955-9534-ae5358e89041%40googlegroups.com. > > > > For more options, visit https://groups.google.com/d/optout. >
If I wanted to get the eigenvectors (and eigenvalues) of a 10x10 symbolic matrix that is relatively sparse, is it possible to use sympy to solve this issue? Can the eigenvects() operation be parallelized in any way? I am trying to use OCTAVE as well (which calls from sympy), but once I get above 4x4 the time required to get a solution seems to scale geometrically: (2x2 in <1 sec, 3x3 in ~2 sec, 4x4 in ~minutes, 5x5 ~hr, 7x7 ~12 hr). Is there some code somewhere with a robust eigensolver that can generate the eigenfunctions and eigenvalues of a 10x10 symbolic matrix? Based on my 7x7 matrix I know the denominators of the solution can be huge, but this is an important problem that I need to solve. Thanks. -- You received this message because you are subscribed to the Google Groups "sympy" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at https://groups.google.com/group/sympy. To view this discussion on the web visit https://groups.google.com/d/msgid/sympy/d95a66fe-9135-4365-9386-6641bf51d9fa%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
