[SciPy-user] qz decomposition how to?

Nils Wagner nwagner at mecha.uni-stuttgart.de
Fri Nov 11 09:04:45 CST 2005


Sven Schreiber wrote:
>Hi,
>total Scipy newbie here -- I have tried to find an answer on the web and user guides, but I'm a
>little lost in different versions etc. So here goes:
>
>Is it possible to perform a QZ (alias generalized Schur) decomposition with some pre-built Scipy
>version? (preferably on Windows, but I'd be also glad to hear about other options) Relatively
>low-level Lapack accessing would be ok; btw as far as I understand that would be lapack functions xGGES.
>
>Currently I have windows Enthought Python 2.3.5 installed (uninstalled previously used Python 2.4 to
>hopefully have all the Scipy tools fitting together).
>
>Thanks much for your time and help,
>-sven  	
>
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>SciPy-user at scipy.net
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>  
Use

help (linalg.flapack)

      t,sdim,w,vs,work,info =
cgees(cselect,a,compute_v=1,sort_t=0,lwork=3*n,cselect_extra_args=(),overwrite_a=0)
      t,sdim,w,vs,work,info =
zgees(zselect,a,compute_v=1,sort_t=0,lwork=3*n,zselect_extra_args=(),overwrite_a=0)
      t,sdim,wr,wi,vs,work,info =
dgees(dselect,a,compute_v=1,sort_t=0,lwork=3*n,dselect_extra_args=(),overwrite_a=0)
      t,sdim,wr,wi,vs,work,info =
sgees(sselect,a,compute_v=1,sort_t=0,lwork=3*n,sselect_extra_args=(),overwrite_a=0)
      alphar,alphai,beta,vl,vr,work,info =
sggev(a,b,compute_vl=1,compute_vr=1,lwork=8*n,overwrite_a=0,overwrite_b=0)
      alphar,alphai,beta,vl,vr,work,info =
dggev(a,b,compute_vl=1,compute_vr=1,lwork=8*n,overwrite_a=0,overwrite_b=0)
      alpha,beta,vl,vr,work,info =
cggev(a,b,compute_vl=1,compute_vr=1,lwork=8*n,overwrite_a=0,overwrite_b=0)
      alpha,beta,vl,vr,work,info =
zggev(a,b,compute_vl=1,compute_vr=1,lwork=8*n,overwrite_a=0,overwrite_b=0)

See also linalg.schur, linalg.rsf2csf and linalg.eig

Nils
 



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