σ £αSc @`sηdZddlmZmZmZddddddd d d d d dg ZddlmZddlj Z e j Z d„Z d„Z d„Z d„Zdd„Zd„Zd„Zdd„Zd„Zdd„Zdd„ZdS(sSBackward compatible with LinearAlgebra from Numeric This module is a lite version of the linalg.py module in SciPy which contains high-level Python interface to the LAPACK library. The lite version only accesses the following LAPACK functions: dgesv, zgesv, dgeev, zgeev, dgesdd, zgesdd, dgelsd, zgelsd, dsyevd, zheevd, dgetrf, dpotrf. i(tdivisiontabsolute_importtprint_functiont LinAlgErrortsolve_linear_equationstinversetcholesky_decompositiont eigenvaluest Heigenvaluestgeneralized_inverset determinanttsingular_value_decompositiont eigenvectorst Heigenvectorstlinear_least_squares(t transposeNcC`stj||ƒS(N(tlinalgtsolve(tatb((sY/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/linear_algebra.pyRscC`s tj|ƒS(N(Rtinv(R((sY/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/linear_algebra.pyRscC`s tj|ƒS(N(Rtcholesky(R((sY/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/linear_algebra.pyR$scC`s tj|ƒS(N(Rteigvals(R((sY/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/linear_algebra.pyR)stLcC`stj||ƒS(N(Rteigvalsh(RtUPLO((sY/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/linear_algebra.pyR,scC`s%tj|ƒ\}}|t|ƒfS(N(RteigR(tAtwtv((sY/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/linear_algebra.pyR 1scC`s%tj|ƒ\}}|t|ƒfS(N(RteighR(RRR((sY/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/linear_algebra.pyR 5sg»½ΧΩί|Ϋ=cC`stj||ƒS(N(Rtpinv(Rtrcond((sY/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/linear_algebra.pyR ;scC`s tj|ƒS(N(Rtdet(R((sY/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/linear_algebra.pyR @scC`stj|||ƒS(sϋreturns x,resids,rank,s where x minimizes 2-norm(|b - Ax|) resids is the sum square residuals rank is the rank of A s is the rank of the singular values of A in descending order If b is a matrix then x is also a matrix with corresponding columns. If the rank of A is less than the number of columns of A or greater than the number of rows, then residuals will be returned as an empty array otherwise resids = sum((b-dot(A,x)**2). Singular values less than s[0]*rcond are treated as zero. (Rtlstsq(RRR ((sY/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/linear_algebra.pyREs cC`stj||ƒS(N(Rtsvd(Rt full_matrices((sY/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/linear_algebra.pyR Ts(t__doc__t __future__RRRt__all__t numpy.coreRt numpy.linalgRRRRRRRR R R R RR (((sY/opt/xtal/ccp4-6.5-linux32/lib/python2.7/site-packages/numpy/oldnumeric/linear_algebra.pyts*