ó ¡¼™\c@ spddlmZmZddlmZddlmZddlmZddl m Z de fd„ƒYZ dS( iÿÿÿÿ(tprint_functiontdivision(tBasic(t_sympify(t transpose(t MatrixExprt DotProductcB s#eZdZd„Zed„ZRS(sC Dot product of vector matrices The input should be two 1 x n or n x 1 matrices. The output represents the scalar dotproduct. This is similar to using MatrixElement and MatMul, except DotProduct does not require that one vector to be a row vector and the other vector to be a column vector. >>> from sympy import MatrixSymbol, DotProduct >>> A = MatrixSymbol('A', 1, 3) >>> B = MatrixSymbol('B', 1, 3) >>> DotProduct(A, B) DotProduct(A, B) >>> DotProduct(A, B).doit() A[0, 0]*B[0, 0] + A[0, 1]*B[0, 1] + A[0, 2]*B[0, 2] cC sÄt||fƒ\}}|js0tdƒ‚n|jsHtdƒ‚nd|jkrftdƒ‚nd|jkr„tdƒ‚nt|jƒt|jƒkr±tdƒ‚ntj|||ƒS(Ns(Argument 1 of DotProduct is not a matrixs(Argument 2 of DotProduct is not a matrixis(Argument 1 of DotProduct is not a vectors(Argument 2 of DotProduct is not a vectors,DotProduct arguments are not the same length(Rt is_Matrixt TypeErrortshapetsetRt__new__(tclstarg1targ2((sDlib/python2.7/site-packages/sympy/matrices/expressions/dotproduct.pyR s  cC sÝ|jdj|jdjkr||jdjddkr[|jdt|jdƒ}qÕt|jdƒ|jd}nY|jdjddkr±|jd|jd}n$t|jdƒt|jdƒ}|dS(Nii(targsR R(tselftexpandtmul((sDlib/python2.7/site-packages/sympy/matrices/expressions/dotproduct.pytdoit.s !!$(t__name__t __module__t__doc__R tFalseR(((sDlib/python2.7/site-packages/sympy/matrices/expressions/dotproduct.pyR s N( t __future__RRt sympy.coreRtsympy.core.sympifyRt$sympy.matrices.expressions.transposeRt"sympy.matrices.expressions.matexprRR(((sDlib/python2.7/site-packages/sympy/matrices/expressions/dotproduct.pyts