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| from sympy.core import Basic, Expr | |
| from sympy.core.sympify import _sympify | |
| from sympy.matrices.expressions.transpose import transpose | |
| class DotProduct(Expr): | |
| """ | |
| 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] | |
| """ | |
| def __new__(cls, arg1, arg2): | |
| arg1, arg2 = _sympify((arg1, arg2)) | |
| if not arg1.is_Matrix: | |
| raise TypeError("Argument 1 of DotProduct is not a matrix") | |
| if not arg2.is_Matrix: | |
| raise TypeError("Argument 2 of DotProduct is not a matrix") | |
| if not (1 in arg1.shape): | |
| raise TypeError("Argument 1 of DotProduct is not a vector") | |
| if not (1 in arg2.shape): | |
| raise TypeError("Argument 2 of DotProduct is not a vector") | |
| if set(arg1.shape) != set(arg2.shape): | |
| raise TypeError("DotProduct arguments are not the same length") | |
| return Basic.__new__(cls, arg1, arg2) | |
| def doit(self, expand=False, **hints): | |
| if self.args[0].shape == self.args[1].shape: | |
| if self.args[0].shape[0] == 1: | |
| mul = self.args[0]*transpose(self.args[1]) | |
| else: | |
| mul = transpose(self.args[0])*self.args[1] | |
| else: | |
| if self.args[0].shape[0] == 1: | |
| mul = self.args[0]*self.args[1] | |
| else: | |
| mul = transpose(self.args[0])*transpose(self.args[1]) | |
| return mul[0] | |