Coverage for /usr/lib/python3/dist-packages/sympy/matrices/expressions/dotproduct.py: 23%

1from sympy.core import Basic, Expr 

2from sympy.core.sympify import _sympify 

3from sympy.matrices.expressions.transpose import transpose 

4 

5 

6class DotProduct(Expr): 

7 """ 

8 Dot product of vector matrices 

9 

10 The input should be two 1 x n or n x 1 matrices. The output represents the 

11 scalar dotproduct. 

12 

13 This is similar to using MatrixElement and MatMul, except DotProduct does 

14 not require that one vector to be a row vector and the other vector to be 

15 a column vector. 

16 

17 >>> from sympy import MatrixSymbol, DotProduct 

18 >>> A = MatrixSymbol('A', 1, 3) 

19 >>> B = MatrixSymbol('B', 1, 3) 

20 >>> DotProduct(A, B) 

21 DotProduct(A, B) 

22 >>> DotProduct(A, B).doit() 

23 A[0, 0]*B[0, 0] + A[0, 1]*B[0, 1] + A[0, 2]*B[0, 2] 

24 """ 

25 

26 def __new__(cls, arg1, arg2): 

27 arg1, arg2 = _sympify((arg1, arg2)) 

28 

29 if not arg1.is_Matrix: 

30 raise TypeError("Argument 1 of DotProduct is not a matrix") 

31 if not arg2.is_Matrix: 

32 raise TypeError("Argument 2 of DotProduct is not a matrix") 

33 if not (1 in arg1.shape): 

34 raise TypeError("Argument 1 of DotProduct is not a vector") 

35 if not (1 in arg2.shape): 

36 raise TypeError("Argument 2 of DotProduct is not a vector") 

37 

38 if set(arg1.shape) != set(arg2.shape): 

39 raise TypeError("DotProduct arguments are not the same length") 

40 

41 return Basic.__new__(cls, arg1, arg2) 

42 

43 def doit(self, expand=False, **hints): 

44 if self.args[0].shape == self.args[1].shape: 

45 if self.args[0].shape[0] == 1: 

46 mul = self.args[0]*transpose(self.args[1]) 

47 else: 

48 mul = transpose(self.args[0])*self.args[1] 

49 else: 

50 if self.args[0].shape[0] == 1: 

51 mul = self.args[0]*self.args[1] 

52 else: 

53 mul = transpose(self.args[0])*transpose(self.args[1]) 

54 

55 return mul[0]