Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.8/site-packages/opt_einsum/backends/object_arrays.py: 17%

1""" 

2Functions for performing contractions with array elements which are objects. 

3""" 

4 

5import functools 

6import operator 

7 

8import numpy as np 

9 

10 

11def object_einsum(eq, *arrays): 

12 """A ``einsum`` implementation for ``numpy`` arrays with object dtype. 

13 The loop is performed in python, meaning the objects themselves need 

14 only to implement ``__mul__`` and ``__add__`` for the contraction to be 

15 computed. This may be useful when, for example, computing expressions of 

16 tensors with symbolic elements, but note it will be very slow when compared 

17 to ``numpy.einsum`` and numeric data types! 

18 

19 Parameters 

20 ---------- 

21 eq : str 

22 The contraction string, should specify output. 

23 arrays : sequence of arrays 

24 These can be any indexable arrays as long as addition and 

25 multiplication is defined on the elements. 

26 

27 Returns 

28 ------- 

29 out : numpy.ndarray 

30 The output tensor, with ``dtype=object``. 

31 """ 

32 

33 # when called by ``opt_einsum`` we will always be given a full eq 

34 lhs, output = eq.split("->") 

35 inputs = lhs.split(",") 

36 

37 sizes = {} 

38 for term, array in zip(inputs, arrays): 

39 for k, d in zip(term, array.shape): 

40 sizes[k] = d 

41 

42 out_size = tuple(sizes[k] for k in output) 

43 out = np.empty(out_size, dtype=object) 

44 

45 inner = tuple(k for k in sizes if k not in output) 

46 inner_size = tuple(sizes[k] for k in inner) 

47 

48 for coo_o in np.ndindex(*out_size): 

49 

50 coord = dict(zip(output, coo_o)) 

51 

52 def gen_inner_sum(): 

53 for coo_i in np.ndindex(*inner_size): 

54 coord.update(dict(zip(inner, coo_i))) 

55 locs = (tuple(coord[k] for k in term) for term in inputs) 

56 elements = (array[loc] for array, loc in zip(arrays, locs)) 

57 yield functools.reduce(operator.mul, elements) 

58 

59 out[coo_o] = functools.reduce(operator.add, gen_inner_sum()) 

60 

61 return out