Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.10/site-packages/astroid/brain/brain_numpy_core_multiarray.py: 94%

1# Licensed under the LGPL: https://www.gnu.org/licenses/old-licenses/lgpl-2.1.en.html 

2# For details: https://github.com/pylint-dev/astroid/blob/main/LICENSE 

3# Copyright (c) https://github.com/pylint-dev/astroid/blob/main/CONTRIBUTORS.txt 

4 

5"""Astroid hooks for numpy.core.multiarray module.""" 

6 

7import functools 

8 

9from astroid import nodes 

10from astroid.brain.brain_numpy_utils import ( 

11 attribute_name_looks_like_numpy_member, 

12 infer_numpy_attribute, 

13 infer_numpy_name, 

14 member_name_looks_like_numpy_member, 

15) 

16from astroid.brain.helpers import register_module_extender 

17from astroid.builder import parse 

18from astroid.inference_tip import inference_tip 

19from astroid.manager import AstroidManager 

20from astroid.nodes.node_classes import Attribute, Name 

21 

22 

23def numpy_core_multiarray_transform() -> nodes.Module: 

24 return parse( 

25 """ 

26 # different functions defined in multiarray.py 

27 def inner(a, b): 

28 return numpy.ndarray([0, 0]) 

29 

30 def vdot(a, b): 

31 return numpy.ndarray([0, 0]) 

32 """ 

33 ) 

34 

35 

36METHODS_TO_BE_INFERRED = { 

37 "array": """def array(object, dtype=None, copy=True, order='K', subok=False, ndmin=0): 

38 return numpy.ndarray([0, 0])""", 

39 "dot": """def dot(a, b, out=None): 

40 return numpy.ndarray([0, 0])""", 

41 "empty_like": """def empty_like(a, dtype=None, order='K', subok=True): 

42 return numpy.ndarray((0, 0))""", 

43 "concatenate": """def concatenate(arrays, axis=None, out=None): 

44 return numpy.ndarray((0, 0))""", 

45 "where": """def where(condition, x=None, y=None): 

46 return numpy.ndarray([0, 0])""", 

47 "empty": """def empty(shape, dtype=float, order='C'): 

48 return numpy.ndarray([0, 0])""", 

49 "bincount": """def bincount(x, weights=None, minlength=0): 

50 return numpy.ndarray([0, 0])""", 

51 "busday_count": """def busday_count( 

52 begindates, enddates, weekmask='1111100', holidays=[], busdaycal=None, out=None 

53 ): 

54 return numpy.ndarray([0, 0])""", 

55 "busday_offset": """def busday_offset( 

56 dates, offsets, roll='raise', weekmask='1111100', holidays=None, 

57 busdaycal=None, out=None 

58 ): 

59 return numpy.ndarray([0, 0])""", 

60 "can_cast": """def can_cast(from_, to, casting='safe'): 

61 return True""", 

62 "copyto": """def copyto(dst, src, casting='same_kind', where=True): 

63 return None""", 

64 "datetime_as_string": """def datetime_as_string(arr, unit=None, timezone='naive', casting='same_kind'): 

65 return numpy.ndarray([0, 0])""", 

66 "is_busday": """def is_busday(dates, weekmask='1111100', holidays=None, busdaycal=None, out=None): 

67 return numpy.ndarray([0, 0])""", 

68 "lexsort": """def lexsort(keys, axis=-1): 

69 return numpy.ndarray([0, 0])""", 

70 "may_share_memory": """def may_share_memory(a, b, max_work=None): 

71 return True""", 

72 # Not yet available because dtype is not yet present in those brains 

73 # "min_scalar_type": """def min_scalar_type(a): 

74 # return numpy.dtype('int16')""", 

75 "packbits": """def packbits(a, axis=None, bitorder='big'): 

76 return numpy.ndarray([0, 0])""", 

77 # Not yet available because dtype is not yet present in those brains 

78 # "result_type": """def result_type(*arrays_and_dtypes): 

79 # return numpy.dtype('int16')""", 

80 "shares_memory": """def shares_memory(a, b, max_work=None): 

81 return True""", 

82 "unpackbits": """def unpackbits(a, axis=None, count=None, bitorder='big'): 

83 return numpy.ndarray([0, 0])""", 

84 "unravel_index": """def unravel_index(indices, shape, order='C'): 

85 return (numpy.ndarray([0, 0]),)""", 

86 "zeros": """def zeros(shape, dtype=float, order='C'): 

87 return numpy.ndarray([0, 0])""", 

88} 

89 

90 

91def register(manager: AstroidManager) -> None: 

92 register_module_extender( 

93 manager, "numpy.core.multiarray", numpy_core_multiarray_transform 

94 ) 

95 

96 method_names = frozenset(METHODS_TO_BE_INFERRED.keys()) 

97 

98 manager.register_transform( 

99 Attribute, 

100 inference_tip(functools.partial(infer_numpy_attribute, METHODS_TO_BE_INFERRED)), 

101 functools.partial(attribute_name_looks_like_numpy_member, method_names), 

102 ) 

103 manager.register_transform( 

104 Name, 

105 inference_tip(functools.partial(infer_numpy_name, METHODS_TO_BE_INFERRED)), 

106 functools.partial(member_name_looks_like_numpy_member, method_names), 

107 )