Coverage for /pythoncovmergedfiles/medio/medio/usr/local/lib/python3.9/dist-packages/numpy/exceptions.py: 54%

1""" 

2Exceptions and Warnings (:mod:`numpy.exceptions`) 

3================================================= 

4 

5General exceptions used by NumPy. Note that some exceptions may be module 

6specific, such as linear algebra errors. 

7 

8.. versionadded:: NumPy 1.25 

9 

10 The exceptions module is new in NumPy 1.25. Older exceptions remain 

11 available through the main NumPy namespace for compatibility. 

12 

13.. currentmodule:: numpy.exceptions 

14 

15Warnings 

16-------- 

17.. autosummary:: 

18 :toctree: generated/ 

19 

20 ComplexWarning Given when converting complex to real. 

21 VisibleDeprecationWarning Same as a DeprecationWarning, but more visible. 

22 RankWarning Issued when the design matrix is rank deficient. 

23 

24Exceptions 

25---------- 

26.. autosummary:: 

27 :toctree: generated/ 

28 

29 AxisError Given when an axis was invalid. 

30 DTypePromotionError Given when no common dtype could be found. 

31 TooHardError Error specific to `numpy.shares_memory`. 

32 

33""" 

34 

35 

36__all__ = [ 

37 "ComplexWarning", "VisibleDeprecationWarning", "ModuleDeprecationWarning", 

38 "TooHardError", "AxisError", "DTypePromotionError"] 

39 

40 

41# Disallow reloading this module so as to preserve the identities of the 

42# classes defined here. 

43if '_is_loaded' in globals(): 

44 raise RuntimeError('Reloading numpy._globals is not allowed') 

45_is_loaded = True 

46 

47 

48class ComplexWarning(RuntimeWarning): 

49 """ 

50 The warning raised when casting a complex dtype to a real dtype. 

51 

52 As implemented, casting a complex number to a real discards its imaginary 

53 part, but this behavior may not be what the user actually wants. 

54 

55 """ 

56 pass 

57 

58 

59class ModuleDeprecationWarning(DeprecationWarning): 

60 """Module deprecation warning. 

61 

62 .. warning:: 

63 

64 This warning should not be used, since nose testing is not relevant 

65 anymore. 

66 

67 The nose tester turns ordinary Deprecation warnings into test failures. 

68 That makes it hard to deprecate whole modules, because they get 

69 imported by default. So this is a special Deprecation warning that the 

70 nose tester will let pass without making tests fail. 

71 

72 """ 

73 pass 

74 

75 

76class VisibleDeprecationWarning(UserWarning): 

77 """Visible deprecation warning. 

78 

79 By default, python will not show deprecation warnings, so this class 

80 can be used when a very visible warning is helpful, for example because 

81 the usage is most likely a user bug. 

82 

83 """ 

84 pass 

85 

86 

87class RankWarning(RuntimeWarning): 

88 """Matrix rank warning. 

89  

90 Issued by polynomial functions when the design matrix is rank deficient. 

91  

92 """ 

93 pass 

94 

95 

96# Exception used in shares_memory() 

97class TooHardError(RuntimeError): 

98 """max_work was exceeded. 

99 

100 This is raised whenever the maximum number of candidate solutions 

101 to consider specified by the ``max_work`` parameter is exceeded. 

102 Assigning a finite number to max_work may have caused the operation 

103 to fail. 

104 

105 """ 

106 pass 

107 

108 

109class AxisError(ValueError, IndexError): 

110 """Axis supplied was invalid. 

111 

112 This is raised whenever an ``axis`` parameter is specified that is larger 

113 than the number of array dimensions. 

114 For compatibility with code written against older numpy versions, which 

115 raised a mixture of :exc:`ValueError` and :exc:`IndexError` for this 

116 situation, this exception subclasses both to ensure that 

117 ``except ValueError`` and ``except IndexError`` statements continue 

118 to catch ``AxisError``. 

119 

120 .. versionadded:: 1.13 

121 

122 Parameters 

123 ---------- 

124 axis : int or str 

125 The out of bounds axis or a custom exception message. 

126 If an axis is provided, then `ndim` should be specified as well. 

127 ndim : int, optional 

128 The number of array dimensions. 

129 msg_prefix : str, optional 

130 A prefix for the exception message. 

131 

132 Attributes 

133 ---------- 

134 axis : int, optional 

135 The out of bounds axis or ``None`` if a custom exception 

136 message was provided. This should be the axis as passed by 

137 the user, before any normalization to resolve negative indices. 

138 

139 .. versionadded:: 1.22 

140 ndim : int, optional 

141 The number of array dimensions or ``None`` if a custom exception 

142 message was provided. 

143 

144 .. versionadded:: 1.22 

145 

146 

147 Examples 

148 -------- 

149 >>> array_1d = np.arange(10) 

150 >>> np.cumsum(array_1d, axis=1) 

151 Traceback (most recent call last): 

152 ... 

153 numpy.exceptions.AxisError: axis 1 is out of bounds for array of dimension 1 

154 

155 Negative axes are preserved: 

156 

157 >>> np.cumsum(array_1d, axis=-2) 

158 Traceback (most recent call last): 

159 ... 

160 numpy.exceptions.AxisError: axis -2 is out of bounds for array of dimension 1 

161 

162 The class constructor generally takes the axis and arrays' 

163 dimensionality as arguments: 

164 

165 >>> print(np.exceptions.AxisError(2, 1, msg_prefix='error')) 

166 error: axis 2 is out of bounds for array of dimension 1 

167 

168 Alternatively, a custom exception message can be passed: 

169 

170 >>> print(np.exceptions.AxisError('Custom error message')) 

171 Custom error message 

172 

173 """ 

174 

175 __slots__ = ("axis", "ndim", "_msg") 

176 

177 def __init__(self, axis, ndim=None, msg_prefix=None): 

178 if ndim is msg_prefix is None: 

179 # single-argument form: directly set the error message 

180 self._msg = axis 

181 self.axis = None 

182 self.ndim = None 

183 else: 

184 self._msg = msg_prefix 

185 self.axis = axis 

186 self.ndim = ndim 

187 

188 def __str__(self): 

189 axis = self.axis 

190 ndim = self.ndim 

191 

192 if axis is ndim is None: 

193 return self._msg 

194 else: 

195 msg = f"axis {axis} is out of bounds for array of dimension {ndim}" 

196 if self._msg is not None: 

197 msg = f"{self._msg}: {msg}" 

198 return msg 

199 

200 

201class DTypePromotionError(TypeError): 

202 """Multiple DTypes could not be converted to a common one. 

203 

204 This exception derives from ``TypeError`` and is raised whenever dtypes 

205 cannot be converted to a single common one. This can be because they 

206 are of a different category/class or incompatible instances of the same 

207 one (see Examples). 

208 

209 Notes 

210 ----- 

211 Many functions will use promotion to find the correct result and 

212 implementation. For these functions the error will typically be chained 

213 with a more specific error indicating that no implementation was found 

214 for the input dtypes. 

215 

216 Typically promotion should be considered "invalid" between the dtypes of 

217 two arrays when `arr1 == arr2` can safely return all ``False`` because the 

218 dtypes are fundamentally different. 

219 

220 Examples 

221 -------- 

222 Datetimes and complex numbers are incompatible classes and cannot be 

223 promoted: 

224 

225 >>> np.result_type(np.dtype("M8[s]"), np.complex128) 

226 DTypePromotionError: The DType <class 'numpy.dtype[datetime64]'> could not 

227 be promoted by <class 'numpy.dtype[complex128]'>. This means that no common 

228 DType exists for the given inputs. For example they cannot be stored in a 

229 single array unless the dtype is `object`. The full list of DTypes is: 

230 (<class 'numpy.dtype[datetime64]'>, <class 'numpy.dtype[complex128]'>) 

231 

232 For example for structured dtypes, the structure can mismatch and the 

233 same ``DTypePromotionError`` is given when two structured dtypes with 

234 a mismatch in their number of fields is given: 

235 

236 >>> dtype1 = np.dtype([("field1", np.float64), ("field2", np.int64)]) 

237 >>> dtype2 = np.dtype([("field1", np.float64)]) 

238 >>> np.promote_types(dtype1, dtype2) 

239 DTypePromotionError: field names `('field1', 'field2')` and `('field1',)` 

240 mismatch. 

241 

242 """ 

243 pass