o YÚÁieã@sŠUdZddlmZmZddlmZmZmZ gZ e e e d<ddœdd„Zd d œd d „Zd d œd d„Zd d œdd„Zddd„Zddd„ZdS)aÜ Extra testing functions that forbid 0d-input, see #21044 While the xp_assert_* functions generally aim to follow the conventions of the underlying `xp` library, NumPy in particular is inconsistent in its handling of scalars vs. 0d-arrays, see https://github.com/numpy/numpy/issues/24897. For example, this means that the following operations (as of v2.0.1) currently return scalars, even though a 0d-array would often be more appropriate: import numpy as np np.array(0) * 2 # scalar, not 0d array - np.array(0) # scalar, not 0d-array np.sin(np.array(0)) # scalar, not 0d array np.mean([1, 2, 3]) # scalar, not 0d array Libraries like CuPy tend to return a 0d-array in scenarios like those above, and even `xp.asarray(0)[()]` remains a 0d-array there. To deal with the reality of the inconsistencies present in NumPy, as well as 20+ years of code on top, the `xp_assert_*` functions here enforce consistency in the only way that doesn't go against the tide, i.e. by forbidding 0d-arrays as the return type. However, when scalars are not generally the expected NumPy return type, it remains preferable to use the assert functions from the `scipy._lib._array_api` module, which have less surprising behaviour. é)Úarray_namespaceÚis_numpy)Úxp_assert_closeÚxp_assert_equalÚxp_assert_lessÚ__all__N)ÚxpcKsNd}|dur t|ƒ}| |¡}t|ƒr|jdksdSd}| |¡s%J|ƒ‚dS)NT©aÂResult is a NumPy 0d-array. Many SciPy functions intend to follow the convention of many NumPy functions, returning a scalar when a 0d-array would be correct. The specialized `xp_assert_*` functions in the `scipy._lib._array_api_no_0d` module err on the side of caution and do not accept 0d-arrays by default. If the correct result may legitimately be a 0d-array, pass `check_0d=True`, or use the `xp_assert_*` functions from `scipy._lib._array_api`.)rÚasarrayrÚshapeÚisscalar)ÚactualÚdesiredrÚkwargsÚ__tracebackhide__Ú_msgr r úB/tmp/pip-target-1s0edx8b/lib/python/scipy/_lib/_array_api_no_0d.pyÚ _check_scalar#s rF)Úcheck_0dcKó0d}|s t||fi|¤Žt||fd|i|¤ŽS©NTr)rÚxp_assert_equal_base©r rrrrr r rr;srcKrr)rÚxp_assert_close_baserr r rrFórcKrr)rÚxp_assert_less_baserr r rrOrrécOó6ddd| }}t||g|¢R||dddœ|¤ŽS©zPBackwards compatible replacement. In new code, use xp_assert_close instead. rgø?é F)ÚatolÚrtolÚ check_dtypeÚ check_shape©r©r rÚdecimalÚargsÚkwdsr!r r r rÚassert_array_almost_equalXóþÿþr)écOrrr$r%r r rÚassert_almost_equalar*r,)r)r+)Ú__doc__Úscipy._lib._array_apirrrrrrrrrÚlistÚstrÚ__annotations__rr)r,r r r rÚs