""" A NumPy sub-namespace that conforms to the Python array API standard. This is a proof-of-concept namespace that wraps the corresponding NumPy functions to give a conforming implementation of the Python array API standard (https://data-apis.github.io/array-api/latest/). The standard is currently in an RFC phase and comments on it are both welcome and encouraged. Comments should be made either at https://github.com/data-apis/array-api or at https://github.com/data-apis/consortium-feedback/discussions. This submodule will be accompanied with a NEP (not yet written) proposing its inclusion in NumPy. NumPy already follows the proposed spec for the most part, so this module serves mostly as a thin wrapper around it. However, NumPy also implements a lot of behavior that is not included in the spec, so this serves as a restricted subset of the API. Only those functions that are part of the spec are included in this namespace, and all functions are given with the exact signature given in the spec, including the use of position-only arguments, and omitting any extra keyword arguments implemented by NumPy but not part of the spec. Note that the array object itself is unchanged, as implementing a restricted subclass of ndarray seems unnecessarily complex for the purposes of this namespace, so the API of array methods and other behaviors of the array object will include things that are not part of the spec. The spec is designed as a "minimal API subset" and explicitly allows libraries to include behaviors not specified by it. But users of this module that intend to write portable code should be aware that only those behaviors that are listed in the spec are guaranteed to be implemented across libraries. A few notes about the current state of this submodule: - There is a test suite that tests modules against the array API standard at https://github.com/data-apis/array-api-tests. The test suite is still a work in progress, but the existing tests pass on this module, with a few exceptions: - Device support is not yet implemented in NumPy (https://data-apis.github.io/array-api/latest/design_topics/device_support.html). As a result, the `device` attribute of the array object is missing, and array creation functions that take the `device` keyword argument will fail with NotImplementedError. - DLPack support (see https://github.com/data-apis/array-api/pull/106) is not included here, as it requires a full implementation in NumPy proper first. - np.argmin and np.argmax do not implement the keepdims keyword argument. - Some linear algebra functions in the spec are still a work in progress (to be added soon). These will be updated once the spec is. - Some tests in the test suite are still not fully correct in that they test all datatypes whereas certain functions are only defined for a subset of datatypes. The test suite is yet complete, and even the tests that exist are not guaranteed to give a comprehensive coverage of the spec. Therefore, those reviewing this submodule should refer to the standard documents themselves. - All functions include type annotations, corresponding to those given in the spec (see _types.py for definitions of the types 'array', 'device', and 'dtype'). These do not currently fully pass mypy due to some limitations in mypy. - The array object is not modified at all. That means that functions return np.ndarray, which has methods and attributes that aren't part of the spec. Modifying/subclassing ndarray for the purposes of the array API namespace was considered too complex for this initial implementation. - All functions that would otherwise accept array-like input have been wrapped to only accept ndarray (with the exception of methods on the array object, which are not modified). - All places where the implementations in this submodule are known to deviate from their corresponding functions in NumPy are marked with "# Note" comments. Reviewers should make note of these comments. """ __all__ = [] from ._constants import e, inf, nan, pi __all__ += ['e', 'inf', 'nan', 'pi'] from ._creation_functions import asarray, arange, empty, empty_like, eye, from_dlpack, full, full_like, linspace, ones, ones_like, zeros, zeros_like __all__ += ['asarray', 'arange', 'empty', 'empty_like', 'eye', 'from_dlpack', 'full', 'full_like', 'linspace', 'ones', 'ones_like', 'zeros', 'zeros_like'] from ._data_type_functions import finfo, iinfo, result_type __all__ += ['finfo', 'iinfo', 'result_type'] from ._dtypes import int8, int16, int32, int64, uint8, uint16, uint32, uint64, float32, float64, bool __all__ += ['int8', 'int16', 'int32', 'int64', 'uint8', 'uint16', 'uint32', 'uint64', 'float32', 'float64', 'bool'] from ._elementwise_functions import abs, acos, acosh, add, asin, asinh, atan, atan2, atanh, bitwise_and, bitwise_left_shift, bitwise_invert, bitwise_or, bitwise_right_shift, bitwise_xor, ceil, cos, cosh, divide, equal, exp, expm1, floor, floor_divide, greater, greater_equal, isfinite, isinf, isnan, less, less_equal, log, log1p, log2, log10, logaddexp, logical_and, logical_not, logical_or, logical_xor, multiply, negative, not_equal, positive, pow, remainder, round, sign, sin, sinh, square, sqrt, subtract, tan, tanh, trunc __all__ += ['abs', 'acos', 'acosh', 'add', 'asin', 'asinh', 'atan', 'atan2', 'atanh', 'bitwise_and', 'bitwise_left_shift', 'bitwise_invert', 'bitwise_or', 'bitwise_right_shift', 'bitwise_xor', 'ceil', 'cos', 'cosh', 'divide', 'equal', 'exp', 'expm1', 'floor', 'floor_divide', 'greater', 'greater_equal', 'isfinite', 'isinf', 'isnan', 'less', 'less_equal', 'log', 'log1p', 'log2', 'log10', 'logaddexp', 'logical_and', 'logical_not', 'logical_or', 'logical_xor', 'multiply', 'negative', 'not_equal', 'positive', 'pow', 'remainder', 'round', 'sign', 'sin', 'sinh', 'square', 'sqrt', 'subtract', 'tan', 'tanh', 'trunc'] from ._linear_algebra_functions import cross, det, diagonal, inv, norm, outer, trace, transpose __all__ += ['cross', 'det', 'diagonal', 'inv', 'norm', 'outer', 'trace', 'transpose'] # from ._linear_algebra_functions import cholesky, cross, det, diagonal, dot, eig, eigvalsh, einsum, inv, lstsq, matmul, matrix_power, matrix_rank, norm, outer, pinv, qr, slogdet, solve, svd, trace, transpose # # __all__ += ['cholesky', 'cross', 'det', 'diagonal', 'dot', 'eig', 'eigvalsh', 'einsum', 'inv', 'lstsq', 'matmul', 'matrix_power', 'matrix_rank', 'norm', 'outer', 'pinv', 'qr', 'slogdet', 'solve', 'svd', 'trace', 'transpose'] from ._manipulation_functions import concat, expand_dims, flip, reshape, roll, squeeze, stack __all__ += ['concat', 'expand_dims', 'flip', 'reshape', 'roll', 'squeeze', 'stack'] from ._searching_functions import argmax, argmin, nonzero, where __all__ += ['argmax', 'argmin', 'nonzero', 'where'] from ._set_functions import unique __all__ += ['unique'] from ._sorting_functions import argsort, sort __all__ += ['argsort', 'sort'] from ._statistical_functions import max, mean, min, prod, std, sum, var __all__ += ['max', 'mean', 'min', 'prod', 'std', 'sum', 'var'] from ._utility_functions import all, any __all__ += ['all', 'any']