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+"""
+A NumPy sub-namespace that conforms to the Python array API standard.
+
+This submodule accompanies NEP 47, which proposes its inclusion in NumPy. It
+is still considered experimental, and will issue a warning when imported.
+
+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.
+
+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. The behavior of some functions is also modified from the NumPy behavior
+to conform to the standard. Note that the underlying array object itself is
+wrapped in a wrapper Array() class, but is otherwise unchanged. This submodule
+is implemented in pure Python with no C extensions.
+
+The array API 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.
+Consequently, the NumPy implementation was chosen to be both conforming and
+minimal, so that users can use this implementation of the array API namespace
+and be sure that behaviors that it defines will be available in conforming
+namespaces from other 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:
+
+ - 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.
+
+ The test suite is not yet complete, and even the tests that exist are not
+ guaranteed to give a comprehensive coverage of the spec. Therefore, when
+ reviewing and using this submodule, you should refer to the standard
+ documents themselves. There are some tests in numpy.array_api.tests, but
+ they primarily focus on things that are not tested by the official array API
+ test suite.
+
+- There is a custom array object, numpy.array_api.Array, which is returned by
+ all functions in this module. All functions in the array API namespace
+ implicitly assume that they will only receive this object as input. The only
+ way to create instances of this object is to use one of the array creation
+ functions. It does not have a public constructor on the object itself. The
+ object is a small wrapper class around numpy.ndarray. The main purpose of it
+ is to restrict the namespace of the array object to only those dtypes and
+ only those methods that are required by the spec, as well as to limit/change
+ certain behavior that differs in the spec. In particular:
+
+ - The array API namespace does not have scalar objects, only 0-D arrays.
+ Operations on Array that would create a scalar in NumPy create a 0-D
+ array.
+
+ - Indexing: Only a subset of indices supported by NumPy are required by the
+ spec. The Array object restricts indexing to only allow those types of
+ indices that are required by the spec. See the docstring of the
+ numpy.array_api.Array._validate_indices helper function for more
+ information.
+
+ - Type promotion: Some type promotion rules are different in the spec. In
+ particular, the spec does not have any value-based casting. The spec also
+ does not require cross-kind casting, like integer -> floating-point. Only
+ those promotions that are explicitly required by the array API
+ specification are allowed in this module. See NEP 47 for more info.
+
+ - Functions do not automatically call asarray() on their input, and will not
+ work if the input type is not Array. The exception is array creation
+ functions, and Python operators on the Array object, which accept Python
+ scalars of the same type as the array dtype.
+
+- All functions include type annotations, corresponding to those given in the
+ spec (see _typing.py for definitions of some custom types). These do not
+ currently fully pass mypy due to some limitations in mypy.
+
+- Dtype objects are just the NumPy dtype objects, e.g., float64 =
+ np.dtype('float64'). The spec does not require any behavior on these dtype
+ objects other than that they be accessible by name and be comparable by
+ equality, but it was considered too much extra complexity to create custom
+ objects to represent dtypes.
+
+- All places where the implementations in this submodule are known to deviate
+ from their corresponding functions in NumPy are marked with "# Note:"
+ comments.
+
+Still TODO in this module are:
+
+- DLPack support for numpy.ndarray is still in progress. See
+ https://github.com/numpy/numpy/pull/19083.
+
+- The copy=False keyword argument to asarray() is not yet implemented. This
+ requires support in numpy.asarray() first.
+
+- Some functions are not yet fully tested in the array API test suite, and may
+ require updates that are not yet known until the tests are written.
+
+- The spec is still in an RFC phase and may still have minor updates, which
+ will need to be reflected here.
+
+- The linear algebra extension in the spec will be added in a future pull
+ request.
+
+- Complex number support in array API spec is planned but not yet finalized,
+ as are the fft extension and certain linear algebra functions such as eig
+ that require complex dtypes.
+
+"""
+
+import warnings
+
+warnings.warn(
+ "The numpy.array_api submodule is still experimental. See NEP 47.", stacklevel=2
+)
+
+__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,
+ meshgrid,
+ ones,
+ ones_like,
+ zeros,
+ zeros_like,
+)
+
+__all__ += [
+ "asarray",
+ "arange",
+ "empty",
+ "empty_like",
+ "eye",
+ "from_dlpack",
+ "full",
+ "full_like",
+ "linspace",
+ "meshgrid",
+ "ones",
+ "ones_like",
+ "zeros",
+ "zeros_like",
+]
+
+from ._data_type_functions import (
+ broadcast_arrays,
+ broadcast_to,
+ can_cast,
+ finfo,
+ iinfo,
+ result_type,
+)
+
+__all__ += [
+ "broadcast_arrays",
+ "broadcast_to",
+ "can_cast",
+ "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",
+]
+
+# einsum is not yet implemented in the array API spec.
+
+# from ._linear_algebra_functions import einsum
+# __all__ += ['einsum']
+
+from ._linear_algebra_functions import matmul, tensordot, transpose, vecdot
+
+__all__ += ["matmul", "tensordot", "transpose", "vecdot"]
+
+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"]