FM / array

/opt/cloudlinux/venv/lib/python3.11/site-packages/numpy/array_api/

/opt/cloudlinux/venv/lib/python3.11/site-packages/numpy/array_api

Name	Size	Mode	Actions
tests/	-	0755	rm
__pycache__/	-	0755	rm
linalg.py	18221	0644	edit dl rm
setup.py	341	0644	edit dl rm
_array_object.py	43739	0644	edit dl rm
_constants.py	66	0644	edit dl rm
_creation_functions.py	10050	0644	edit dl rm
_data_type_functions.py	6288	0644	edit dl rm
_dtypes.py	4823	0644	edit dl rm
_elementwise_functions.py	25992	0644	edit dl rm
_indexing_functions.py	601	0644	edit dl rm
_manipulation_functions.py	3317	0644	edit dl rm
_searching_functions.py	1715	0644	edit dl rm
_set_functions.py	2948	0644	edit dl rm
_sorting_functions.py	2031	0644	edit dl rm
_statistical_functions.py	3584	0644	edit dl rm
_typing.py	1228	0644	edit dl rm
_utility_functions.py	824	0644	edit dl rm
__init__.py	10355	0644	edit dl rm

Edit: /opt/cloudlinux/venv/lib/python3.11/site-packages/numpy/array_api/_set_functions.py (2948B)

from __future__ import annotations

from ._array_object import Array

from typing import NamedTuple

import numpy as np

# Note: np.unique() is split into four functions in the array API:
# unique_all, unique_counts, unique_inverse, and unique_values (this is done
# to remove polymorphic return types).

# Note: The various unique() functions are supposed to return multiple NaNs.
# This does not match the NumPy behavior, however, this is currently left as a
# TODO in this implementation as this behavior may be reverted in np.unique().
# See https://github.com/numpy/numpy/issues/20326.

# Note: The functions here return a namedtuple (np.unique() returns a normal
# tuple).

class UniqueAllResult(NamedTuple):
    values: Array
    indices: Array
    inverse_indices: Array
    counts: Array

class UniqueCountsResult(NamedTuple):
    values: Array
    counts: Array

class UniqueInverseResult(NamedTuple):
    values: Array
    inverse_indices: Array

def unique_all(x: Array, /) -> UniqueAllResult:
    """
    Array API compatible wrapper for :py:func:`np.unique <numpy.unique>`.

See its docstring for more information.
    """
    values, indices, inverse_indices, counts = np.unique(
        x._array,
        return_counts=True,
        return_index=True,
        return_inverse=True,
        equal_nan=False,
    )
    # np.unique() flattens inverse indices, but they need to share x's shape
    # See https://github.com/numpy/numpy/issues/20638
    inverse_indices = inverse_indices.reshape(x.shape)
    return UniqueAllResult(
        Array._new(values),
        Array._new(indices),
        Array._new(inverse_indices),
        Array._new(counts),
    )

def unique_counts(x: Array, /) -> UniqueCountsResult:
    res = np.unique(
        x._array,
        return_counts=True,
        return_index=False,
        return_inverse=False,
        equal_nan=False,
    )

return UniqueCountsResult(*[Array._new(i) for i in res])

def unique_inverse(x: Array, /) -> UniqueInverseResult:
    """
    Array API compatible wrapper for :py:func:`np.unique <numpy.unique>`.

See its docstring for more information.
    """
    values, inverse_indices = np.unique(
        x._array,
        return_counts=False,
        return_index=False,
        return_inverse=True,
        equal_nan=False,
    )
    # np.unique() flattens inverse indices, but they need to share x's shape
    # See https://github.com/numpy/numpy/issues/20638
    inverse_indices = inverse_indices.reshape(x.shape)
    return UniqueInverseResult(Array._new(values), Array._new(inverse_indices))

def unique_values(x: Array, /) -> Array:
    """
    Array API compatible wrapper for :py:func:`np.unique <numpy.unique>`.

See its docstring for more information.
    """
    res = np.unique(
        x._array,
        return_counts=False,
        return_index=False,
        return_inverse=False,
        equal_nan=False,
    )
    return Array._new(res)

from __future__ import annotations from ._array_object import Array from typing import NamedTuple import numpy as np # Note: np.unique() is split into four functions in the array API: # unique_all, unique_counts, unique_inverse, and unique_values (this is done # to remove polymorphic return types). # Note: The various unique() functions are supposed to return multiple NaNs. # This does not match the NumPy behavior, however, this is currently left as a # TODO in this implementation as this behavior may be reverted in np.unique(). # See https://github.com/numpy/numpy/issues/20326. # Note: The functions here return a namedtuple (np.unique() returns a normal # tuple). class UniqueAllResult(NamedTuple): values: Array indices: Array inverse_indices: Array counts: Array class UniqueCountsResult(NamedTuple): values: Array counts: Array class UniqueInverseResult(NamedTuple): values: Array inverse_indices: Array def unique_all(x: Array, /) -> UniqueAllResult: """ Array API compatible wrapper for :py:func:`np.unique `. See its docstring for more information. """ values, indices, inverse_indices, counts = np.unique( x._array, return_counts=True, return_index=True, return_inverse=True, equal_nan=False, ) # np.unique() flattens inverse indices, but they need to share x's shape # See https://github.com/numpy/numpy/issues/20638 inverse_indices = inverse_indices.reshape(x.shape) return UniqueAllResult( Array._new(values), Array._new(indices), Array._new(inverse_indices), Array._new(counts), ) def unique_counts(x: Array, /) -> UniqueCountsResult: res = np.unique( x._array, return_counts=True, return_index=False, return_inverse=False, equal_nan=False, ) return UniqueCountsResult(*[Array._new(i) for i in res]) def unique_inverse(x: Array, /) -> UniqueInverseResult: """ Array API compatible wrapper for :py:func:`np.unique `. See its docstring for more information. """ values, inverse_indices = np.unique( x._array, return_counts=False, return_index=False, return_inverse=True, equal_nan=False, ) # np.unique() flattens inverse indices, but they need to share x's shape # See https://github.com/numpy/numpy/issues/20638 inverse_indices = inverse_indices.reshape(x.shape) return UniqueInverseResult(Array._new(values), Array._new(inverse_indices)) def unique_values(x: Array, /) -> Array: """ Array API compatible wrapper for :py:func:`np.unique `. See its docstring for more information. """ res = np.unique( x._array, return_counts=False, return_index=False, return_inverse=False, equal_nan=False, ) return Array._new(res)