OXIESEC PANEL

Name	Size	Modified	Perms
📁 ..	-	10/26/2024 01:27:22 PM	rwxr-xr-x
📄 __init__.py	9.98 KB	10/26/2024 01:27:11 PM	rw-r--r--
📁 __pycache__	-	10/26/2024 01:28:08 PM	rwxr-xr-x
📄 _array_object.py	42.21 KB	10/26/2024 01:27:08 PM	rw-r--r--
📄 _constants.py	66 bytes	10/26/2024 01:27:09 PM	rw-r--r--
📄 _creation_functions.py	9.81 KB	10/26/2024 01:27:09 PM	rw-r--r--
📄 _data_type_functions.py	4.38 KB	10/26/2024 01:27:09 PM	rw-r--r--
📄 _dtypes.py	3.62 KB	10/26/2024 01:27:09 PM	rw-r--r--
📄 _elementwise_functions.py	24.19 KB	10/26/2024 01:27:10 PM	rw-r--r--
📄 _manipulation_functions.py	2.94 KB	10/26/2024 01:27:10 PM	rw-r--r--
📄 _searching_functions.py	1.42 KB	10/26/2024 01:27:10 PM	rw-r--r--
📄 _set_functions.py	2.88 KB	10/26/2024 01:27:10 PM	rw-r--r--
📄 _sorting_functions.py	1.71 KB	10/26/2024 01:27:11 PM	rw-r--r--
📄 _statistical_functions.py	3.3 KB	10/26/2024 01:27:11 PM	rw-r--r--
📄 _typing.py	1.34 KB	10/26/2024 01:27:11 PM	rw-r--r--
📄 _utility_functions.py	824 bytes	10/26/2024 01:27:11 PM	rw-r--r--
📄 linalg.py	17.44 KB	10/26/2024 01:27:07 PM	rw-r--r--
📄 setup.py	341 bytes	10/26/2024 01:27:08 PM	rw-r--r--
📁 tests	-	10/26/2024 01:29:20 PM	rwxr-xr-x

Editing: _set_functions.py

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)