113 lines
3.2 KiB
Python
113 lines
3.2 KiB
Python
from __future__ import annotations
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from ._array_object import Array
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from ._data_type_functions import result_type
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from typing import List, Optional, Tuple, Union
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import numpy as np
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# Note: the function name is different here
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def concat(
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arrays: Union[Tuple[Array, ...], List[Array]], /, *, axis: Optional[int] = 0
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) -> Array:
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"""
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Array API compatible wrapper for :py:func:`np.concatenate <numpy.concatenate>`.
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See its docstring for more information.
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"""
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# Note: Casting rules here are different from the np.concatenate default
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# (no for scalars with axis=None, no cross-kind casting)
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dtype = result_type(*arrays)
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arrays = tuple(a._array for a in arrays)
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return Array._new(np.concatenate(arrays, axis=axis, dtype=dtype))
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def expand_dims(x: Array, /, *, axis: int) -> Array:
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"""
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Array API compatible wrapper for :py:func:`np.expand_dims <numpy.expand_dims>`.
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See its docstring for more information.
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"""
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return Array._new(np.expand_dims(x._array, axis))
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def flip(x: Array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None) -> Array:
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"""
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Array API compatible wrapper for :py:func:`np.flip <numpy.flip>`.
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See its docstring for more information.
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"""
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return Array._new(np.flip(x._array, axis=axis))
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# Note: The function name is different here (see also matrix_transpose).
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# Unlike transpose(), the axes argument is required.
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def permute_dims(x: Array, /, axes: Tuple[int, ...]) -> Array:
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"""
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Array API compatible wrapper for :py:func:`np.transpose <numpy.transpose>`.
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See its docstring for more information.
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"""
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return Array._new(np.transpose(x._array, axes))
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# Note: the optional argument is called 'shape', not 'newshape'
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def reshape(x: Array,
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/,
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shape: Tuple[int, ...],
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*,
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copy: Optional[Bool] = None) -> Array:
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"""
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Array API compatible wrapper for :py:func:`np.reshape <numpy.reshape>`.
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See its docstring for more information.
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"""
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data = x._array
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if copy:
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data = np.copy(data)
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reshaped = np.reshape(data, shape)
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if copy is False and not np.shares_memory(data, reshaped):
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raise AttributeError("Incompatible shape for in-place modification.")
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return Array._new(reshaped)
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def roll(
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x: Array,
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/,
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shift: Union[int, Tuple[int, ...]],
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*,
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axis: Optional[Union[int, Tuple[int, ...]]] = None,
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) -> Array:
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"""
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Array API compatible wrapper for :py:func:`np.roll <numpy.roll>`.
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See its docstring for more information.
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"""
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return Array._new(np.roll(x._array, shift, axis=axis))
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def squeeze(x: Array, /, axis: Union[int, Tuple[int, ...]]) -> Array:
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"""
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Array API compatible wrapper for :py:func:`np.squeeze <numpy.squeeze>`.
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See its docstring for more information.
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"""
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return Array._new(np.squeeze(x._array, axis=axis))
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def stack(arrays: Union[Tuple[Array, ...], List[Array]], /, *, axis: int = 0) -> Array:
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"""
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Array API compatible wrapper for :py:func:`np.stack <numpy.stack>`.
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See its docstring for more information.
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"""
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# Call result type here just to raise on disallowed type combinations
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result_type(*arrays)
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arrays = tuple(a._array for a in arrays)
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return Array._new(np.stack(arrays, axis=axis))
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