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# Copyright (c) 2005-2011, NumPy Developers.
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following
# disclaimer in the documentation and/or other materials provided
# with the distribution.
# * Neither the name of the NumPy Developers nor the names of any
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
from __future__ import annotations
from typing import Any
try:
# requires numpy>=2.0
from numpy import isdtype # type: ignore[attr-defined,unused-ignore]
HAS_STRING_DTYPE = True
except ImportError:
import numpy as np
from numpy.typing import DTypeLike
kind_mapping = {
"bool": np.bool_,
"signed integer": np.signedinteger,
"unsigned integer": np.unsignedinteger,
"integral": np.integer,
"real floating": np.floating,
"complex floating": np.complexfloating,
"numeric": np.number,
}
def isdtype(
dtype: np.dtype[Any] | type[Any], kind: DTypeLike | tuple[DTypeLike, ...]
) -> bool:
kinds = kind if isinstance(kind, tuple) else (kind,)
str_kinds = {k for k in kinds if isinstance(k, str)}
type_kinds = {k.type for k in kinds if isinstance(k, np.dtype)}
if unknown_kind_types := set(kinds) - str_kinds - type_kinds:
raise TypeError(
f"kind must be str, np.dtype or a tuple of these, got {unknown_kind_types}"
)
if unknown_kinds := {k for k in str_kinds if k not in kind_mapping}:
raise ValueError(
f"unknown kind: {unknown_kinds}, must be a np.dtype or one of {list(kind_mapping)}"
)
# verified the dtypes already, no need to check again
translated_kinds = {kind_mapping[k] for k in str_kinds} | type_kinds
if isinstance(dtype, np.generic):
return isinstance(dtype, translated_kinds)
else:
return any(np.issubdtype(dtype, k) for k in translated_kinds)
HAS_STRING_DTYPE = False
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