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import types
import zipfile
from collections.abc import Callable, Collection, Iterable, Iterator, Mapping, Sequence
from re import Pattern
from typing import IO, Any, ClassVar, Generic, Protocol, TypeAlias, overload, type_check_only
from typing import Literal as L
from _typeshed import StrOrBytesPath, StrPath, SupportsKeysAndGetItem, SupportsRead, SupportsWrite
from typing_extensions import Self, TypeVar, deprecated, override
import numpy as np
from numpy._core.multiarray import packbits, unpackbits
from numpy._typing import ArrayLike, DTypeLike, NDArray, _DTypeLike, _SupportsArrayFunc
from numpy.ma.mrecords import MaskedRecords
from ._datasource import DataSource as DataSource
__all__ = [
"fromregex",
"genfromtxt",
"load",
"loadtxt",
"packbits",
"save",
"savetxt",
"savez",
"savez_compressed",
"unpackbits",
]
_T_co = TypeVar("_T_co", covariant=True)
_SCT = TypeVar("_SCT", bound=np.generic)
_SCT_co = TypeVar("_SCT_co", bound=np.generic, default=Any, covariant=True)
_FName: TypeAlias = StrPath | Iterable[str] | Iterable[bytes]
_FNameRead: TypeAlias = StrPath | SupportsRead[str] | SupportsRead[bytes]
_FNameWriteBytes: TypeAlias = StrPath | SupportsWrite[bytes]
_FNameWrite: TypeAlias = _FNameWriteBytes | SupportsWrite[bytes]
@type_check_only
class _SupportsReadSeek(SupportsRead[_T_co], Protocol[_T_co]):
def seek(self, offset: int, whence: int, /) -> object: ...
class BagObj(Generic[_T_co]):
def __init__(self, /, obj: SupportsKeysAndGetItem[str, _T_co]) -> None: ...
def __getattribute__(self, key: str, /) -> _T_co: ...
def __dir__(self) -> list[str]: ...
class NpzFile(Mapping[str, NDArray[_SCT_co]]):
_MAX_REPR_ARRAY_COUNT: ClassVar[int] = 5
zip: zipfile.ZipFile
fid: IO[str] | None
files: list[str]
allow_pickle: bool
pickle_kwargs: Mapping[str, Any] | None
f: BagObj[NpzFile[_SCT_co]]
#
def __init__(
self,
/,
fid: IO[Any],
own_fid: bool = False,
allow_pickle: bool = False,
pickle_kwargs: Mapping[str, object] | None = None,
*,
max_header_size: int = 10_000,
) -> None: ...
def __del__(self) -> None: ...
def __enter__(self) -> Self: ...
def __exit__(self, cls: type[BaseException] | None, e: BaseException | None, tb: types.TracebackType | None, /) -> None: ...
@override
def __len__(self) -> int: ...
@override
def __iter__(self) -> Iterator[str]: ...
@override
def __getitem__(self, key: str, /) -> NDArray[_SCT_co]: ...
def close(self) -> None: ...
# NOTE: Returns a `NpzFile` if file is a zip file;
# returns an `ndarray`/`memmap` otherwise
def load(
file: StrOrBytesPath | _SupportsReadSeek[bytes],
mmap_mode: L["r+", "r", "w+", "c"] | None = None,
allow_pickle: bool = False,
fix_imports: bool = True,
encoding: L["ASCII", "latin1", "bytes"] = "ASCII",
*,
max_header_size: int = 10_000,
) -> Any: ...
@overload
def save(file: _FNameWriteBytes, arr: ArrayLike, allow_pickle: bool = True) -> None: ...
@overload
@deprecated("The 'fix_imports' flag is deprecated in NumPy 2.1.")
def save(file: _FNameWriteBytes, arr: ArrayLike, allow_pickle: bool, fix_imports: bool) -> None: ...
@overload
@deprecated("The 'fix_imports' flag is deprecated in NumPy 2.1.")
def save(file: _FNameWriteBytes, arr: ArrayLike, allow_pickle: bool = True, *, fix_imports: bool) -> None: ...
#
def savez(file: _FNameWriteBytes, *args: ArrayLike, allow_pickle: bool = True, **kwds: ArrayLike) -> None: ...
#
def savez_compressed(file: _FNameWriteBytes, *args: ArrayLike, allow_pickle: bool = True, **kwds: ArrayLike) -> None: ...
# File-like objects only have to implement `__iter__` and,
# optionally, `encoding`
@overload
def loadtxt(
fname: _FName,
dtype: None = None,
comments: str | Sequence[str] | None = "#",
delimiter: str | None = None,
converters: Mapping[int | str, Callable[[str], Any]] | Callable[[str], Any] | None = None,
skiprows: int = 0,
usecols: int | Sequence[int] | None = None,
unpack: bool = False,
ndmin: L[0, 1, 2] = 0,
encoding: str | None = None,
max_rows: int | None = None,
*,
quotechar: str | None = None,
like: _SupportsArrayFunc | None = None,
) -> NDArray[np.float64]: ...
@overload
def loadtxt(
fname: _FName,
dtype: _DTypeLike[_SCT],
comments: str | Sequence[str] | None = "#",
delimiter: str | None = None,
converters: Mapping[int | str, Callable[[str], Any]] | Callable[[str], Any] | None = None,
skiprows: int = 0,
usecols: int | Sequence[int] | None = None,
unpack: bool = False,
ndmin: L[0, 1, 2] = 0,
encoding: str | None = None,
max_rows: int | None = None,
*,
quotechar: str | None = None,
like: _SupportsArrayFunc | None = None,
) -> NDArray[_SCT]: ...
@overload
def loadtxt(
fname: _FName,
dtype: DTypeLike,
comments: str | Sequence[str] | None = "#",
delimiter: str | None = None,
converters: Mapping[int | str, Callable[[str], Any]] | Callable[[str], Any] | None = None,
skiprows: int = 0,
usecols: int | Sequence[int] | None = None,
unpack: bool = False,
ndmin: L[0, 1, 2] = 0,
encoding: str | None = None,
max_rows: int | None = None,
*,
quotechar: str | None = None,
like: _SupportsArrayFunc | None = None,
) -> NDArray[Any]: ...
def savetxt(
fname: StrPath | _FNameWrite,
X: ArrayLike,
fmt: str | Sequence[str] = "%.18e",
delimiter: str = " ",
newline: str = "\n",
header: str = "",
footer: str = "",
comments: str = "# ",
encoding: str | None = None,
) -> None: ...
@overload
def fromregex(
file: _FNameRead,
regexp: str | bytes | Pattern[Any],
dtype: _DTypeLike[_SCT],
encoding: str | None = None,
) -> NDArray[_SCT]: ...
@overload
def fromregex(
file: _FNameRead,
regexp: str | bytes | Pattern[Any],
dtype: DTypeLike,
encoding: str | None = None,
) -> NDArray[Any]: ...
@overload
def genfromtxt(
fname: _FName,
dtype: None = None,
comments: str = ...,
delimiter: str | int | Iterable[int] | None = ...,
skip_header: int = ...,
skip_footer: int = ...,
converters: Mapping[int | str, Callable[[str], Any]] | None = ...,
missing_values: Any = ...,
filling_values: Any = ...,
usecols: Sequence[int] | None = ...,
names: L[True] | str | Collection[str] | None = ...,
excludelist: Sequence[str] | None = ...,
deletechars: str = ...,
replace_space: str = ...,
autostrip: bool = ...,
case_sensitive: bool | L["upper", "lower"] = ...,
defaultfmt: str = ...,
unpack: bool | None = ...,
usemask: bool = ...,
loose: bool = ...,
invalid_raise: bool = ...,
max_rows: int | None = ...,
encoding: str = ...,
*,
ndmin: L[0, 1, 2] = ...,
like: _SupportsArrayFunc | None = ...,
) -> NDArray[Any]: ...
@overload
def genfromtxt(
fname: _FName,
dtype: _DTypeLike[_SCT],
comments: str = ...,
delimiter: str | int | Iterable[int] | None = ...,
skip_header: int = ...,
skip_footer: int = ...,
converters: Mapping[int | str, Callable[[str], Any]] | None = ...,
missing_values: Any = ...,
filling_values: Any = ...,
usecols: Sequence[int] | None = ...,
names: L[True] | str | Collection[str] | None = ...,
excludelist: Sequence[str] | None = ...,
deletechars: str = ...,
replace_space: str = ...,
autostrip: bool = ...,
case_sensitive: bool | L["upper", "lower"] = ...,
defaultfmt: str = ...,
unpack: bool | None = ...,
usemask: bool = ...,
loose: bool = ...,
invalid_raise: bool = ...,
max_rows: int | None = ...,
encoding: str = ...,
*,
ndmin: L[0, 1, 2] = ...,
like: _SupportsArrayFunc | None = ...,
) -> NDArray[_SCT]: ...
@overload
def genfromtxt(
fname: _FName,
dtype: DTypeLike,
comments: str = ...,
delimiter: str | int | Iterable[int] | None = ...,
skip_header: int = ...,
skip_footer: int = ...,
converters: Mapping[int | str, Callable[[str], Any]] | None = ...,
missing_values: Any = ...,
filling_values: Any = ...,
usecols: Sequence[int] | None = ...,
names: L[True] | str | Collection[str] | None = ...,
excludelist: Sequence[str] | None = ...,
deletechars: str = ...,
replace_space: str = ...,
autostrip: bool = ...,
case_sensitive: bool | L["upper", "lower"] = ...,
defaultfmt: str = ...,
unpack: bool | None = ...,
usemask: bool = ...,
loose: bool = ...,
invalid_raise: bool = ...,
max_rows: int | None = ...,
encoding: str = ...,
*,
ndmin: L[0, 1, 2] = ...,
like: _SupportsArrayFunc | None = ...,
) -> NDArray[Any]: ...
@overload
def recfromtxt(fname: _FName, *, usemask: L[False] = False, **kwargs: object) -> np.recarray[Any, np.dtype[np.record]]: ...
@overload
def recfromtxt(fname: _FName, *, usemask: L[True], **kwargs: object) -> MaskedRecords[Any, np.dtype[np.void]]: ...
@overload
def recfromcsv(fname: _FName, *, usemask: L[False] = False, **kwargs: object) -> np.recarray[Any, np.dtype[np.record]]: ...
@overload
def recfromcsv(fname: _FName, *, usemask: L[True], **kwargs: object) -> MaskedRecords[Any, np.dtype[np.void]]: ...
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