up follow livre

venv/lib/python3.13/site-packages/matplotlib/cbook.pyi

@@ -0,0 +1,173 @@
+import collections.abc
+from collections.abc import Callable, Collection, Generator, Iterable, Iterator
+import contextlib
+import os
+from pathlib import Path
+
+from matplotlib.artist import Artist
+
+import numpy as np
+from numpy.typing import ArrayLike
+
+from typing import (
+    Any,
+    Generic,
+    IO,
+    Literal,
+    TypeVar,
+    overload,
+)
+
+_T = TypeVar("_T")
+
+def _get_running_interactive_framework() -> str | None: ...
+
+class CallbackRegistry:
+    exception_handler: Callable[[Exception], Any]
+    callbacks: dict[Any, dict[int, Any]]
+    def __init__(
+        self,
+        exception_handler: Callable[[Exception], Any] | None = ...,
+        *,
+        signals: Iterable[Any] | None = ...,
+    ) -> None: ...
+    def connect(self, signal: Any, func: Callable) -> int: ...
+    def disconnect(self, cid: int) -> None: ...
+    def process(self, s: Any, *args, **kwargs) -> None: ...
+    def blocked(
+        self, *, signal: Any | None = ...
+    ) -> contextlib.AbstractContextManager[None]: ...
+
+class silent_list(list[_T]):
+    type: str | None
+    def __init__(self, type: str | None, seq: Iterable[_T] | None = ...) -> None: ...
+
+def strip_math(s: str) -> str: ...
+def is_writable_file_like(obj: Any) -> bool: ...
+def file_requires_unicode(x: Any) -> bool: ...
+@overload
+def to_filehandle(
+    fname: str | os.PathLike | IO,
+    flag: str = ...,
+    return_opened: Literal[False] = ...,
+    encoding: str | None = ...,
+) -> IO: ...
+@overload
+def to_filehandle(
+    fname: str | os.PathLike | IO,
+    flag: str,
+    return_opened: Literal[True],
+    encoding: str | None = ...,
+) -> tuple[IO, bool]: ...
+@overload
+def to_filehandle(
+    fname: str | os.PathLike | IO,
+    *,  # if flag given, will match previous sig
+    return_opened: Literal[True],
+    encoding: str | None = ...,
+) -> tuple[IO, bool]: ...
+def open_file_cm(
+    path_or_file: str | os.PathLike | IO,
+    mode: str = ...,
+    encoding: str | None = ...,
+) -> contextlib.AbstractContextManager[IO]: ...
+def is_scalar_or_string(val: Any) -> bool: ...
+@overload
+def get_sample_data(
+    fname: str | os.PathLike, asfileobj: Literal[True] = ...
+) -> np.ndarray | IO: ...
+@overload
+def get_sample_data(fname: str | os.PathLike, asfileobj: Literal[False]) -> str: ...
+def _get_data_path(*args: Path | str) -> Path: ...
+def flatten(
+    seq: Iterable[Any], scalarp: Callable[[Any], bool] = ...
+) -> Generator[Any, None, None]: ...
+
+class _Stack(Generic[_T]):
+    def __init__(self) -> None: ...
+    def clear(self) -> None: ...
+    def __call__(self) -> _T: ...
+    def __len__(self) -> int: ...
+    def __getitem__(self, ind: int) -> _T: ...
+    def forward(self) -> _T: ...
+    def back(self) -> _T: ...
+    def push(self, o: _T) -> _T: ...
+    def home(self) -> _T: ...
+
+def safe_masked_invalid(x: ArrayLike, copy: bool = ...) -> np.ndarray: ...
+def print_cycles(
+    objects: Iterable[Any], outstream: IO = ..., show_progress: bool = ...
+) -> None: ...
+
+class Grouper(Generic[_T]):
+    def __init__(self, init: Iterable[_T] = ...) -> None: ...
+    def __contains__(self, item: _T) -> bool: ...
+    def join(self, a: _T, *args: _T) -> None: ...
+    def joined(self, a: _T, b: _T) -> bool: ...
+    def remove(self, a: _T) -> None: ...
+    def __iter__(self) -> Iterator[list[_T]]: ...
+    def get_siblings(self, a: _T) -> list[_T]: ...
+
+class GrouperView(Generic[_T]):
+    def __init__(self, grouper: Grouper[_T]) -> None: ...
+    def __contains__(self, item: _T) -> bool: ...
+    def __iter__(self) -> Iterator[list[_T]]: ...
+    def joined(self, a: _T, b: _T) -> bool: ...
+    def get_siblings(self, a: _T) -> list[_T]: ...
+
+def simple_linear_interpolation(a: ArrayLike, steps: int) -> np.ndarray: ...
+def delete_masked_points(*args): ...
+def _broadcast_with_masks(*args: ArrayLike, compress: bool = ...) -> list[ArrayLike]: ...
+def boxplot_stats(
+    X: ArrayLike,
+    whis: float | tuple[float, float] = ...,
+    bootstrap: int | None = ...,
+    labels: ArrayLike | None = ...,
+    autorange: bool = ...,
+) -> list[dict[str, Any]]: ...
+
+ls_mapper: dict[str, str]
+ls_mapper_r: dict[str, str]
+
+def contiguous_regions(mask: ArrayLike) -> list[np.ndarray]: ...
+def is_math_text(s: str) -> bool: ...
+def violin_stats(
+    X: ArrayLike, method: Callable, points: int = ..., quantiles: ArrayLike | None = ...
+) -> list[dict[str, Any]]: ...
+def pts_to_prestep(x: ArrayLike, *args: ArrayLike) -> np.ndarray: ...
+def pts_to_poststep(x: ArrayLike, *args: ArrayLike) -> np.ndarray: ...
+def pts_to_midstep(x: np.ndarray, *args: np.ndarray) -> np.ndarray: ...
+
+STEP_LOOKUP_MAP: dict[str, Callable]
+
+def index_of(y: float | ArrayLike) -> tuple[np.ndarray, np.ndarray]: ...
+def safe_first_element(obj: Collection[_T]) -> _T: ...
+def sanitize_sequence(data): ...
+def normalize_kwargs(
+    kw: dict[str, Any],
+    alias_mapping: dict[str, list[str]] | type[Artist] | Artist | None = ...,
+) -> dict[str, Any]: ...
+def _lock_path(path: str | os.PathLike) -> contextlib.AbstractContextManager[None]: ...
+def _str_equal(obj: Any, s: str) -> bool: ...
+def _str_lower_equal(obj: Any, s: str) -> bool: ...
+def _array_perimeter(arr: np.ndarray) -> np.ndarray: ...
+def _unfold(arr: np.ndarray, axis: int, size: int, step: int) -> np.ndarray: ...
+def _array_patch_perimeters(x: np.ndarray, rstride: int, cstride: int) -> np.ndarray: ...
+def _setattr_cm(obj: Any, **kwargs) -> contextlib.AbstractContextManager[None]: ...
+
+class _OrderedSet(collections.abc.MutableSet):
+    def __init__(self) -> None: ...
+    def __contains__(self, key) -> bool: ...
+    def __iter__(self): ...
+    def __len__(self) -> int: ...
+    def add(self, key) -> None: ...
+    def discard(self, key) -> None: ...
+
+def _setup_new_guiapp() -> None: ...
+def _format_approx(number: float, precision: int) -> str: ...
+def _g_sig_digits(value: float, delta: float) -> int: ...
+def _unikey_or_keysym_to_mplkey(unikey: str, keysym: str) -> str: ...
+def _is_torch_array(x: Any) -> bool: ...
+def _is_jax_array(x: Any) -> bool: ...
+def _unpack_to_numpy(x: Any) -> Any: ...
+def _auto_format_str(fmt: str, value: Any) -> str: ...