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seaborn: complete the distributions module (#11131)

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This commit is contained in:
Ali Hamdan
2023-12-10 16:18:59 +01:00
committed by GitHub
parent 88193cd7df
commit 6ae413f2c0
3 changed files with 85 additions and 59 deletions
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5
stubs/seaborn/seaborn/_stats/density.pyi
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@@ -1,13 +1,12 @@
from collections.abc import Callable
from dataclasses import dataclass
from seaborn._stats.base import Stat
from seaborn.external.kde import gaussian_kde
from seaborn.external.kde import _BwMethodType
@dataclass
class KDE(Stat):
bw_adjust: float = 1
bw_method: str | float | Callable[[gaussian_kde], float] = "scott"
bw_method: _BwMethodType = "scott"
common_norm: bool | list[str] = True
common_grid: bool | list[str] = True
gridsize: int | None = 200

117
stubs/seaborn/seaborn/distributions.pyi
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@@ -1,28 +1,37 @@
from _typeshed import Incomplete
from collections.abc import Iterable
from typing import Any
from typing_extensions import Literal, deprecated
from typing import Any, Protocol, TypeVar
from typing_extensions import Literal, TypeAlias, deprecated
from matplotlib.axes import Axes
from matplotlib.colors import Colormap
from matplotlib.colors import Colormap, Normalize
from matplotlib.typing import ColorType
from numpy.typing import ArrayLike
from ._core.typing import ColumnName, DataSource
from .axisgrid import FacetGrid
from .utils import _LogScale, _Palette
from .external.kde import _BwMethodType
from .utils import _DataSourceWideForm, _LogScale, _Palette, _Vector
__all__ = ["displot", "histplot", "kdeplot", "ecdfplot", "rugplot", "distplot"]
_T = TypeVar("_T")
_OneOrPair: TypeAlias = _T | tuple[_T, _T]
class _Fit(Protocol):
def fit(self, a: ArrayLike) -> tuple[ArrayLike, ...]: ...
def pdf(self, x: ArrayLike, *params: ArrayLike) -> ArrayLike: ...
def histplot(
data: Incomplete | None = None,
data: DataSource | _DataSourceWideForm | None = None,
*,
x: Incomplete | None = None,
y: Incomplete | None = None,
hue: Incomplete | None = None,
weights: Incomplete | None = None,
x: ColumnName | _Vector | None = None,
y: ColumnName | _Vector | None = None,
hue: ColumnName | _Vector | None = None,
weights: ColumnName | _Vector | None = None,
stat: str = "count",
bins: Incomplete = "auto",
bins: _OneOrPair[str | int | ArrayLike] = "auto",
binwidth: float | tuple[float, float] | None = None,
binrange: Incomplete | None = None,
binrange: _OneOrPair[tuple[float, float]] | None = None,
discrete: bool | None = None,
cumulative: bool = False,
common_bins: bool = True,
@@ -41,8 +50,8 @@ def histplot(
cbar_ax: Axes | None = None,
cbar_kws: dict[str, Any] | None = None,
palette: _Palette | Colormap | None = None,
hue_order: Iterable[str] | None = None,
hue_norm: Incomplete | None = None,
hue_order: Iterable[ColumnName] | None = None,
hue_norm: tuple[float, float] | Normalize | None = None,
color: ColorType | None = None,
log_scale: _LogScale | None = None,
legend: bool = True,
@@ -50,30 +59,30 @@ def histplot(
**kwargs: Any,
) -> Axes: ...
def kdeplot(
data: Incomplete | None = None,
data: DataSource | _DataSourceWideForm | None = None,
*,
x: Incomplete | None = None,
y: Incomplete | None = None,
hue: Incomplete | None = None,
weights: Incomplete | None = None,
x: ColumnName | _Vector | None = None,
y: ColumnName | _Vector | None = None,
hue: ColumnName | _Vector | None = None,
weights: ColumnName | _Vector | None = None,
palette: _Palette | Colormap | None = None,
hue_order: Iterable[str] | None = None,
hue_norm: Incomplete | None = None,
hue_order: Iterable[ColumnName] | None = None,
hue_norm: tuple[float, float] | Normalize | None = None,
color: ColorType | None = None,
fill: bool | None = None,
multiple: Literal["layer", "stack", "fill"] = "layer",
common_norm: bool = True,
common_grid: bool = False,
cumulative: bool = False,
bw_method: str = "scott",
bw_method: _BwMethodType = "scott",
bw_adjust: float = 1,
warn_singular: bool = True,
log_scale: _LogScale | None = None,
levels: int | Iterable[int] = 10,
levels: int | Iterable[float] = 10,
thresh: float = 0.05,
gridsize: int = 200,
cut: float = 3,
clip: Incomplete | None = None,
clip: _OneOrPair[tuple[float | None, float | None]] | None = None,
legend: bool = True,
cbar: bool = False,
cbar_ax: Axes | None = None,
@@ -82,58 +91,58 @@ def kdeplot(
**kwargs: Any,
) -> Axes: ...
def ecdfplot(
data: Incomplete | None = None,
data: DataSource | _DataSourceWideForm | None = None,
*,
x: Incomplete | None = None,
y: Incomplete | None = None,
hue: Incomplete | None = None,
weights: Incomplete | None = None,
stat: Literal["proportion", "count"] = "proportion",
x: ColumnName | _Vector | None = None,
y: ColumnName | _Vector | None = None,
hue: ColumnName | _Vector | None = None,
weights: ColumnName | _Vector | None = None,
stat: Literal["proportion", "percent", "count"] = "proportion",
complementary: bool = False,
palette: _Palette | Colormap | None = None,
hue_order: Iterable[str] | None = None,
hue_norm: Incomplete | None = None,
hue_order: Iterable[ColumnName] | None = None,
hue_norm: tuple[float, float] | Normalize | None = None,
log_scale: _LogScale | None = None,
legend: bool = True,
ax: Axes | None = None,
**kwargs: Any,
) -> Axes: ...
def rugplot(
data: Incomplete | None = None,
data: DataSource | _DataSourceWideForm | None = None,
*,
x: Incomplete | None = None,
y: Incomplete | None = None,
hue: Incomplete | None = None,
x: ColumnName | _Vector | None = None,
y: ColumnName | _Vector | None = None,
hue: ColumnName | _Vector | None = None,
height: float = 0.025,
expand_margins: bool = True,
palette: _Palette | Colormap | None = None,
hue_order: Iterable[str] | None = None,
hue_norm: Incomplete | None = None,
hue_order: Iterable[ColumnName] | None = None,
hue_norm: tuple[float, float] | Normalize | None = None,
legend: bool = True,
ax: Axes | None = None,
**kwargs: Any,
) -> Axes: ...
def displot(
data: Incomplete | None = None,
data: DataSource | _DataSourceWideForm | None = None,
*,
x: Incomplete | None = None,
y: Incomplete | None = None,
hue: Incomplete | None = None,
row: Incomplete | None = None,
col: Incomplete | None = None,
weights: Incomplete | None = None,
x: ColumnName | _Vector | None = None,
y: ColumnName | _Vector | None = None,
hue: ColumnName | _Vector | None = None,
row: ColumnName | _Vector | None = None,
col: ColumnName | _Vector | None = None,
weights: ColumnName | _Vector | None = None,
kind: Literal["hist", "kde", "ecdf"] = "hist",
rug: bool = False,
rug_kws: dict[str, Any] | None = None,
log_scale: _LogScale | None = None,
legend: bool = True,
palette: _Palette | Colormap | None = None,
hue_order: Iterable[str] | None = None,
hue_norm: Incomplete | None = None,
hue_order: Iterable[ColumnName] | None = None,
hue_norm: tuple[float, float] | Normalize | None = None,
color: ColorType | None = None,
col_wrap: int | None = None,
row_order: Iterable[str] | None = None,
col_order: Iterable[str] | None = None,
row_order: Iterable[ColumnName] | None = None,
col_order: Iterable[ColumnName] | None = None,
height: float = 5,
aspect: float = 1,
facet_kws: dict[str, Any] | None = None,
@@ -141,12 +150,12 @@ def displot(
) -> FacetGrid: ...
@deprecated("Function `distplot` is deprecated and will be removed in seaborn v0.14.0")
def distplot(
a: Incomplete | None = None,
bins: Incomplete | None = None,
a: ArrayLike | None = None,
bins: ArrayLike | None = None,
hist: bool = True,
kde: bool = True,
rug: bool = False,
fit: Incomplete | None = None,
fit: _Fit | None = None,
hist_kws: dict[str, Any] | None = None,
kde_kws: dict[str, Any] | None = None,
rug_kws: dict[str, Any] | None = None,
@@ -155,7 +164,7 @@ def distplot(
vertical: bool = False,
norm_hist: bool = False,
axlabel: str | Literal[False] | None = None,
label: Incomplete | None = None,
label: str | None = None,
ax: Axes | None = None,
x: Incomplete | None = None,
x: ArrayLike | None = None,
) -> Axes: ...

22
stubs/seaborn/seaborn/external/kde.pyi vendored
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@@ -1,4 +1,5 @@
from collections.abc import Callable
from typing import Any, Protocol
from typing_extensions import Literal, TypeAlias
import numpy as np
@@ -6,8 +7,25 @@ from numpy.typing import ArrayLike, NDArray
__all__ = ["gaussian_kde"]
_Scalar: TypeAlias = np.generic | bool | int | float | complex | bytes | memoryview # see np.isscalar
_BwMethodType: TypeAlias = Literal["scott", "silverman"] | Callable[[gaussian_kde], object] | _Scalar | None
# define a "Gaussian KDE" protocol so that we can also pass `scipy.stats.gaussian_kde` to
# functions that expect it without adding a dependency on scipy
class _GaussianKDELike(Protocol):
dataset: NDArray[np.float64]
def __init__(self, dataset: ArrayLike, bw_method: Any | None = ..., weights: ArrayLike | None = ...) -> None: ...
def evaluate(self, points: ArrayLike) -> NDArray[Any]: ...
def __call__(self, points: ArrayLike) -> NDArray[Any]: ...
def scotts_factor(self) -> float: ...
def silverman_factor(self) -> float: ...
def covariance_factor(self) -> float: ...
def pdf(self, x: ArrayLike) -> NDArray[Any]: ...
def set_bandwidth(self, bw_method: Any | None = ...) -> None: ...
@property
def weights(self) -> NDArray[Any]: ...
@property
def neff(self) -> NDArray[Any]: ...
_Scalar: TypeAlias = float | np.number[Any]
_BwMethodType: TypeAlias = Literal["scott", "silverman"] | Callable[[_GaussianKDELike], _Scalar] | _Scalar | None
class gaussian_kde:
dataset: NDArray[np.float64]