8000 ENH: Add annotations for `np.lib.histograms` by BvB93 · Pull Request #20063 · numpy/numpy · GitHub
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ENH: Add annotations for np.lib.histograms #20063

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Merged
merged 2 commits into from
Oct 9, 2021
Merged

ENH: Add annotations for np.lib.histograms #20063

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37e8cb3
ENH: Add annotations for `np.lib.histograms`
Jun 4, 2021
bdd87c7
TST: Add typing tests for `np.lib.histograms`
Oct 7, 2021
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52 changes: 48 additions & 4 deletions numpy/lib/histograms.pyi
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Original file line number Diff line number Diff line change
@@ -1,7 +1,51 @@
from typing import List
from typing import (
Literal as L,
List,
Tuple,
Any,
SupportsIndex,
Sequence,
)

from numpy.typing import (
NDArray,
ArrayLike,
)

_BinKind = L[
"stone",
"auto",
"doane",
"fd",
"rice",
"scott",
"sqrt",
"sturges",
]

__all__: List[str]

def histogram_bin_edges(a, bins=..., range=..., weights=...): ...
def histogram(a, bins=..., range=..., normed=..., weights=..., density=...): ...
def histogramdd(sample, bins=..., range=..., normed=..., weights=..., density=...): ...
def histogram_bin_edges(
a: ArrayLike,
bins: _BinKind | SupportsIndex | ArrayLike = ...,
range: None | Tuple[float, float] = ...,
weights: None | ArrayLike = ...,
) -> NDArray[Any]: ...

def histogram(
a: ArrayLike,
bins: _BinKind | SupportsIndex | ArrayLike = ...,
range: None | Tuple[float, float] = ...,
normed: None = ...,
weights: None | ArrayLike = ...,
density: bool = ...,
) -> Tuple[NDArray[Any], NDArray[Any]]: ...

def histogramdd(
sample: ArrayLike,
bins: SupportsIndex | ArrayLike = ...,
range: Sequence[Tuple[float, float]] = ...,
normed: None | bool = ...,
weights: None | ArrayLike = ...,
density: None | bool = ...,
) -> Tuple[NDArray[Any], List[NDArray[Any]]]: ...
13 changes: 13 additions & 0 deletions numpy/typing/tests/data/fail/histograms.pyi
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@@ -0,0 +1,13 @@
import numpy as np
import numpy.typing as npt

AR_i8: npt.NDArray[np.int64]
AR_f8: npt.NDArray[np.float64]

np.histogram_bin_edges(AR_i8, range=(0, 1, 2)) # E: incompatible type

np.histogram(AR_i8, range=(0, 1, 2)) # E: incompatible type
np.histogram(AR_i8, normed=True) # E: incompatible type

np.histogramdd(AR_i8, range=(0, 1)) # E: incompatible type
np.histogramdd(AR_i8, range=[(0, 1, 2)]) # E: incompatible type
19 changes: 19 additions & 0 deletions numpy/typing/tests/data/reveal/histograms.pyi
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import numpy as np
import numpy.typing as npt

AR_i8: npt.NDArray[np.int64]
AR_f8: npt.NDArray[np.float64]

reveal_type(np.histogram_bin_edges(AR_i8, bins="auto")) # E: numpy.ndarray[Any, numpy.dtype[Any]]
reveal_type(np.histogram_bin_edges(AR_i8, bins="rice", range=(0, 3))) # E: numpy.ndarray[Any, numpy.dtype[Any]]
reveal_type(np.histogram_bin_edges(AR_i8, bins="scott", weights=AR_f8)) # E: numpy.ndarray[Any, numpy.dtype[Any]]

reveal_type(np.histogram(AR_i8, bins="auto")) # E: Tuple[numpy.ndarray[Any, numpy.dtype[Any]], numpy.ndarray[Any, numpy.dtype[Any]]]
reveal_type(np.histogram(AR_i8, bins="rice", range=(0, 3))) # E: Tuple[numpy.ndarray[Any, numpy.dtype[Any]], numpy.ndarray[Any, numpy.dtype[Any]]]
reveal_type(np.histogram(AR_i8, bins="scott", weights=AR_f8)) # E: Tuple[numpy.ndarray[Any, numpy.dtype[Any]], numpy.ndarray[Any, numpy.dtype[Any]]]
reveal_type(np.histogram(AR_f8, bins=1, density=True)) # E: Tuple[numpy.ndarray[Any, numpy.dtype[Any]], numpy.ndarray[Any, numpy.dtype[Any]]]

reveal_type(np.histogramdd(AR_i8, bins=[1])) # E: Tuple[numpy.ndarray[Any, numpy.dtype[Any]], builtins.list[numpy.ndarray[Any, numpy.dtype[Any]]]]
reveal_type(np.histogramdd(AR_i8, range=[(0, 3)])) # E: Tuple[numpy.ndarray[Any, numpy.dtype[Any]], builtins.list[numpy.ndarray[Any, numpy.dtype[Any]]]]
reveal_type(np.histogramdd(AR_i8, weights=AR_f8)) # E: Tuple[numpy.ndarray[Any, numpy.dtype[Any]], builtins.list[numpy.ndarray[Any, numpy.dtype[Any]]]]
reveal_type(np.histogramdd(AR_f8, density=True)) # E: Tuple[numpy.ndarray[Any, numpy.dtype[Any]], builtins.list[numpy.ndarray[Any, numpy.dtype[Any]]]]
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