48 行
1.4 KiB
Python
48 行
1.4 KiB
Python
from typing import (
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Sequence,
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TypeVar,
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)
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import numpy as np
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from pandas._typing import npt
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_SparseIndexT = TypeVar("_SparseIndexT", bound=SparseIndex)
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class SparseIndex:
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length: int
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npoints: int
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def __init__(self): ...
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@property
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def ngaps(self) -> int: ...
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@property
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def nbytes(self) -> int: ...
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@property
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def indices(self) -> npt.NDArray[np.int32]: ...
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def equals(self, other) -> bool: ...
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def lookup(self, index: int) -> np.int32: ...
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def lookup_array(self, indexer: npt.NDArray[np.int32]) -> npt.NDArray[np.int32]: ...
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def to_int_index(self) -> IntIndex: ...
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def to_block_index(self) -> BlockIndex: ...
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def intersect(self: _SparseIndexT, y_: SparseIndex) -> _SparseIndexT: ...
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def make_union(self: _SparseIndexT, y_: SparseIndex) -> _SparseIndexT: ...
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class IntIndex(SparseIndex):
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indices: npt.NDArray[np.int32]
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def __init__(
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self, length: int, indices: Sequence[int], check_integrity: bool = ...
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): ...
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class BlockIndex(SparseIndex):
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nblocks: int
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blocs: np.ndarray
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blengths: np.ndarray
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def __init__(self, length: int, blocs: np.ndarray, blengths: np.ndarray): ...
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def make_mask_object_ndarray(
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arr: npt.NDArray[np.object_], fill_value
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) -> npt.NDArray[np.bool_]: ...
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def get_blocks(
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indices: npt.NDArray[np.int32],
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) -> tuple[npt.NDArray[np.int32], npt.NDArray[np.int32]]: ...
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