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- from _typeshed import Incomplete
- import numpy as np
- from numpy.lib._function_base_impl import average
- from numpy.lib._index_tricks_impl import AxisConcatenator
- from .core import MaskedArray, dot
- __all__ = [
- "apply_along_axis",
- "apply_over_axes",
- "atleast_1d",
- "atleast_2d",
- "atleast_3d",
- "average",
- "clump_masked",
- "clump_unmasked",
- "column_stack",
- "compress_cols",
- "compress_nd",
- "compress_rowcols",
- "compress_rows",
- "corrcoef",
- "count_masked",
- "cov",
- "diagflat",
- "dot",
- "dstack",
- "ediff1d",
- "flatnotmasked_contiguous",
- "flatnotmasked_edges",
- "hsplit",
- "hstack",
- "in1d",
- "intersect1d",
- "isin",
- "mask_cols",
- "mask_rowcols",
- "mask_rows",
- "masked_all",
- "masked_all_like",
- "median",
- "mr_",
- "ndenumerate",
- "notmasked_contiguous",
- "notmasked_edges",
- "polyfit",
- "row_stack",
- "setdiff1d",
- "setxor1d",
- "stack",
- "union1d",
- "unique",
- "vander",
- "vstack",
- ]
- def count_masked(arr, axis=...): ...
- def masked_all(shape, dtype = ...): ...
- def masked_all_like(arr): ...
- class _fromnxfunction:
- __name__: Incomplete
- __doc__: Incomplete
- def __init__(self, funcname) -> None: ...
- def getdoc(self): ...
- def __call__(self, *args, **params): ...
- class _fromnxfunction_single(_fromnxfunction):
- def __call__(self, x, *args, **params): ...
- class _fromnxfunction_seq(_fromnxfunction):
- def __call__(self, x, *args, **params): ...
- class _fromnxfunction_allargs(_fromnxfunction):
- def __call__(self, *args, **params): ...
- atleast_1d: _fromnxfunction_allargs
- atleast_2d: _fromnxfunction_allargs
- atleast_3d: _fromnxfunction_allargs
- vstack: _fromnxfunction_seq
- row_stack: _fromnxfunction_seq
- hstack: _fromnxfunction_seq
- column_stack: _fromnxfunction_seq
- dstack: _fromnxfunction_seq
- stack: _fromnxfunction_seq
- hsplit: _fromnxfunction_single
- diagflat: _fromnxfunction_single
- def apply_along_axis(func1d, axis, arr, *args, **kwargs): ...
- def apply_over_axes(func, a, axes): ...
- def median(a, axis=..., out=..., overwrite_input=..., keepdims=...): ...
- def compress_nd(x, axis=...): ...
- def compress_rowcols(x, axis=...): ...
- def compress_rows(a): ...
- def compress_cols(a): ...
- def mask_rows(a, axis = ...): ...
- def mask_cols(a, axis = ...): ...
- def ediff1d(arr, to_end=..., to_begin=...): ...
- def unique(ar1, return_index=..., return_inverse=...): ...
- def intersect1d(ar1, ar2, assume_unique=...): ...
- def setxor1d(ar1, ar2, assume_unique=...): ...
- def in1d(ar1, ar2, assume_unique=..., invert=...): ...
- def isin(element, test_elements, assume_unique=..., invert=...): ...
- def union1d(ar1, ar2): ...
- def setdiff1d(ar1, ar2, assume_unique=...): ...
- def cov(x, y=..., rowvar=..., bias=..., allow_masked=..., ddof=...): ...
- def corrcoef(x, y=..., rowvar=..., bias = ..., allow_masked=..., ddof = ...): ...
- class MAxisConcatenator(AxisConcatenator):
- @staticmethod
- def concatenate(arrays: Incomplete, axis: int = 0) -> Incomplete: ... # type: ignore[override] # pyright: ignore[reportIncompatibleMethodOverride]
- @classmethod
- def makemat(cls, arr: Incomplete) -> Incomplete: ... # type: ignore[override] # pyright: ignore[reportIncompatibleVariableOverride]
- class mr_class(MAxisConcatenator):
- def __init__(self) -> None: ...
- mr_: mr_class
- def ndenumerate(a, compressed=...): ...
- def flatnotmasked_edges(a): ...
- def notmasked_edges(a, axis=...): ...
- def flatnotmasked_contiguous(a): ...
- def notmasked_contiguous(a, axis=...): ...
- def clump_unmasked(a): ...
- def clump_masked(a): ...
- def vander(x, n=...): ...
- def polyfit(x, y, deg, rcond=..., full=..., w=..., cov=...): ...
- #
- def mask_rowcols(a: Incomplete, axis: Incomplete | None = None) -> MaskedArray[Incomplete, np.dtype[Incomplete]]: ...
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