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