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Current File : /proc/self/root/proc/self/root/proc/thread-self/root/proc/thread-self/root/opt/cloudlinux/venv/lib64/python3.11/site-packages/numpy/ma/extras.pyi
from typing import Any
from numpy.lib.index_tricks import AxisConcatenator

from numpy.ma.core import (
    dot as dot,
    mask_rowcols as mask_rowcols,
)

__all__: list[str]

def count_masked(arr, axis=...): ...
def masked_all(shape, dtype = ...): ...
def masked_all_like(arr): ...

class _fromnxfunction:
    __name__: Any
    __doc__: Any
    def __init__(self, funcname): ...
    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 average(a, axis=..., weights=..., returned=..., keepdims=...): ...
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):
    concatenate: Any
    @classmethod
    def makemat(cls, arr): ...
    def __getitem__(self, key): ...

class mr_class(MAxisConcatenator):
    def __init__(self): ...

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=...): ...

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