nvim_config/typings/numpy/ma/extras.pyi

"""
This type stub file was generated by pyright.
"""

from typing import Any
from numpy.lib.index_tricks import AxisConcatenator

__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) -> 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 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) -> 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=...):
    ...