You can not select more than 25 topics
			Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
		
		
		
		
		
			
		
			
				
					
					
						
							86 lines
						
					
					
						
							2.6 KiB
						
					
					
				
			
		
		
	
	
							86 lines
						
					
					
						
							2.6 KiB
						
					
					
				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=...): ...
 |