Alle Dateien aus dem Pythonkurs
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

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=...): ...