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Direktori : /proc/thread-self/root/opt/cloudlinux/venv/lib/python3.11/site-packages/numpy/ma/ |
Current File : //proc/thread-self/root/opt/cloudlinux/venv/lib/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=...): ...