peacock-data-public-datasets-idc-llm_eval
/
env-llmeval
/lib
/python3.10
/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 | |
| 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=...): ... | |