3RNN/Lib/site-packages/numpy/ma/core.pyi
2024-05-26 19:49:15 +02:00

472 lines
14 KiB
Python

from collections.abc import Callable
from typing import Any, TypeVar
from numpy import ndarray, dtype, float64
from numpy import (
amax as amax,
amin as amin,
bool_ as bool_,
expand_dims as expand_dims,
clip as clip,
indices as indices,
ones_like as ones_like,
squeeze as squeeze,
zeros_like as zeros_like,
)
from numpy.lib.function_base import (
angle as angle,
)
# TODO: Set the `bound` to something more suitable once we
# have proper shape support
_ShapeType = TypeVar("_ShapeType", bound=Any)
_DType_co = TypeVar("_DType_co", bound=dtype[Any], covariant=True)
__all__: list[str]
MaskType = bool_
nomask: bool_
class MaskedArrayFutureWarning(FutureWarning): ...
class MAError(Exception): ...
class MaskError(MAError): ...
def default_fill_value(obj): ...
def minimum_fill_value(obj): ...
def maximum_fill_value(obj): ...
def set_fill_value(a, fill_value): ...
def common_fill_value(a, b): ...
def filled(a, fill_value=...): ...
def getdata(a, subok=...): ...
get_data = getdata
def fix_invalid(a, mask=..., copy=..., fill_value=...): ...
class _MaskedUFunc:
f: Any
__doc__: Any
__name__: Any
def __init__(self, ufunc): ...
class _MaskedUnaryOperation(_MaskedUFunc):
fill: Any
domain: Any
def __init__(self, mufunc, fill=..., domain=...): ...
def __call__(self, a, *args, **kwargs): ...
class _MaskedBinaryOperation(_MaskedUFunc):
fillx: Any
filly: Any
def __init__(self, mbfunc, fillx=..., filly=...): ...
def __call__(self, a, b, *args, **kwargs): ...
def reduce(self, target, axis=..., dtype=...): ...
def outer(self, a, b): ...
def accumulate(self, target, axis=...): ...
class _DomainedBinaryOperation(_MaskedUFunc):
domain: Any
fillx: Any
filly: Any
def __init__(self, dbfunc, domain, fillx=..., filly=...): ...
def __call__(self, a, b, *args, **kwargs): ...
exp: _MaskedUnaryOperation
conjugate: _MaskedUnaryOperation
sin: _MaskedUnaryOperation
cos: _MaskedUnaryOperation
arctan: _MaskedUnaryOperation
arcsinh: _MaskedUnaryOperation
sinh: _MaskedUnaryOperation
cosh: _MaskedUnaryOperation
tanh: _MaskedUnaryOperation
abs: _MaskedUnaryOperation
absolute: _MaskedUnaryOperation
fabs: _MaskedUnaryOperation
negative: _MaskedUnaryOperation
floor: _MaskedUnaryOperation
ceil: _MaskedUnaryOperation
around: _MaskedUnaryOperation
logical_not: _MaskedUnaryOperation
sqrt: _MaskedUnaryOperation
log: _MaskedUnaryOperation
log2: _MaskedUnaryOperation
log10: _MaskedUnaryOperation
tan: _MaskedUnaryOperation
arcsin: _MaskedUnaryOperation
arccos: _MaskedUnaryOperation
arccosh: _MaskedUnaryOperation
arctanh: _MaskedUnaryOperation
add: _MaskedBinaryOperation
subtract: _MaskedBinaryOperation
multiply: _MaskedBinaryOperation
arctan2: _MaskedBinaryOperation
equal: _MaskedBinaryOperation
not_equal: _MaskedBinaryOperation
less_equal: _MaskedBinaryOperation
greater_equal: _MaskedBinaryOperation
less: _MaskedBinaryOperation
greater: _MaskedBinaryOperation
logical_and: _MaskedBinaryOperation
alltrue: _MaskedBinaryOperation
logical_or: _MaskedBinaryOperation
sometrue: Callable[..., Any]
logical_xor: _MaskedBinaryOperation
bitwise_and: _MaskedBinaryOperation
bitwise_or: _MaskedBinaryOperation
bitwise_xor: _MaskedBinaryOperation
hypot: _MaskedBinaryOperation
divide: _MaskedBinaryOperation
true_divide: _MaskedBinaryOperation
floor_divide: _MaskedBinaryOperation
remainder: _MaskedBinaryOperation
fmod: _MaskedBinaryOperation
mod: _MaskedBinaryOperation
def make_mask_descr(ndtype): ...
def getmask(a): ...
get_mask = getmask
def getmaskarray(arr): ...
def is_mask(m): ...
def make_mask(m, copy=..., shrink=..., dtype=...): ...
def make_mask_none(newshape, dtype=...): ...
def mask_or(m1, m2, copy=..., shrink=...): ...
def flatten_mask(mask): ...
def masked_where(condition, a, copy=...): ...
def masked_greater(x, value, copy=...): ...
def masked_greater_equal(x, value, copy=...): ...
def masked_less(x, value, copy=...): ...
def masked_less_equal(x, value, copy=...): ...
def masked_not_equal(x, value, copy=...): ...
def masked_equal(x, value, copy=...): ...
def masked_inside(x, v1, v2, copy=...): ...
def masked_outside(x, v1, v2, copy=...): ...
def masked_object(x, value, copy=..., shrink=...): ...
def masked_values(x, value, rtol=..., atol=..., copy=..., shrink=...): ...
def masked_invalid(a, copy=...): ...
class _MaskedPrintOption:
def __init__(self, display): ...
def display(self): ...
def set_display(self, s): ...
def enabled(self): ...
def enable(self, shrink=...): ...
masked_print_option: _MaskedPrintOption
def flatten_structured_array(a): ...
class MaskedIterator:
ma: Any
dataiter: Any
maskiter: Any
def __init__(self, ma): ...
def __iter__(self): ...
def __getitem__(self, indx): ...
def __setitem__(self, index, value): ...
def __next__(self): ...
class MaskedArray(ndarray[_ShapeType, _DType_co]):
__array_priority__: Any
def __new__(cls, data=..., mask=..., dtype=..., copy=..., subok=..., ndmin=..., fill_value=..., keep_mask=..., hard_mask=..., shrink=..., order=...): ...
def __array_finalize__(self, obj): ...
def __array_wrap__(self, obj, context=...): ...
def view(self, dtype=..., type=..., fill_value=...): ...
def __getitem__(self, indx): ...
def __setitem__(self, indx, value): ...
@property
def dtype(self): ...
@dtype.setter
def dtype(self, dtype): ...
@property
def shape(self): ...
@shape.setter
def shape(self, shape): ...
def __setmask__(self, mask, copy=...): ...
@property
def mask(self): ...
@mask.setter
def mask(self, value): ...
@property
def recordmask(self): ...
@recordmask.setter
def recordmask(self, mask): ...
def harden_mask(self): ...
def soften_mask(self): ...
@property
def hardmask(self): ...
def unshare_mask(self): ...
@property
def sharedmask(self): ...
def shrink_mask(self): ...
@property
def baseclass(self): ...
data: Any
@property
def flat(self): ...
@flat.setter
def flat(self, value): ...
@property
def fill_value(self): ...
@fill_value.setter
def fill_value(self, value=...): ...
get_fill_value: Any
set_fill_value: Any
def filled(self, fill_value=...): ...
def compressed(self): ...
def compress(self, condition, axis=..., out=...): ...
def __eq__(self, other): ...
def __ne__(self, other): ...
def __ge__(self, other): ...
def __gt__(self, other): ...
def __le__(self, other): ...
def __lt__(self, other): ...
def __add__(self, other): ...
def __radd__(self, other): ...
def __sub__(self, other): ...
def __rsub__(self, other): ...
def __mul__(self, other): ...
def __rmul__(self, other): ...
def __div__(self, other): ...
def __truediv__(self, other): ...
def __rtruediv__(self, other): ...
def __floordiv__(self, other): ...
def __rfloordiv__(self, other): ...
def __pow__(self, other): ...
def __rpow__(self, other): ...
def __iadd__(self, other): ...
def __isub__(self, other): ...
def __imul__(self, other): ...
def __idiv__(self, other): ...
def __ifloordiv__(self, other): ...
def __itruediv__(self, other): ...
def __ipow__(self, other): ...
def __float__(self): ...
def __int__(self): ...
@property # type: ignore[misc]
def imag(self): ...
get_imag: Any
@property # type: ignore[misc]
def real(self): ...
get_real: Any
def count(self, axis=..., keepdims=...): ...
def ravel(self, order=...): ...
def reshape(self, *s, **kwargs): ...
def resize(self, newshape, refcheck=..., order=...): ...
def put(self, indices, values, mode=...): ...
def ids(self): ...
def iscontiguous(self): ...
def all(self, axis=..., out=..., keepdims=...): ...
def any(self, axis=..., out=..., keepdims=...): ...
def nonzero(self): ...
def trace(self, offset=..., axis1=..., axis2=..., dtype=..., out=...): ...
def dot(self, b, out=..., strict=...): ...
def sum(self, axis=..., dtype=..., out=..., keepdims=...): ...
def cumsum(self, axis=..., dtype=..., out=...): ...
def prod(self, axis=..., dtype=..., out=..., keepdims=...): ...
product: Any
def cumprod(self, axis=..., dtype=..., out=...): ...
def mean(self, axis=..., dtype=..., out=..., keepdims=...): ...
def anom(self, axis=..., dtype=...): ...
def var(self, axis=..., dtype=..., out=..., ddof=..., keepdims=...): ...
def std(self, axis=..., dtype=..., out=..., ddof=..., keepdims=...): ...
def round(self, decimals=..., out=...): ...
def argsort(self, axis=..., kind=..., order=..., endwith=..., fill_value=...): ...
def argmin(self, axis=..., fill_value=..., out=..., *, keepdims=...): ...
def argmax(self, axis=..., fill_value=..., out=..., *, keepdims=...): ...
def sort(self, axis=..., kind=..., order=..., endwith=..., fill_value=...): ...
def min(self, axis=..., out=..., fill_value=..., keepdims=...): ...
# NOTE: deprecated
# def tostring(self, fill_value=..., order=...): ...
def max(self, axis=..., out=..., fill_value=..., keepdims=...): ...
def ptp(self, axis=..., out=..., fill_value=..., keepdims=...): ...
def partition(self, *args, **kwargs): ...
def argpartition(self, *args, **kwargs): ...
def take(self, indices, axis=..., out=..., mode=...): ...
copy: Any
diagonal: Any
flatten: Any
repeat: Any
squeeze: Any
swapaxes: Any
T: Any
transpose: Any
def tolist(self, fill_value=...): ...
def tobytes(self, fill_value=..., order=...): ...
def tofile(self, fid, sep=..., format=...): ...
def toflex(self): ...
torecords: Any
def __reduce__(self): ...
def __deepcopy__(self, memo=...): ...
class mvoid(MaskedArray[_ShapeType, _DType_co]):
def __new__(
self,
data,
mask=...,
dtype=...,
fill_value=...,
hardmask=...,
copy=...,
subok=...,
): ...
def __getitem__(self, indx): ...
def __setitem__(self, indx, value): ...
def __iter__(self): ...
def __len__(self): ...
def filled(self, fill_value=...): ...
def tolist(self): ...
def isMaskedArray(x): ...
isarray = isMaskedArray
isMA = isMaskedArray
# 0D float64 array
class MaskedConstant(MaskedArray[Any, dtype[float64]]):
def __new__(cls): ...
__class__: Any
def __array_finalize__(self, obj): ...
def __array_prepare__(self, obj, context=...): ...
def __array_wrap__(self, obj, context=...): ...
def __format__(self, format_spec): ...
def __reduce__(self): ...
def __iop__(self, other): ...
__iadd__: Any
__isub__: Any
__imul__: Any
__ifloordiv__: Any
__itruediv__: Any
__ipow__: Any
def copy(self, *args, **kwargs): ...
def __copy__(self): ...
def __deepcopy__(self, memo): ...
def __setattr__(self, attr, value): ...
masked: MaskedConstant
masked_singleton: MaskedConstant
masked_array = MaskedArray
def array(
data,
dtype=...,
copy=...,
order=...,
mask=...,
fill_value=...,
keep_mask=...,
hard_mask=...,
shrink=...,
subok=...,
ndmin=...,
): ...
def is_masked(x): ...
class _extrema_operation(_MaskedUFunc):
compare: Any
fill_value_func: Any
def __init__(self, ufunc, compare, fill_value): ...
# NOTE: in practice `b` has a default value, but users should
# explicitly provide a value here as the default is deprecated
def __call__(self, a, b): ...
def reduce(self, target, axis=...): ...
def outer(self, a, b): ...
def min(obj, axis=..., out=..., fill_value=..., keepdims=...): ...
def max(obj, axis=..., out=..., fill_value=..., keepdims=...): ...
def ptp(obj, axis=..., out=..., fill_value=..., keepdims=...): ...
class _frommethod:
__name__: Any
__doc__: Any
reversed: Any
def __init__(self, methodname, reversed=...): ...
def getdoc(self): ...
def __call__(self, a, *args, **params): ...
all: _frommethod
anomalies: _frommethod
anom: _frommethod
any: _frommethod
compress: _frommethod
cumprod: _frommethod
cumsum: _frommethod
copy: _frommethod
diagonal: _frommethod
harden_mask: _frommethod
ids: _frommethod
mean: _frommethod
nonzero: _frommethod
prod: _frommethod
product: _frommethod
ravel: _frommethod
repeat: _frommethod
soften_mask: _frommethod
std: _frommethod
sum: _frommethod
swapaxes: _frommethod
trace: _frommethod
var: _frommethod
count: _frommethod
argmin: _frommethod
argmax: _frommethod
minimum: _extrema_operation
maximum: _extrema_operation
def take(a, indices, axis=..., out=..., mode=...): ...
def power(a, b, third=...): ...
def argsort(a, axis=..., kind=..., order=..., endwith=..., fill_value=...): ...
def sort(a, axis=..., kind=..., order=..., endwith=..., fill_value=...): ...
def compressed(x): ...
def concatenate(arrays, axis=...): ...
def diag(v, k=...): ...
def left_shift(a, n): ...
def right_shift(a, n): ...
def put(a, indices, values, mode=...): ...
def putmask(a, mask, values): ...
def transpose(a, axes=...): ...
def reshape(a, new_shape, order=...): ...
def resize(x, new_shape): ...
def ndim(obj): ...
def shape(obj): ...
def size(obj, axis=...): ...
def diff(a, /, n=..., axis=..., prepend=..., append=...): ...
def where(condition, x=..., y=...): ...
def choose(indices, choices, out=..., mode=...): ...
def round(a, decimals=..., out=...): ...
def inner(a, b): ...
innerproduct = inner
def outer(a, b): ...
outerproduct = outer
def correlate(a, v, mode=..., propagate_mask=...): ...
def convolve(a, v, mode=..., propagate_mask=...): ...
def allequal(a, b, fill_value=...): ...
def allclose(a, b, masked_equal=..., rtol=..., atol=...): ...
def asarray(a, dtype=..., order=...): ...
def asanyarray(a, dtype=...): ...
def fromflex(fxarray): ...
class _convert2ma:
__doc__: Any
def __init__(self, funcname, params=...): ...
def getdoc(self): ...
def __call__(self, *args, **params): ...
arange: _convert2ma
empty: _convert2ma
empty_like: _convert2ma
frombuffer: _convert2ma
fromfunction: _convert2ma
identity: _convert2ma
ones: _convert2ma
zeros: _convert2ma
def append(a, b, axis=...): ...
def dot(a, b, strict=..., out=...): ...
def mask_rowcols(a, axis=...): ...