UniformRandomSpace

class kgpy.labeled.UniformRandomSpace(start=None, stop=None, num=None, axis=None, seed=42)

Bases: _RandomSpaceMixin, _LinearMixin[StartArrayT, StopArrayT]

__init__(start=None, stop=None, num=None, axis=None, seed=42)
Parameters
Return type

None

Attributes

array

axes

axis

ndim

num

range

seed

shape

start

start_broadcasted

stop

stop_broadcasted

type_array

type_array_auxiliary

unit

Methods

__init__([start, stop, num, axis, seed])

add_axes(axes)

rtype

typing.TypeVar(AbstractArrayT, bound= AbstractArray)

broadcast_shapes(*arrs)

rtype

typing.Dict[str, int]

combine_axes(axes[, axis_new])

rtype

kgpy.labeled.Array

copy()

rtype

typing.TypeVar(CopyableT, bound= Copyable)

copy_shallow()

rtype

typing.TypeVar(CopyableT, bound= Copyable)

matrix_determinant(axis_rows, axis_columns)

rtype

kgpy.labeled.Array

matrix_inverse(axis_rows, axis_columns)

rtype

kgpy.labeled.Array

matrix_multiply(other, axis_rows, axis_columns)

rtype

kgpy.labeled.Array

max([axis, where])

rtype

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

mean([axis, where])

rtype

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

min([axis, where])

rtype

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

ndindex(shape)

rtype

typing.Iterator[typing.Dict[str, int]]

shape_broadcasted(*arrs)

rtype

typing.Dict[str, int]

Inheritance Diagram

Inheritance diagram of kgpy.labeled.UniformRandomSpace

type_array_primary

alias of ndarray

add_axes(axes)
Return type

typing.TypeVar(AbstractArrayT, bound= AbstractArray)

Parameters
  • self (AbstractArrayT) –

  • axes (List) –

classmethod broadcast_shapes(*arrs)
Return type

typing.Dict[str, int]

Parameters

arrs (AbstractArrayT) –

combine_axes(axes, axis_new=None)
Return type

kgpy.labeled.Array

Parameters
copy()
Return type

typing.TypeVar(CopyableT, bound= Copyable)

Parameters

self (CopyableT) –

copy_shallow()
Return type

typing.TypeVar(CopyableT, bound= Copyable)

Parameters

self (CopyableT) –

matrix_determinant(axis_rows, axis_columns)
Return type

kgpy.labeled.Array

Parameters
  • self (AbstractArrayT) –

  • axis_rows (str) –

  • axis_columns (str) –

matrix_inverse(axis_rows, axis_columns)
Return type

kgpy.labeled.Array

Parameters
  • self (AbstractArrayT) –

  • axis_rows (str) –

  • axis_columns (str) –

matrix_multiply(other, axis_rows, axis_columns)
Return type

kgpy.labeled.Array

Parameters
  • self (AbstractArrayT) –

  • other (OtherAbstractArrayT) –

  • axis_rows (str) –

  • axis_columns (str) –

max(axis=None, where=<no value>)
Return type

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters
mean(axis=None, where=<no value>)
Return type

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters
min(axis=None, where=<no value>)
Return type

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters
classmethod ndindex(shape)
Return type

typing.Iterator[typing.Dict[str, int]]

Parameters

shape (Dict[str, int]) –

shape_broadcasted(*arrs)
Return type

typing.Dict[str, int]

Parameters
  • self (AbstractArrayT) –

  • arrs (AbstractArrayT) –

property array: Union[Sequence[Sequence[Sequence[Sequence[Sequence[Any]]]]], _SupportsArray[dtype], Sequence[_SupportsArray[dtype]], Sequence[Sequence[_SupportsArray[dtype]]], Sequence[Sequence[Sequence[_SupportsArray[dtype]]]], Sequence[Sequence[Sequence[Sequence[_SupportsArray[dtype]]]]], bool, int, float, complex, str, bytes, Sequence[Union[bool, int, float, complex, str, bytes]], Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]], Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]], Sequence[Sequence[Sequence[Sequence[Union[bool, int, float, complex, str, bytes]]]]], Quantity]
property axes: List[str]
axis: str = None
property ndim: int
num: int = None
property range: Array
seed: typing.Optional[int] = 42
property shape: Dict[str, int]
start: typing.TypeVar(StartArrayT, bound= typing.Union[typing.Sequence[typing.Sequence[typing.Sequence[typing.Sequence[typing.Sequence[typing.Any]]]]], numpy.typing._array_like._SupportsArray[numpy.dtype], typing.Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]], typing.Sequence[typing.Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]], typing.Sequence[typing.Sequence[typing.Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]], typing.Sequence[typing.Sequence[typing.Sequence[typing.Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]]], bool, int, float, complex, str, bytes, typing.Sequence[typing.Union[bool, int, float, complex, str, bytes]], typing.Sequence[typing.Sequence[typing.Union[bool, int, float, complex, str, bytes]]], typing.Sequence[typing.Sequence[typing.Sequence[typing.Union[bool, int, float, complex, str, bytes]]]], typing.Sequence[typing.Sequence[typing.Sequence[typing.Sequence[typing.Union[bool, int, float, complex, str, bytes]]]]], astropy.units.Quantity, kgpy.labeled.AbstractArray]) = None
property start_broadcasted: AbstractArray
stop: typing.TypeVar(StopArrayT, bound= typing.Union[typing.Sequence[typing.Sequence[typing.Sequence[typing.Sequence[typing.Sequence[typing.Any]]]]], numpy.typing._array_like._SupportsArray[numpy.dtype], typing.Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]], typing.Sequence[typing.Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]], typing.Sequence[typing.Sequence[typing.Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]], typing.Sequence[typing.Sequence[typing.Sequence[typing.Sequence[numpy.typing._array_like._SupportsArray[numpy.dtype]]]]], bool, int, float, complex, str, bytes, typing.Sequence[typing.Union[bool, int, float, complex, str, bytes]], typing.Sequence[typing.Sequence[typing.Union[bool, int, float, complex, str, bytes]]], typing.Sequence[typing.Sequence[typing.Sequence[typing.Union[bool, int, float, complex, str, bytes]]]], typing.Sequence[typing.Sequence[typing.Sequence[typing.Sequence[typing.Union[bool, int, float, complex, str, bytes]]]]], astropy.units.Quantity, kgpy.labeled.AbstractArray]) = None
property stop_broadcasted: AbstractArray
type_array: typing.ClassVar[typing.Tuple[typing.Type, ...]] = (<class 'bool'>, <class 'int'>, <class 'float'>, <class 'complex'>, <class 'numpy.generic'>, <class 'numpy.ndarray'>)
type_array_auxiliary: typing.ClassVar[typing.Tuple[typing.Type, ...]] = (<class 'bool'>, <class 'int'>, <class 'float'>, <class 'complex'>, <class 'numpy.generic'>)
property unit: Optional[Unit]