Range

class kgpy.labeled.Range(start=0, stop=None, step=1, axis=None)

Bases: AbstractArray[ndarray]

__init__(start=0, stop=None, step=1, axis=None)

Parameters

• start (int) –

• stop (Optional[int]) –

• step (int) –

• axis (Optional[str]) –

Return type

None

Attributes

array
axes
axis
ndim
shape
start
step
stop
type_array
type_array_auxiliary
unit

Methods

__init__([start, stop, step, axis])
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

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

• self (AbstractArrayT) –

• axes (Sequence[str]) –

• axis_new (Optional[str]) –

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

• self (NDArrayMethodsMixinT) –

• axis (Optional[Union[str, Sequence[str]]]) –

• where (NDArrayMethodsMixinT) –

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

Return type

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters

• self (NDArrayMethodsMixinT) –

• axis (Optional[Union[str, Sequence[str]]]) –

• where (NDArrayMethodsMixinT) –

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

Return type

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters

• self (NDArrayMethodsMixinT) –

• axis (Optional[Union[str, Sequence[str]]]) –

• where (NDArrayMethodsMixinT) –

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: ndarray

property axes: List[str]

axis: str = None

property ndim: int

property shape: Dict[str, int]

start: int = 0

step: int = 1

stop: int = None

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]