Cartesian

class kgpy.vectors.Cartesian

Bases: VectorInterface

__init__()

Return type:

None

Attributes

array
array_labeled
broadcasted
centers
component_sum
components
coordinates
dtype
indices
length
ndim
normalized
shape
tuple
type_coordinates
type_matrix
unit

Methods

__init__()
add_axes(axes)	rtype: typing.TypeVar(VectorInterfaceT, bound= VectorInterface)
aligned(shape)	rtype: typing.TypeVar(AbstractVectorT, bound= AbstractVector)
all([axis, where])	rtype: typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)
any([axis, where])	rtype: typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)
astype(dtype[, order, casting, subok, copy])	rtype: typing.TypeVar(VectorInterfaceT, bound= VectorInterface)
broadcast_to(shape)	rtype: typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)
combine_axes(axes[, axis_new])	rtype: typing.TypeVar(VectorInterfaceT, bound= VectorInterface)
copy()	rtype: typing.TypeVar(CopyableT, bound= Copyable)
copy_shallow()	rtype: typing.TypeVar(CopyableT, bound= Copyable)
from_coordinates(coordinates)	rtype: typing.TypeVar(AbstractVectorT, bound= AbstractVector)
index(value[, axis])	rtype: typing.Dict[str, typing.TypeVar(ArrayInterfaceT, bound= ArrayInterface)]
index_below_brute(value[, axis])	rtype: typing.Dict[str, typing.TypeVar(ArrayInterfaceT, bound= ArrayInterface)]
index_nearest_brute(value[, axis, where])	rtype: typing.Dict[str, typing.TypeVar(ArrayInterfaceT, bound= ArrayInterface)]
index_secant(value[, axis, damping])	rtype: typing.Dict[str, typing.TypeVar(ArrayT, bound= Array)]
interp_linear(item)	rtype: typing.TypeVar(ArrayInterfaceT, bound= ArrayInterface)
linear_space(start, stop, num[, endpoint])	rtype: typing.TypeVar(AbstractVectorT, bound= AbstractVector)
max([axis, initial, where])	rtype: typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)
mean([axis, where])	rtype: typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)
min([axis, initial, where])	rtype: typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)
ndindex([axis_ignored])	rtype: typing.Iterator[typing.Dict[str, int]]
outer(other)	rtype: typing.TypeVar(AbstractMatrixT, bound= AbstractMatrix)
prototype()	rtype: typing.Type[typing.TypeVar(AbstractVectorT, bound= AbstractVector)]
ptp([axis])	rtype: typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)
reshape(shape)	rtype: typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)
rms([axis, where])	rtype: typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)
std([axis, where])	rtype: typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)
stratified_random_space(start, stop, num, axis)	rtype: typing.TypeVar(AbstractVectorT, bound= AbstractVector)
sum([axis, where])	rtype: typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)
to(unit)	rtype: typing.TypeVar(ArrayInterfaceT, bound= ArrayInterface)
to_matrix()	rtype: typing.TypeVar(AbstractMatrixT, bound= AbstractMatrix)

Inheritance Diagram

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add_axes(axes)

Return type:

typing.TypeVar(VectorInterfaceT, bound= VectorInterface)

Parameters:

• self (VectorInterfaceT) –

• axes (List) –

aligned(shape)

Return type:

typing.TypeVar(AbstractVectorT, bound= AbstractVector)

Parameters:

• self (VectorInterfaceT) –

• shape (Dict[str, int]) –

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

Return type:

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters:

• self (NDArrayMethodsMixinT) –

• axis (str | Sequence[str] | None) –

• where (NDArrayMethodsMixinT) –

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

Return type:

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters:

• self (NDArrayMethodsMixinT) –

• axis (str | Sequence[str] | None) –

• where (NDArrayMethodsMixinT) –

astype(dtype, order='K', casting='unsafe', subok=True, copy=True)

Return type:

typing.TypeVar(VectorInterfaceT, bound= VectorInterface)

Parameters:

• self (VectorInterfaceT) –

• dtype (dtype[Any] | None | type[Any] | _SupportsDType[dtype[Any]] | str | tuple[Any, int] | tuple[Any, SupportsIndex | Sequence[SupportsIndex]] | list[Any] | _DTypeDict | tuple[Any, Any]) –

• order (str) –

• subok (bool) –

• copy (bool) –

broadcast_to(shape)

Return type:

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters:

• self (NDArrayMethodsMixinT) –

• shape (Dict[str, int]) –

combine_axes(axes, axis_new=None)

Return type:

typing.TypeVar(VectorInterfaceT, bound= VectorInterface)

Parameters:

• self (VectorInterfaceT) –

• axes (Sequence[str]) –

• axis_new (str | None) –

copy()

Return type:

typing.TypeVar(CopyableT, bound= Copyable)

Parameters:

self (CopyableT) –

copy_shallow()

Return type:

typing.TypeVar(CopyableT, bound= Copyable)

Parameters:

self (CopyableT) –

classmethod from_coordinates(coordinates)

Return type:

typing.TypeVar(AbstractVectorT, bound= AbstractVector)

Parameters:

coordinates (Dict[str, int | float | ndarray | Quantity | AbstractArray | AbstractArray | VectorInterface]) –

index(value, axis=None)

Return type:

typing.Dict[str, typing.TypeVar(ArrayInterfaceT, bound= ArrayInterface)]

Parameters:

• self (ArrayInterfaceT) –

• value (ArrayInterfaceT) –

• axis (str | Sequence[str] | None) –

index_below_brute(value, axis=None)

Return type:

typing.Dict[str, typing.TypeVar(ArrayInterfaceT, bound= ArrayInterface)]

Parameters:

• self (ArrayInterfaceT) –

• value (ArrayInterfaceT) –

• axis (str | Sequence[str] | None) –

index_nearest_brute(value, axis=None, where=None)

Return type:

typing.Dict[str, typing.TypeVar(ArrayInterfaceT, bound= ArrayInterface)]

Parameters:

• self (ArrayInterfaceT) –

• value (ArrayInterfaceT) –

• axis (str | Sequence[str] | None) –

• where (ArrayInterfaceT | None) –

index_secant(value, axis=None, damping=1)

Return type:

typing.Dict[str, typing.TypeVar(ArrayT, bound= Array)]

Parameters:

• self (ArrayInterfaceT) –

• value (ArrayInterfaceT) –

• axis (str | Sequence[str] | None) –

• damping (float) –

interp_linear(item)

Return type:

typing.TypeVar(ArrayInterfaceT, bound= ArrayInterface)

Parameters:

• self (ArrayInterfaceT) –

• item (Dict[str, AbstractArrayT]) –

classmethod linear_space(start, stop, num, endpoint=True)

Return type:

typing.TypeVar(AbstractVectorT, bound= AbstractVector)

Parameters:

• start (AbstractVectorT) –

• stop (AbstractVectorT) –

• num (AbstractVectorT) –

• endpoint (bool) –

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

Return type:

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters:

• self (NDArrayMethodsMixinT) –

• axis (str | Sequence[str] | None) –

• initial (int | float | ndarray | Quantity | None) –

• where (NDArrayMethodsMixinT) –

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

Return type:

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters:

• self (NDArrayMethodsMixinT) –

• axis (str | Sequence[str] | None) –

• where (NDArrayMethodsMixinT) –

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

Return type:

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters:

• self (NDArrayMethodsMixinT) –

• axis (str | Sequence[str] | None) –

• initial (int | float | ndarray | Quantity | None) –

• where (NDArrayMethodsMixinT) –

ndindex(axis_ignored=None)

Return type:

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

Parameters:

• self (Type[ArrayInterfaceT]) –

• axis_ignored (str | Sequence[str] | None) –

outer(other)

Return type:

typing.TypeVar(AbstractMatrixT, bound= AbstractMatrix)

Parameters:

• self (AbstractVectorT) –

• other (AbstractVectorT) –

abstract classmethod prototype()

Return type:

typing.Type[typing.TypeVar(AbstractVectorT, bound= AbstractVector)]

ptp(axis=None)

Return type:

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters:

• self (NDArrayMethodsMixinT) –

• axis (str | Sequence[str] | None) –

reshape(shape)

Return type:

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters:

• self (NDArrayMethodsMixinT) –

• shape (Dict[str, int]) –

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

Return type:

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters:

• self (NDArrayMethodsMixinT) –

• axis (str | Sequence[str] | None) –

• where (NDArrayMethodsMixinT) –

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

Return type:

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters:

• self (NDArrayMethodsMixinT) –

• axis (str | Sequence[str] | None) –

• where (NDArrayMethodsMixinT) –

classmethod stratified_random_space(start, stop, num, axis, endpoint=True, shape_extra=None)

Return type:

typing.TypeVar(AbstractVectorT, bound= AbstractVector)

Parameters:

• start (AbstractVectorT) –

• stop (AbstractVectorT) –

• num (AbstractVectorT) –

• axis (AbstractVectorT) –

• endpoint (bool) –

• shape_extra (Dict[str, int] | None) –

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

Return type:

typing.TypeVar(NDArrayMethodsMixinT, bound= NDArrayMethodsMixin)

Parameters:

• self (NDArrayMethodsMixinT) –

• axis (str | Sequence[str] | None) –

• where (NDArrayMethodsMixinT) –

abstract to(unit)

Return type:

typing.TypeVar(ArrayInterfaceT, bound= ArrayInterface)

Parameters:

• self (ArrayInterfaceT) –

• unit (UnitBase) –

to_matrix()

Return type:

typing.TypeVar(AbstractMatrixT, bound= AbstractMatrix)

Parameters:

self (AbstractVectorT) –

property array: ndarray

property array_labeled: ArrayInterface

property broadcasted: ArrayInterfaceT

property centers: ArrayInterfaceT

property component_sum: int | float | ndarray | Quantity | AbstractArray | AbstractArray

property components: List[str]

abstract property coordinates: Dict[str, int | float | ndarray | Quantity | AbstractArray | AbstractArray | VectorInterface]

property dtype

property indices: Dict[str, ArrayT]

property length: int | float | ndarray | Quantity | AbstractArray | AbstractArray

property ndim: int

property normalized: VectorInterfaceT

property shape: Dict[str, int]

property tuple: Tuple[int | float | ndarray | Quantity | AbstractArray | AbstractArray | VectorInterface, ...]

type_coordinates = (<class 'str'>, <class 'bool'>, <class 'int'>, <class 'float'>, <class 'complex'>, <class 'numpy.generic'>, <class 'numpy.ndarray'>, <class 'kgpy.labeled.AbstractArray'>, <class 'kgpy.uncertainty.AbstractArray'>)

property type_matrix: Type[AbstractMatrix]

abstract property unit: float | Unit