# for Python <= 3.8

from typing import (

overload,

Union,

List,

Tuple,

Type,

TextIO,

Any,

Callable,

Optional,

Iterator,

)

from typing_extensions import Literal as L

from typing_extensions import Self

# array like

# these are input to many functions in spatialmath.base, and can be a list, tuple or

# ndarray. The elements are generally float, but some functions accept symbolic

# arguments as well, which leads to a NumPy array with dtype=object

#

# The variants like ArrayLike2 indicate that a list, tuple or ndarray of length 2 is

# expected. Static checking of tuple length is possible but not a lists. This might be

# possible in future versions of Python, but for now it is a hint to the coder about

# what is expected

from numpy.typing import DTypeLike, NDArray # , ArrayLike

from typing import cast

# from typing import TypeVar

# NDArray = TypeVar('NDArray')

import numpy as np

ArrayLike = Union[float, List[float], Tuple[float, ...], NDArray]

ArrayLikePure = Union[List[float], Tuple[float, ...], NDArray]

ArrayLike2 = Union[List, Tuple[float, float], NDArray]

ArrayLike3 = Union[List, Tuple[float, float, float], NDArray]

ArrayLike4 = Union[List, Tuple[float, float, float, float], NDArray]

ArrayLike6 = Union[List, Tuple[float, float, float, float, float, float], NDArray]

# real vectors

R1 = NDArray[np.floating] # R^1

R2 = NDArray[np.floating] # R^2

R3 = NDArray[np.floating] # R^3

R4 = NDArray[np.floating] # R^4

R6 = NDArray[np.floating] # R^6

R8 = NDArray[np.floating] # R^8

# real matrices

R1x1 = NDArray # R^{1x1} matrix

R2x2 = NDArray # R^{3x3} matrix

R3x3 = NDArray # R^{3x3} matrix

R4x4 = NDArray # R^{4x4} matrix

R6x6 = NDArray # R^{6x6} matrix

R8x8 = NDArray # R^{8x8} matrix

R1x3 = NDArray # R^{1x3} row vector

R3x1 = NDArray # R^{3x1} column vector

R1x2 = NDArray # R^{1x2} row vector

R2x1 = NDArray # R^{2x1} column vector

Points2 = NDArray # R^{2xN} matrix

Points3 = NDArray # R^{2xN} matrix

RNx3 = NDArray # R^{Nx3} matrix

# Lie group elements

SO2Array = NDArray # SO(2) rotation matrix

SE2Array = NDArray # SE(2) rigid-body transform

SO3Array = NDArray # SO(3) rotation matrix

SE3Array = NDArray # SE(3) rigid-body transform

# Lie algebra elements

so2Array = NDArray # so(2) Lie algebra of SO(2), skew-symmetrix matrix

se2Array = NDArray # se(2) Lie algebra of SE(2), augmented skew-symmetrix matrix

so3Array = NDArray # so(3) Lie algebra of SO(3), skew-symmetrix matrix

se3Array = NDArray # se(3) Lie algebra of SE(3), augmented skew-symmetrix matrix

# quaternion arrays

QuaternionArray = NDArray

UnitQuaternionArray = NDArray

Rn = Union[R2, R3]

SOnArray = Union[SO2Array, SO3Array]

SEnArray = Union[SE2Array, SE3Array]

sonArray = Union[so2Array, so3Array]

senArray = Union[se2Array, se3Array]

# __all__ = [

# overload,

# Union,

# List,

# Tuple,

# Type,

# TextIO,

# Any,

# Callable,

# Optional,

# Iterator,

# ArrayLike,

# ArrayLike2,

# ArrayLike3,

# ArrayLike4,

# ArrayLike6,

# # real vectors

# R2,

# R3,

# R4,

# R6,

# R8,

# # real matrices

# R2x2,

# R3x3,

# R4x4,

# R6x6,

# R8x8,

# R1x3,

# R3x1,

# R1x2,

# R2x1,

# Points2,

# Points3,

# RNx3,

# # Lie group elements

# SO2Array,

# SE2Array,

# SO3Array,

# SE3Array,

# # Lie algebra elements

# so2Array,

# se2Array,

# so3Array,

# se3Array,

# # quaternion arrays

# QuaternionArray,

# UnitQuaternionArray,

# Rn,

# SOnArray,

# SEnArray,

# sonArray,

# senArray,

# ]

Color = Union[str, ArrayLike3]