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150 lines (129 loc) · 3.58 KB
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# 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]