Source code for sym.ops.pose2.group_ops

# -----------------------------------------------------------------------------
# This file was autogenerated by symforce from template:
#     ops/CLASS/group_ops.py.jinja
# Do NOT modify by hand.
# -----------------------------------------------------------------------------

# ruff: noqa: PLR0915, F401, PLW0211, PLR0914

import math
import typing as T

import numpy

import sym


[docs]class GroupOps(object): """ Python GroupOps implementation for :py:class:`symforce.geo.pose2.Pose2`. """
[docs] @staticmethod def identity(): # type: () -> sym.Pose2 # Total ops: 0 # Input arrays # Intermediate terms (0) # Output terms _res = [0.0] * 4 _res[0] = 1 _res[1] = 0 _res[2] = 0 _res[3] = 0 return sym.Pose2.from_storage(_res)
[docs] @staticmethod def inverse(a): # type: (sym.Pose2) -> sym.Pose2 # Total ops: 8 # Input arrays _a = a.data # Intermediate terms (0) # Output terms _res = [0.0] * 4 _res[0] = _a[0] _res[1] = -_a[1] _res[2] = -_a[0] * _a[2] - _a[1] * _a[3] _res[3] = -_a[0] * _a[3] + _a[1] * _a[2] return sym.Pose2.from_storage(_res)
[docs] @staticmethod def compose(a, b): # type: (sym.Pose2, sym.Pose2) -> sym.Pose2 # Total ops: 14 # Input arrays _a = a.data _b = b.data # Intermediate terms (0) # Output terms _res = [0.0] * 4 _res[0] = _a[0] * _b[0] - _a[1] * _b[1] _res[1] = _a[0] * _b[1] + _a[1] * _b[0] _res[2] = _a[0] * _b[2] - _a[1] * _b[3] + _a[2] _res[3] = _a[0] * _b[3] + _a[1] * _b[2] + _a[3] return sym.Pose2.from_storage(_res)
[docs] @staticmethod def between(a, b): # type: (sym.Pose2, sym.Pose2) -> sym.Pose2 # Total ops: 20 # Input arrays _a = a.data _b = b.data # Intermediate terms (0) # Output terms _res = [0.0] * 4 _res[0] = _a[0] * _b[0] + _a[1] * _b[1] _res[1] = _a[0] * _b[1] - _a[1] * _b[0] _res[2] = -_a[0] * _a[2] + _a[0] * _b[2] - _a[1] * _a[3] + _a[1] * _b[3] _res[3] = -_a[0] * _a[3] + _a[0] * _b[3] + _a[1] * _a[2] - _a[1] * _b[2] return sym.Pose2.from_storage(_res)
[docs] @staticmethod def inverse_with_jacobian(a): # type: (sym.Pose2) -> T.Tuple[sym.Pose2, numpy.ndarray] # Total ops: 14 # Input arrays _a = a.data # Intermediate terms (5) _tmp0 = -_a[1] _tmp1 = _a[0] * _a[2] + _a[1] * _a[3] _tmp2 = _a[1] * _a[2] _tmp3 = _a[0] * _a[3] _tmp4 = -_a[0] # Output terms _res = [0.0] * 4 _res[0] = _a[0] _res[1] = _tmp0 _res[2] = -_tmp1 _res[3] = _tmp2 - _tmp3 _res_D_a = numpy.zeros((3, 3)) _res_D_a[0, 0] = -(_a[0] ** 2) - _a[1] ** 2 _res_D_a[1, 0] = _tmp2 - _tmp3 _res_D_a[2, 0] = _tmp1 _res_D_a[0, 1] = 0 _res_D_a[1, 1] = _tmp4 _res_D_a[2, 1] = _a[1] _res_D_a[0, 2] = 0 _res_D_a[1, 2] = _tmp0 _res_D_a[2, 2] = _tmp4 return sym.Pose2.from_storage(_res), _res_D_a
[docs] @staticmethod def compose_with_jacobians(a, b): # type: (sym.Pose2, sym.Pose2) -> T.Tuple[sym.Pose2, numpy.ndarray, numpy.ndarray] # Total ops: 22 # Input arrays _a = a.data _b = b.data # Intermediate terms (8) _tmp0 = _a[0] * _b[0] - _a[1] * _b[1] _tmp1 = _a[1] * _b[0] _tmp2 = _a[0] * _b[1] _tmp3 = _tmp1 + _tmp2 _tmp4 = _a[0] * _b[2] - _a[1] * _b[3] _tmp5 = _a[1] * _b[2] _tmp6 = _a[0] * _b[3] _tmp7 = _tmp0**2 - _tmp3 * (-_tmp1 - _tmp2) # Output terms _res = [0.0] * 4 _res[0] = _tmp0 _res[1] = _tmp3 _res[2] = _a[2] + _tmp4 _res[3] = _a[3] + _tmp5 + _tmp6 _res_D_a = numpy.zeros((3, 3)) _res_D_a[0, 0] = _tmp7 _res_D_a[1, 0] = -_tmp5 - _tmp6 _res_D_a[2, 0] = _tmp4 _res_D_a[0, 1] = 0 _res_D_a[1, 1] = 1 _res_D_a[2, 1] = 0 _res_D_a[0, 2] = 0 _res_D_a[1, 2] = 0 _res_D_a[2, 2] = 1 _res_D_b = numpy.zeros((3, 3)) _res_D_b[0, 0] = _tmp7 _res_D_b[1, 0] = 0 _res_D_b[2, 0] = 0 _res_D_b[0, 1] = 0 _res_D_b[1, 1] = _a[0] _res_D_b[2, 1] = _a[1] _res_D_b[0, 2] = 0 _res_D_b[1, 2] = -_a[1] _res_D_b[2, 2] = _a[0] return sym.Pose2.from_storage(_res), _res_D_a, _res_D_b
[docs] @staticmethod def between_with_jacobians(a, b): # type: (sym.Pose2, sym.Pose2) -> T.Tuple[sym.Pose2, numpy.ndarray, numpy.ndarray] # Total ops: 35 # Input arrays _a = a.data _b = b.data # Intermediate terms (14) _tmp0 = _a[1] * _b[1] _tmp1 = _a[0] * _b[0] _tmp2 = _tmp0 + _tmp1 _tmp3 = _a[1] * _b[0] _tmp4 = _a[0] * _b[1] _tmp5 = -_tmp3 + _tmp4 _tmp6 = _a[0] * _a[2] + _a[1] * _a[3] _tmp7 = _a[1] * _b[3] _tmp8 = _a[0] * _b[2] _tmp9 = _a[1] * _a[2] _tmp10 = _a[0] * _a[3] _tmp11 = _a[0] * _b[3] - _a[1] * _b[2] _tmp12 = -_a[0] _tmp13 = -_a[1] # Output terms _res = [0.0] * 4 _res[0] = _tmp2 _res[1] = _tmp5 _res[2] = -_tmp6 + _tmp7 + _tmp8 _res[3] = -_tmp10 + _tmp11 + _tmp9 _res_D_a = numpy.zeros((3, 3)) _res_D_a[0, 0] = _tmp2 * (-_tmp0 - _tmp1) - _tmp5**2 _res_D_a[1, 0] = -_tmp10 + _tmp11 + _tmp9 _res_D_a[2, 0] = _tmp6 - _tmp7 - _tmp8 _res_D_a[0, 1] = 0 _res_D_a[1, 1] = _tmp12 _res_D_a[2, 1] = _a[1] _res_D_a[0, 2] = 0 _res_D_a[1, 2] = _tmp13 _res_D_a[2, 2] = _tmp12 _res_D_b = numpy.zeros((3, 3)) _res_D_b[0, 0] = _tmp2**2 - _tmp5 * (_tmp3 - _tmp4) _res_D_b[1, 0] = 0 _res_D_b[2, 0] = 0 _res_D_b[0, 1] = 0 _res_D_b[1, 1] = _a[0] _res_D_b[2, 1] = _tmp13 _res_D_b[0, 2] = 0 _res_D_b[1, 2] = _a[1] _res_D_b[2, 2] = _a[0] return sym.Pose2.from_storage(_res), _res_D_a, _res_D_b