Erdnaxela3/bioptim_gui

import numpy as np

from bioptim_gui_api.acrobatics_ocp.variables.variable_computers.straight_acrobatics_variables import (
    StraightAcrobaticsVariables,
)


class StraightAcrobaticsVariablesWithSpine(StraightAcrobaticsVariables):
    X = 0
    Y = 1
    Z = 2
    Xrot = 3
    Yrot = 4
    Zrot = 5
    XrotStomach = 6
    YrotStomach = 7
    ZrotStomach = 8
    XrotRib = 9
    YrotRib = 10
    ZrotRib = 11
    XrotNipple = 12
    YrotNipple = 13
    ZrotNipple = 14
    XrotShoulder = 15
    YrotShoulder = 16
    ZrotShoulder = 17
    ZrotRightUpperArm = 18
    YrotRightUpperArm = 19
    ZrotLeftUpperArm = 20
    YrotLeftUpperArm = 21

    dofs = [
        "Pelvis translation X",
        "Pelvis translation Y",
        "Pelvis translation Z",
        "Pelvis rotation X",
        "Pelvis rotation Y",
        "Pelvis rotation Z",
        "Stomach rotation X",
        "Stomach rotation Y",
        "Stomach rotation Z",
        "Rib rotation X",
        "Rib rotation Y",
        "Rib rotation Z",
        "Nipple rotation X",
        "Nipple rotation Y",
        "Nipple rotation Z",
        "Shoulder rotation X",
        "Shoulder rotation Y",
        "Shoulder rotation Z",
        "Right upper arm rotation Z",
        "Right upper arm rotation Y",
        "Left upper arm rotation Z",
        "Left upper arm rotation Y",
    ]

    nb_q, nb_qdot, nb_tau = 22, 22, 16

    arm_dofs = [
        ZrotRightUpperArm,
        YrotRightUpperArm,
        ZrotLeftUpperArm,
        YrotLeftUpperArm,
    ]

    shoulder_dofs = [
        ZrotRightUpperArm,
        YrotRightUpperArm,
        ZrotLeftUpperArm,
        YrotLeftUpperArm,
    ]

    q_min_bounds = np.array(
        [
            [-1] * 3,
            [-1] * 3,
            [-0.1] * 3,
            [0] * 3,
            [-np.pi / 4] * 3,
            [0] * 3,
            [-np.pi / 12] * 3,
            [-np.pi / 12] * 3,
            [-np.pi / 12] * 3,
            [-np.pi / 12] * 3,
            [-np.pi / 12] * 3,
            [-np.pi / 12] * 3,
            [-np.pi / 12] * 3,
            [-np.pi / 12] * 3,
            [-np.pi / 12] * 3,
            [-np.pi / 12] * 3,
            [-np.pi / 12] * 3,
            [-np.pi / 12] * 3,
            [-0.65] * 3,
            [-0.05] * 3,
            [-2.0] * 3,
            [-3.0] * 3,
        ]
    )

    q_max_bounds = np.array(
        [
            [1] * 3,
            [1] * 3,
            [15] * 3,
            [0] * 3,
            [np.pi / 4] * 3,
            [0] * 3,
            [np.pi / 12] * 3,
            [np.pi / 12] * 3,
            [np.pi / 12] * 3,
            [np.pi / 12] * 3,
            [np.pi / 12] * 3,
            [np.pi / 12] * 3,
            [np.pi / 12] * 3,
            [np.pi / 12] * 3,
            [np.pi / 12] * 3,
            [np.pi / 12] * 3,
            [np.pi / 12] * 3,
            [np.pi / 12] * 3,
            [2.0] * 3,
            [3.0] * 3,
            [0.65] * 3,
            [0.05] * 3,
        ]
    )

    @classmethod
    def _fill_landing_phase(cls, x_bounds, half_twists: list) -> dict:
        super()._fill_landing_phase(x_bounds, half_twists)

        x_bounds[-1]["min"][cls.XrotStomach : cls.ZrotShoulder, 2] = -0.01
        x_bounds[-1]["max"][cls.XrotStomach : cls.ZrotShoulder, 2] = 0.01