""" Data, constants, and paths. """
import numpy as np
INITIAL_ANGLES = {
"RF": {
# Base ThC yaw pitch CTr pitch
"stage_1": np.array([0.0, 0.45, -0.07, -2.14]),
# Base ThC yaw pitch roll CTr pitch CTr roll
"stage_2": np.array([0.0, 0.45, -0.07, -0.32, -2.14, 1.4]),
# Base ThC yaw pitch roll CTr pitch CTr roll FTi pitch
"stage_3": np.array([0.0, 0.45, -0.07, -0.32, -2.14, -1.25, 1.48, 0.0]),
# Base ThC yaw pitch roll CTr pitch CTr roll FTi pitch TiTa pitch
"stage_4": np.array([0.0, 0.45, -0.07, -0.32, -2.14, -1.25, 1.48, 0.0, 0.0]),
},
# Same order for the contralateral leg
"LF": {
"stage_1": np.array([0.0, -0.45, -0.07, -2.14]),
"stage_2": np.array([0.0, -0.45, -0.07, 0.32, -2.14, 1.4]),
"stage_3": np.array([0.0, -0.45, -0.07, 0.32, -2.14, 1.25, 1.48, 0.0]),
"stage_4": np.array([0.0, -0.45, -0.07, 0.32, -2.14, 1.25, 1.48, 0.0, 0.0]),
},
}
# Lower bound of a DOF should be strictly lower than the initial angle.
# Upper bound of a DOF should be strictly bigger than the initial angle.
BOUNDS = {
"RF_ThC_roll": (np.deg2rad(-130), np.deg2rad(50)),
"RF_ThC_yaw": (np.deg2rad(-50), np.deg2rad(50)),
"RF_ThC_pitch": (np.deg2rad(-40), np.deg2rad(60)),
"RF_CTr_pitch": (np.deg2rad(-180), np.deg2rad(0)),
"RF_CTr_roll": (np.deg2rad(-150), np.deg2rad(0)),
"RF_FTi_pitch": (np.deg2rad(0), np.deg2rad(170)),
"RF_TiTa_pitch": (np.deg2rad(-150), np.deg2rad(0)),
"LF_ThC_roll": (np.deg2rad(-50), np.deg2rad(130)),
"LF_ThC_yaw": (np.deg2rad(-50), np.deg2rad(50)),
"LF_ThC_pitch": (np.deg2rad(-40), np.deg2rad(60)),
"LF_CTr_pitch": (np.deg2rad(-180), np.deg2rad(0)),
"LF_CTr_roll": (np.deg2rad(0), np.deg2rad(150)),
"LF_FTi_pitch": (np.deg2rad(0), np.deg2rad(170)),
"LF_TiTa_pitch": (np.deg2rad(-150), np.deg2rad(0)),
}
# Size of the template body segments
NMF_SIZE = {
"RF_Coxa": 0.40,
"RM_Coxa": 0.182,
"RH_Coxa": 0.199,
"LF_Coxa": 0.40,
"LM_Coxa": 0.182,
"LH_Coxa": 0.199,
"RF_Femur": 0.69,
"RM_Femur": 0.7829999999999999,
"RH_Femur": 0.8360000000000001,
"LF_Femur": 0.69,
"LM_Femur": 0.7829999999999999,
"LH_Femur": 0.8360000000000001,
"RF_Tibia": 0.54,
"RM_Tibia": 0.668,
"RH_Tibia": 0.6849999999999998,
"LF_Tibia": 0.54,
"LM_Tibia": 0.668,
"LH_Tibia": 0.6849999999999998,
"RF_Tarsus": 0.63,
"RM_Tarsus": 0.6949999999999998,
"RH_Tarsus": 0.7950000000000002,
"LF_Tarsus": 0.63,
"LM_Tarsus": 0.6949999999999998,
"LH_Tarsus": 0.7950000000000002,
"RF": 2.26,
"RM": 2.328,
"RH": 2.515,
"LF": 2.26,
"LM": 2.328,
"LH": 2.515,
"Antenna": 0.2745906043549196,
"Antenna_mid_thorax": 0.9355746896961248,
}
# Key points to align, to be provided in the alignment.Align class
PTS2ALIGN = {
"R_head": ["base_anten_R", "tip_anten_R"],
"RF_leg": [
"thorax_coxa_R",
"coxa_femur_R",
"femur_tibia_R",
"tibia_tarsus_R",
"claw_R",
],
"Thorax": ["thorax_wing_R", "thorax_midpoint_tether", "thorax_wing_L"],
"L_head": ["base_anten_L", "tip_anten_L"],
"LF_leg": [
"thorax_coxa_L",
"coxa_femur_L",
"femur_tibia_L",
"tibia_tarsus_L",
"claw_L",
],
}
[docs]
def get_pts2align(path: str):
"""Deletes the keys from the PTS2ALIGN dictionary."""
pts_temp = PTS2ALIGN.copy()
if "_RF" in path:
del pts_temp["RF_leg"]
elif "_LF" in path:
del pts_temp["LF_leg"]
elif "_RLF" in path or "_LRF" in path:
del pts_temp["LF_leg"]
del pts_temp["RF_leg"]
return pts_temp
# Key points that are used in alignment
SKELETON = [
"base_anten_R",
"tip_anten_R",
"thorax_coxa_R",
"coxa_femur_R",
"femur_tibia_R",
"tibia_tarsus_R",
"claw_R",
"thorax_wing_R",
"thorax_midpoint_tether",
"thorax_wing_L",
"base_anten_L",
"tip_anten_L",
"thorax_coxa_L",
"coxa_femur_L",
"femur_tibia_L",
"tibia_tarsus_L",
"claw_L",
]
# Pose of each body landmark in the NeuroMechFly v0.0.6 model
# Note that each leg segment represents the joint in the proximal part
# For example, RF_Coxa means Thorax-Coxa joint
NMF_TEMPLATE = {
"RF_Coxa": np.array([0.33, -0.17, 1.07]),
"RF_Femur": np.array([0.33, -0.17, 0.67]),
"RF_Tibia": np.array([0.33, -0.17, -0.02]),
"RF_Tarsus": np.array([0.33, -0.17, -0.56]),
"RF_Claw": np.array([0.33, -0.17, -1.19]),
"LF_Coxa": np.array([0.33, 0.17, 1.07]),
"LF_Femur": np.array([0.33, 0.17, 0.67]),
"LF_Tibia": np.array([0.33, 0.17, -0.02]),
"LF_Tarsus": np.array([0.33, 0.17, -0.56]),
"LF_Claw": np.array([0.33, 0.17, -1.19]),
"R_Antenna_base": np.array([1.01, -0.10, 1.41]),
"L_Antenna_base": np.array([1.01, 0.10, 1.41]),
"R_Antenna_edge": np.array([1.06, -0.10, 1.14]),
"L_Antenna_edge": np.array([1.06, 0.10, 1.14]),
# "Labellum": np.array([0.75, 0.0, 0.81]),
"R_post_vertical": np.array([0.7, -0.2, 1.59]),
"L_post_vertical": np.array([0.7, 0.2, 1.59]),
# "R_ant_orb": np.array([0.88, -0.18, 1.49]),
# "L_ant_orb": np.array([0.88, 0.18, 1.49]),
"R_wing": np.array([0.08, -0.4, 1.43]),
"L_wing": np.array([0.08, 0.4, 1.43]),
"Neck": np.array([0.53, 0.0, 1.3]),
"Thorax_mid": np.array([0.08, 0.0, 1.43]),
"L_dorsal_hum": np.array([0.41, 0.37, 1.32]),
# "L_ant_notopleural": np.array([0.28, 0.39, 1.39]),
"R_dorsal_hum": np.array([0.41, -0.37, 1.32]),
# "R_ant_notopleural": np.array([0.30, -0.39, 1.39]),
}
