File size: 4,064 Bytes
05f9189 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 | """Export the ultra-simple Electric Slide count map and 50 Hz joint references."""
from __future__ import annotations
import argparse
import csv
import json
import math
from pathlib import Path
import sys
import numpy as np
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
from choreography import BEAT_SECONDS, CONTROL_HZ, STAND_POSE
from simple_choreography import (
SHOW_SECONDS,
SIMPLE_COUNTS,
command_vector,
count_phase,
joint_bias,
)
JOINT_ORDER = (
"left_hip_yaw", "left_hip_roll", "left_hip_pitch", "left_knee",
"left_ankle", "neck_pitch", "head_pitch", "head_yaw", "head_roll",
"right_hip_yaw", "right_hip_roll", "right_hip_pitch", "right_knee",
"right_ankle",
)
def main() -> None:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("output_dir", type=Path)
args = parser.parse_args()
output_dir = args.output_dir.resolve()
output_dir.mkdir(parents=True, exist_ok=True)
jsonl_path = output_dir / "simple_joint_targets_50hz.jsonl"
sample_count = int(math.ceil(SHOW_SECONDS * CONTROL_HZ))
with jsonl_path.open("w", encoding="utf-8") as stream:
for sample in range(sample_count):
time_seconds = sample / CONTROL_HZ
wall, count, phase = count_phase(time_seconds)
spec = SIMPLE_COUNTS[count]
bias = joint_bias(time_seconds).astype(float)
nominal = np.asarray(STAND_POSE, dtype=float) + bias
row = {
"sample": sample,
"time_seconds": time_seconds,
"beat": time_seconds / BEAT_SECONDS,
"wall": wall + 1,
"count": count + 1,
"phase": phase,
"label": spec.label,
"swing_foot": spec.swing,
"placement": spec.placement,
"weight_transfer": spec.weight_transfer,
"command_13d": command_vector(time_seconds).astype(float).tolist(),
"additive_joint_bias_14d": bias.tolist(),
"nominal_joint_target_14d": nominal.tolist(),
}
stream.write(json.dumps(row, separators=(",", ":")) + "\n")
csv_path = output_dir / "simple_16_count_choreography.csv"
with csv_path.open("w", newline="", encoding="utf-8") as stream:
writer = csv.DictWriter(
stream,
fieldnames=("count", "label", "swing_foot", "placement", "weight_transfer"),
)
writer.writeheader()
for index, spec in enumerate(SIMPLE_COUNTS, start=1):
writer.writerow(
{
"count": index,
"label": spec.label,
"swing_foot": spec.swing,
"placement": spec.placement,
"weight_transfer": spec.weight_transfer,
}
)
summary = {
"version": "simple-v3",
"control_hz": CONTROL_HZ,
"bpm": 60.0 / BEAT_SECONDS,
"walls": 4,
"counts_per_wall": len(SIMPLE_COUNTS),
"duration_seconds": SHOW_SECONDS,
"sample_count": sample_count,
"joint_order": JOINT_ORDER,
"stand_pose_14d": STAND_POSE,
"command_order_13d": (
"vx", "vy", "yaw_rate", "neck_pitch", "head_pitch", "head_yaw",
"head_roll", "body_x", "body_y", "body_z", "body_roll",
"body_pitch", "body_yaw",
),
"important": (
"nominal_joint_target_14d is STAND_POSE plus the v3 choreography bias. "
"At runtime the official balance-policy action is added before joint-limit "
"clipping. The beak-snap label is implemented through neck/head pitch because "
"the official 14-actuator model has no jaw joint. The free root is never written."
),
}
(output_dir / "simple_reference_summary.json").write_text(
json.dumps(summary, indent=2), encoding="utf-8"
)
print(jsonl_path)
print(csv_path)
if __name__ == "__main__":
main()
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