metadata.json

{
  "description": "HRIR spatial map for binaural audio rendering",
  "model": "rigid sphere + ear canal + pinna + torso + air absorption",
  "grid": {
    "azimuth_step_deg": 5.0,
    "azimuth_range": [
      0.0,
      355.0
    ],
    "n_azimuths": 72,
    "distances_m": [
      0.10000000149011612,
      0.10999999940395355,
      0.11999999731779099,
      0.12999999523162842,
      0.14000000059604645,
      0.15000000596046448,
      0.1599999964237213,
      0.17000000178813934,
      0.18000000715255737,
      0.1899999976158142,
      0.20000000298023224,
      0.2199999988079071,
      0.25,
      0.2800000011920929,
      0.30000001192092896,
      0.33000001311302185,
      0.36000001430511475,
      0.4000000059604645,
      0.44999998807907104,
      0.5,
      0.6000000238418579,
      0.75,
      1.0,
      1.25,
      1.5,
      2.0
    ],
    "n_distances": 26,
    "elevation_deg": 0.0
  },
  "audio": {
    "sample_rate": 48000,
    "ir_length_samples": 512,
    "ir_length_ms": 10.67,
    "dtype": "float32"
  },
  "shape": {
    "hrir_L": [
      72,
      26,
      512
    ],
    "hrir_R": [
      72,
      26,
      512
    ]
  },
  "total_points": 1872,
  "npz_size_bytes": 7147591,
  "head_params": {
    "head_radius_m": 0.0875,
    "ear_canal_length_m": 0.025
  },
  "usage": "data = np.load('hrir_spatial_map.npz'); hrir_L = data['hrir_L'][az_idx, dist_idx]; output = np.convolve(mono, hrir_L)"
}