matrix-shooter-train / matrix /code /matrix_stats.py
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"""Full distribution statistics for a matrix_capture.py run (clip, frame and coverage level).
usage: matrix_stats.py DATA_DIR OUT_DIR
Reads every clip's meta.json, frames.jsonl and graybox cond frames. Writes
OUT_DIR/stats.json and per map: frames-<map>.png (player frames per 2 m cell),
sectors-<map>.png (yaw sectors seen per 10 m block, 0-8).
"In view" counts living characters whose direction from the camera lies inside
the horizontal field of view (80 degrees, 70 when aiming) and within 40 m; walls
are not traced, so it is an upper bound on what is actually visible.
"""
import collections
import json
import math
import sys
from pathlib import Path
import cv2
import numpy as np
SKY_TOL = 12
def hist(values, edges):
counts = [0] * (len(edges) - 1)
for v in values:
for i in range(len(edges) - 1):
if edges[i] <= v < edges[i + 1]:
counts[i] += 1
break
return counts
def share(n, d):
return round(n / d, 4) if d else None
def forward(q):
x, y, z, w = q
# Rotate (0, 0, -1) by quaternion (x, y, z, w).
return (-(2 * (x * z + w * y)), -(2 * (y * z - w * x)), -(1 - 2 * (x * x + y * y)))
def main():
data, out = Path(sys.argv[1]), Path(sys.argv[2])
out.mkdir(parents=True, exist_ok=True)
stats = {}
for map_id in ('paris', 'tsinghua'):
clips = sorted(c for c in (data / map_id).glob('clip_*') if (c / 'meta.json').exists())
metas = [json.loads((c / 'meta.json').read_text()) for c in clips]
c = collections.Counter
clip = dict(
clips=len(metas), frames_per_clip=metas[0]['frames'], fps=metas[0]['fps'],
teams=dict(sorted(c(f"{m['teams'][0]}v{m['teams'][1]}" for m in metas).items())),
characters=dict(sorted(c(m['teams'][0] + m['teams'][1] for m in metas).items())),
distance=dict(c(m['distance'] for m in metas if m['teams'][1])),
side=dict(c(m['side'] for m in metas if m['teams'][1])),
pitch_tier=dict(sorted(c(str(m['pitch_bias']) for m in metas).items())),
anchors=dict(c(m['anchor'] or 'block' for m in metas).most_common()),
start_yaw_sector=hist([(m['setup']['player']['yaw'] % (2 * math.pi)) / (math.pi / 4) for m in metas], list(range(9))),
teams_by_distance={d: dict(sorted(c(f"{m['teams'][0]}v{m['teams'][1]}" for m in metas if m['distance'] == d and m['teams'][1]).items()))
for d in ('close', 'mid', 'far')},
max_drift=max(m['max_drift'] for m in metas),
kills_per_clip=dict(sorted(c(m['kills'] for m in metas if m['teams'][1]).items())),
player_shots_per_clip=hist([m['shots'] for m in metas if m['teams'][1]], [0, 1, 10, 20, 30, 40, 1000]),
player_hit_rate=share(sum(m['hits'] for m in metas), sum(m['shots'] for m in metas)),
wall_s_mean=round(float(np.mean([m['wall_s'] for m in metas])), 1))
frames = collections.Counter()
yaw_frames, pitch_frames, cam_dist, near_enemy, in_view_enemy, in_view_any = [], [], [], [], [], []
cells, sectors, block_frames = collections.Counter(), collections.defaultdict(set), collections.Counter()
refills, respawns, displacement = 0, 0, []
sky_clip = []
top = collections.Counter()
for cdir, m in zip(clips, metas):
fight = m['teams'][1] > 0
prev, start, last = None, None, None
for line in (cdir / 'frames.jsonl').read_text().splitlines():
row = json.loads(line)
s, inp, cam = row['state'], row['input'], row['camera']
p = s['player']
frames['total'] += 1
frames['fight'] += fight
held = set(inp['down'])
frames['bullets'] += s['bullets'] > 0
frames['fight_bullets'] += fight and s['bullets'] > 0
frames['grenade_flying'] += s['grenades'] > 0
frames['reloading'] += s['reloading'] > 0
frames[f"weapon{s['weapon']}"] += 1
frames['avatar_hidden'] += not cam['v']
start = start or (p['x'], p['z'])
last = (p['x'], p['z'])
yaw_frames.append((s['yaw'] % (2 * math.pi)) / (math.pi / 4))
pitch_frames.append(s['pitch'])
if cam['s']:
cam_dist.append(cam['s']['distance'])
cells[(math.floor(p['x'] / 2), math.floor(p['z'] / 2))] += 1
block = (math.floor(p['x'] / 10), math.floor(p['z'] / 10))
block_frames[block] += 1
sectors[block].add(int((s['yaw'] % (2 * math.pi)) / (math.pi / 4)) % 8)
if prev:
if p['health'] > prev['player']['health'] + 50:
refills += 1
respawns += sum(1 for a, b in zip(s['actors'], prev['actors']) if a['alive'] and not b['alive'])
# Who is in front of the camera (three.js frame: z = -nav z).
fx, fy, fz = forward(cam['q'])
horiz = math.hypot(fx, fz) or 1
half = math.radians(cam['fov'] * 960 / 544 / 2) if False else math.radians(40)
cx, cz = cam['p'][0], cam['p'][2]
seen_enemy = seen_any = 0
dists = []
for a in s['actors']:
if not a['alive']:
continue
ax, az = a['x'], -a['z']
dx, dz = ax - cx, az - cz
d = math.hypot(dx, dz)
if a['team'] == 1:
dists.append(math.hypot(a['x'] - p['x'], a['z'] - p['z']))
if d < 40 and d > .3:
cos = (dx * fx + dz * fz) / (d * horiz)
if cos > math.cos(half):
seen_any += 1
seen_enemy += a['team'] == 1
if fight:
in_view_enemy.append(seen_enemy)
if dists:
near_enemy.append(min(dists))
in_view_any.append(seen_any)
for k in ('j', 'k', 'c', 'w', 'a', 's', 'd'):
frames[f'key_{k}'] += k in held or (prev is not None and k in prev['held'])
for k in ('shift', ' ', 'f', 'r', '1', '2', '3'):
frames[f'tap_{k}'] += k in inp['down']
prev = dict(row['state'], held=held | (prev['held'] - set(inp['up']) if prev else set()))
displacement.append(math.hypot(last[0] - start[0], last[1] - start[1]))
# Graybox ground check: share of the bottom third that is sky colour.
shares = []
for l in (0, 15, 30, 45, 59):
im = cv2.imread(str(cdir / 'cond' / f'{l:06d}.png'))
if im is None:
continue
if len(top) < 2000:
top.update(map(tuple, im[0, ::40].tolist()))
shares.append(im)
sky_clip.append(shares)
sky = np.array(top.most_common(1)[0][0])
sky_share = []
for images in sky_clip:
vals = [float((np.abs(im[2 * im.shape[0] // 3:].astype(int) - sky).sum(-1) < SKY_TOL).mean()) for im in images]
sky_share.append(float(np.mean(vals)) if vals else 0.0)
n = frames['total']
sector_counts = [len(v) for v in sectors.values()]
bf = sorted(block_frames.values())
frame = dict(
frames=n, fight_frames=frames['fight'],
yaw_sector_frame_share=[share(x, n) for x in hist(yaw_frames, list(range(9)))],
pitch_hist=dict(zip(['<-0.3', '-0.3~-0.1', '-0.1~0.05', '0.05~0.2', '>=0.2'],
[share(x, n) for x in hist(pitch_frames, [-9, -.3, -.1, .05, .2, 9])])),
camera_distance_hist=dict(zip(['<1.15 (avatar hidden)', '1.15~2.4', '2.4~4', '>=4'],
[share(x, len(cam_dist)) for x in hist(cam_dist, [0, 1.15, 2.4, 4, 99])])),
blocks_visited=len(sectors), block_frames_min_median_max=[bf[0], bf[len(bf) // 2], bf[-1]],
blocks_by_yaw_sectors=dict(sorted(collections.Counter(sector_counts).items())),
blocks_all_8_sectors=share(sum(x == 8 for x in sector_counts), len(sector_counts)),
cells_2m_visited=len(cells),
fight_frames_with_bullets=share(frames['fight_bullets'], frames['fight']),
fight_enemies_in_view=dict(zip(['0', '1', '2', '3', '4+'], [share(x, len(in_view_enemy)) for x in hist(in_view_enemy, [0, 1, 2, 3, 4, 99])])),
characters_in_view=dict(zip(['0', '1', '2', '3', '4+'], [share(x, len(in_view_any)) for x in hist(in_view_any, [0, 1, 2, 3, 4, 99])])),
nearest_enemy_m=dict(zip(['<5', '5~10', '10~20', '20~35', '>=35'], [share(x, len(near_enemy)) for x in hist(near_enemy, [0, 5, 10, 20, 35, 999])])),
fire_held=share(frames['key_j'], n), aim_held=share(frames['key_k'], n), crouch=share(frames['key_c'], n),
move_w=share(frames['key_w'], n), strafe=share(frames['key_a'] + frames['key_d'], n), back_s=share(frames['key_s'], n),
reloading=share(frames['reloading'], n), grenade_in_air=share(frames['grenade_flying'], n),
weapon_share={'pistol': share(frames['weapon0'], n), 'rifle': share(frames['weapon1'], n), 'shotgun': share(frames['weapon2'], n)},
avatar_hidden=share(frames['avatar_hidden'], n),
events_per_clip={'dash': round(frames['tap_shift'] / len(metas), 2), 'jump': round(frames['tap_ '] / len(metas), 2),
'grenade': round(frames['tap_f'] / len(metas), 2), 'reload_key': round(frames['tap_r'] / len(metas), 2),
'weapon_switch': round((frames['tap_1'] + frames['tap_2'] + frames['tap_3']) / len(metas), 2),
'bot_respawn': round(respawns / len(metas), 2), 'player_refill': round(refills / len(metas), 2)},
displacement_m=dict(zip(['<5', '5~15', '15~30', '>=30'], hist(displacement, [0, 5, 15, 30, 999]))),
graybox_sky_bottom_third=dict(mean=round(float(np.mean(sky_share)), 3),
clips=dict(zip(['<10%', '10~30%', '30~50%', '>=50%'], hist(sky_share, [0, .1, .3, .5, 1.01])))))
stats[map_id] = dict(clip=clip, frame=frame)
# Maps: frames per 2 m cell, and yaw sectors per 10 m block.
xs = [k[0] for k in cells]
zs = [k[1] for k in cells]
grid = np.zeros((max(zs) - min(zs) + 1, max(xs) - min(xs) + 1))
for (x, z), v in cells.items():
grid[z - min(zs), x - min(xs)] = v
norm = np.log1p(grid) / np.log1p(grid).max()
image = cv2.applyColorMap((norm * 255).astype(np.uint8), cv2.COLORMAP_VIRIDIS)
image[grid == 0] = (245, 245, 245)
cv2.imwrite(str(out / f'frames-{map_id}.png'), cv2.resize(image[::-1], None, fx=6, fy=6, interpolation=cv2.INTER_NEAREST))
bx = [k[0] for k in sectors]
bz = [k[1] for k in sectors]
sec = np.full((max(bz) - min(bz) + 1, max(bx) - min(bx) + 1), -1)
for (x, z), v in sectors.items():
sec[z - min(bz), x - min(bx)] = len(v)
image = cv2.applyColorMap((np.clip(sec, 0, 8) * 31).astype(np.uint8), cv2.COLORMAP_VIRIDIS)
image[sec < 0] = (245, 245, 245)
image = cv2.resize(image[::-1], None, fx=30, fy=30, interpolation=cv2.INTER_NEAREST)
for (x, z), v in sectors.items():
row = sec.shape[0] - 1 - (z - min(bz))
cv2.putText(image, str(len(v)), ((x - min(bx)) * 30 + 9, row * 30 + 21), 0, .5, (255, 255, 255) if len(v) < 6 else (0, 0, 0), 1)
cv2.imwrite(str(out / f'sectors-{map_id}.png'), image)
print(map_id, 'done', flush=True)
(out / 'stats.json').write_text(json.dumps(stats, indent=1, ensure_ascii=False))
print(json.dumps(stats, ensure_ascii=False))
if __name__ == '__main__':
main()