1 files changed, 118 insertions, 0 deletions
diff --git a/scripts/analyze-p45-char.py b/scripts/analyze-p45-char.py
new file mode 100644
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+++ b/scripts/analyze-p45-char.py
@@ -0,0 +1,118 @@
+#!/usr/bin/env python3
+"""P45 character-animation analysis.
+
+Reads the 4x `p45-char-{a,b,c}.png` crops (real LV_P45_SHOT screenshots, cropped
+around the avatar cell) + the shot log and writes docs/evidence/p45-analysis.txt:
+
+  1. character source cell + on-screen dest rect + facing/frame per frame;
+  2. pairwise inter-frame difference: Δchanged_px (max-channel > 16) and mean |Δ|;
+  3. the deterministic frame sequence table (frame index -> source cell) per facing;
+  4. a palette check that the original pixel-art character really is in each crop.
+
+Exit 0 when the differences are significant, 1 otherwise, 2 on usage error.
+"""
+
+import re
+import sys
+from pathlib import Path
+
+import numpy as np
+from PIL import Image
+
+CELL_W = 32
+CELL_H = 48
+VARIANT_STRAW_HAT = 4
+DIR_SOUTH = 1
+DIR_EAST = 3
+CHANGED_MIN = 400
+LINE_RE = re.compile(r"p45-shot=(\S+) tick=(\d+) facing=(\S+) moving=(\w+) dest=(\d+),(\d+),(\d+),(\d+) frame=(.+)")
+SKIN = np.array([234, 194, 152])
+ROBE = np.array([146, 96, 70])
+STRAW = np.array([216, 190, 120])
+
+
+def source_x(variant, direction, frame):
+    return ((variant * 4 + direction) * 6 + frame) * CELL_W
+
+
+def load(path):
+    return np.asarray(Image.open(path).convert("RGB"), dtype=int)
+
+
+def palette_hits(img):
+    def near(ref):
+        return (np.abs(img - ref).max(axis=2) <= 18).sum()
+    return int(near(SKIN) + near(ROBE) + near(STRAW))
+
+
+def main(argv):
+    if len(argv) != 4:
+        sys.stderr.write(__doc__)
+        return 2
+    record_dir = Path(argv[1])
+    log_text = Path(argv[2]).read_text(encoding="utf-8")
+    out_txt = Path(argv[3])
+    shots = []
+    for line in log_text.splitlines():
+        m = LINE_RE.search(line)
+        if m:
+            shots.append(
+                {
+                    "name": m.group(1),
+                    "tick": int(m.group(2)),
+                    "facing": m.group(3),
+                    "moving": m.group(4) == "true",
+                    "dest": tuple(int(m.group(i)) for i in range(5, 9)),
+                    "frame": m.group(9),
+                }
+            )
+    if len(shots) < 3:
+        sys.stderr.write("need three p45-shot frames\n")
+        return 1
+
+    images = {s["name"]: load(record_dir / f"{s['name']}.png") for s in shots}
+    lines = ["P45 character animation analysis (LV_P45_SHOT=1, 4x NEAREST crops)", ""]
+    failures = []
+    for s in shots:
+        x, y, w, h = s["dest"]
+        hits = palette_hits(images[s["name"]])
+        lines.append(f"[{s['name']}] facing={s['facing']} moving={s['moving']} frame={s['frame']} "
+                     f"dest=({x},{y},{w}x{h}) palette_hits={hits}")
+        if w != CELL_W or h != CELL_H:
+            failures.append(f"{s['name']} dest cell is not 32x48")
+        if hits < 50:
+            failures.append(f"{s['name']} character palette not found ({hits})")
+
+    lines.append("")
+    lines.append("inter-frame delta (4x crop, aligned on the same avatar cell):")
+    names = [s["name"] for s in shots]
+    for i in range(len(names)):
+        for j in range(i + 1, len(names)):
+            a, b = images[names[i]], images[names[j]]
+            d = np.abs(a - b)
+            changed = int((d.max(axis=2) > 16).sum())
+            mean = float(d.mean())
+            lines.append(f"   {names[i]} vs {names[j]}: changed_px(>16)={changed} mean_abs_diff={mean:.2f}")
+            if changed < CHANGED_MIN:
+                failures.append(f"{names[i]}-{names[j]} changed_px {changed} < {CHANGED_MIN}")
+
+    lines.append("")
+    lines.append("deterministic frame sequence (source cell x offsets, StrawHat variant):")
+    for label, direction in (("SouthFacing", DIR_SOUTH), ("EastFacing", DIR_EAST)):
+        offsets = [source_x(VARIANT_STRAW_HAT, direction, f) for f in range(6)]
+        lines.append(f"   {label}: walk1..4+idle1..2 -> {offsets}")
+
+    lines.append("")
+    lines.append("verdict = " + ("PASS" if not failures else "FAIL"))
+    out_txt.parent.mkdir(parents=True, exist_ok=True)
+    out_txt.write_text("\n".join(lines) + "\n", encoding="utf-8")
+    sys.stdout.write("\n".join(lines) + "\n")
+    if failures:
+        for f in failures:
+            sys.stderr.write(f"FAIL {f}\n")
+        return 1
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main(sys.argv))