from __future__ import annotations import sys import os from pathlib import Path import pandas as pd # ----------------------------------------------------------------------------- # 稳健路径配置 # ----------------------------------------------------------------------------- PROJECT_ROOT = Path("/root/autodl-tmp/SplatAtlas") # App C 候选输入 APP_C_SRC_FULL = PROJECT_ROOT / "outputs" / "phase2" / "task_2_3_appE_full.csv" APP_C_SRC_FILT = PROJECT_ROOT / "outputs" / "phase2" / "task_2_3_appE_filtered_P01_P04.csv" # App D 输入 APP_D_SRC = PROJECT_ROOT / "outputs" / "phase4" / "task_4_1_seed_variance_summary_reconstructed.csv" OUT_DIR = PROJECT_ROOT / "tex" OUT_DIR.mkdir(parents=True, exist_ok=True) APP_C_OUT = OUT_DIR / "appC_paired_rows.tex" APP_D_OUT = OUT_DIR / "appD_seed_summary_rows.tex" SEED_P95 = 0.384 # ----------------------------------------------------------------------------- # 映射字典 # ----------------------------------------------------------------------------- VARIANT_DISPLAY = { "pgsr": "PGSR", "erankgs": "eRankGS", "lightgaussian": "LightGaussian", "steepgs": "SteepGS", } METHOD_DISPLAY = { "vanilla_3dgs": r"\texttt{vanilla\_3dgs}", "analyticsplatting": r"\texttt{analyticsplatting}", "erankgs": r"\texttt{erankgs}", "ges": r"\texttt{ges}", "lightgaussian": r"\texttt{lightgaussian}", "minisplatting": r"\texttt{minisplatting}", "opti3dgs": r"\texttt{opti3dgs}", "pgsr": r"\texttt{pgsr}", "steepgs": r"\texttt{steepgs}", "3dgsmcmc": r"\texttt{3dgsmcmc}", } SCENE_DISPLAY = { "bicycle": "Bicycle", "bonsai": "Bonsai", "counter": "Counter", "flowers": "Flowers", "garden": "Garden", "kitchen": "Kitchen", "room": "Room", "stump": "Stump", "treehill": "Treehill", "auditorium": "Auditorium", "ballroom": "Ballroom", "barn": "Barn", "caterpillar": "Caterpillar", "courtroom": "Courtroom", "lighthouse": "Lighthouse", "museum": "Museum", "palace": "Palace", "playground": "Playground", "temple": "Temple", "train": "Train", "truck": "Truck", "drjohnson": "DrJohnson", "playroom": "Playroom", "chair": "Chair", "drums": "Drums", "ficus": "Ficus", "hotdog": "Hotdog", "lego": "Lego", "materials": "Materials", "mic": "Mic", "ship": "Ship", } def fmt_scene(key) -> str: k = str(key).strip().lower() name = SCENE_DISPLAY.get(k, str(key)) return rf"\textsc{{{name}}}" def fmt_signed(x, prec: int = 3) -> str: if pd.isna(x): return "---" return f"{x:+.{prec}f}" def fmt_unsigned(x, prec: int = 3) -> str: if pd.isna(x): return "---" return f"{x:.{prec}f}" # ----------------------------------------------------------------------------- # 生成逻辑 # ----------------------------------------------------------------------------- def generate_app_c() -> int: if APP_C_SRC_FULL.exists(): print(f"[App C] reading {APP_C_SRC_FULL}") df = pd.read_csv(APP_C_SRC_FULL) print(f"[App C] loaded {len(df)} rows total from FULL CSV") df = df[df["pair_id"].isin(["P01", "P02", "P03", "P04"])].copy() print(f"[App C] after P01-P04 filter: {len(df)} rows (expect 124)") elif APP_C_SRC_FILT.exists(): print(f"[App C] reading {APP_C_SRC_FILT}") df = pd.read_csv(APP_C_SRC_FILT) print(f"[App C] loaded {len(df)} rows total from FILTERED CSV (expect 124)") else: print("ERROR: missing App C source files. Searching for candidates:") os.system('find /root/autodl-tmp/SplatAtlas/outputs -name "task_2_3_appE*.csv"') sys.exit(1) df["_scene_disp"] = df["scene"].astype(str).str.lower().map(SCENE_DISPLAY).fillna(df["scene"]) df = df.sort_values(["pair_id", "_scene_disp"]).reset_index(drop=True) lines: list[str] = [] lines.append("% AUTOGENERATED by tools/generate_appendix_rows.py - DO NOT EDIT BY HAND.\n") last_pair = None n_data_rows = 0 for _, row in df.iterrows(): if last_pair is not None and row["pair_id"] != last_pair: lines.append(r"\midrule" + "\n") last_pair = row["pair_id"] variant_disp = VARIANT_DISPLAY.get(row["variant"], row["variant"]) scene_disp = fmt_scene(row["scene"]) cells = [ row["pair_id"], variant_disp, scene_disp, fmt_signed(row["delta_psnr_full"]), fmt_signed(row["delta_sh_net_effect"]), fmt_signed(row["delta_sh_corruption_rate"]), fmt_signed(row["delta_opacity_net_effect"]), fmt_signed(row["delta_opacity_pathology_rate"]), fmt_signed(row["delta_coverage_error_fraction"]), fmt_signed(row["delta_residual_error"]), ] lines.append(" & ".join(cells) + r" \\" + "\n") n_data_rows += 1 APP_C_OUT.write_text("".join(lines)) print(f"[App C] wrote {APP_C_OUT} ({n_data_rows} data rows)") return n_data_rows def generate_app_d() -> int: if not APP_D_SRC.exists(): print("ERROR: missing App D source files. Searching for candidates:") os.system('find /root/autodl-tmp/SplatAtlas/outputs -name "*seed_variance*summary*.csv"') sys.exit(1) print(f"[App D] reading {APP_D_SRC}") df = pd.read_csv(APP_D_SRC) print(f"[App D] loaded {len(df)} rows total") scene_col = "SceneNormalized" if "SceneNormalized" in df.columns else "Scene" method_col = "Method" out_lines: list[str] = [] out_lines.append("% AUTOGENERATED by tools/generate_appendix_rows.py - DO NOT EDIT BY HAND.\n") n_data_rows = 0 for scene_idx, scene in enumerate(["bonsai", "lego"]): if scene_idx > 0: out_lines.append(r"\midrule" + "\n") df_scene = df[df[scene_col].astype(str).str.lower() == scene].copy() df_scene = df_scene.sort_values(method_col) scene_disp = fmt_scene(scene) for _, row in df_scene.iterrows(): method_key = row[method_col] escaped_key = str(method_key).replace("_", r"\_") method_disp = METHOD_DISPLAY.get(method_key, rf"\texttt{{{escaped_key}}}") psnr_mean = row["PSNR_mean"] psnr_std = row["PSNR_std"] psnr_min = row["PSNR_min"] psnr_max = row["PSNR_max"] status = str(row.get("Status", "OK")).strip().upper() if status == "METHOD_FAILURE": flag = r"\textsc{Failure}" elif status == "OUTLIER" or (not pd.isna(psnr_std) and psnr_std > SEED_P95): flag = r"\textsc{Outlier}" else: flag = "---" cells = [ method_disp, scene_disp, fmt_unsigned(psnr_mean), fmt_unsigned(psnr_std), fmt_unsigned(psnr_min), fmt_unsigned(psnr_max), flag, ] out_lines.append(" & ".join(cells) + r" \\" + "\n") n_data_rows += 1 APP_D_OUT.write_text("".join(out_lines)) print(f"[App D] wrote {APP_D_OUT} ({n_data_rows} data rows)") return n_data_rows # ----------------------------------------------------------------------------- # Main & Sanity Checks # ----------------------------------------------------------------------------- if __name__ == "__main__": print("\n========================================================") print("1. Generating LaTeX row fragments") print("========================================================") c_rows = generate_app_c() d_rows = generate_app_d() print("\n========================================================") print("2. SANITY CHECKS") print("========================================================") print(f"[Check] App C output rows equals 124: {'PASS' if c_rows == 124 else 'FAIL'} ({c_rows})") print(f"[Check] App D output rows equals 20: {'PASS' if d_rows == 20 else 'FAIL'} ({d_rows})") # 验证 App D 中的特殊标记 with open(APP_D_OUT, "r") as f: d_content = f.read() ana_outlier = ("analyticsplatting" in d_content and "Outlier" in d_content) era_failure = ("erankgs" in d_content and "Failure" in d_content) print(f"[Check] analyticsplatting has \\textsc{{Outlier}}: {'PASS' if ana_outlier else 'FAIL'}") print(f"[Check] erankgs has \\textsc{{Failure}}: {'PASS' if era_failure else 'FAIL'}") print("\n========================================================") print("Generated:") print(f"- {APP_C_OUT}: {c_rows} rows") print(f"- {APP_D_OUT}: {d_rows} rows") print("========================================================")