| |
| """Render the cross-domain manuscript assets from audited saved-response metrics.""" |
| import argparse |
| from decimal import Decimal, ROUND_HALF_UP |
| import json |
| from pathlib import Path |
|
|
| import matplotlib |
| matplotlib.use("Agg") |
| import matplotlib.pyplot as plt |
| import numpy as np |
|
|
| from analyze_crossdomain_paper import MODELS, STATES |
|
|
| NAMES = {"qwen38-flash-next": "Qwen 3.8 Flash Next", "gemma4-31b-it": "Gemma 4 31B", |
| "qwen": "Qwen 3.8 27B", "gemma4-26b-a4b-it": "Gemma 4 26B A4B", |
| "glm": "GLM 5.3 Flash", "molmo2-8b": "Molmo2-8B"} |
|
|
|
|
| def percentage(n, d, places=2): |
| return str((Decimal(int(n)) * 100 / Decimal(int(d))).quantize(Decimal(10) ** -places, rounding=ROUND_HALF_UP)) |
|
|
|
|
| def pct(value, places=2): |
| |
| return str(Decimal(str(round(value * 100, 9))).quantize(Decimal(10) ** -places, rounding=ROUND_HALF_UP)) |
|
|
|
|
| def table(path, header, rows, columns): |
| path.write_text("\n".join([r"\begin{tabular}{@{}" + columns + r"@{}}", r"\toprule", |
| header + r" \\", r"\midrule", *rows, |
| r"\bottomrule", r"\end{tabular}"]) + "\n") |
|
|
|
|
| def model_table(data, path): |
| """Report complete task success before its decision diagnostics.""" |
| rows = [] |
| for model in MODELS: |
| cells = [] |
| for source in STATES: |
| domain = data["domains"][source] |
| counts = domain["models"][model]["counts"] |
| cells.extend([ |
| percentage(counts["joint_groups_correct"], 1000, 1), |
| percentage(counts["groups_correct"], 1000, 1), |
| percentage(counts["failures"], domain["views"]), |
| ]) |
| rows.append(NAMES[model] + " & " + " & ".join(cells) + r" \\") |
| rows.extend([ |
| r"\midrule", |
| r"Always answerable & 0.0 & 0.0 & 40.00 & 0.0 & 0.0 & 25.00 & 0.0 & 0.0 & 33.33 \\", |
| r"Always unanswerable & 0.0 & 0.0 & 60.00 & 0.0 & 0.0 & 75.00 & 0.0 & 0.0 & 66.67 \\", |
| ]) |
| header = ( |
| r"& \multicolumn{3}{c}{PlotQA} & \multicolumn{3}{c}{CLEVR} & \multicolumn{3}{c}{GQA} \\ " |
| r"\cmidrule(lr){2-4}\cmidrule(lr){5-7}\cmidrule(l){8-10} " |
| r"System & $J_5\uparrow$ & $B_5\uparrow$ & $E\downarrow$ " |
| r"& $J_4\uparrow$ & $B_4\uparrow$ & $E\downarrow$ " |
| r"& $J_3\uparrow$ & $B_3\uparrow$ & $E\downarrow$" |
| ) |
| table(path, header, rows, "lrrrrrrrrr") |
|
|
|
|
| def main(): |
| parser = argparse.ArgumentParser(description=__doc__) |
| parser.add_argument("--analysis", type=Path, required=True) |
| parser.add_argument("--output", type=Path, required=True) |
| args = parser.parse_args() |
| data = json.loads(args.analysis.read_text()) |
| out = args.output |
| out.mkdir(parents=True, exist_ok=True) |
| domains = data["domains"] |
| model_table(data, out / "model_table.tex") |
|
|
| rows = [] |
| for model in MODELS: |
| cells = [] |
| for source in STATES: |
| m = domains[source]["models"][model]["metrics"] |
| cells.extend([pct(m["balanced_failure"]), pct(m["common_state_failure"])]) |
| rows.append(NAMES[model] + " & " + " & ".join(cells) + r" \\") |
| rows += [r"\midrule", r"Always answerable & 50.00 & 33.33 & 50.00 & 33.33 & 50.00 & 33.33 \\"] |
| table(out / "balanced_table.tex", r"System & PlotQA Bal. & $E_{FSM}$ & CLEVR Bal. & $E_{FSM}$ & GQA Bal. & $E_{FSM}$", rows, "lrrrrrr") |
|
|
| rows = [] |
| for model in MODELS: |
| cells = [] |
| for source in STATES: |
| c = domains[source]["models"][model]["counts"] |
| cells.extend([percentage(c["strict_answers_correct"], c["answerable_views"]), |
| percentage(c["joint_groups_correct"], 1000, 1)]) |
| rows.append(NAMES[model] + " & " + " & ".join(cells) + r" \\") |
| table(out / "answer_table.tex", r"System & PlotQA $A$ & $J_5$ & CLEVR $A$ & $J_4$ & GQA $A$ & $J_3$", rows, "lrrrrrr") |
|
|
| rows = [] |
| for model in MODELS: |
| cells = [] |
| for stratum in ["location", "other"]: |
| c = domains["gqa"]["location_sensitivity"]["models"][model][stratum] |
| cells.extend([percentage(c["failures"], c["views"]), percentage(c["groups_correct"], c["groups"], 1), |
| percentage(c["missing_failures"], c["groups"])]) |
| rows.append(NAMES[model] + " & " + " & ".join(cells) + r" \\") |
| table(out / "location_table.tex", r"System & Loc. Fail & $B_3$ & $M$ Fail & Other Fail & $B_3$ & $M$ Fail", rows, "lrrrrrr") |
|
|
| rows = [] |
| for source in STATES: |
| for model in MODELS: |
| d = domains[source]["models"][model] |
| c = d["counts"] |
| lo, hi = d["intervals_95"]["failure"] |
| rows.append(source.upper() + " / " + NAMES[model] + " & " + str(c["valid_decision_errors"]) + "/" + str(c["valid"]) + |
| " & " + str(c["invalid"]) + " & " + pct(lo) + "--" + pct(hi) + r" \\") |
| table(out / "denominator_table.tex", r"Domain / system & $W/V$ & Invalid & Failure 95\% interval", rows, "lrrr") |
|
|
| plt.rcParams.update({"font.family": "DejaVu Sans", "font.size": 12, "pdf.fonttype": 42}) |
| fig, axes = plt.subplots(1, 3, figsize=(8.3, 3.7), gridspec_kw={"width_ratios": [5, 4, 3]}) |
| for ax, (source, states) in zip(axes, STATES.items()): |
| values = np.array([[domains[source]["models"][m]["states"][s]["failures"] / 10 for s in states] for m in MODELS]) |
| ax.imshow(values, cmap="YlOrRd", vmin=0, vmax=80, aspect="auto") |
| for i in range(len(MODELS)): |
| for j in range(len(states)): |
| ax.text(j, i, f"{values[i, j]:.1f}", ha="center", va="center", |
| color="white" if values[i, j] > 48 else "#222222", fontsize=11) |
| ax.set_title({"plotqa": "A PlotQA", "clevr": "B CLEVR", "gqa": "C GQA"}[source], loc="left", fontsize=12) |
| ax.set_xticks(range(len(states)), [{"FULL": "F", "A_SAME": "S", "A_CHANGED": "C", "U_MISSING": "M", "U_INVALID": "I"}[s] for s in states]) |
| ax.set_yticks(range(6), [NAMES[m] for m in MODELS] if source == "plotqa" else []) |
| ax.tick_params(length=0) |
| fig.tight_layout(w_pad=.6, rect=(0, .06, 1, 1)) |
| fig.text(.60, .025, "Failure (%); 1,000 views per cell", ha="center", fontsize=12) |
| for ext in ["pdf", "png"]: |
| fig.savefig(out / ("state_failures." + ext), dpi=220, bbox_inches="tight") |
| plt.close(fig) |
| summary = {"status": "passed", "model_domain_cells": 18, |
| "rounded_percentages": "decimal half-up from integer counts; percentages are not truncated", |
| "tables": ["model_table.tex", "balanced_table.tex", "answer_table.tex", "denominator_table.tex", "location_table.tex"], |
| "figure": "state_failures.pdf", "sha_validation_performed": False} |
| (out / "asset-validation.json").write_text(json.dumps(summary, indent=2) + "\n") |
| print(json.dumps(summary)) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
