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d07f416 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 | #!/usr/bin/env python3
from __future__ import annotations
from dataclasses import dataclass
from pathlib import Path
import matplotlib.pyplot as plt
import pandas as pd
ROOT = Path(__file__).resolve().parents[1]
PLOTS_DIR = ROOT / "artifacts" / "plots"
@dataclass(frozen=True)
class SaveSpec:
stem: str
title: str
ylabel: str
ylim: tuple[float, float] | None = (0.0, 1.05)
METHOD_ORDER = ["MChatbot (ours)", "GPT-5.3", "Grok-4", "Claude-Haiku"]
OURS_COLOR = "#1f77b4"
BASELINE_COLOR = "#9aa0a6"
def _style_axes(ax: plt.Axes, title: str, ylabel: str, ylim: tuple[float, float] | None) -> None:
ax.set_title(title)
ax.set_ylabel(ylabel)
if ylim is not None:
ax.set_ylim(*ylim)
ax.grid(axis="y", alpha=0.25)
ax.set_axisbelow(True)
def _bar_with_labels(ax: plt.Axes, x: list[str], y: list[float], colors: list[str]) -> None:
bars = ax.bar(x, y, color=colors)
for b, v in zip(bars, y):
ax.text(
b.get_x() + b.get_width() / 2,
b.get_height() + 0.015,
f"{v:.3f}".rstrip("0").rstrip("."),
ha="center",
va="bottom",
fontsize=9,
)
def _save(fig: plt.Figure, stem: str) -> None:
PLOTS_DIR.mkdir(parents=True, exist_ok=True)
fig.tight_layout()
fig.savefig(PLOTS_DIR / f"{stem}.png", dpi=300, bbox_inches="tight")
fig.savefig(PLOTS_DIR / f"{stem}.pdf", bbox_inches="tight")
plt.close(fig)
def plot_qna_accuracy() -> None:
df = pd.DataFrame(
{
"Method": METHOD_ORDER,
"QnA Accuracy": [0.875, 0.750, 0.775, 0.800],
}
)
colors = [OURS_COLOR] + [BASELINE_COLOR] * (len(df) - 1)
fig, ax = plt.subplots(figsize=(6.6, 3.6))
_bar_with_labels(ax, df["Method"].tolist(), df["QnA Accuracy"].tolist(), colors)
_style_axes(ax, "EA: QnA Accuracy (40 queries)", "Accuracy", (0.0, 1.0))
ax.tick_params(axis="x", rotation=10)
_save(fig, "ea_qna_accuracy")
def plot_model_building() -> None:
df = pd.DataFrame(
{
"Method": METHOD_ORDER,
"MCR": [1.00, 0.30, 0.90, 1.00],
"MAC": [0.82, 0.12, 0.56, 0.68],
}
)
fig, axes = plt.subplots(1, 2, figsize=(9.2, 3.6), sharey=True)
for ax, metric, title in zip(
axes,
["MCR", "MAC"],
["EB: Model Compilation Rate (MCR)", "EB: Model Answer Correctness (MAC)"],
):
colors = [OURS_COLOR] + [BASELINE_COLOR] * (len(df) - 1)
_bar_with_labels(ax, df["Method"].tolist(), df[metric].tolist(), colors)
_style_axes(ax, title, metric, (0.0, 1.0))
ax.tick_params(axis="x", rotation=15)
_save(fig, "eb_model_building_mcr_mac")
def plot_query_translation() -> None:
df = pd.DataFrame(
{
"Method": METHOD_ORDER,
"QCR": [1.000, 0.075, 0.075, 0.525],
"QAR": [0.725, 0.075, 0.075, 0.450],
"EM": [0.450, 0.050, 0.025, 0.425],
"Token F1": [0.743, 0.641, 0.586, 0.725],
}
)
fig, axes = plt.subplots(2, 2, figsize=(10.2, 6.6), sharex=True)
metrics = [("QCR", "QCR"), ("QAR", "QAR"), ("EM", "Exact Match"), ("Token F1", "Token F1")]
for ax, (col, ylabel) in zip(axes.flatten(), metrics):
colors = [OURS_COLOR] + [BASELINE_COLOR] * (len(df) - 1)
_bar_with_labels(ax, df["Method"].tolist(), df[col].tolist(), colors)
_style_axes(ax, f"EB.2: {col}", ylabel, (0.0, 1.0))
ax.tick_params(axis="x", rotation=15)
_save(fig, "eb2_query_translation_qcr_qar_em_f1")
def plot_ablation() -> None:
df = pd.DataFrame(
{
"Configuration": ["Full MChatbot", "No IR (direct generation)", "No repair loop"],
"MCR": [1.00, 0.60, 0.80],
"MAC": [0.84, 0.32, 0.58],
}
)
fig, axes = plt.subplots(1, 2, figsize=(9.2, 3.6), sharey=True)
for ax, metric in zip(axes, ["MCR", "MAC"]):
colors = [OURS_COLOR, BASELINE_COLOR, BASELINE_COLOR]
_bar_with_labels(ax, df["Configuration"].tolist(), df[metric].tolist(), colors)
_style_axes(ax, f"RQ3 Ablation: {metric}", metric, (0.0, 1.0))
ax.tick_params(axis="x", rotation=10)
_save(fig, "rq3_ablation_mcr_mac")
def main() -> int:
plt.rcParams.update(
{
"font.size": 11,
"axes.titlesize": 12,
"axes.labelsize": 11,
"figure.dpi": 120,
}
)
plot_qna_accuracy()
plot_model_building()
plot_query_translation()
plot_ablation()
print(f"Wrote plots to: {PLOTS_DIR.resolve()}")
return 0
if __name__ == "__main__":
raise SystemExit(main())
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