Datasets:
File size: 3,257 Bytes
9ce14ad | 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 | """Validate synthetic asbestos exposure & mesothelioma dataset."""
from __future__ import annotations
from pathlib import Path
import matplotlib.pyplot as plt
import pandas as pd
SCENARIO_FILES = {
"former_mining_community": "asbestos_mining_community.csv",
"urban_construction": "asbestos_urban_construction.csv",
"rural_asbestos_roofing": "asbestos_rural_roofing.csv",
}
COLORS = {"former_mining_community": "#e6550d", "urban_construction": "#756bb1", "rural_asbestos_roofing": "#31a354"}
def load_data() -> pd.DataFrame:
frames = []
for scenario, filename in SCENARIO_FILES.items():
df = pd.read_csv(Path("data") / filename)
frames.append(df)
return pd.concat(frames, ignore_index=True)
def plot_validation(df: pd.DataFrame, output_path: Path) -> None:
fig, axes = plt.subplots(4, 2, figsize=(14, 16))
axes = axes.flatten()
for s in SCENARIO_FILES:
subset = df[df["scenario"] == s]
axes[0].hist(subset["cumulative_exposure"], bins=40, alpha=0.5, color=COLORS[s], label=s, range=(0, 100))
axes[0].set_title("Cumulative Exposure Distribution (f/mL·yr)")
axes[0].legend(fontsize=7)
disease_cols = ["mesothelioma", "asbestosis", "lung_cancer", "pleural_plaques"]
dis = df.groupby("scenario")[disease_cols].mean() * 100
dis.plot(kind="bar", ax=axes[1])
axes[1].set_title("Asbestos-Related Disease (%)")
axes[1].legend(fontsize=6)
ft = df.groupby(["scenario", "fibre_type"]).size().groupby(level=0).apply(lambda s: s / s.sum())
ft.unstack().plot(kind="bar", stacked=True, ax=axes[2])
axes[2].set_title("Fibre Type Distribution")
axes[2].legend(fontsize=7)
exp = df.groupby(["scenario", "exposure_type"]).size().groupby(level=0).apply(lambda s: s / s.sum())
exp.unstack().plot(kind="bar", stacked=True, ax=axes[3])
axes[3].set_title("Exposure Type Distribution")
axes[3].legend(fontsize=5)
for s in SCENARIO_FILES:
subset = df[df["scenario"] == s]
axes[4].scatter(subset["cumulative_exposure"], subset["any_asbestos_disease"],
s=4, alpha=0.05, color=COLORS[s], label=s)
axes[4].set_title("Cumulative Exposure vs Disease")
axes[4].legend(fontsize=7)
resp_cols = ["dyspnoea", "cough_chronic", "reduced_fvc"]
resp = df.groupby("scenario")[resp_cols].mean() * 100
resp.plot(kind="bar", ax=axes[5])
axes[5].set_title("Respiratory Symptoms (%)")
axes[5].legend(fontsize=7)
reg_cols = ["ban_in_place", "medical_surveillance", "ppe_use", "chest_xray_done"]
reg = df.groupby("scenario")[reg_cols].mean() * 100
reg.plot(kind="bar", ax=axes[6])
axes[6].set_title("Regulation & Surveillance (%)")
axes[6].legend(fontsize=6)
mort_cols = ["died", "hiv_positive", "compensation_claimed"]
mort = df.groupby("scenario")[mort_cols].mean() * 100
mort.plot(kind="bar", ax=axes[7])
axes[7].set_title("Mortality, HIV & Compensation (%)")
axes[7].legend(fontsize=7)
plt.tight_layout()
fig.savefig(output_path, dpi=200)
plt.close(fig)
def main() -> None:
df = load_data()
plot_validation(df, Path("validation_report.png"))
print("Saved validation_report.png")
if __name__ == "__main__":
main()
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