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42d733e 039d570 42d733e 039d570 42d733e 039d570 | 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 | import pandas as pd
import plotly.graph_objects as go
# 1. Your REAL Dashboard Data (Immediate Onset + 16-Hour Deep Aging)
# Data extracted from corr_10min, corr_30min, corr_60min, corr_120min, and corr_16hs
data = {
'Time': ['10 Min', '30 Min', '60 Min', '120 Min', '16 Hrs'],
'Corr_TPS': [-0.631, -0.615, -0.583, -0.523, -0.427],
'Corr_Leakage': [0.520, 0.594, 0.580, 0.501, 0.451]
}
df = pd.DataFrame(data)
# 2. IEEE Formatting
layout_update = dict(
font_family="Times New Roman",
font_size=14,
paper_bgcolor='white',
plot_bgcolor='white',
margin=dict(l=60, r=20, t=50, b=50),
xaxis=dict(showgrid=True, gridwidth=1, gridcolor='LightGray', zerolinecolor='Black', title='Inference Duration'),
yaxis=dict(showgrid=True, gridwidth=1, gridcolor='LightGray', zerolinecolor='Black', title='Pearson Correlation (r)')
)
# 3. Create the Chart
fig_corr = go.Figure()
# Plot the two metrics
fig_corr.add_trace(go.Scatter(x=df['Time'], y=df['Corr_TPS'], mode='lines+markers', name='Temp vs TPS (Aging)', line=dict(color='blue', width=3), marker=dict(size=10)))
fig_corr.add_trace(go.Scatter(x=df['Time'], y=df['Corr_Leakage'], mode='lines+markers', name='Temp vs Leakage', line=dict(color='red', width=3), marker=dict(size=10, symbol='square')))
fig_corr.update_layout(title="Immediate Onset of Thermal Degradation", **layout_update)
# 4. Export as PDF for LaTeX
fig_corr.write_image("export_temporal_correlations.pdf", scale=3)
print("✅ Success! export_temporal_correlations.pdf generated with 16-hour deep aging data.")
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