Example 1: Production Analysis Report (+2)
Example 1: Production Analysis Report
# Configuration
report_config = {
'title': 'Monthly Production Analysis',
'project': 'Field A Development',
'summary': '''
<div class="summary-grid">
<div class="metric-card">
<div class="metric-value">125,000</div>
<div class="metric-label">Total Oil (bbl)</div>
</div>
<div class="metric-card">
<div class="metric-value">98.5%</div>
<div class="metric-label">Uptime</div>
</div>
</div>
''',
'charts': [
{'type': 'line', 'x': 'date', 'y': 'production', 'title': 'Daily Production'},
{'type': 'bar', 'x': 'well', 'y': 'cumulative', 'title': 'Well Performance'}
]
}
# Generate
generate_report(
data_path='../data/processed/production.csv',
output_path='../reports/production_report.html',
**report_config
)
Example 2: Structural Analysis Report
report_config = {
'title': 'Structural Analysis Results',
'methodology': '<p>Analysis performed per DNV-RP-C201 using finite element method.</p>',
'charts': [
{'type': 'heatmap', 'x': 'x_coord', 'y': 'y_coord', 'values': 'stress', 'title': 'Stress Distribution'},
{'type': 'scatter', 'x': 'load', 'y': 'displacement', 'title': 'Load-Displacement Curve'}
],
'conclusions': '<p>All structural elements satisfy design criteria with safety factor > 1.5</p>'
}
Example 3: Multi-Panel Dashboard
from plotly.subplots import make_subplots
def create_dashboard(df: pd.DataFrame, output_path: str):
"""Create multi-panel analysis dashboard."""
fig = make_subplots(
rows=2, cols=2,
subplot_titles=('Trend', 'Distribution', 'Comparison', 'Correlation')
)
# Add traces to each panel
fig.add_trace(go.Scatter(x=df['date'], y=df['value'], mode='lines'), row=1, col=1)
fig.add_trace(go.Histogram(x=df['value']), row=1, col=2)
fig.add_trace(go.Bar(x=df['category'], y=df['count']), row=2, col=1)
fig.add_trace(go.Scatter(x=df['x'], y=df['y'], mode='markers'), row=2, col=2)
fig.update_layout(height=800, title_text="Analysis Dashboard")
fig.write_html(output_path)
return output_path
vamseeachanta