tests/example_html_output.py - common_agents_notes - IvanMysin/Topics

tests/example_html_output.py
116 строк4 KB
ivan
Work on autoreview by theses
08 янв 2026, 20:58
08 янв 2026, 20:583ca3f82
#!/usr/bin/env python3
"""
Example script demonstrating HTML report generation.

This script shows how to use the new HTML output feature.
"""

import sys
sys.path.append('../src')

import pandas as pd
import numpy as np
from report_generator import ReportGenerator

# Create sample data for demonstration
sample_data = {
    'id': [1, 2, 3, 4, 5],
    'title': [
        'Memory encoding in hippocampus',
        'Neural activity patterns',
        'Spatial navigation study',
        'Gene expression analysis',
        'Working memory mechanisms'
    ],
    'doi': [
        '10.1016/j.neuron.2023.01.001',
        '10.1038/s41586-023-01234-5',
        '10.1093/brain/awz001',
        '10.1002/dneu.2023.05678',
        '19199423'
    ],
    'abstract': [
        'This study investigates memory encoding processes in the hippocampal formation...',
        'We analyzed neural activity patterns during spatial tasks...',
        'Navigation strategies were examined using virtual reality...',
        'Gene expression patterns in hippocampal subregions were studied...',
        'Working memory mechanisms were explored through fMRI...'
    ],
    'date': ['2023-01-15', '2023-02-20', '2023-03-10', '2023-04-05', '2023-05-12'],
    'cluster': [0, 0, 1, 2, 3],
    'similarity': [0.95, 0.88, 0.92, 0.85, 0.91],
    'ai_summary': [
        'Study examines hippocampal memory encoding...',
        'Analysis reveals neural activity patterns...',
        'Explores spatial navigation in VR...',
        'Investigates gene expression in hippocampus...',
        'Explores working memory using fMRI...'
    ]
}

sample_topic_words = {
    0: [('memory', 15), ('encoding', 12), ('hippocampus', 10)],
    1: [('neural', 8), ('activity', 7), ('patterns', 6)],
    2: [('spatial', 10), ('navigation', 9), ('vr', 5)],
    3: [('gene', 8), ('expression', 7), ('analysis', 6)],
}

sample_descriptions = {
    0: 'Cluster 0 focuses on memory encoding processes in the hippocampus',
    1: 'Cluster 1 contains studies on neural activity patterns',
    2: 'Cluster 2 explores spatial navigation research',
    3: 'Cluster 3 includes gene expression analyses',
}

# Create DataFrame
df = pd.DataFrame(sample_data)

# Initialize report generator
print("📊 Initializing ReportGenerator...")
report_gen = ReportGenerator()

print("\n✅ Generating reports in different formats:\n")

# Generate HTML reports
print("1️⃣ Generating HTML reports...")
report_gen.generate_all_reports(
    df=df,
    topic_words=sample_topic_words,
    similarities={},
    method='example',
    generate_descriptions=False,
    cluster_descriptions=sample_descriptions,
    output_format='html'
)

# Generate Markdown reports
print("\n2️⃣ Generating Markdown reports...")
report_gen.generate_all_reports(
    df=df,
    topic_words=sample_topic_words,
    similarities={},
    method='example',
    generate_descriptions=False,
    cluster_descriptions=sample_descriptions,
    output_format='markdown'
)

# Generate both formats
print("\n3️⃣ Generating both HTML and Markdown reports...")
report_gen.generate_all_reports(
    df=df,
    topic_words=sample_topic_words,
    similarities={},
    method='example',
    generate_descriptions=False,
    cluster_descriptions=sample_descriptions,
    output_format='both'
)

print("\n✅ Example completed! Check the results/ directory for generated reports.")
print("\nGenerated files:")
print("  - results/00_summary.html (HTML summary)")
print("  - results/00_summary.md (Markdown summary)")
print("  - results/cluster_00.html (HTML cluster 0)")
print("  - results/cluster_00.md (Markdown cluster 0)")
print("  - And more cluster files...")