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Visualization Overview

ComProScanner provides comprehensive visualization tools for both extracted data and evaluation results.

Two Visualization Modules

1. Data Visualizer

Visualize extracted composition-property data:

  • Material family distributions
  • Precursor analysis
  • Characterization techniques
  • Knowledge graphs

Learn more →

2. Evaluation Visualizer

Visualize evaluation metrics for both single models and multiple model comparisons:

  • Bar charts
  • Radar charts
  • Heatmaps
  • Violin plots
  • Histograms

Learn more →

Quick Examples

Data Visualization

from comproscanner import data_visualizer

# Pie chart
fig = data_visualizer.plot_family_pie_chart(
    data_sources=["results.json"],
    output_file="families.png"
)

# Knowledge graph
data_visualizer.create_knowledge_graph(
    result_file="results.json"
)

Evaluation Visualization

from comproscanner import eval_visualizer

# Bar chart for single model
fig = eval_visualizer.plot_single_bar_chart(
    result_file="evaluation.json",
    output_file="metrics.png"
)

# Radar chart comparison for multiple models
fig = eval_visualizer.plot_multiple_radar_charts(
    result_sources=["eval1.json", "eval2.json"],
    model_names=["Model A", "Model B"],
    output_file="comparison.png"
)

Supported Input Sources

python plot_function(data_sources=["results.json"])

python plot_function(data_sources=["r1.json", "r2.json", "r3.json"])

python plot_function(folder_path="results_folder/")

python plot_function(data_sources=[data_dict1, data_dict2])

Next Steps