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GNN advanced visualization and interactive plots. Use when creating D2 diagrams, dashboards, interactive network visualizations, timeline charts, heatmaps, or data extraction for custom visualizations.
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基于 SOC 职业分类
Generalized Notation Notation (GNN) processing pipeline for Active Inference generative models. Use when working with GNN files, running the 25-step pipeline, parsing model specifications, generating simulations, or producing visualizations and reports from GNN model definitions.
GNN command-line interface dispatch and health checks. Use when invoking the `gnn` CLI, validating subcommand availability, or checking command-line access to pipeline modules.
GNN LLM-enhanced analysis and model interpretation. Use when generating natural language descriptions of GNN models, getting AI-assisted model explanations, or performing LLM-powered analysis of Active Inference specifications.
GNN Language Server Protocol integration. Use when starting editor diagnostics, checking hover behavior, or validating LSP support for GNN files.
GNN Model Context Protocol processing and tool registration. Use when registering GNN operations as MCP tools, building MCP server configurations, or integrating GNN capabilities with LLM tool-use workflows.
GNN pipeline orchestration and configuration management. Use when configuring pipeline execution, setting step inclusion/exclusion, managing pipeline state, or customizing the 25-step execution flow.
| name | gnn-advanced-viz |
| description | GNN advanced visualization and interactive plots. Use when creating D2 diagrams, dashboards, interactive network visualizations, timeline charts, heatmaps, or data extraction for custom visualizations. |
Generates advanced visualizations including D2 diagrams, interactive dashboards, network and timeline visualizations, heatmaps, and data extraction for GNN models.
# Run advanced visualization
python src/9_advanced_viz.py --target-dir input/gnn_files --output-dir output --verbose
# As part of pipeline
python src/main.py --only-steps 9 --verbose
from advanced_visualization import (
AdvancedVisualizer,
create_visualization_from_data, create_network_visualization,
create_timeline_visualization, create_heatmap_visualization,
DashboardGenerator, generate_dashboard,
VisualizationDataExtractor, extract_visualization_data,
process_advanced_viz,
)
# Create visualizations
viz = AdvancedVisualizer()
create_network_visualization(data, output_path="net.html")
create_heatmap_visualization(data, output_path="heat.html")
# Generate dashboards
gen = DashboardGenerator()
generate_dashboard(model_data, output_dir="output/")
# Extract visualization data
extractor = VisualizationDataExtractor()
viz_data = extract_visualization_data(parsed_model)
# D2 diagram generation (if available)
from advanced_visualization import D2Visualizer, D2_AVAILABLE
if D2_AVAILABLE:
d2 = D2Visualizer()
AdvancedVisualizer — main advanced visualization classDashboardGenerator / generate_dashboard — interactive HTML dashboardsVisualizationDataExtractor / extract_visualization_data — data preparationD2Visualizer / D2DiagramSpec / D2GenerationResult — D2 diagram supportcreate_network_visualization, create_timeline_visualization, create_heatmap_visualization# Core interactive visualization
uv sync
# For D2 diagrams (requires d2 CLI)
# Install d2: https://d2lang.com/tour/install
output/9_advanced_viz_output/This module registers tools with the GNN MCP server (see mcp.py):
check_visualization_capabilitiesget_advanced_visualization_module_infolist_d2_visualization_typesprocess_advanced_visualization