graynet

graynet computes single-subject morphometric networks and ROI statistics from cortical Freesurfer outputs and supported volumetric feature maps.

graynet 2.0 writes canonical run-level outputs as Parquet tables plus JSON metadata:

• run_metadata.json

• edges_raw.parquet

• edges_summary.parquet when summary edges are requested

• roi_stats.parquet when ROI statistics are requested

GraphML and CSV remain available as optional exports.

Contents:

• Installation
  • Quick sanity check
  • Requirements
  • Citation
• Command line interface
  • Positional Arguments
  • Named Arguments
  • Sub-commands
• Single-feature edge extraction
• Multi-edge extraction
• ROI-wise statistics
• Exporting GraphML or CSV
• Examples using API
  • Single-feature edge extraction
  • Reading run outputs
  • Multi-edge extraction
  • ROI-wise statistics
• How to use graynet results
• Loading a run
• Filtering raw edges
• Converting to an ML matrix
• Reconstructing a NetworkX graph
• Iterating subject by subject
• Optional exports
• Cortical graynet
  • Computing ROI-wise statistics
  • How to run Freesurfer
  • Qcache recon-all flag
• Volumetric graynet
  • Computing ROI-wise statistics
• API
  • API Reference
• Citation

Indices and tables

• Index

• Module Index

• Search Page