Fluxspace Core is the brains of Fluxspace. It handles the raw magnetic sensor data, finds unusual patterns, and turns them into clean, usable maps that highlight potential problem areas. It’s the behind-the-scenes system that makes the insights on Fluxspace possible.
This data/ directory organizes all information flowing through that pipeline, from untouched sensor readings to finalized outputs.
Contains untouched, original input data collected from sensors or field scans.
Purpose:
- Preserve original measurements
- Act as the source-of-truth for all processing
- Never be edited manually
Examples:
- Raw magnetometer CSV files
- Direct sensor exports
- Field scan logs
Contains cleaned and transformed versions of the raw data.
Purpose:
- Data after filtering, normalization, or formatting
- Inputs for anomaly detection scripts
- Intermediate datasets ready for analysis
Examples:
- Smoothed magnetic field data
- Cleaned CSVs
- Standardized coordinate data
These files are derived from raw/ and can be regenerated if the pipeline changes.
Contains final outputs generated by Fluxspace Core.
Purpose:
- Results ready for visualization or external tools
- Deliverables for mapping or reporting
Examples:
- Anomaly maps (CSV / PNG)
- QGIS-ready layers
- Final processed datasets
These represent the end products of the analysis pipeline.
raw → processed → exports
Raw sensor data enters here, is cleaned and analyzed, and is finally exported as actionable results and visualizations.
- Keep sensitive or large real-world datasets out of version control if needed.
- Use small example files for testing and demonstration purposes.
- This structure supports reproducibility and clear data provenance.