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Data Processing

Understanding and configuring data processing options

🔄 Processing Parameters

  • CGM Gap Handling: How many missing readings to interpolate
  • Insulin Classification: Thresholds for bolus vs basal
  • Data Validation: Maximum valid insulin doses

⚙️ Configuration Examples

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# Conservative gap filling (15 mins max)
python -m src.cli data.sqlite --interpolation-limit 3

# Higher insulin thresholds
python -m src.cli data.sqlite --bolus-limit 12.0 --max-dose 25.0

# Strict validation
python -m src.cli data.sqlite --bolus-limit 6.0 --max-dose 12.0

📊 Output Structure

  • complete_dataset/: Full processed data with applied parameters
  • monthly/: Split data maintaining processing settings
  • processing_notes.json: Configuration and quality metrics
Example Output Structure: 
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data/exports
├── 2023-06-03_to_2024-09-28_complete
│   ├── aligned_data.csv
│   ├── carbs.csv
│   ├── cgm.csv
│   ├── insulin.csv
│   ├── notes.csv
│   └── processing_notes.json
└── monthly
    ├── 2023-06
    │   ├── aligned_data.csv
    │   ├── carbs.csv
    │   ├── cgm.csv
    │   ├── insulin.csv
    │   ├── notes.csv
    │   └── processing_notes.json
    ├── 2023-07
    │   ├── aligned_data.csv
    │   ├── carbs.csv
    │   ├── cgm.csv
    │   ├── insulin.csv
    │   ├── notes.csv
    │   └── processing_notes.json