KplotDigitiser Usage

Run

python3 KplotDigitiser.py image.ext

Example:

python3 KplotDigitiser.py Figure1_strain.pdf

The script will ask for output CSV file name (unless -o/--output is provided).

Run Without Input Argument

python3 KplotDigitiser.py

It will:

1. Show supported extensions.
2. Ask for image file path.
3. Continue normal extraction flow.

Supported Input Formats

• Raster: png, jpg, jpeg, tif, tiff, bmp, webp, gif, jp2, ppm, pgm, pbm, pnm
• Vector: pdf, eps, ps

For vector inputs, image rendering is done internally (DPI/page configurable).

Common Options

• -o, --output PATH
  Output CSV path.

• --dry-run
  Detect and report points without writing CSV.

• --report-json PATH
  Save extraction metadata report as JSON.

• --long-format
  Write combined rows as series,p,value,sem.

• --split-series
  Write one CSV per configured series (template/config mode).

• --dpi N
  Rendering DPI for pdf/eps/ps (default 300 if not overridden by config).

• --page N
  1-based page for pdf/eps/ps (default 1).

Build Config (Optional Advanced Mode)

python3 KplotDigitiser.py image.ext --build-config

This opens interactive calibration/ROI setup and writes a JSON config.

Output Behavior

• Known built-in figures: uses built-in templates/tables directly.
• Unknown figures: uses generic auto-extraction.
• Multi-series scatter: outputs separate columns per detected series in generic mode.

Quick Examples

python3 KplotDigitiser.py medium.png
python3 KplotDigitiser.py Figure_atlas_density.pdf --dry-run --report-json density_report.json
python3 KplotDigitiser.py Figure_dft_validation.pdf -o dft_points.csv --report-json dft_report.json