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Convert .plux files to image formats and compute surface heterogeneity metrics.

Project description

PLUXTools

PLUXTools – A utility for converting .plux surface metrology archives and calculating quantitative heterogeneity metrics


A Python-based module for automated conversion of Sensofar .plux topography data into usable image formats (PNG and TIFF), followed by optional surface texture analysis using image-derived metrics.


Basic usage

PLUXTools supports .plux files containing metrology information and structured surface maps. It extracts the core data using index.xml and .raw layers, and converts it into common image formats for downstream analysis or publication.

Conversion only

python -m pluxtools.convert [input_file.plux]

This will:

  1. Extract the .plux archive
  2. Parse image dimensions from index.xml
  3. Convert the raw topography (LAYER_0_stack.raw) to .png and .tiff formats

Heterogeneity metrics

PLUXTools can calculate basic surface texture metrics from extracted images. These metrics provide a summary of spatial heterogeneity and surface roughness. Metrics calculated

  • Laplacian Variance – measure of surface sharpness and detail
  • Shannon Entropy – texture randomness and complexity
  • Sobel Mean Gradient – average spatial edge strength

Metric calculation usage

python -m pluxtools.metrics [directory_of_images]

All supported image formats in the specified directory will be processed, including: .png, .jpg, .jpeg, .tif, and .tiff

Example output

filename laplacian_variance entropy sobel_mean
sample_1.png 54.23 6.22 0.0452
sample_2.tiff 48.14 6.12 0.0385

Installation instructions

We recommend using a virtual environment.

Install via PyPI

pip3 install pluxtools

Install from source

git clone https://github.com/yourgroup/pluxtools.git
cd pluxtools
pip install -e .

Dependencies

PLUXTools requires the following packages:

  • numpy
  • pillow
  • opencv-python
  • scikit-image
  • pandas
  • tqdm

Output and structure

All converted image files are saved to the same directory as the input .plux archive. Metric outputs are saved as a single .csv file summarising calculated features per image.

Notes

  • .plux files are ZIP-compressed archives with metadata and binary topography data
  • Image dimensions are parsed from index.xml
  • Bit depth and format are inferred from the size of the .raw file
  • Only LAYER_0_stack.raw is processed
  • No manual configuration of dimensions is required

License

MIT License © DrATedder 2025

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