Streamlit application

For users who prefer a graphical interface over a Python script, ePDFsuite includes a Streamlit web application that exposes the full workflow through a browser-based GUI — no programming required.

Online version (no installation)

The app is publicly hosted on the Streamlit Community Cloud — no Python, no installation required:

Simply open the link in your browser, upload your files and start processing.

Local installation

For offline use or to work with a local installation, see the launch guide on GitHub for detailed instructions (conda environment setup, epdfsuite-app command, or bash script).

In short:

conda activate epdfsuite
epdfsuite-app

The app opens at http://localhost:8501.

Interface overview

The app is organised in two tabs.

Tab 1 — Define Sample and Reference

Each column (Sample / Reference) follows the same two-step flow:

Step 1 — Upload Files

  • Image — DM4, DM3, tif or tiff diffraction image

  • PONI file (optional) — pyFAI geometric calibration file

  • Mask file (optional) — EDF mask; or click 🎨 Draw mask to open the pyFAI-drawmask GUI directly on the loaded image

  • MTF file (optional) — for detector deconvolution

    • When a MTF file is provided, an expander 🔧 MTF Deconvolution Parameters appears. The Wiener regularisation parameter ε is read automatically from column 3 of the MTF file and can be adjusted if needed.

For the reference column, PONI, mask and MTF files default to the sample values when left empty (a caption indicates which file is reused).

Step 2 — Create Processor & Detect Centre

Click 🚀 Create SAEDProcessor to:

  1. Instantiate SAEDProcessor (MTF deconvolution applied here if a MTF file was provided).

  2. Run the iso-intensity contour algorithm automatically to locate the beam centre — no manual estimate required.

  3. Pre-fill the Center X / Y number inputs with the detected coordinates.

A log-scale image of the diffraction pattern is displayed with a white crosshair at the current centre position.

If detection fails (unusual geometry, very strong beamstop), the pixel with the maximum intensity is used as a fallback and a warning is printed in the console.

Refining the centre manually

Edit the Center X and Center Y fields as needed, then click 🔄 Update to apply the new coordinates to the processor. The crosshair updates accordingly.

Note

When you later click 🚀 Calculate PDF in Tab 2, the centre is synchronised from the number-input fields automatically — the values shown in the boxes are always the ones used for integration, whether they came from auto-detection or manual entry.

Tab 2 — Extract ePDF

Adjust the PDF computation parameters with sliders and extract G(r):

  • bgscale — background scaling factor

  • qmin, qmax, qmaxinst — Q-range limits (Å⁻¹)

  • rpoly — polynomial background degree (PDFgetX3 convention)

  • Lorch modification function toggle

The G(r) plot updates in real time. Click Save to export the result as a .gr file compatible with PDFgui and PDFBatchAnalysis.

When to use the app vs. the Python API

Use case

App

Python API

Quick exploration of a new dataset

✅ recommended

possible

Reproducible batch processing

✗

✅ recommended

Processing multiple files automatically

✗

✅ extract_ePDF_from_mutliple_files()

Integration in a Jupyter notebook

✗

✅ recommended