xpcs-viewer 1.0.6

pyXPCSViewer: A python-based interactive tool to visualize and model XPCS dataset

A python-based interactive visualization tool to view XPCS dataset.

To cite pyXPCSViewer:

Chu et al., “pyXPCSviewer: an open-source interactive tool for X-ray photon correlation spectroscopy visualization and analysis”, Journal of Synchrotron Radiation, (2022) 29, 1122–1129.

Supported Format

This tools supports the customized nexus fileformat developed at APS-8IDI’s XPCS data format for both multi-tau and two-time correlation.

Install and Uninstall

Updated 03/11/2025

It is highly recommended to set up a new virtual environment to isolate pyXPCSViewer, so it does not interfere with dependencies of your existing applications.

0. Install conda following the instructions at link.

1. Create a brand-new environment with conda:

   conda create -n your_env_name python==3.10.16

   Replace your_env_name with your preferred environment name.

2. Activate the new environment:

   conda activate your_env_name

3. Install pyXPCSViewer:

   pip install xpcs-viewer

   Note: Running conda and pip commands together is generally not recommended. pyXPCSViewer will only use pip or conda once compatibility issues are resolved.

4. Launch pyXPCSViewer:

   1. Activate your environment if you have not already.

   2. Run:

      pyxpcsviewer path_to_hdf_directory   # Run the viewer from the hdf directory
      pyxpcsviewer                         # Run in the current directory

   run_viewer, an alias to pyxpcsviewer, can also be used to luanch the viewer.

5. To upgrade:

   1. Activate your environment if you have not already.

   2. Run:

      pip install -U xpcs-viewer

6. To uninstall:

   1. Activate your environment if you have not already.

   2. Run:

      pip uninstall xpcs-viewer

   3. If you want to remove the environment altogether, first deactivate it:

      conda deactivate

      Then remove it:

      conda remove -n your_env_name --all

Gallery

1. The integrated scattering pattern over the whole time series.

   

2. The reduced one-dimensional small-angle scattering data.

   

3. The sample’s stability against X-ray beam damage. The time series is divided into 10 sections. The SAXS-1D curve is plotted for each section.

   

4. Intensity fluctuation vs. Time.

   

5. Average Tool box.

   

6. g2 plot for multitau analysis. Users can fit the time scale using a single exponential function, with options to specify the fitting range and fitting flags (fix or fit).

   

7. Diffusion analysis. g2 fitting in the previous panel is required to plot \(\tau \mbox{vs.} q\).

   

8. Two-time correlation. Users can select two q indexes either on the q-map or on the SAXS-2D image.

   

9. Experiment condition viewer. It reads the file structure and string entries of the selected HDF file.