CDI analysis using a command-line script

The simplest way to analyse a CDI dataset using PyNX is to use a command-line script.

Note regarding command-line arguments:

• previous versions of PyNX (<2024) used e.g. pynx-ptycho-cxi data=data.cxi

• now command-line arguments all start with -- to use standard parsing libarries and make it easier to documentation

• you can use equivalently pynx-ptycho-cxi --data=data.cxi or pynx-ptycho-cxi --data data.cxi, with the exception of options where the supplied value begins with --, e.g. it is mandatory to use --support_post_expand=-2,2, as using --support_post_expand -2 2 will try to interpret -2 as a new command-line argument

There are two main scripts which can be currently used: pynx-cdi-id01 and pynx-cdi-id10, which differ only by a few default options (HIO vs RAAR algorithm, and for id10: --positivity and --mask=zero options).

A simple data analysis can be done, when reading a CXI file, using:

pynx-id01cdi.py data=data.cxi

This will simply run the analysis with default parameter. The initial support will be determined using auto-correlation (which is usually fine for Bragg CDI where no beamstop is used), no positivity…

A more detailed example using a Vaterite dataset (Cherkas et al., Crystal Growth & Design 17, 4183–4188 (2017)):

# If necessary, activate your python environment with PyNX
source /path/to/my/python/environment/bin activate

# Download the example dataset
curl -O http://ftp.esrf.fr/pub/scisoft/PyNX/data/T25_60_3D.cxi

# View the CXI file using the silx viewer:
silx view T25_60_3D.cxi

# Run the PyNX analysis script
pynx-cdi-id10 --data T25_60_3D.cxi --support circle --support_size 70\
              --nb_raar 800 --nb_hio 0 --nb_er 200 --verbose 50\
              --support_smooth_width_begin 3 --support_smooth_width_end 1\
              --positivity --support_threshold 0.2 --max_size 512\
              --support_threshold_method max --liveplot

# View the result from the output CXI file using the silx viewer
silx view latest.cxi

# Note that you can see all the parameters used for the optimisation
# in entry_last/image_1/process_1/

# You can tune the threshold if you want to improve the solution,
# or try HIO instead of RAAR (``--nb_hio 800 --nb_raar 0``)

To perform a more complete analysis, it is advised to use multiple runs, select the best from the free log-likelihood, and combine them:

# Perform 10 runs and combine the 5 best ones (takes a little longer,
# 30s per run on a V100 GPU, liveplot is disabled)
# Note --support_threshold 0.1 0.2 means threshold is randomly chosen
# between 0.1 and 0.2 for each run

rm -f *LLK*.cxi  # remove previous results

pynx-cdi-id10 --data T25_60_3D.cxi --support circle --support_size 70\
              --nb_raar 800 --nb_hio 0 --nb_er 200 --verbose 50\
              --support_smooth_width_begin 3 --support_smooth_width_end 1\
              --positivity support_threshold 0.1 0.2 --max_size 512\
              --support_threshold_method max --nb_run 10 --nb_run_keep 5

# Perform a modes analysis and produce a movie (requires ffmpeg)
pynx-cdi-analysis.py *LLK*.cxi modes movie

# Look at modes analysis
silx view modes.h5

# See movie of slices from modes analysis
vlc cdi-3d-slices.mp4

More information

The full documentation for the command-line scripts can be obtained by using the --help command-line option, e.g.:

pynx-cdi-id10 --help

For more information, please read the online documentation on CDI scripts