Integration tool: diff_tomo

Purpose

Azimuthal integration for diffraction tomography.

Diffraction tomography is an experiment where 2D diffraction patterns are recorded while performing a 2D scan, one (the slowest) in rotation around the sample center and the other (the fastest) along a translation through the sample. Diff_tomo is a script (based on pyFAI and h5py) which allows the reduction of this 4D dataset into a 3D dataset containing the rotations angle (hundreds), the translation step (hundreds) and the many diffraction angles (thousands). The resulting dataset can be opened using PyMca roitool where the 1d dataset has to be selected as last dimension. This file is not (yet) NeXus compliant.

This tool can be used for mapping experiments if one considers the slow scan direction as the rotation, but a tool named diff_map operates in a similar way, provides a Graphical interface and is more flexible.

tips: If the number of files is too large, use double quotes around “*.edf”

Usage:

diff_tomo [options] -p ponifile imagefiles*

Options:

-h, --help	show this help message and exit
-V, --version	show program’s version number and exit
-o FILE, --output FILE
	HDF5 File where processed sinogram was saved, by default diff_tomo.h5
-v, --verbose	switch to verbose/debug mode, defaut: quiet
-P FILE, --prefix FILE
	Prefix or common base for all files
-e EXTENSION, --extension EXTENSION
	Process all files with this extension
-t NTRANS, --nTrans NTRANS
	number of points in translation. Mandatory
-r NROT, --nRot NROT
	number of points in rotation. Mandatory
-c NDIFF, --nDiff NDIFF
	number of points in diffraction powder pattern, Mandatory
-d FILE, --dark FILE
	list of dark images to average and subtract
-f FILE, --flat FILE
	list of flat images to average and divide
-m FILE, --mask FILE
	file containing the mask, no mask by default
-p FILE, --poni FILE
	file containing the diffraction parameter (poni-file), Mandatory
-O OFFSET, --offset OFFSET
	do not process the first files
-g, --gpu	process using OpenCL on GPU
-S, --stats	show statistics at the end

Most of those options are mandatory to define the structure of the dataset.

$ diff_tomo --help
usage: diff_tomo [options] -p ponifile imagefiles*

Azimuthal integration for diffraction tomography. Diffraction tomography is an
experiment where 2D diffraction patterns are recorded while performing a 2D
scan, one (the slowest) in rotation around the sample center and the other
(the fastest) along a translation through the sample. Diff_tomo is a script
(based on pyFAI and h5py) which allows the reduction of this 4D dataset into a
3D dataset containing the rotations angle (hundreds), the translation step
(hundreds) and the many diffraction angles (thousands). The resulting dataset
can be opened using the PyMca ROItool where the 1d dataset has to be selected
as last dimension. The output file aims at being NeXus compliant. This tool
can be used for mapping experiments if one considers the slow scan direction
as the rotation. but the *diff_map* tool provides in addition a graphical user
interface.

positional arguments:
  FILE                  List of files to calibrate

optional arguments:
  -h, --help            show this help message and exit
  -V, --version         show program's version number and exit
  -o FILE, --output FILE
                        HDF5 File where processed sinogram was saved, by
                        default diff_tomo.h5
  -v, --verbose         switch to verbose/debug mode, defaut: quiet
  -P FILE, --prefix FILE
                        Prefix or common base for all files
  -e EXTENSION, --extension EXTENSION
                        Process all files with this extension
  -t NTRANS, --nTrans NTRANS
                        number of points in translation. Mandatory
  -r NROT, --nRot NROT  number of points in rotation. Mandatory
  -c NDIFF, --nDiff NDIFF
                        number of points in diffraction powder pattern,
                        Mandatory
  -d FILE, --dark FILE  list of dark images to average and subtract
  -f FILE, --flat FILE  list of flat images to average and divide
  -m FILE, --mask FILE  file containing the mask, no mask by default
  -p FILE, --poni FILE  file containing the diffraction parameter (poni-file),
                        Mandatory
  -O OFFSET, --offset OFFSET
                        do not process the first files
  -g, --gpu             process using OpenCL on GPU
  -S, --stats           show statistics at the end

If the number of files is too large, use double quotes "*.edf"