Modern x-ray diffraction (XRD) is very often performed using two-dimensional, or "area"
detectors--the solid state equivalent of film. Commonly used technologies include CCD detectors
(usually with some kind of x-ray fluorescent screen), other solid state technologies, image plates, or wire detectors. These are
generally supplied by the vendor with built-in software that collects the data and performs some
kind of specialized analysis, such as protein crystallography or phase identification via powder
The problem comes when the user tries to use the equipment for a purpose other than that envisioned
by the manufacturer--for example, looking at small-angle x-ray scattering (SAXS) from protein
solutions, or diffuse scattering from amorphous polymers, on a system intended for crystallography.
The scientist then quickly encounters two related problems: the on-board software is not sufficiently
flexible to perform the desired analysis, and the file format structure is so obscure that
what started as a simple data analysis project turns into a lengthy exercise in interpreting
binary data with custom compression.
This is where Datasqueeze comes in. This application allows you to read most of
the XRD formats that are currently on the market (with more being added continuously),
analyze the data, and export the results on both graphical and text formats that can
be easily used by other applications.
Datasqueeze is a graphical interface for analyzing
data from 2D x-ray detectors. The data
are represented as a false color image, with substantial control over the colors displayed. Basic functions include changing the color scale of the false
color image, calibrating the image (i.e., determining parameters such as the image center and the angular scale of the image),
producing radial or azimuthal x-y plots of intensity, and saving analyzed data both as images or in formats suitable
for input to other programs such as Matlab or
The x-y data extracted from the 2D images can also
be least-squares fits to a variety of functions.
Datasqueeze will run on multiple platforms, including Windows, Linux, and Macintosh OS X. This means that the scientist is not tied to the computer that produced the data, or to a central "analysis computer," but can carry the data off to his or her office to be examined at leisure.
Datasqueeze is particularly useful for the analysis of powder diffraction data, diffuse scattering from polymers or liquid crystals, or small-angle scattering ("SAXS") from colloids, polymers, gels, or solutions.
Datasqueeze is not well suited for extracting intensities from many sharp Bragg peaks in a single-crystal diffraction type experiment (although it has been used to
extract information about pixel statistics in such images). Datasqueeze is unsuitable for the analysis of data produced on curved detectors. It may read in the data from such detectors, but the conversion
to scattering angle will be unreliable.
Datasqueeze is unsuitable for the analysis of radiographic or tomographic images obtained from the transmission of x-rays through a patient or sample.
To install and run Datasqueeze you need the following:
New data formats are being added continuously
(contact us if there is a new format you would like to see added). Currently supported formats include the following:
- A computer operating under the Windows, Linux, or Macintosh OS X (10.9 or above)
operating systems. (The program also runs under
Solaris, and perhaps other Unix, operating systems, but this has not been extensively tested.)
- Java version 1.8 or above.
- A CPU running at at least 300 MHz.
- A color monitor display resolution of at least 1024 x 768
- Area Detector Systems Corporation (ADSC)
Quantum CCD detectors (the same format is used for Brandeis B4 detectors).
- Square arrays of 2-byte binary pixels, which could be little-endian or big-endian.
- Bruker-Nonius KappaCCD
- Bruker-Siemens standard format (used by the SAXS, GADDS, and SMART data collection systems.)
- Crytallographic Binary File (CBF), a format used widely in the protein crystallography community and also by Pilatus and Dectris detectors.
- CrysAlis, a format is used by a number of detectors sold by Agilent Technologies (formerly Oxford Instruments), including the Eos and Atlas series of CCD cameras.
- Ditabis IPC,
a format used by the Ditabis Image Plate System, primarily used for electron microscopy but also in some x-ray diffractometers.
- ESRF format (used by many detectors at the European
Synchrotron Radiation Facility).
- Esperanto: This format is used by Agilent Technologies as a way to import files from other detectors.
- Fuji image plates.
- Gatan DM3 format (primarily used for electron microscopy data).
- PNG, GIF, or JPG grayscale images. Note that graphics images are not the preferred
way of reading in data from x-ray detectors--they are intended only
as a way of reading in non-xray data, for example
produced as a Fourier transform of some optical image. A graphics file is not the
same as the original data file. A typical data file contains at least 1024x1024 pixels, and has a depth
of at least 16 bits (depending on the detector type). Graphics images are generally much
smaller (so spatial resolution has been lost) and have much less dynamic range. Additionally,
note that Datasqueeze expects grayscale images. It converts the image color to an
intensity by adding the red, blue, and green components. If you start with a
color image, this is almost certainly not how the data were encoded.
- MAR Research CCD and image plate formats (multiple formats,
- Matlab format. This is not the native file
format for any detector of which we are aware, but is sometimes used as a tool for analyzing 2D data images.
- Molecular Metrology format.
- Nonius DIP image plates.
- Rigaku image plates and CCD cameras (Mercury, Raxis-II, Raxis-IV,
- Princeton/Roper CCD formats.
- SBIG CCD
format. These detectors are primarily used for astronomical observations, but are also incorporated in some x-ray diffraction applications.
- Black and white tiff images. This format is used, for example, for some CCD detectors at CHESS. Note that you can also open a MAR CCD file as a tiff file, but this is not recommended since the tiff header contains less information about the instrument format than the MAR header.
a binary format sometimes used for inter-computer data transfer.
The following is a summary of some of the capabiliites of Datasqueeze. For more detailed information, feel
free the refer to the manual which also is distributed with the application.
- Add and subtract frames. Multiple data frames can be
added or subtracted to improve statistics or subtract a background image.
- Control the appearance of the false color image. The data are
represented on the screen as a 512 x 512 pixel2 image.
The user can control the color scheme, magnification, binning, and other features, and can optionally
superimpose a cartesian or polar grid to help locate positions of features of interest.
- Calibrate the pattern. For meaningful data analysis it is necessary to set accurate values of the beam center and
image angular range and to correct for non-circularity. A simple and intuitive wizard
guides the user through the process, but parameters can also be set manually or retrieved from a previous calibration.
Datasqueeze was initially developed to analyze data produced in a small-angle configuration, in which the direct beam strikes either the
detector or a point close to the detector, and the detector face is approximately normal to the direct beam. However, it is also capable
of analyzing data in which the detector has been rotated by a large angle away from the beam center
- Manipulate the data. Data can be rebinned (to reduce noise), averaged to force symmetrization, de-zinged, or directly
Fourier transformed. Data can also be represented in a false color image in polar, rather than Cartesian, coordinates, sometimes known as an "unwrapped" image.
- Report dataset statistics. The user can obtain histogram-type information about the number of
pixels with differing numbers of counts.
- Import 1D Data. Data previously saved in 1D format by other applications can be imported as an
alternative to native 2D data. Datasqueeze supports multiple ascii formats, comma-separated-variable (csv), PLV, CPI, or
- Plot the data. The user can make and save a variety of possible one-dimensional (x-y) plots of the
data (radial, azimuthal, Porod, Guinier, etc.). The plot regions can be selected manually or graphically. The user has substantial
control over the size and appearance of the resulting plot.
A graphical indexing tool assists in the determination of the lattice parameters of a
powder diffraction pattern. The user selects a Bravais lattice, and then observes where the
diffraction lines would fall for various choices of the lattice parameters. An "autoindex" feature uses
a grid search to make an informed guess as to the best lattice parameters for a particular latter, which is particularly useful
in the case of lower-symmetry patterns.
- Fit the data. The plotted data can be
least-squares fit to a wide variety of models suitable
for powder diffraction analysis (Lorentzian, Gaussian, Voigt), small-angle scattering from
spheres, rods, or disks, or polymers (e.g. Kinning-Thomas).
- Massage the data. Data can be "de-zinged" (to remove artifacts often seen in ccd data), smoothed,
re-binned, or symmetrize about vertical and/or horizontal axes.
A masking feature allows the user to remove selected regions from analysis.
- Apply Fraser correction to fiber patterns.
In some cases a sample has cylindrical symmetry, such that in reciprocal space the data are circularly averaged about the long axis of the fiber, or the "meridian." The meridian often coincides with a particular crystallographic direction. This results in a distortion of the diffraction pattern observed on a flat area detector (or film) because portions of the Ewald sphere are inaccessible. The Fraser correction (R. D. B. Fraser, T. P. Macrae, A. Miller, R. J. Rowlands, J. Appl. Cryst. 9, 81 (1976))
maps the observed data onto a Cartesian grid.
- Automate your analysis. Construct batch (or script) files for automated processing of multiple data files. There is also a "Process Multiple Files" option, in which
multiple (in principle, hundreds or thousands) of files are all processed in
exactly the same way.
- Get a close-up look at the data. Use the Examine panel to inspect your data at a pixel-by-pixel level, or
use the Statistics feature to obtain obtain basic information about maximum, minimum,
and average intensity per pixel, and construct histograms of
pixel intensity frequencies both for the data set as a whole and for the
region selected for plotting. Open the Info window
to get access to (format-dependent) metadata.
- Save your results. Data that have been reduced to one dimension can be exported to a variety of formats, including
multiple ascii formats, comma-separated-variable (csv), PLV, or CPI.
Both the plot image and the false color 2D data image can be saved
as journal-quality graphical images (jpeg, tiff, or png). The 2D data themselves can be exported
in ascii or tiff format or as Matlab format files.
- Extensive documentation. In addition to the the detailed
manual , an onboard
help menu provides clear descriptions
of all features and a tutorial guide. Most features are also right-clickable for quick explanations.
Last updated September 12, 2021
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