This is a guide on the facilities available for macromolecular data processing at MAX IV. Click on the following links to display information on each topic.

The image files from the Eiger detector are written out in the NeXus format, using the HDF5 data convention as a container. Each h5 container stores up to 1000 images. For each data set a master file is written containing experimental and instrumentation metadata that complies with the Gold Standard for macromolecular crystallography diffraction data. The files are stored in a directory of the form /data/visitors/biomax/’proposal’/’date’/raw/’yourprotein’/’yourprotein-yourcrystal’. For proprietary proposals, the path is the same, but replacing ‘visitors’ with ‘proprietary’. The /data/visitors and /data/proprietary directories are mounted on all the MAX IV computers available to users.

Important: don’t change the file names or paths, which might break the internal data-links and also causes failure of most software.

During the experiment, the data are available on the high speed local storage at MAX IV.  After that, non-proprietary data are archived. Note that although the data are on a separate location after archiving, you can still use the the same path (displayed in EXI) to access the data. The data can be accessed for transfer via Globus or sftp. They can be made public via SciCat. Further offline processing can be carried out remotely at LUNARC or, for small jobs, on the MAX IV offline HPC cluster.

As soon as a data set has been collected and written to the local disk, MXCuBE3 launches several automated data processing pipelines. fast_dp and EDNA produce very fast results for rapid feedback on data quality, while autoPROC and DIALS runs significantly slower; autoPROC performs anisotropy analysis which results in better data in some cases. The output files of the automated processing are stored under the ‘/data/visitors/biomax/’proposal’/’date’/process’ subdirectory (or  ‘/data/proprietary/biomax/’proposal’/’date’/process’ for proprietary proposals) , but you can also inspect the results in EXI running on a remote browser and download them directly to your own computer.

You can see images as they are being collected with either ALBULA or Adxv. Click the Albula Autoload or adxv autoload icon on the beamline desktop to launch your prefered program in monitoring mode.

A useful feature of Adxv  is that it can add frames together, a useful feature to assess visually the quality of the diffraction for thin phi sliced data. Use the “slabs” box to set the number of images to add together; 5-10 is a good choice for data collected in 0.1 degree frames.

Adxv can also be run offline via a script from the command line on the biomax-remote server and the beamline workstations. To load a dataset, type:
adxv_eiger xxxx_master.h5
The adxv_eiger wrapper will read all the necessary metadata information in the master file supplied. When changing to a new dataset, launch the same command from the terminal instead of loading the dataset directly in the Adxv GUI (otherwise it uses the metadata information from the previous dataset).

Users can process the data in the ‘process’ subfolder in their session directory in the /data/visitors/biomax area.
For manual data processing during or after the experiment we recommend use of the PReSTO platform, available to general non industry users on the MAX IV HPC clusters. During the beamtime, users can log in to the so called online HPC cluster. After the beamtime, users can log in remotely to the offline HPC cluster.

To log in to the online cluster (during beamtime, from the beamline machines or from remote-biomax):

  • Click on Applications (first item in the top panel of the desktop).
  • Hover over the Internet menu and select the ThinLinc Client application.
  • Type clu0-fe-1 as the server, your username and your password and the return key.
  • By default, the ThinLinc desktop will be set to full screen mode. You can use the F8 key to exit this.
  • When you finish your work, please log out (click on the System item in the panel and select “Log out”. If you do not log out, your session will keep on running indefinitely.

To log in remotely from outside MAX IV to the  “offline” cluster (offline-fe1), users need to download and install in their home computer the Pulse Secure software to establish a VPN connection to MAX IV and the Thinlinc client (remote desktop) to log in to the HPC front end computer.

The offline cluster has fewer nodes than the online cluster, but otherwise the configuration is similar. The /data disk is mounted on both clusters, as well as the home disk. For more help, see IT environment at BioMAX.

Accessing PReSTO software from the thinlinc client desktop

Once you have logged in to the appropriate HPC with ThinLinc, the easiest way to launch a PReSTO ready terminal is through the thinlinc client “Applications” menu.

It is possible to run jobs from a terminal window, but please do not use run resource intensive jobs on the front end. Use the compute nodes instead, either with the sbatch command or in interactive mode:

  1. open a terminal
  2. Type: interactive -n 'n-of-CPUs' -t 'time'. For example, interactive -n 10 -t 01:00:00 will give you 10 CPUs for one hour.

Logout after using your session (use the logout function in the System menu) to release resources.

The next sections provide information to run some supported packages from PReSTO on the MAX IV cluster. To fully explore the capabilities of the software and job submission in the cluster (important if you are planning to go beyond data reduction and run longer jobs) please refer to the individual programs documentation and the PReSTO help pages. The entire list of software available through PReSTO is listed here.



  • Open the GUI: Applications → PreSTO → XDSAPP3. (the old XDSAPP does not work for data collected after February 2022)
  • Allocate the number of cores and the time for the job (we suggest the maximum number of cores available and 1 hour). If you cannot get the GUI to open, it can be because the nodes are very busy; try allocating fewer cores to the job (eg, 20 instead of 24).
  • Go to the Settings tab and select the location of your output directory. You must specify a directory in the ‘process’ subdirectory of your proposal or in your home area; by default, the program will attempt to create a subdirectory will be created in the directory where the input data are. This fails, as the data directories are write-protected.
  • Load the master file of the data set to process. You need to choose the directory where the data are located first, then select the master file. This will populate all the fields in the “Settings” tab, used to generate the input XDS.INP file.
  • You can choose whether to run the different tasks one by one or run them all as a supertask by clicking “Do all”.
  • To view a graphical display of the results of the INTEGRATE and CORRECT steps and the dataset statistics, use the corresponding tabs.


  • Open the GUI: Applications → PreSTO → XDSGUI.
  • Allocate the number of cores for the job and the time (we suggest the maximum number of cores and 1 hour).
  • On the projects TAB, select the directory where you want to store the processing results; create the directory first from a terminal if it does not exist. By default the result files will be written to the same directory as the images.
  • On the Frame tab, load the master file of the data set to process and then generate the XDS.INP file.
  • Edit the XDS.INP file to insert the line
    LIB= /sw/pkg/presto/software/Durin/2019v1-foss-2019b-6/lib/
    For fast processing we also recommend defining the number of jobs and number of processors in the input. The product of the two numbers should be equal to or less than twice the total number of cores allocated. Eg. on the offline cluster, insert the two following lines:


  • Save the input and click on Run XDS to start the job.


Use an interactive node to run Xia2: Open a terminal in the thinlinc client, eg, from the Applications -> System Tools menu and load the DIALS module:
interactive --exclusive -t 01:00:00
module load gopresto DIALS

  • As suggested in the example, one hour (01:00:00) is usually long enough to process the data set. For large data sets with many reflections, a longer time may be required.
  • You can tell if you have obtained a data processing node by typing “hostname” in the window. The output will be cnXX, with XX being the node number. If you cannot get a node (perhaps because the cluster is very busy) try requesting fewer cores, for example:
    interactive -n 12 -t 01:00:00
    That will book only 12 cores.
  • Change the directory to where you want to store the output files.
  • We recommend using the dials pipeline using the command: ‘xia2 pipeline=dials image=/data/visitors/biomax/…/’path_to_master’.h5′. You can also run Xia2 to run XDS based pipelines, however running XDS directly seems to be more advantageous in that case. Type ‘xia2’ for help using the program.
  • If the job finishes earlier than expected, type “exit” to release the node.

An alternative way to run DIALS is through the CCP4i2 interface (accessed through Applications → PreSTO → CCP4 → CCP4 Interface 2). Create a new project from the Project tab if necessary, and then, click on the Task menu and select Integrate X-ray images, and DIALS. When the software opens the DIALS interface, follow the screen instructions.


Use an interactive node to run autoPROC: Open a terminal from the Applications -> System Tools menu and load the autoPROC module:
interactive --exclusive -t 01:00:00
module load gopresto autoPROC

  • As suggested in the example, one hour (01:00:00) is usually long enough to process the data set. For large data sets with many reflections, a longer time may be required.
  • You can tell if you have obtained a data processing node by typing “hostname” in the window. The output will be cnXX, with XX being the node number.
  • Go to the directory where you wish to store the data and start autoPROC from the command line:process -h5 /'pathto masterfile_master'.h5 autoPROC_XdsKeyword_MAXIMUM_NUMBER_OF_JOBS=5 autoPROC_XdsKeyword_MAXIMUM_NUMBER_OF_PROCESSORS=8
    Make sure that the number of jobs times the number of processors does not exceed the resources of the node, otherwise the job will fail.
  • If the job finishes earlier than expected, type “exit” to release the node.

Further advice

  • Please see some of the scripts written by PReSTO developers for data processing on the MAX IV HPC clusters. Prior to running native.script or anomalous.script, the output directory must be created.
  • This is the pipeline that appears to generate the best results to date:
    1. Process with XDSAPP3 to 0.3-0.4 Å higher resolution than XDSAPP3 suggests by default.
    2. Use the output XDS_ASCII.HKL as input for the STARANISO server.The resulting anisotropic dataset will be better than standard autoPROC run.
  • Try out DIALS, since this software is undergoing continuous improvement.

PReSTO includes the program CrystFEL for processing SSX data using either fixed target or injector based sample delivery.

Currently, for some SSX experiments, several input files for CrystFEL are generated automatically for each data set collected. The files are located in raw images folder, in a subdirectory  called process. For example, for the images located in the directory

the processing files wil be stored under
/data/visitors/biomax/20200775/20221112/raw/Insulin/Insulin-HEC_1/process (a subdirectory starting with “crystfel” will be created for each data set)

The crystfel processing directory contains the following files:

  1. crystfel.geom : Geometrical description of the experiment setup.
  2. file.lst: A list of the image files in the data set.
  3. A shell script to launch the data processing in the HPC.
  4. mask.h5 and mask.tif: A mask file with bad/unreliable detector pixels.

Please contact staff if you are doing a SSX experiments and the files are not generated.

To process the data, copy the files to the directory where you want to store the results and run The script will automatically book a processing node for 20 hours, which should be enough for most jobs. The script can be modfied to supply different data processing parameters

The data can also be processed with the CrystFEL GUI. To launch it, use the command

module load gopresto CrystFEL

Please consult Thomas White guide at to learn how to use the GUI.

Please reference the software used to process the data in any publications resulting from the experiment: A list of references is available here.

The following video tutorials illustrate some of the procedures documented above. If the video looks blurry, change the “Quality” setting (under the cogwheel icon below the video) to 1080p.

Page manager: Ana Gonzalez April 2, 2024