canSAS-XI/DataFormats

Session Notes

Jan : real world examples of nxcanSAS from facilities needed. Tim suggests everyone putting them on Zenodo to get DOIs Pete - post issues on cansas examples github

Pete - request for more examples of NXcanSAS files: https://github.com/canSAS-org/NXcanSAS_examples/issues/3#issuecomment-509619529

Reduced data from multiple detectors

• Is this a general problem?
• Jeff : looking at how to handle this for VSANS at NIST
• Issue for both raw and reduced : raw easier
• How to convert from raw to reduced? Very instrument dependent. Choice of detector combination to Q space varies with instrument and experiment and whether 1D or 2D
  • AJJ : question is of multiple 2D q-spaces rather than detector spaces.
  • Tim : multiple physical detectors vs moving detector
  • AJJ : multiple SASdata entries in a single SASentry
  • Jan : how to get software to read complex datasets (e.g. lots of mag fields with many detectors)
  • AJJ : discussion of complexity ... some of the complex analyses will require the users to understand their data. Perhaps plugins in e.g. DPDAK?

• Sven-Jannik : Is there a standard location for motors etc. Not really ... each instrument/facility does it differently.
  • can we have a standard set of metadata tags for NXcanSAS to support
• Armin : how about more detailed application definitions?
• Pete : Application definitions tend to be generic - can use search methods, specify nexus path on data loading as one way. Similar to translation dictionaries.
• Brian : how to include multi-modal data - probably at the same level as a SASentry
• Detectors : how do we link detector metadata to the q-spaces derived from them. e.g. multiple detector configurations might be used to give a single Q space. This is true for 1D as well.
• Stitching : discussion of stitching - U-Ser was interested in how we at SANS beamlines manage stiching - automated or manual. Explained that it still requires user input with expert help to define data combination routine and choices of overlap/data cutoff etc.

• Adam : SESANS data - what to do? Not I vs Q, but is small angle scattering. Should create equivalent of SASData for SESANS data. This allows for combined SANS/SESANS experiments to write one set of sample metadata and two datasets to file - similar to having multiple SASdata entries for eg USAXS+SAXS+WAXS

Discussion of dataset representation in python

Need dataset representation that maintains information about units and uncertainties and can ideally support other metadata.

• xarray - not fully featured.
• scippy (c++ version of xarray for mantid) - reinventing numpy! not what we are looking for here.
• DAWN has the java based dataset representation that supports uncertainties and units.

Large datasets are a problem - example of tomography/imaging where can't read whole file into memory. So need lazy data loading.

• nexpy supports network streaming / reading online rather than having to load whole dataset

Multiple detectors - multiple kinds of detector (Tim)

Not only do we have multiple detectors, but we might have multiple types of detector running at different frame rates e.g. optical camera + x-ray detector working at different frequencies. More frames from one than the other

• SAXS + WAXS at DESY - just write two nexus files to avoid the problem. Server issues and I/O
• I22 - timeframe generation (one file) + two separate detector files. Acquisition gives you a header nexus file linked to the others. Currently looking at stacking in the right order in data structures - slowest at top.
• ESS and other spallation sources - all timestamped so do post-hoc correlations.
• Pete - timestamping at synchrotrons will be coming. XPCS can use this.
• Brian : Visualisation
  • Time slider bars - showing last collected image.

Metadata for Machine Learning

• Datasets generated by Diamond for machine learning project should be put online for others to use (3Tb issue!)
• Metadata from sample is required for most machine learning applications that would be useful to users.
• XPDF users need the information about the sample to be able to process data at all (same for liquids neutron diffraction).
• Need to move on from basics such as simple dimensions etc (Pete) - however, we don't know what we need to know to feed the machine learning algorithms.
• What are the users going to give us?
  • Very little ... without encouragement
  • Use header nexus file with link to raw detector data. Basically digital logbook.
  • Pete - shouldn't limit metadata for edge cases. Need to have the metadata possible and turn off as needed.
  • Pete - automated addition of data from proposal/safety form
  • Brian - adding analyte composition and density etc.
  • Pete - issue with NXsample : requires chemical formula, not composition.
  • Some are easy for low throughput. Need an efficient way of entering the information.
  • Should look at what the MX do.
  • Needs to be end-to-end. Has to be a benefit to user.
  • Machine learning : Pete - need some samples with bad metadata to teach algorithm!

Actions

• Implementation of a SESANSdata group equivalent to SASdata : Adam W to develop proposal

• Upload example datasets to Zenodo and/or github. (Relevant github issue here : https://github.com/canSAS-org/NXcanSAS_examples/issues/3#issuecomment-509619529) : Action for all canSAS who have data in NXcanSAS format

• Linking of detector metadata to sasdata entries. Jeff K to develop proposal

• Writing of notes with examples for NXcanSAS usage. Should be included in NXcanSAS documentation or on cansas.org. Needs to be more than just developer docs : Action for all canSAS who have examples of how they have used NXcanSAS for specific cases.

• Build a list of suggested metadata with standard names. Including how to build sample descriptions. Brian P to write a proposal for sample relevant metadata and to circulate to Data Formats group