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/sdf/data/lcls/ds/<hutch>/<experiment>/hdf5/smalldata
Example notebooks
See 2. Example analysis notebooks.
Smalldata analysis workflow
The analysis is generally split in two steps, allowing for easy diagnostics and customization of the analysis process. Please contact your controls and data POC to assess the best approach for your experiment.
- The first step is the generation of the "small data" file, the colloquial name for run-based hdf5 files which contain different data arrays where the first dimension is the number of events (shot-to-shot information retained). This production can be run automatically on each new run so that the data is available only a few minutes after the run has ended. It can also be run on request in case you want to tweak the data extraction. Processing of the area detector can be configured at this stage, performing operation such as extracting a region of interest, azimuthal integration, photon counting, etc. It is non-recommended to save full large area detector data at this step.
The following pages describe this in more details: - The second stage depends much more on the type of experiment. Different options are available:
- Binning of the full detector images can be performed by setting up the cube analysis, which will return a h5 file of binned data and images, resulting in a relatively light-weight file. While the shot-to-shot information is lost at this point, this approach is generally recommended, as it is more carefree and does not require to delve into the details of the binning procedure. It is also almost mandatory in cases where the analysis of the full image is needed (Q-resolved diffused scattering analysis, for example). Note that the shot-to-shot information remains readily available from the file produced in the first step (without the area detector data).
Details on the cube workflow are given here: Cube production - Adapt one of the templated analysis notebooks to suit the current experiment needs. These custom templates have been made for the more common experiments performed at different endstations at LCLS and are available at
/reg/g/psdm/sw/tools/smalldata_tools/example_notebooks(please refrain from modifying these released notebooks in place). This approach works well for lightweight data analysis, for which the area detector images are reduced to a single (or few) number (integration of a ROI, azimuthal binning, for example) in the first step. It is also suited when detailed shot-to-shot information needs to be examined, and full control over the data binning process is desired.
Documentation on the example notebooks can be found here: Example notebooks.
- Binning of the full detector images can be performed by setting up the cube analysis, which will return a h5 file of binned data and images, resulting in a relatively light-weight file. While the shot-to-shot information is lost at this point, this approach is generally recommended, as it is more carefree and does not require to delve into the details of the binning procedure. It is also almost mandatory in cases where the analysis of the full image is needed (Q-resolved diffused scattering analysis, for example). Note that the shot-to-shot information remains readily available from the file produced in the first step (without the area detector data).
The contents of the smallData files are described here
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Old
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analysis infrastructure (data taken before 2023)
Online and offline analysis
Two analysis infrastructures comprising of various queues and interactive nodes, are available to use depending on the status of the experiment.
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ssh -X psana source /reg/g/psdm/etc/psconda.sh -py3 # Environment to use psana, etc |
Working directories
The working directory structure can be confusing, as some of the offline folders are mounted and accessible from the online system. As a rule of thumb, until things are moved away from the online system, one should exclusively work on the ffb.
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for the fast feedback system (psffb).
Access data
The data will be written to:
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for the processing using the 'SLAC' endpoint / the psana system. Data will be moved from the FFB system to this directory within 3-4 weeks after the experiment has ended.
JupyterHub
General information about JupyterHub at LCLS: JupyterHub
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/reg/g/psdm/sw/jupyterhub/psjhub/jhub/generate-keys.sh |
Make experiment folder accessible from JupyerHub session
In Jupyter hub, you can only navigate within your home folder. It is thus recommended to create shortcuts (soft-links) to the relevant experiment folders, for ease-of-access.
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ln -s /cds/data/drpsrcf/<hutch>/<experiment>/ ./<link_name>
Advanced topics
The results folder is backed-up and for that reason can only hold-up to 10'000 files after which a quota exceeded error will pop up. Users' who wish to build code with more files should do it on the scratch folder (online: /cds/data/drpsrcf/<hutch>/<experiment>/scratch), where there is no file limits (but no back-up).
Smalldata analysis workflow
The analysis is generally split in two steps, allowing for easy diagnostics and customization of the analysis process. Please contact your controls and data POC to assess the best approach for your experiment.
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Generation of small hdf5 files
Adding Data from area detectors
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The contents of the smallData files are described here
Overview
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