We gratefully acknowledge funding from the Initiative and Network Fund of the Helmholtz Association within the Helmholtz Young Investigator Group moreSTEM under Contract No. VH-NG-1317 at Forschungszentrum J\u00fclich in Germany.
\n\nWe gratefully acknowledge funding from the Information & Data Science Pilot Project 'Ptychography 4.0' of the Helmholtz Association.
\n\nWe kindly acknowledge funding from Google Summer of Code 2019 under the umbrella of the Python software foundation.
\n\nSTEMx equipment and software for 4D STEM data acquisition with K2 IS camera courtesy of Gatan Inc.
\n\nLiberTEM development is supported by AIDAS
\n\nLiberTEM development is part of the Joint Lab MDMC.
\n\nForschungszentrum J\u00fclich is supporting LiberTEM with funding for personnel, access to its infrastructure and administrative support.
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"personal" } }, { "affiliations": [ { "name": "Monash University eResearch Centre" } ], "person_or_org": { "family_name": "Schyndel van", "given_name": "Jay", "name": "Schyndel van, Jay", "type": "personal" } }, { "affiliations": [ { "name": "ETH Z\u00fcrich" } ], "person_or_org": { "family_name": "Shin", "given_name": "Jaeweon", "name": "Shin, Jaeweon", "type": "personal" } }, { "affiliations": [ { "name": "Columbia University" } ], "person_or_org": { "family_name": "Sunku", "given_name": "Sai", "name": "Sunku, Sai", "type": "personal" } }, { "affiliations": [ { "name": "Norwegian University of Science and Technology" } ], "person_or_org": { "family_name": "\u00c5nes", "given_name": "H\u00e5kon W.", "identifiers": [ { "identifier": "0000-0002-1213-2911", "scheme": "orcid" } ], "name": "\u00c5nes, H\u00e5kon W.", "type": "personal" } }, { "affiliations": [ { "name": "Korea Astronomy and Space Science Institute" } ], "person_or_org": { "family_name": "Chen", "given_name": "Yaocheng", "identifiers": [ { "identifier": "0000-0002-8967-4911", "scheme": "orcid" } ], "name": "Chen, Yaocheng", "type": "personal" } }, { "affiliations": [ { "name": "J\u00fclich Research Centre, Ernst Ruska Centre" } ], "person_or_org": { "family_name": "M\u00fcller-Caspary", "given_name": "Knut", "identifiers": [ { "identifier": "0000-0002-2588-7993", "scheme": "orcid" } ], "name": "M\u00fcller-Caspary, Knut", "type": "personal" } }, { "affiliations": [ { "name": "J\u00fclich Research Centre, Ernst Ruska Centre" } ], "person_or_org": { "family_name": "Dunin-Borkowski", "given_name": "Rafal E.", "identifiers": [ { "identifier": "0000-0001-8082-0647", "scheme": "orcid" } ], "name": "Dunin-Borkowski, Rafal E.", "type": "personal" } } ], "description": "LiberTEM is an open source platform for high-throughput distributed processing\nof large-scale binary data sets and live data streams using a modified\nMapReduce programming model. The\ncurrent focus is pixelated\nscanning transmission electron microscopy (STEM)\n[MacLaren et al. (2016),\nOphus (2019)] and scanning electron\nbeam diffraction data.
\nMapReduce-like processing allows to specify an algorithm through two functions:\nOne function that is mapped on portions of the input data, and another function\nthat merges (reduces) a partial result from this mapping step into the complete\nresult. A wide range of TEM and 4D STEM processing tasks can be expressed in\nthis fashion, see Applications.
\nThe UDF interface of LiberTEM offers a standardized, versatile API to decouple\nthe mathematical core of an algorithm from details of data source, parallelism,\nand use of results. Mapping and merging can be performed in any order and with\ndifferent subdivisions of the input data, including running parts of the\ncalculation concurrently. That means the same implementation can be used in a\nwide range of modalities, including massive scaling on clusters. Since each\nmerge step produces an intermediate result, this style of processing is suitable\nfor displaying live results from a running calculation in a GUI application and\nfor processing live data streams.\nA closed-loop feedback between processing and instrument control can be realized\nas well. See User-defined functions for more details on the\nLiberTEM UDF interface.
\nThe LiberTEM back-end offers high throughput and scalability on PCs, single server\nnodes, clusters and cloud services. On clusters it can use fast distributed\nlocal storage on high-performance SSDs. That way it achieves very high\naggregate IO performance on a compact and\ncost-efficient system built from stock components. All CPU cores and CUDA\ndevices in a system can be used in parallel.
\nLiberTEM is supported on Linux, Mac OS X and Windows. Other platforms that allow\ninstallation of a suitable Python version and the required packages will likely\nwork as well. The GUI is running in a web browser.
\nInstallation
The short version:
\n$ virtualenv -p python3 ~/libertem-venv/\n$ source ~/libertem-venv/bin/activate\n(libertem-venv) $ python -m pip install \"libertem[torch]\"\n\n# optional for GPU support\n# See also https://docs.cupy.dev/en/stable/install.html\n(libertem-venv) $ python -m pip install cupy\n\n
Please see our documentation for details!
\nAlternatively, to run the LiberTEM Docker image:
\n$ docker run -p 127.0.0.1:9000:9000 --mount type=bind,source=/path/to/your/data/,dst=/data/,ro ghcr.io/libertem/libertem\n\n
or
\n$ apptainer exec docker://ghcr.io/libertem/libertem /venv/bin/libertem-server\n\n
Deployment for offline data processing on a single-node system for a local user\nis thoroughly tested and can be considered stable. Deployment on a cluster is\nexperimental and still requires some additional work, see Issue #105. Back-end support for live data processing\nis still experimental as well, see https://github.com/LiberTEM/LiberTEM-live.
\nApplications
Since LiberTEM is programmable through user-defined functions (UDFs), it can be used for a wide\nrange of processing tasks on array-like data and data streams. The following\napplications have been implemented already:
\nSome of these applications are available through an interactive web GUI. Please see the\napplications section\nof our documentation for details!
\nThe Python API and user-defined functions (UDFs) can be used for complex\noperations such as arbitrary linear operations and other features like data\nexport. Example Jupyter notebooks are available in the examples directory. If you are having\ntrouble running the examples, please let us know by filing an issue or\nby joining our Gitter chat.
\nLiberTEM is suitable as a high-performance processing backend for other\napplications, including live data streams. Contact us if you are interested!
\nLiberTEM is evolving rapidly and prioritizes features following user demand and\ncontributions. Currently we are working on live data processing, improving application support for sparse\ndata and event-based detectors, performance improvements for GPU processing, and implementing\nanalysis methods for various applications of pixelated\nSTEM and other large-scale detector data. If you like to influence the direction\nthis project is taking, or if you'd like to contribute, please join our\ngitter chat and our general mailing list.
\nFile formats
LiberTEM currently opens most file formats used for pixelated STEM. See our\ngeneral information on loading data and format-specific\ndocumentation for more\ninformation!
\nLive processing and detectors (experimental)
See LiberTEM-live!
\nLicense
LiberTEM is licensed under the MIT license.
\nAcknowledgements
We are very grateful for your continuing support for LiberTEM!
\nSee the acknowledgement page for a list of authors and\ncontributors to LiberTEM and its subprojects. See also our info on funding and industry partners.
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", "description": "Open repository for EU-funded research outputs from Horizon Europe, Euratom, and earlier Framework Programmes.", "funding": [ { "funder": { "id": "00k4n6c32" } } ], "organizations": [ { "id": "00k4n6c32" } ], "page": "The EU Open Research Repository is a Zenodo-community dedicated to fostering open science and enhancing the visibility and accessibility of research outputs funded by the European Union. The community is managed by CERN on behalf of the European Commission.
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