leonarski_f
9c543f60b6
The home page introduces Rugnux, the viewer and the acquisition system in three cards, with the licence stated once, and the sidebar is regrouped by program: what a user of Rugnux or the viewer needs comes first, and the algorithms, formats, interfaces, hardware and FPGA pages sit under one collapsed "Technical reference" hub (TECHNICAL.md). No page moves, so every existing URL stays. Download pages (RUGNUX_DOWNLOAD.md, VIEWER_DOWNLOAD.md) are rendered by a small Sphinx extension (docs/_ext/jfjoch_downloads.py) from the `release` in conf.py, which update_version.sh rewrites, so no version string on them is maintained by hand; a script then asks the Gitea API for the newest published release and repoints the buttons at its assets, naming any archive that release does not carry. Without network access the build-time links stand. JUNGFRAUJOCH.md is the landing page of the acquisition side with its install pointers. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu (cherry picked from commit 050442592504ce879dc51d78b6d3d1c58268a800)
53 lines
2.6 KiB
Markdown
53 lines
2.6 KiB
Markdown
# Download the Jungfraujoch Viewer
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`jfjoch_viewer` is a standalone desktop application, pre-built for Linux, macOS and Windows with
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the Qt runtime included. The links point at the current release; the full list of what each release
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ships is on its release page.
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```{eval-rst}
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.. jfjoch-downloads:: viewer
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```
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On a machine with an NVIDIA GPU take the **GPU** build: its embedded spot finding, indexing and
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integration run on the card, and it also starts on a machine without one, on the CPU. The **CPU
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only** build runs the same pipeline at lower throughput and is the smaller download. A V100 needs
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the CUDA 12 build; the CUDA 13 builds start at Turing (T4) — see
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[Release contents](RELEASE_CONTENTS.md#gpu-generations-and-the-nvidia-driver).
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## After downloading
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**Linux.** The archive has no top-level directory, so unpack it into a directory of its own, then
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run the program from its `bin/`:
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```
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mkdir -p ~/jfjoch_viewer
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tar xzf jfjoch_viewer-<version>-linux-cuda12.tgz -C ~/jfjoch_viewer
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~/jfjoch_viewer/bin/jfjoch_viewer dataset_master.h5
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```
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The archive also carries the desktop entry, icon and D-Bus service file under `share/`, which the
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desktop picks up when the archive is unpacked into a prefix it searches, such as `/usr/local`. The
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Linux repositories carry the viewer as the `jfjoch-viewer` package as well
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([package repositories](REPOSITORIES.md)).
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**macOS.** Open the disk image and drag `jfjoch_viewer` onto the *Applications* shortcut next to
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it. The image is signed and notarized by Apple, so it opens like any other application. Apple
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Silicon only; Intel Macs are not supported.
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**Windows.** Run the installer. The CUDA and CPU variants share one install directory and replace
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each other, and are told apart in *Add/Remove Programs* as *Jungfraujoch (CUDA)* and *Jungfraujoch
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(CPU)*.
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Then **File ▸ Open** a Jungfraujoch or NXmx master file, a `_process.h5` written by Rugnux, or any
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frame of a miniCBF, marCCD or SMV sweep; **File ▸ Open HTTP** follows a live collection from a
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running broker. [jfjoch_viewer](JFJOCH_VIEWER.md) is the manual, with a
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[guided tour](JFJOCH_VIEWER.md#a-guided-tour) of the four views most people use.
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## From source
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The viewer builds on Linux, Windows (MSVC and CUDA) and macOS; Qt 6 is the one dependency that
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has to be installed first, everything else is fetched by the configure. See
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[Building from source on Windows](JFJOCH_VIEWER.md#building-from-source-on-windows) and
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[on macOS](JFJOCH_VIEWER.md#building-from-source-on-macos); on Linux configure the full tree with
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`-DJFJOCH_VIEWER_BUILD=ON` ([Deployment](DEPLOYMENT.md#install-jungfraujoch-image-viewer)).
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