Hi Gleb,
Sorry for the trouble. I think we’re not doing a great job on “read standard XY” files – we probably have fairly limited experience with all the software that can produce XY files.
A header like this:
# 2th_deg Intensity
2.0000 37.222
2.0082 37.399
2.0164 36.199
2.0245 35.727
Will work for your file - needing the “#” and then calling “2th” to specify 2-theta.
I think we would be happy to be able to make this better!
FWIW, this should also be able a TIFF file and a correponding PONI calibration file as used by pyFAI.
--Matt
Hello, Could someone, please, send me an example of an XRD file that could be read by the Larch XRD1D viewer? It seems that none of my x-y 2 column files I tried can be read (attached), with or without a header: the error message is attached
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From: Gleb Pokrovski via Ifeffit <ifeffit@millenia.cars.aps.anl.gov>
Date: Tuesday, September 16, 2025 at 6:37 AM
To: ifeffit@millenia.cars.aps.anl.gov <ifeffit@millenia.cars.aps.anl.gov>
Cc: Gleb Pokrovski <gleb.pokrovski@get.omp.eu>
Subject: [Ifeffit] Re: Larch 2025.3.0: Larch XRD1D viewer: reading XRD files
Hello,
Could someone, please, send me an example of an XRD file that could be read by
the Larch XRD1D viewer? It seems that none of my x-y 2 column files I tried can be read (attached), with or without a header:
the error message is attached here as a screen caption.
Should the file header/file itself have a particular syntax/format to be read?
thank you,
with best regards,
Gleb
On 10/09/2025 20:47, Matthew Newville via Ifeffit wrote:
Hi Folks, A new version of Larch and the Larix GUI are now available for download and for automated update. The last message about Larch 2025. 2. 0 was in late May, though there were updates pushed on in late July too. Since then, there have been
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Hi Folks,
A new version of Larch and the Larix GUI are now available for download and for automated update. The last message about Larch 2025.2.0 was in late May, though there were updates pushed on in late July too. Since then, there have been many updates and improvements, especially to the Larix GUI.
A more complete list of changes is at https://github.com/xraypy/xraylarch/releases/tag/2025.3.0 (and see https://github.com/xraypy/xraylarch/releases/tag/2025.2.2 too), but a few of the most obvious changes include:
1. The “List of Groups/Files” in Larix and many related “List of Groups” windows have a richer set of options with the Right Mouse Button. All these actions also now have "keyboard shortcuts" or "accelerators" (Ctrl- / Alt- keys) that do most actions to move and select groups. This allows much faster and easier manipulation of the list of datasets.
2. Configuring lotting options such as linewidths, colors, themes, and so forth is easier and better. The "plot" tab is "Edit Preferences" now has (only) a "Save Plot Configuration" to save the configuration of the current Plot Window #1 (to the file ".larch/wxmplot.yaml"). From the Plot Window, you can configure these settings (themes, colors, etc) for any plot. When you are happy with those, saving them from the Larix Preferences window will save those settings for future sessions.
3. Saving and Loading Session Files is more robust, and saving will happen in the background, without hanging the main window.
4. The main Larix window now has a Title (ie, “Top Window Bar”) that shows the name of the “Current Session File”. You can change that with “Save Session As”. The Plot Windows (or most of them anyway) will have Titles that show this Session File name and the name of the Analysis Panel or Data Task window that generated the plot. If you are running 2 Larix sessions, this makes it much easier to tell what windows go together.
5. On startup, you may be prompted to open recently automatically saved Session files for Sessions that did not exist cleanly. There has long been a list of “autosaved sessions” that you can import, but this will tell you if any session did not close well.
6. 2025.2.0 introduces a Generic XY Data Analysis Panel, for non-XAS data. You can now choose any X, Y arrays for a group as the XY data, and overplot several groups of scaled or unscaled datasets. And the Curve Fit Panel allows pretty generic curve-fitting for X, Y data.
There have been many bug fixes and other improvements, too.
As always, Mauro Rovezzi and Shelly Kelly and her group at the APS deserve a lot of credit for either making or inspiring these changes. There have also been bug reports and pull requests from a growing number of people. The GitHub repository is really the best place for this, but thanks to everyone.
Let us know if you have any questions, comments, or suggestions.
--Matt
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