January 2026 - Ifeffit - millenia.cars.aps.anl.gov

Reminder: X-ray Larch Developer's / Topics in XAS Analysis meeting, Jan 29th
by Matthew Newville 28 Jan '26

28 Jan '26

Hi All, A reminder that we will have an X-ray Larch Developer’s / Topics in XAS Analysis meeting tomorrow, approximately 24 hours from now. Athar Khodabakhsh from Helmholtz-Zentrum Berlin will give a presentation on Machine Learning work with XAS. Time: January 29, at 1500 UTC (4 PM Paris, 9 AM Chicago) Topic: Athar Khodabakhsh, Helmholtz-Zentrum Berlin, Convolutional AutoEncoder for Anomaly Detection and Chemical State Identification in XAS Zoom link: available at https://millenia.cars.aps.anl.gov/xraylarch/meetings/ Hope to see some of you there, --Matt

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XAFS and Andrea Di Cicco on CNN
by Anatoly Frenkel 26 Jan '26

26 Jan '26

Hi all, It was a pleasant surprise to see that XAFS made it to the CNN Business Edition. Furthermore, it is nice to see that Andrea Di Cicco was prominently featured in the article (attached) as well. Anatoly ------------------------------------------------------------------- Anatoly I. Frenkel Professor and Deputy Chair Department of Materials Science and Chemical Engineering Affiliate Professor, Department of Chemistry * Stony Brook University * Stony Brook, NY 11794 Email: anatoly.frenkel(a)stonybrook.edu <https://urldefense.us/v3/__https://mail.bnl.gov/OWA/redir.aspx?C=F6wCGt4adz… > https://urldefense.us/v3/__http://you.stonybrook.edu/frenkel__;!!G_uCfscf7e… Joint Appointment: Senior Chemist Chemistry Division, *Brookhaven National Laboratory* Upton, NY 11973 Email: frenkel(a)bnl.gov https://urldefense.us/v3/__https://www.bnl.gov/staff/frenkel__;!!G_uCfscf7e… -------------------------------------------------------------------

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Numpy error during Upgrade to Larch 2026
by Danilo Oliveira de Souza 23 Jan '26

23 Jan '26

Dear Matt, I tried to upgrade my Larch version to this brand new one, but I faced some issues, which are reported below, concerning the NumPy version used for compilation (1.x) and that one I have installed in my PC (2.4.1). I ran the upgrade using the Anaconda prompt instead of the shortcut ("Update Larch") contained in the Larch folder. As you see on the top of the report, it was suggested to downgrade the Numpy present on my PC, but I'm wondering if there is a less conservative solution for that. Any clue? *A module that was compiled using NumPy 1.x cannot be run inNumPy 2.4.1 as it may crash. To support both 1.x and 2.xversions of NumPy, modules must be compiled with NumPy 2.0.Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.If you are a user of the module, the easiest solution will be todowngrade to 'numpy<2' or try to upgrade the affected module.We expect that some modules will need time to support NumPy 2.Traceback (most recent call last): File "C:\ProgramData\anaconda3\Lib\threading.py", line 1002, in _bootstrap self._bootstrap_inner() File "C:\ProgramData\anaconda3\Lib\threading.py", line 1045, in _bootstrap_inner self.run() File "C:\ProgramData\anaconda3\Lib\threading.py", line 982, in run self._target(*self._args, **self._kwargs) File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\wxxas\larix_app.py", line 58, in importer from larch.wxxas.xasgui import LarixFrame File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\wxxas\xasgui.py", line 28, in <module> from larch.io <https://urldefense.us/v3/__http://larch.io__;!!G_uCfscf7eWS!eDQ14v3BGN9E-bk… > import save_session, read_session File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\io\__init__.py", line 23, in <module> from .gse_mcafile import gsemca_group, GSEMCA_File File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\io\gse_mcafile.py", line 9, in <module> from larch.xrf import MCA, ROI File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\xrf\__init__.py", line 11, in <module> from .mca import MCA, isLarchMCAGroup, Environment, create_mca File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\xrf\mca.py", line 14, in <module> from ..math import interp, index_nearest File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\math\__init__.py", line 5, in <module> import lmfit File "C:\ProgramData\anaconda3\Lib\site-packages\lmfit\__init__.py", line 38, in <module> from .confidence import conf_interval, conf_interval2d File "C:\ProgramData\anaconda3\Lib\site-packages\lmfit\confidence.py", line 10, in <module> from .minimizer import MinimizerException File "C:\ProgramData\anaconda3\Lib\site-packages\lmfit\minimizer.py", line 41, in <module> from .parameter import Parameter, Parameters File "C:\ProgramData\anaconda3\Lib\site-packages\lmfit\parameter.py", line 13, in <module> from .jsonutils import decode4js, encode4js File "C:\ProgramData\anaconda3\Lib\site-packages\lmfit\jsonutils.py", line 15, in <module> from pandas import DataFrame, Series, read_json File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\pandas\__init__.py", line 62, in <module> from pandas.core.api import ( File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\pandas\core\api.py", line 28, in <module> from pandas.core.arrays import Categorical File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\pandas\core\arrays\__init__.py", line 1, in <module> from pandas.core.arrays.arrow import ArrowExtensionArray File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\pandas\core\arrays\arrow\__init__.py", line 5, in <module> from pandas.core.arrays.arrow.array import ArrowExtensionArray File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\pandas\core\arrays\arrow\array.py", line 64, in <module> from pandas.core.arrays.masked import BaseMaskedArray File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\pandas\core\arrays\masked.py", line 60, in <module> from pandas.core import ( File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\pandas\core\nanops.py", line 52, in <module> bn = import_optional_dependency("bottleneck", errors="warn") File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\pandas\compat\_optional.py", line 135, in import_optional_dependency module = importlib.import_module(name) File "C:\ProgramData\anaconda3\Lib\importlib\__init__.py", line 126, in import_module return _bootstrap._gcd_import(name[level:], package, level) File "C:\ProgramData\anaconda3\Lib\site-packages\bottleneck\__init__.py", line 7, in <module> from .move import (move_argmax, move_argmin, move_max, move_mean, move_median,AttributeError: _ARRAY_API not foundException in thread Thread-1 (importer):Traceback (most recent call last): File "C:\ProgramData\anaconda3\Lib\threading.py", line 1045, in _bootstrap_inner self.run() File "C:\ProgramData\anaconda3\Lib\threading.py", line 982, in run self._target(*self._args, **self._kwargs) File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\wxxas\larix_app.py", line 58, in importer from larch.wxxas.xasgui import LarixFrame File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\wxxas\xasgui.py", line 28, in <module> from larch.io <https://urldefense.us/v3/__http://larch.io__;!!G_uCfscf7eWS!eDQ14v3BGN9E-bk… > import save_session, read_session File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\io\__init__.py", line 23, in <module> from .gse_mcafile import gsemca_group, GSEMCA_File File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\io\gse_mcafile.py", line 9, in <module> from larch.xrf import MCA, ROI File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\xrf\__init__.py", line 11, in <module> from .mca import MCA, isLarchMCAGroup, Environment, create_mca File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\xrf\mca.py", line 14, in <module> from ..math import interp, index_nearest File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\math\__init__.py", line 28, in <module> from .pca import pca_train, pca_fit, nmf_train, save_pca_model, read_pca_model File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\math\pca.py", line 16, in <module> from sklearn.decomposition import PCA File "C:\ProgramData\anaconda3\Lib\site-packages\sklearn\__init__.py", line 82, in <module> from .base import clone File "C:\ProgramData\anaconda3\Lib\site-packages\sklearn\base.py", line 17, in <module> from .utils import _IS_32BIT File "C:\ProgramData\anaconda3\Lib\site-packages\sklearn\utils\__init__.py", line 19, in <module> from .murmurhash import murmurhash3_32 File "sklearn\utils\murmurhash.pyx", line 1, in init sklearn.utils.murmurhashValueError: numpy.dtype size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObjectTraceback (most recent call last): File "C:\ProgramData\anaconda3\Lib\site-packages\wx\core.py", line 3425, in <lambda> lambda event: event.callable(*event.args, **event.kw <https://urldefense.us/v3/__http://event.kw__;!!G_uCfscf7eWS!eDQ14v3BGN9E-bk… >) ) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\wxxas\larix_app.py", line 62, in ShowMain from larch.wxxas.xasgui import LarixFrame File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\wxxas\xasgui.py", line 28, in <module> from larch.io <https://urldefense.us/v3/__http://larch.io__;!!G_uCfscf7eWS!eDQ14v3BGN9E-bk… > import save_session, read_session File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\io\__init__.py", line 23, in <module> from .gse_mcafile import gsemca_group, GSEMCA_File File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\io\gse_mcafile.py", line 9, in <module> from larch.xrf import MCA, ROI File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\xrf\__init__.py", line 11, in <module> from .mca import MCA, isLarchMCAGroup, Environment, create_mca File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\xrf\mca.py", line 14, in <module> from ..math import interp, index_nearest File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\math\__init__.py", line 28, in <module> from .pca import pca_train, pca_fit, nmf_train, save_pca_model, read_pca_model File "C:\Users\danil\AppData\Roaming\Python\Python311\site-packages\larch\math\pca.py", line 16, in <module> from sklearn.decomposition import PCA File "C:\ProgramData\anaconda3\Lib\site-packages\sklearn\__init__.py", line 82, in <module> from .base import clone File "C:\ProgramData\anaconda3\Lib\site-packages\sklearn\base.py", line 17, in <module> from .utils import _IS_32BIT File "C:\ProgramData\anaconda3\Lib\site-packages\sklearn\utils\__init__.py", line 19, in <module> from .murmurhash import murmurhash3_32 File "sklearn\utils\murmurhash.pyx", line 1, in init sklearn.utils.murmurhashValueError: numpy.dtype size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObject* Cheers, Danilo OLIVEIRA DE SOUZA

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XrayLarch Developer's / Topics in XAS Analysis meeting, Jan 29th
by Matthew Newville 20 Jan '26

20 Jan '26

Hi Folks, We have had nearly regular Zoom meetings on X-ray Larch Development over the past few years, but have not had one in several months. In discussions with Mauro and others, we would like to bring these meetings back and expand the scope to include focused discussions on selected topics and/or presentations of developments in XAS analysis and data science that might be of interest to Larch users and developers. To start, we’ve invited Athar Khodabakhsh from Helmholtz-Zentrum Berlin to speak on Machine Learning work with XAS, similar to a talk given at the recent DataXAS meeting at ETH Zurich (in association with Paul Scherrer Institute). This meeting will be: January 29, at 1500 UTC (4 PM Paris, 9 AM Chicago) Athar Khodabakhsh, Helmholtz-Zentrum Berlin, Convolutional AutoEncoder for Anomaly Detection and Chemical State Identification in XAS To avoid publishing a Zoom link on this mailing list, the link will be available at https://millenia.cars.aps.anl.gov/xraylarch/meetings/ several hours before the meeting begins. If anyone would like to attend or have the Zoom link, please feel free to contact me. Please let me know if you are interested in giving a presentation or have a suggestion for a topic for discussion. Hope to see you there, --Matthew Newville (newville(a)cars.uchicago.edu)

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Larch 2026.1.0
by Matthew Newville 20 Jan '26

20 Jan '26

Hi Folks, Larch 2026.1.0 is now available and will begin to appear for automatic updates. There have been many fixes made since 2025.3.0 was released (in September). A few of the most important recent changes are: 1. The Larch Desktop folder now includes a shortcut for Jupyter Lab, running in the Python environment with Larch installed. This should make it much easier to run a notebook using Larch. It also includes a Terminal useful for running updates. 2. Many more Jupyter and Python examples are now available, including showing how to plot with wxmplot or Bokeh. Using wxmplot gives the same plots as created with Larix, shown in plot windows exterior to the browser, while using Bokeh shows plots embedded in the browser, but with more built-in interactivity than standard matplotlib plots. 3. In Larix, improvements in reading data, normalization, and copying normalization parameters continue. 4. In Larix, all the panels that “build model to fit data” (Feffit, Pre-edge Peaks, general purpose curve-fitting) now do a much better job of using the latest model for a particular data group and switching between these models when you switch groups. That is, if you have completely different Path models (say, for different edges) in one Session, the Feffit Panel now fully and correctly replaces the Feffit model when selecting each data group. 5. Feff Paths in the Feffit Panel now show a table with the Path geometry, including scattering angles. 6. More release information is at https://urldefense.us/v3/__https://github.com/xraypy/xraylarch/releases/tag… As usual, many of these changes came from Mauro Rovezzi. Thanks to all those who helped with code, bug reports, suggestions, or even just encouragement to continue in these challenging times ;) If you have any trouble, questions, or suggestions, please let us know. We’re planning to start up Larch developer Zoom meetings again, and to expand these discussions to other developed methods. I’ll send out a separate message about that in the next day or so. —Matt Newville

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Help installing Demeter from source
by Joe Graves 16 Jan '26

16 Jan '26

Hello everybody, I'm a graduate student and new to XAFS analysis. I'm trying to install Demeter from source on Linux (Fedora 43). The instructions to do so from Bruce Ravel all point toward the github of Ifeffit, which as I'm sure you all know, doesn't exist anymore as ifeffit has been deprecated in favor of Larch. Are there any updated instructions for installing Demeter from source? Alternatively, can I install Demeter from source using the old instructions, but installing Larch when I would otherwise be instructed to install ifeffit? P.S. I would like to add that that Bruce Ravel's links to the ifeffit mailing list are also all broken. I was able to subscribe when I found the following link using a search engine: https://millenia.cars.aps.anl.gov/mailman3/lists/ifeffit.millenia.cars.aps.… Joe Graves PhD Student, Department of Chemistry Graduate Research Assistant, School of Energy Resources Member of the Moreau Lab

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