Dear Matt, I have a question and a comment regarding Larch. I would appreciate if you could have a look. 1) The flattening algorithm for XAS in Larch works differently with respect to Athena when linear post-edge function is used for normalization. In Larch the normalized spectrum is always fitted by a parabola for flattening, no matter which function was used for normalization. It works fine when the post-edge function is also a parabola, but when it is a straight line, the resulting flattened spectrum does not stick to Y=1, as it is expected to do (and as it does in Athena). My question is: is it a bug or a feature? Just in case, I made some minor modifications in the pre_edge.py file that allow to get the same results as in Athena when linear post-edge is used. Maybe these corrections are a bit clumsy, but it seems to work. If anyone needs, I can share. 2) There is a typo in the larch web-manual in the description of the nnorm parameter of the pre_edge() function. It is stated that it is the number of terms in the fitting polynomial (i.e., 1+degree) whereas it seems that it is just its degree. So, nnorm=1 corresponds to a linear function and nnorm=2 to quadratic. In the gui help it is partially corrected, but the phrase "Default=3 (quadratic)" stays. It is not critical at all, but may be misleading for beginners... Using the possibility, I would like to thank you for all the great work you are doing on Larch. It really helps for large datasets! All the best, Kirill -- Dr. Kirill A. Lomachenko Scientist at BM23/ID24 beamlines European Synchrotron Radiation Facility 71 avenue des Martyrs CS 40220 38043 Grenoble Cedex 9, France Tel: +33 438 88 19 14 www.esrf.eu