• Accepted Paper

diffpy.morph: Python tools for model-independent comparisons between sets of one-dimensional functions

Andrew Yang, Christopher L. Farrow, Pavol Juhás, Luis Kitsu Iglesias, Chia-Hao Liu, Samuel D. Marks, Vivian R. K. Wall, Joshua Safin, Sean M. Drewry, Caden Myers, Dillon F. Hanlon, Nicholas Leonard, Cedomir Petrovic, Ahhyun Jeong, Dmitri V. Talapin, Linda F. Nazar, Haidong Zhou, Samuel W. Teitelbaum, Tim B. van Driel, Soham Banerjee, Emil S. Bozin, Michael F. Toney, Katharine Page, Naomi S. Ginsberg, and Simon J. L. Billinge

Phys. Rev. Materials - Accepted 22 July, 2026

DOI: https://doi.org/10.1103/t39r-v3lx

Abstract

diffpy.morph addresses a need to gain scientific insights from 1D scientific spectra in model independent ways. A powerful approach for this is to take differences between pairs of spectra and look for meaningful changes that might indicate underlying chemical, structural, or other modifications. The challenge is that the difference curve may contain uninteresting differences such as experimental inconsistencies and benign physical changes such as the effects of thermal expansion. diffpy.morph allows researchers to apply simple transformations, or ``morphs", to one of the datasets to remove the unwanted differences revealing, when they are present, non-trivial differences. diffpy.morph is an open-source Python package available on the Python Package Index and conda-forge. Here, we describe its functionality and apply it to solve a range of experimental challenges on diffraction and PDF data from x-rays and neutrons, though we note that it may be applied to any 1D function in principle.

Export citation

Export citation

Choose format for download:

Download Citation

If the author has provided any supplemental materials with this article they will be available upon publication of the version of record.

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation