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Guided automated integration of 2D images to 1D patterns using pyFAI

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GuidedIntegration

Guided automated integration of 2D images to 1D patterns using pyFAI, including both graphical user interface and command line interface options. Guided Integration is a self-contained script with the functionality described below.

Citation: Guided Integration Version 0.1 (2023). https://github.com/adamcorrao/GuidedIntegration
Citation for latest paper on pyFAI: Kieffer, J., Valls, V., Blanc, N. & Hennig, C. (2020). J. Synchrotron Rad. 27, 558-566.

Functionality:

-Guided setup for automated integration of 2D images to 1D patterns using pyFAI
-Loading of integration (.int) text file for routine use (not recommended for 1st time users and those unfamiliar with pyFAI)
-GUI and command line interface options for selecting directories to parse for images to integrate
-Automates creation of separate directories for 1D patterns in a specified directory for each image directory selected
-Saves an editable integration (.int) text file for easy parameter editing and routine use
-Generates a record (.rec) file containing a list of directories parsed, a list of images integrated, and info from .int file**

To do prior to integration:

-Save an instrument geometry file (.poni) from calibration (e.g., pyFAI-calib2)
-Create a mask if needed (e.g., for detector edges, beamstop, dead pixels) and save as one of the following filetypes: *.tif | *.edf | *.npy | *.msk

Required libraries:

-Scientific python libraries (e.g., numpy, pandas)
-pyFAI (& all dependencies)
-tkfilebrowser
-tqdm

Notes to user:

-NSLS-II filepath assumes 2D images are in subfolders as follows: tiff_base/samplename/dark_sub
-APS/SSRL filepath has options for 2D images contained in a single directory or multiple

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