/GuidedIntegration

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

Primary LanguagePythonMIT LicenseMIT

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