Roadmap

Requests from August 14, 2017 APS User Meeting

• Change spot mask size on the fly (implemented)

• Add are you sure question before Calibrate All (make conditional on number of images?)

• Legend for powder diffraction plots [like G(r)]
  • add legend string for powder diffraction entries that defaults to PWDR name

• Set colors for powder diffraction plots by color map (implemented)

• Document how metadata is picked up in image reading

• Subtraction of powder patterns: modify so that one pattern can be subtracted from many

• Dark image subtraction: want to automatically scale image by transmission factor which needs to be picked up from image metadata (Steven W.)

• Autointegration: export to CHI files is always 2theta, not Q.

• Masks: deleting spot masks sometimes does not seem to work smoothly

• Speed up image integration when there are lots of masks (Kamila will provide an example)

• Improve subtraction of background powder patterns (done: new option in Histogram/Background? tree)

Other topics:

• Sequential refinement: would like to refine different sets of atomic parameters for different histograms (this would likely require significant restructuring)

• Implement gain map for images (probably better done as part of data collection process in AreaDetector? or QAVG)

PDF Modeling:

Two important needs for PDF modeling capabilities in G2 include combined PDF/Rietveld fitting to model defect structures and the ability to compute a PDF for a crystalline model would allow that to be subtracted from the PDF to give a partial PDF for non-crystalline phases

Create conda-constructor packages for Mac (done), Linux and Windows that install GSAS-II with a single download.

An initial goal is to import structures along with their distortion parameters from IsoDistort, but there might be something more general here.

GSAS-II at present requires Python 2.7 and wxPython 2.8 through 3.0. We are working through the code to make it compatible with the reworked wxPython (Phoenix, 4.x) implementation as well as make changes to make the code compatible with Python 3.6.

The goal is to provide the capability to perform GSAS-II refinements via Python scripts, without having to use the GSAS-II graphical user interface interactively.