Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Feature Request: Include option for normalisation in "Load and Merge" #1028

Open
mducle opened this issue Oct 29, 2024 · 0 comments
Open

Feature Request: Include option for normalisation in "Load and Merge" #1028

mducle opened this issue Oct 29, 2024 · 0 comments

Comments

@mducle
Copy link
Member

mducle commented Oct 29, 2024

Summary

In the "Data Loading" tab, MSlice has an option to "Load and Merge" data which sums all the selected datafiles and returns a single workspace. It would be good if a normalisation factor for each file could be included somehow. There should be three options for normalisation factors:

  1. User specified
  2. Integrated proton current
  3. Summed of uncertainties

Detailed description.

The "Load" and "Load and Merge" code shares the same load_workspace function code here with a keyword option merge. It internally uses the Mantid Load algorithm but for merge=True passes a single string with + between each filename, taking advantage of Mantid's MultipleFileProperty (docs here to cause Load to sum all the input files. There is no easy way for a normalisation factor to be included in this call, so the implementation will have to load each file manually, apply the normalisation factor and sum the result.

In addition, there is the complication that reduced data files at both ISIS and SNS are already normalised, so this normalisation factor should be "undone" first. E.g. given N workspaces with normalisation factors A1, A2, ... AN, the final workspace intensity should be:

sum_equation

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant