-
Notifications
You must be signed in to change notification settings - Fork 1
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
Ewm6378 fix full masking in reduction #479
Conversation
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## next #479 +/- ##
==========================================
+ Coverage 96.52% 96.53% +0.01%
==========================================
Files 63 63
Lines 4488 4503 +15
==========================================
+ Hits 4332 4347 +15
Misses 156 156 ☔ View full report in Codecov by Sentry. |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Tested and verified Reduction workflow was able to complete even though full mask was applied. Warning messages showed as expected.
* Fix for testing on analysis. * Fixes for test on analysis now that I've used pdb to debug. * Test fixes. * Update code cov * Fix diffcal_masking_script.py * Revert * Revert
Description of work
Within testing the
Reduction Workflow
, it was found that errors occur during execution if a masking workspace is used where all data is masked. This causes many group based recipes withinReductionRecipe.py
.Explanation of work
The solution is to skip any algorithm requiring data for fully masked groups, provide a warning to the user, and ensure the workflow completes successfully. The skipped group will impact future reductions using that mask. Logic to handle checking the mask workspace is added to
ReductionRecipe.py
along with additional logic to handle skipping the group in the case the mask is masking all pixels.To test
Dev testing
diffraction calibration
run number
: 58882convergence threshold
: 0.1bins across peak width
: 10sample
: Silicon_NIST_640D_001grouping
: Columnnormalization:
run number
: 58882background run number
: 58810sample
: Silicon_NIST_640D_001grouping
: Columndiffcal_masking_script.py
within mantid workbench to produce a masking workspace where all pixels are masked.NOTE: This
diffcal_masking_script.py
is broken! I only fixed up till L 133 to get the logic to produce a mask that can be used in testing. I have not fixed the whole cis_script as this is out of scope for this story.MaskWorkspace_2
and then save it to a location easily accessible. I would recommend the Desktop.MaskWorkspace_2
so that it is in ADS.MaskWorkspace_2
. And run.CIS testing
Same as dev testing but don't worry about unit tests.
Link to EWM item
EWM#6378
Verification
Acceptance Criteria
This list is for ease of reference, and does not replace reading the EWM story as part of the review. Verify this list matches the EWM story before reviewing.