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Fixing requisites for bao generic with different kinds of observables #344
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Thanks, the tests are failing, but probably just a trivial whitespace issue. |
Shouldn't it be something like this?
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Codecov ReportAttention:
❗ Your organization needs to install the Codecov GitHub app to enable full functionality. Additional details and impacted files@@ Coverage Diff @@
## master #344 +/- ##
==========================================
- Coverage 81.78% 81.75% -0.03%
==========================================
Files 133 133
Lines 11033 11039 +6
==========================================
+ Hits 9023 9025 +2
- Misses 2010 2014 +4 ☔ View full report in Codecov by Sentry. |
Yes, thank you @cmbant for pointing this out. It needs to be
For the time being, all the checks have passed. Please let me know if you prefer all commit history squashed into one. If not, then I will submit the pull request. |
Thanks, why do you need to check it is dict - aren't they all dict? Don't worry about squash, we do that when merging. |
I think rdrag's value ( |
None is caught by the "if v is not None", the whole of {"rdrag":None} is a dict insance? |
(if you have a simple test, it would be good to add it to the unit tests along with the other bao tests) |
…g a bug in bao base_class for inversion of covariance matrix with only one observable.
In case of I've created a basic test using mock data for mixed observables, similar to 'test_generic_camb`, which requires a mock mean and data. Please let me know if this is okay or if you have something different in mind. |
Thanks, probably just need to update BAO's github_release": to "v2.3" for new data tests to pass. |
I am not sure why tests are failing. I did not touch any camb-related files. |
Yeah, weird - I'm sure it's nothing to do with this PR. |
I think it was just a temporary github issue, seems to pass now. Thanks for the PR! |
Fixing computation of requisites for generic BAO when supplied with measurements_file that contains different kinds of observables at several redshifts. To validate the logic, I tested it on the dummy file in the attachment. The older version incorrectly returns
{'angular_diameter_distance': {'z': array([2.34])}, 'Hubble': {'z': array([2.34])}, 'rdrag': None, 'fsigma8': {'z': array([2.34])}}
.bao_mean_check.txt