Closed johnomotani closed 4 years ago
Hello @johnomotani! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found:
There are currently no PEP 8 issues detected in this Pull Request. Cheers! :beers:
Merging #89 into master will increase coverage by
0.09%
. The diff coverage is100%
.
@@ Coverage Diff @@
## master #89 +/- ##
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+ Coverage 47.55% 47.65% +0.09%
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Files 11 11
Lines 1062 1064 +2
Branches 212 213 +1
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+ Hits 505 507 +2
Misses 496 496
Partials 61 61
Impacted Files | Coverage Δ | |
---|---|---|
xbout/load.py | 75.31% <100%> (+0.2%) |
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How can you solve the problem of inconsistent variables between datasets without passing drop_variables to open_boutdataset?
Ah, I'd assumed it was possible in defining something like an open_stormdataset
function, but not actually thought about how. Using a drop_variables
argument of open_boutdataset
is indeed probably the thing to do. I'll fix the comment.
For anyone reading this in future - I actually don't think it's possible to do this at all without using the drop_variables
argument, because otherwise xarray will never perform the merge. Instead do this
# replace 'storm' with whatever your physics model is
def open_stormdataset(datapath=...)
inconsistent_storm_vars_to_drop = ['var1', 'var2', ...]
ds = open_boutdataset(datapath=..., drop_variables=inconsistent_storm_vars_to_drop)
sd = add_storm_specific_coords(ds)
return sd
(We should write a docs page about how to do this - and accessors - for your own BOUT++ physics model.)
Allow user to ignore model-specific variables that may not be consistent between files. Ideally the user should not have to do this by hand, so a model-specific function, e.g.
open_stormdataset
would handle the list of possibly-inconsistent variables for that model.