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Simplify pr variability driver #828
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I have verified that the demo 7 results (statistics numbers in output JSON) is not affected and remaining identical. |
I tried to test this code on Gates by cloning this branch, and I found there is an issue to call 'pcmdi_metrics.precip_variability.lib' as below.
I think this issue occurs after updating "pcmdi_metrics" to version 2.1.2. Could you check this issue? |
@msahn thanks for testing the revised scripts. Does that issue occurs with version 2.2.1 as well? |
@msahn could you try |
I have tested it with pmp v2.2.1, and it is still not working, but the error message is changed. Below is the error message. It seems that "precip_variability_across_timescale" is not added in the file "/home/ahn6/anaconda3/envs/pmp_v20220110/lib/python3.9/site-packages/pcmdi_metrics/precip_variability/lib/init.py".
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@msahn helped identifying where the issue was coming from. It looks like once pmp installed through conda-forge, re-installing from cloned repo is not overwriting the pre-installed pmp. One work around is to generate development dedicated conda env (with all dependecies installed but pmp), following here, then install pmp from the cloned repo, to test the branch in development. @msahn, once you confirm that driver is working correctly in your development env, could you please approve your review, so I can merge following the main branch protection protocol? (at least one review required for merging) Thanks! |
I have tested this code in my pmp development env and confirmed that the results are identical to the previous version. |
In this PR I've simplified the pr variability driver by modularizing metric calculation part, in order to easily call from precip benchmarking metrics collective driver.