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Github user OCWJenkins commented on the
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Github user OCWJenkins commented on the pull request:
https://github.com/apache/climate/pull/213#issuecomment-126522551
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ASF GitHub Bot commented on CLIMATE-650:
GitHub user huikyole opened a pull
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ASF GitHub Bot commented on CLIMATE-650:
Github user OCWJenkins commented on the
Github user OCWJenkins commented on the pull request:
https://github.com/apache/climate/pull/215#issuecomment-126527638
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Github user OCWJenkins commented on the pull request:
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GitHub user huikyole opened a pull request:
https://github.com/apache/climate/pull/214
CLIMATE-648 - Propagation of missing data information from each dataset
A new module ocw.dataset_processor.mask_missing_data has been added. Any
missing data flag is propagated into the all
Github user OCWJenkins commented on the pull request:
https://github.com/apache/climate/pull/214#issuecomment-126524007
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Huikyo Lee created CLIMATE-649:
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Summary: Update bias calculation in CLI
Key: CLIMATE-649
URL: https://issues.apache.org/jira/browse/CLIMATE-649
Project: Apache Open Climate Workbench
Issue
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ASF GitHub Bot commented on CLIMATE-650:
Github user OCWJenkins commented on the
GitHub user huikyole opened a pull request:
https://github.com/apache/climate/pull/213
CLIMATE-643 - Updating unit conversion function
In many cases, observational and model datasets have different units for
the same variable. We need to update variable_unit_conversion module is
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ASF GitHub Bot commented on CLIMATE-643:
GitHub user huikyole opened a pull
Github user OCWJenkins commented on the pull request:
https://github.com/apache/climate/pull/213#issuecomment-126522358
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Huikyo Lee created CLIMATE-650:
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Summary: Fix the ensemble calculation
Key: CLIMATE-650
URL: https://issues.apache.org/jira/browse/CLIMATE-650
Project: Apache Open Climate Workbench
Issue Type:
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ASF GitHub Bot commented on CLIMATE-643:
Github user OCWJenkins commented on the
GitHub user huikyole opened a pull request:
https://github.com/apache/climate/pull/215
CLIMATE-650 - Fix the ensemble calculation
- Fix: ocw.dataset_processor.ensemble now uses numpy.ma.mean instead of
numpy.mean to properly handle missing values.
You can merge this pull request
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Huikyo Lee updated CLIMATE-643:
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Description: In many cases, observational and model datasets have different
units for the same
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ASF GitHub Bot commented on CLIMATE-643:
Github user huikyole closed the pull
Github user huikyole closed the pull request at:
https://github.com/apache/climate/pull/210
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Huikyo Lee created CLIMATE-648:
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Summary: Propagation of missing data information from each dataset
Key: CLIMATE-648
URL: https://issues.apache.org/jira/browse/CLIMATE-648
Project: Apache Open Climate
Github user huikyole commented on the pull request:
https://github.com/apache/climate/pull/210#issuecomment-126383587
@MJJoyce I understand your concerns. However, updating examples was
impossible without adding new modules to the dataset_processor. CLI is also
using the code based
Github user MJJoyce commented on the pull request:
https://github.com/apache/climate/pull/210#issuecomment-126403057
If the changes build off one another just separate them out into different
feature branches and merge/rebase according during the dev work. Otherwise we
end up with
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ASF GitHub Bot commented on CLIMATE-643:
Github user huikyole commented on the
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ASF GitHub Bot commented on CLIMATE-643:
Github user MJJoyce commented on the
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ASF GitHub Bot commented on CLIMATE-643:
Github user MJJoyce commented on the
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ASF GitHub Bot commented on CLIMATE-648:
GitHub user huikyole opened a pull
Github user OCWJenkins commented on the pull request:
https://github.com/apache/climate/pull/214#issuecomment-126523998
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ASF GitHub Bot commented on CLIMATE-648:
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Github user OCWJenkins commented on the
Github user OCWJenkins commented on the pull request:
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Github user MJJoyce commented on the pull request:
https://github.com/apache/climate/pull/210#issuecomment-126409195
To give you an idea of what I'm talking about here @huikyole in case it's
confusing. Here's an example of how I would have broken these down into
multiple tickets and
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