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9 rows where author_association = "CONTRIBUTOR", issue = 144920646 and user = 4295853 sorted by updated_at descending

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  • pwolfram · 9 ✖

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  • Adds cummulative operators to API · 9 ✖

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  • CONTRIBUTOR · 9 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
251146483 https://github.com/pydata/xarray/pull/812#issuecomment-251146483 https://api.github.com/repos/pydata/xarray/issues/812 MDEyOklzc3VlQ29tbWVudDI1MTE0NjQ4Mw== pwolfram 4295853 2016-10-03T15:58:57Z 2016-10-03T15:58:57Z CONTRIBUTOR

@shoyer, is this what you were thinking?

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  Adds cummulative operators to API  144920646
250564105 https://github.com/pydata/xarray/pull/812#issuecomment-250564105 https://api.github.com/repos/pydata/xarray/issues/812 MDEyOklzc3VlQ29tbWVudDI1MDU2NDEwNQ== pwolfram 4295853 2016-09-29T19:16:49Z 2016-09-29T19:16:49Z CONTRIBUTOR

@shoyer, I think this fixes the concerns you raised including the testing. Thanks for all the tips!

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  Adds cummulative operators to API  144920646
248738854 https://github.com/pydata/xarray/pull/812#issuecomment-248738854 https://api.github.com/repos/pydata/xarray/issues/812 MDEyOklzc3VlQ29tbWVudDI0ODczODg1NA== pwolfram 4295853 2016-09-21T20:50:36Z 2016-09-21T20:50:36Z CONTRIBUTOR

@shoyer, this should be ready for another review. I also tested it with this somewhat hacky code at https://gist.github.com/a329d441fe99ae342a34b1a374650138. It may be good to get some type of test like this into the test suite. However, the correct location for testing these methods, in general, is not transparent to me. It doesn't look like we broadly check reduction operations with nans, e.g., prod outside the test_variable.py file. I have made additions here but broader testing may be useful.

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  Adds cummulative operators to API  144920646
248459706 https://github.com/pydata/xarray/pull/812#issuecomment-248459706 https://api.github.com/repos/pydata/xarray/issues/812 MDEyOklzc3VlQ29tbWVudDI0ODQ1OTcwNg== pwolfram 4295853 2016-09-20T22:51:14Z 2016-09-20T22:51:14Z CONTRIBUTOR

@shoyer, @jhamman, and @MaximilianR this should be ready for a preliminary review because it works. The key thing missing is a check for dask version and potentially more testing. Thoughts on these issues are greatly appreciated.

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  Adds cummulative operators to API  144920646
248402441 https://github.com/pydata/xarray/pull/812#issuecomment-248402441 https://api.github.com/repos/pydata/xarray/issues/812 MDEyOklzc3VlQ29tbWVudDI0ODQwMjQ0MQ== pwolfram 4295853 2016-09-20T19:13:02Z 2016-09-20T19:13:59Z CONTRIBUTOR

@shoyer and @jhamman here is the general use of the cumsum and cumprod operators. Note, I probably need to have some type of error checking for the dask version (e.g., we require a version of dask with nancumsum, nanprod, and nancumprod). What is the standard way to do this?

For example, dask 0.11.0 works but dask 0.8.1 does not and returns an error.

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  Adds cummulative operators to API  144920646
218446442 https://github.com/pydata/xarray/pull/812#issuecomment-218446442 https://api.github.com/repos/pydata/xarray/issues/812 MDEyOklzc3VlQ29tbWVudDIxODQ0NjQ0Mg== pwolfram 4295853 2016-05-11T12:37:05Z 2016-05-11T12:37:05Z CONTRIBUTOR

@jhamman, I need to get back to this when I can make the time but will let you know if I have more trouble. Thanks for following up.

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  Adds cummulative operators to API  144920646
207066906 https://github.com/pydata/xarray/pull/812#issuecomment-207066906 https://api.github.com/repos/pydata/xarray/issues/812 MDEyOklzc3VlQ29tbWVudDIwNzA2NjkwNg== pwolfram 4295853 2016-04-07T19:59:35Z 2016-04-07T23:00:18Z CONTRIBUTOR

@shoyer, it looks like I'll need to have a _reduce_method-like method that doesn't reduce the dimensions, e.g., https://github.com/pydata/xarray/blob/master/xarray/core/common.py#L11. I haven't been able to get the current branch to work properly (it returns a numpy array vs xarray datatype) and seem to be something missing. Am I on the right track that I need to add a new abstract method? This seems overly complicated but I haven't been able to get this to work cleanly otherwise, e.g., trying things like

python f = _func_slash_method_wrapper(method, name) setattr(cls, name, cls._binary_op(f))

Some advice or help to get me out of my naivete would be greatly appreciated. Thanks!

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  Adds cummulative operators to API  144920646
204587229 https://github.com/pydata/xarray/pull/812#issuecomment-204587229 https://api.github.com/repos/pydata/xarray/issues/812 MDEyOklzc3VlQ29tbWVudDIwNDU4NzIyOQ== pwolfram 4295853 2016-04-01T22:07:59Z 2016-04-01T22:07:59Z CONTRIBUTOR

@shoyer see https://github.com/dask/dask/pull/1077 for the nancumsum and nancumprod dask PR

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  Adds cummulative operators to API  144920646
203970695 https://github.com/pydata/xarray/pull/812#issuecomment-203970695 https://api.github.com/repos/pydata/xarray/issues/812 MDEyOklzc3VlQ29tbWVudDIwMzk3MDY5NQ== pwolfram 4295853 2016-03-31T14:44:51Z 2016-03-31T14:44:51Z CONTRIBUTOR

@mrocklin and @shoyer, will we need to modify the definitions for nanprod, nancumsum, and nancumprod in dask for this to work in multi-threaded mode? I took a quick look and it appears they are defined https://github.com/dask/dask/blob/d82cf2ac3fa3a61912b7934afe7b2fe9e14cc4ff/dask/array/init.py#L17-L22 so I'm assuming xarray/dask should just work once the issues on the xarray end are resolved but just wanted to double check to make sure this is the case.

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  Adds cummulative operators to API  144920646

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