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- toddrjen · 23 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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792225152 | https://github.com/pydata/xarray/pull/4622#issuecomment-792225152 | https://api.github.com/repos/pydata/xarray/issues/4622 | MDEyOklzc3VlQ29tbWVudDc5MjIyNTE1Mg== | toddrjen 2272878 | 2021-03-07T06:20:08Z | 2021-03-07T06:20:08Z | CONTRIBUTOR | All tests now pass as well. |
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Add additional str accessor methods for DataArray 753097418 | |
791878249 | https://github.com/pydata/xarray/pull/4622#issuecomment-791878249 | https://api.github.com/repos/pydata/xarray/issues/4622 | MDEyOklzc3VlQ29tbWVudDc5MTg3ODI0OQ== | toddrjen 2272878 | 2021-03-06T05:41:39Z | 2021-03-06T05:41:39Z | CONTRIBUTOR | The version here should be complete, in that all planned features are implemented, although of course there may be additional changes. So I removed the |
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Add additional str accessor methods for DataArray 753097418 | |
752865024 | https://github.com/pydata/xarray/pull/4622#issuecomment-752865024 | https://api.github.com/repos/pydata/xarray/issues/4622 | MDEyOklzc3VlQ29tbWVudDc1Mjg2NTAyNA== | toddrjen 2272878 | 2020-12-31T06:43:42Z | 2020-12-31T06:43:42Z | CONTRIBUTOR | The latest version I just pushed should have the requested changes. It also has |
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Add additional str accessor methods for DataArray 753097418 | |
751952795 | https://github.com/pydata/xarray/pull/4622#issuecomment-751952795 | https://api.github.com/repos/pydata/xarray/issues/4622 | MDEyOklzc3VlQ29tbWVudDc1MTk1Mjc5NQ== | toddrjen 2272878 | 2020-12-29T05:34:47Z | 2020-12-29T05:34:47Z | CONTRIBUTOR | @keewis Thanks for the suggestions. I will add everything to the relevant documentation when I have everything completed and the changes are agreed upon. |
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Add additional str accessor methods for DataArray 753097418 | |
750419141 | https://github.com/pydata/xarray/issues/4727#issuecomment-750419141 | https://api.github.com/repos/pydata/xarray/issues/4727 | MDEyOklzc3VlQ29tbWVudDc1MDQxOTE0MQ== | toddrjen 2272878 | 2020-12-23T18:23:20Z | 2020-12-23T18:23:20Z | CONTRIBUTOR | My concern with If the default for Also, just checking dtype won't be sufficient in all cases. Consider this: ```Python import numpy as np import xarray as xr a = xr.DataArray(np.array(1.0, dtype=np.object)) xr.testing.assert_identical(a, b) I think for the purpose of testing being able to make sure the result is exactly what you expect is important. |
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xr.testing.assert_equal does not test for dtype 773750763 | |
749887341 | https://github.com/pydata/xarray/pull/4622#issuecomment-749887341 | https://api.github.com/repos/pydata/xarray/issues/4622 | MDEyOklzc3VlQ29tbWVudDc0OTg4NzM0MQ== | toddrjen 2272878 | 2020-12-23T02:24:39Z | 2020-12-23T02:24:39Z | CONTRIBUTOR | @mathause One possibility might be to make |
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Add additional str accessor methods for DataArray 753097418 | |
749311511 | https://github.com/pydata/xarray/pull/4622#issuecomment-749311511 | https://api.github.com/repos/pydata/xarray/issues/4622 | MDEyOklzc3VlQ29tbWVudDc0OTMxMTUxMQ== | toddrjen 2272878 | 2020-12-22T03:04:48Z | 2020-12-22T03:04:48Z | CONTRIBUTOR | @mathause Sorry for the delay, I have been swamped at work. I probably won't have any time to work on this before Christmas. I have finished implementing the I am currently working on improving the vectorization of some of the functions. The idea is that some arguments, like for example the regular expression pattern or the number of repetitions in rep, will be able to be given an array-like, with the dimensions being broadcast against the original DataArray. This can be useful, for example, if a DataArray combines data of different formats along a dimension (ideally this wouldn't be the case but people don't always have that much control over the data they get). Or it could be used to create an ASCII bar chart where the number of symbols is equal to the value in an array element.
Yes, but I think it would be strange if using the default parameters once works fine, but using them twice or more in a row somehow returns an exception. I think the defaults should either work generally or not be defaults at all. That is just my opinion. More fundamentally, it is just inconsistent with how xarray works elsewhere and so I think it would be unexpected.
Please point out the specific cases if you haven't already done so.
I will add this.
It doesn't work with an object dtype: ```python
This does not raise an exception on my machine at least. I ran into several cases where I was incorrectly getting object dtypes and the tests weren't catching it, hence the dtype checks. |
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Add additional str accessor methods for DataArray 753097418 | |
737625900 | https://github.com/pydata/xarray/pull/4622#issuecomment-737625900 | https://api.github.com/repos/pydata/xarray/issues/4622 | MDEyOklzc3VlQ29tbWVudDczNzYyNTkwMA== | toddrjen 2272878 | 2020-12-03T02:42:24Z | 2020-12-03T02:42:24Z | CONTRIBUTOR |
I thought about doing this at first. However, this could lead to conflicts if the DataArray already has a dimension with that name, which would be a particular problem if people chained together multiple such operations. So I checked what default name xarray uses elsewhere, and it doesn't seem to use default names for the most part (the main exception being DataArray creation). So I think that, in order to avoid unexpected behavior, and to keep consistency, not automatically choosing a name is a better option. |
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Add additional str accessor methods for DataArray 753097418 | |
605542337 | https://github.com/pydata/xarray/pull/3871#issuecomment-605542337 | https://api.github.com/repos/pydata/xarray/issues/3871 | MDEyOklzc3VlQ29tbWVudDYwNTU0MjMzNw== | toddrjen 2272878 | 2020-03-29T01:18:37Z | 2020-03-29T01:18:37Z | CONTRIBUTOR | I have gone over it one more time and made a few documentation fixes. Please take one more look before merging. |
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Implement idxmax and idxmin functions 584837010 | |
605375373 | https://github.com/pydata/xarray/pull/3871#issuecomment-605375373 | https://api.github.com/repos/pydata/xarray/issues/3871 | MDEyOklzc3VlQ29tbWVudDYwNTM3NTM3Mw== | toddrjen 2272878 | 2020-03-28T01:32:00Z | 2020-03-28T01:32:00Z | CONTRIBUTOR | Here is a new commit with the discussed changes. |
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Implement idxmax and idxmin functions 584837010 | |
604798935 | https://github.com/pydata/xarray/pull/3871#issuecomment-604798935 | https://api.github.com/repos/pydata/xarray/issues/3871 | MDEyOklzc3VlQ29tbWVudDYwNDc5ODkzNQ== | toddrjen 2272878 | 2020-03-27T03:41:56Z | 2020-03-27T03:41:56Z | CONTRIBUTOR | I think I have implemented all the requested changes and all tests are passing. Please take a look. |
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Implement idxmax and idxmin functions 584837010 | |
604791067 | https://github.com/pydata/xarray/issues/3899#issuecomment-604791067 | https://api.github.com/repos/pydata/xarray/issues/3899 | MDEyOklzc3VlQ29tbWVudDYwNDc5MTA2Nw== | toddrjen 2272878 | 2020-03-27T03:06:32Z | 2020-03-27T03:06:32Z | CONTRIBUTOR | My pull request #3871 has a fix already. |
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_indexes of DataArray are not deep copied 588821932 | |
604775165 | https://github.com/pydata/xarray/issues/3884#issuecomment-604775165 | https://api.github.com/repos/pydata/xarray/issues/3884 | MDEyOklzc3VlQ29tbWVudDYwNDc3NTE2NQ== | toddrjen 2272878 | 2020-03-27T01:57:44Z | 2020-03-27T01:57:44Z | CONTRIBUTOR | @shoyer xarray uses bottleneck for that if it can in |
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Allow for All-NaN in argmax, argmin 587062505 | |
604462268 | https://github.com/pydata/xarray/pull/3871#issuecomment-604462268 | https://api.github.com/repos/pydata/xarray/issues/3871 | MDEyOklzc3VlQ29tbWVudDYwNDQ2MjI2OA== | toddrjen 2272878 | 2020-03-26T14:28:04Z | 2020-03-26T14:28:04Z | CONTRIBUTOR | I figured out what is going wrong. I will make a commit with a fix and include it in this pull request later today. |
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Implement idxmax and idxmin functions 584837010 | |
604226585 | https://github.com/pydata/xarray/pull/3871#issuecomment-604226585 | https://api.github.com/repos/pydata/xarray/issues/3871 | MDEyOklzc3VlQ29tbWVudDYwNDIyNjU4NQ== | toddrjen 2272878 | 2020-03-26T04:46:07Z | 2020-03-26T04:46:07Z | CONTRIBUTOR | I am not sure why the tests are suddenly failing. The tests were all working, then I rebased on the latest master and they are failing and I can't figure out why. |
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Implement idxmax and idxmin functions 584837010 | |
604220730 | https://github.com/pydata/xarray/issues/3884#issuecomment-604220730 | https://api.github.com/repos/pydata/xarray/issues/3884 | MDEyOklzc3VlQ29tbWVudDYwNDIyMDczMA== | toddrjen 2272878 | 2020-03-26T04:22:18Z | 2020-03-26T04:22:18Z | CONTRIBUTOR | The problem I had when implementing |
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Allow for All-NaN in argmax, argmin 587062505 | |
604219688 | https://github.com/pydata/xarray/pull/3871#issuecomment-604219688 | https://api.github.com/repos/pydata/xarray/issues/3871 | MDEyOklzc3VlQ29tbWVudDYwNDIxOTY4OA== | toddrjen 2272878 | 2020-03-26T04:17:55Z | 2020-03-26T04:17:55Z | CONTRIBUTOR | Please see the newest version with the |
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Implement idxmax and idxmin functions 584837010 | |
603900793 | https://github.com/pydata/xarray/pull/3871#issuecomment-603900793 | https://api.github.com/repos/pydata/xarray/issues/3871 | MDEyOklzc3VlQ29tbWVudDYwMzkwMDc5Mw== | toddrjen 2272878 | 2020-03-25T15:19:01Z | 2020-03-25T15:19:01Z | CONTRIBUTOR | That could work. The corner case we would need to decide on is again promotion. What happens if the fill value is a "higher" type in the numeric tower than the original type? What if it is lower?
What if someone tries to use a string type for numeric data or vice versus? If we do option 1 that is easy. Otherwise we probably need to use numpy casting rules? What about an object dtype fill value? What about a date/time regard dtype? On Mon, Mar 23, 2020, 23:49 Stephan Hoyer notifications@github.com wrote:
|
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Implement idxmax and idxmin functions 584837010 | |
602134329 | https://github.com/pydata/xarray/pull/3871#issuecomment-602134329 | https://api.github.com/repos/pydata/xarray/issues/3871 | MDEyOklzc3VlQ29tbWVudDYwMjEzNDMyOQ== | toddrjen 2272878 | 2020-03-22T01:45:05Z | 2020-03-22T01:45:05Z | CONTRIBUTOR | I fixed the extra space in the docstring and moved the business logic to |
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Implement idxmax and idxmin functions 584837010 | |
601982212 | https://github.com/pydata/xarray/pull/3871#issuecomment-601982212 | https://api.github.com/repos/pydata/xarray/issues/3871 | MDEyOklzc3VlQ29tbWVudDYwMTk4MjIxMg== | toddrjen 2272878 | 2020-03-21T02:41:23Z | 2020-03-21T02:41:23Z | CONTRIBUTOR | @max-sixty
I am not familiar with non-index coordinates, what are those? Do you mean non-dimension coordinates? Does that even make sense in a general way? If they are 1D and tied to just one dimension coordinate that could be done, but if they are not tied to any dimension or tied to multiple dimensions or otherwise not 1D I am not sure what it would mean to take the idxmin/idxmax of them. |
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Implement idxmax and idxmin functions 584837010 | |
601979282 | https://github.com/pydata/xarray/pull/3871#issuecomment-601979282 | https://api.github.com/repos/pydata/xarray/issues/3871 | MDEyOklzc3VlQ29tbWVudDYwMTk3OTI4Mg== | toddrjen 2272878 | 2020-03-21T02:16:27Z | 2020-03-21T02:16:27Z | CONTRIBUTOR | @keewis @max-sixty The new commit with the requested changes has been pushed to this branch (except for the |
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Implement idxmax and idxmin functions 584837010 | |
601947199 | https://github.com/pydata/xarray/pull/3871#issuecomment-601947199 | https://api.github.com/repos/pydata/xarray/issues/3871 | MDEyOklzc3VlQ29tbWVudDYwMTk0NzE5OQ== | toddrjen 2272878 | 2020-03-20T23:06:45Z | 2020-03-20T23:06:45Z | CONTRIBUTOR | @keewis @max-sixty The map thing is purely a convenience function. I know there are other ways to do it, but since I thought this would be a useful feature for users in its own right, I did it that way. But of course I can do it another way if you disagree. The one complication is that using I will address the other comments inline. |
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Implement idxmax and idxmin functions 584837010 | |
597253762 | https://github.com/pydata/xarray/issues/3855#issuecomment-597253762 | https://api.github.com/repos/pydata/xarray/issues/3855 | MDEyOklzc3VlQ29tbWVudDU5NzI1Mzc2Mg== | toddrjen 2272878 | 2020-03-10T18:51:13Z | 2020-03-10T18:51:13Z | CONTRIBUTOR | Submitted to bottleneck. |
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`rolling.mean` gives negative values on non-negative array. 578736255 |
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