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  • xarray · 20 ✖
id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
52799752 MDExOlB1bGxSZXF1ZXN0MjY1NDY5NzQ= 301 Add attribute style access for variables and attributes shoyer 1217238 closed 0   0.3.2 836999 0 2014-12-24T06:41:22Z 2014-12-24T07:07:25Z 2014-12-24T07:07:24Z MEMBER   0 pydata/xarray/pulls/301

Fixes #286

 
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52683871 MDExOlB1bGxSZXF1ZXN0MjY0Nzc5MjQ= 299 Update docs shoyer 1217238 closed 0   0.3.2 836999 0 2014-12-22T20:09:54Z 2014-12-22T21:00:58Z 2014-12-22T21:00:56Z MEMBER   0 pydata/xarray/pulls/299 
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52627673 MDExOlB1bGxSZXF1ZXN0MjY0NDM0MTM= 297 Better decoding of netCDF times shoyer 1217238 closed 0   0.3.2 836999 0 2014-12-22T08:03:02Z 2014-12-22T20:09:43Z 2014-12-22T20:09:41Z MEMBER   0 pydata/xarray/pulls/297

This version avoids using the netCDF4 library unless strictly necessary (e.g., for non-standard calendars).

 
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52627885 MDExOlB1bGxSZXF1ZXN0MjY0NDM1MzY= 298 Fix DataArray.__init__ docstring shoyer 1217238 closed 0   0.3.2 836999 0 2014-12-22T08:07:10Z 2014-12-22T08:25:15Z 2014-12-22T08:25:15Z MEMBER   0 pydata/xarray/pulls/298

xref: #277

 
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52548571 MDExOlB1bGxSZXF1ZXN0MjY0MTA4MDA= 296 BUG: fix string <-> char conversion for non-contiguous arrays shoyer 1217238 closed 0   0.3.2 836999 0 2014-12-20T02:23:57Z 2014-12-20T02:44:03Z 2014-12-20T02:44:01Z MEMBER   0 pydata/xarray/pulls/296 
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33833155 MDU6SXNzdWUzMzgzMzE1NQ== 136 More consistent datetime conversion shoyer 1217238 closed 0   0.3.2 836999 0 2014-05-19T20:16:32Z 2014-12-19T20:54:51Z 2014-12-19T05:27:50Z MEMBER      

Todo: - [x] Decide on rules for datetime conversion - [x] Implement them - [ ] Document them

Currently: - All np.datetime64 arrays or objects are converted to ns precision - We leave other datetime or datetime-like objects intact in numpy arrays of dtype=object.

Arguably, we should convert everything to 'datetime64[ns]', if possible. This is the approach we now take for decoding NetCDF time variables (#126).

Reference discussion: #134. From @akleeman:

In #125 I went the route of forcing datetimes to be datetime64[ns]. This is probably part of a broader conversation, but doing so might save some future headaches. Of course ... it would also restrict us to nanosecond precision. Basically I feel like we should either force datetimes to be datetime64[ns] or make sure that operations on datetime objects preserve their type.

Probably worth getting this in and picking that conversation back up if needed. In which case could you add tests which make sure variables with datetime objects are still datetime objects after concatenation? If those start getting cast to datetime[ns] it'll start get confusing for users.

Also worth considering: how should datetime64[us] datetimes be handled? Currently they get cast to [ns] which, since datetimes do not, could get confusing.

 
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43442970 MDExOlB1bGxSZXF1ZXN0MjE1NjU3Mjg= 236 WIP: convert to/from cdms2 variables shoyer 1217238 closed 0   0.3.2 836999 5 2014-09-22T08:48:52Z 2014-12-19T09:11:42Z 2014-12-19T09:11:39Z MEMBER   0 pydata/xarray/pulls/236

Fixes #133

@DamienIrving am I missing anything obvious here?

 
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52454780 MDExOlB1bGxSZXF1ZXN0MjYzNTUwMTQ= 295 Cleanup & bug fix shoyer 1217238 closed 0   0.3.2 836999 0 2014-12-19T07:17:35Z 2014-12-19T07:21:33Z 2014-12-19T07:21:31Z MEMBER   0 pydata/xarray/pulls/295

Fixes #279.

 
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49478188 MDU6SXNzdWU0OTQ3ODE4OA== 279 BUG: reindex method creates new dims/coords ToddSmall 4194485 closed 0   0.3.2 836999 0 2014-11-20T01:29:21Z 2014-12-19T07:21:31Z 2014-12-19T07:21:31Z NONE      

If you reindex an xray dataset or dataarray with a coordinate with a different name, an extra dimension and coordinate is added to the xray object (with the name of the reindexing coordinate). Here's a simple example:

x1 = xray.DataArray(np.random.randn(5, 6, 7), dims=["lon", "lat", "time"]) time2 = xray.DataArray([1, 3], dims="time2") x2 = x1.reindex(time=time2)

x2 now has coordinates "time" and "time2".

I'm using xray version 0.3.1-4-gee1369f.

 
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52444993 MDExOlB1bGxSZXF1ZXN0MjYzNDk2NDA= 294 Coerce arrays of datetime.datetime objects into datetime64 shoyer 1217238 closed 0   0.3.2 836999 0 2014-12-19T03:39:35Z 2014-12-19T05:27:51Z 2014-12-19T05:27:50Z MEMBER   0 pydata/xarray/pulls/294

Fixes #136

Also includes some speedups for Variable construction

 
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51780993 MDExOlB1bGxSZXF1ZXN0MjU5NTgxNjg= 292 Allow for pd.TimedeltaIndex and serialize it to netCDF shoyer 1217238 closed 0   0.3.2 836999 0 2014-12-12T08:19:32Z 2014-12-12T09:41:03Z 2014-12-12T09:41:01Z MEMBER   0 pydata/xarray/pulls/292

Fixes #55

 
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51526283 MDExOlB1bGxSZXF1ZXN0MjU4MDI4Nzc= 291 Support using dictionaries for labeled indexing shoyer 1217238 closed 0   0.3.2 836999 0 2014-12-10T07:14:47Z 2014-12-11T22:28:26Z 2014-12-11T22:28:19Z MEMBER   0 pydata/xarray/pulls/291

Fixes #187

As of this change, you can use dictionaries for indexing along a dimension, e.g., in the form array.loc[dict(x='2000-01-01')] or array[dict(x=0)].

In particular, you can use this for assignment, not just for selecting values (e.g., array[dict(x=0)] = 0). It was previously difficult to do assignment with labeled dimensions in xray.

 
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51518241 MDExOlB1bGxSZXF1ZXN0MjU3OTg4NjE= 289 Faster path for Dataset/DataArray indexing shoyer 1217238 closed 0   0.3.2 836999 0 2014-12-10T04:48:31Z 2014-12-10T04:53:17Z 2014-12-10T04:53:15Z MEMBER   0 pydata/xarray/pulls/289

My benchmark shows this commit makes things about 35% faster for positional indexing.

 
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51212447 MDExOlB1bGxSZXF1ZXN0MjU2MzAwMzY= 288 Add optional dependency on cyordereddict shoyer 1217238 closed 0   0.3.2 836999 0 2014-12-07T09:15:35Z 2014-12-07T09:53:51Z 2014-12-07T09:53:49Z MEMBER   0 pydata/xarray/pulls/288

This makes indexing a dataset (ds['foo']) about 30% faster in cases where cyordereddict is available.

 
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51205753 MDExOlB1bGxSZXF1ZXN0MjU2Mjc1NTc= 287 Fixes for Dataset.to_dataframe() shoyer 1217238 closed 0   0.3.2 836999 0 2014-12-07T03:24:55Z 2014-12-07T06:22:51Z 2014-12-07T06:22:47Z MEMBER   0 pydata/xarray/pulls/287

Fixes #278

 
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50613204 MDExOlB1bGxSZXF1ZXN0MjUzMTk1Njc= 282 Serialize non-index coordinates to netCDF files shoyer 1217238 closed 0   0.3.2 836999 0 2014-12-02T05:11:23Z 2014-12-07T02:44:14Z 2014-12-07T02:44:11Z MEMBER   0 pydata/xarray/pulls/282

Fixes #231

This PR ensures non-index coordinates can be roundtripped to netCDF and back by using the CF convention of the 'coordinates' attribute on a "data variable".

In cases where there are no data variables available, we fall back to the (extended, non-CF) convention of saving 'coordinates' as a global attribute.

I also added the xray.decode_cf function to the API. This function can decode either datasets or datastores into decoded datasets, which is handy, for example, if a dataset is serialized according to CF conventions but already in memory (e.g., saved in JSON).

@akleeman: I could use some guidance from you on want to do about test_roundtrip_coordinates on TestCFEncodedDataStore. I am tentatively skipping it, but it would be nice to get it working. To do so will require some tweaks to the API for the Datastore.load method.

 
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51059629 MDExOlB1bGxSZXF1ZXN0MjU1NDc1ODY= 285 Fix to_netcdf with 0d sting variables shoyer 1217238 closed 0   0.3.2 836999 0 2014-12-05T03:29:54Z 2014-12-05T03:57:18Z 2014-12-05T03:57:16Z MEMBER   0 pydata/xarray/pulls/285

Fixes #284

 
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47220369 MDExOlB1bGxSZXF1ZXN0MjM1NzUyMjM= 271 Add backends integration test for roundtripping datetime arrays shoyer 1217238 closed 0   0.3.2 836999 0 2014-10-30T00:19:58Z 2014-10-30T02:32:23Z 2014-10-30T02:32:21Z MEMBER   0 pydata/xarray/pulls/271

Not sure how we missed this before.

Also includes a fix for writing datetime arrays with missing values.

 
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47195566 MDExOlB1bGxSZXF1ZXN0MjM1NTk1NjE= 270 Fix guess_time_units if NaT is present shoyer 1217238 closed 0   0.3.2 836999 0 2014-10-29T19:54:05Z 2014-10-29T20:09:18Z 2014-10-29T20:07:02Z MEMBER   0 pydata/xarray/pulls/270 
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46994302 MDExOlB1bGxSZXF1ZXN0MjM0MzY5NzM= 269 Fixes for dtype casting shoyer 1217238 closed 0   0.3.2 836999 0 2014-10-28T06:37:55Z 2014-10-28T06:47:50Z 2014-10-28T06:47:38Z MEMBER   0 pydata/xarray/pulls/269

Fixes #264 Fixes #259 (casting of masked arrays)

 
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