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15862044 MDExOlB1bGxSZXF1ZXN0MTU4NjIwNDQ= 128 closed 0 Expose more information in DataArray.__repr__ shoyer 1217238 This PR changes the `DataArray` representation so that it displays more of the information associated with a data array: - "Coordinates" are indicated by their name and the `repr` of the corresponding pandas.Index object (to indicate how they are used as indices). - "Linked" dataset variables are also listed. - These are other variables in the dataset associated with a DataArray which are also indexed along with the DataArray. - They accessible from the `dataset` attribute or by indexing the data array with a string. - Perhaps their most convenient aspect is that they enable [`groupby` operations by name](http://xray.readthedocs.org/en/latest/tutorial.html#apply) for DataArray objets. - This is an admitedly somewhat confusing (though convenient) notion that I am considering [removing](https://github.com/xray- pydata/xray/issues/117), but we if we don't remove them we should certainly expose their existence more clearly, given the potential benefits in expressiveness and costs in performance. Questions to resolve: - Is "Linked dataset variables" the best name for these? - Perhaps it would be useful to show more information about these linked variables, such as their dimensions and/or shape? Examples of the new repr are on nbviewer: http://nbviewer.ipython.org/gist/shoyer/94936e5b71613683d95a 2014-05-14T06:05:53Z 2014-08-01T05:54:50Z 2014-05-29T04:19:46Z 2014-05-29T04:19:46Z 166ba9652e44423de902351d65e94216f5d8125a   0.2 650893 0 238cb2a3d360e4dc0977c0e37758faf62e262fab ed3143e3082ba339d35dc4678ddabc7e175dd6b8 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/128  
16085838 MDExOlB1bGxSZXF1ZXN0MTYwODU4Mzg= 137 closed 0 Dataset.reduce methods jhamman 2443309 A first attempt at implementing Dataset reduction methods. #131 2014-05-20T01:53:30Z 2014-07-25T06:37:31Z 2014-05-21T20:23:36Z 2014-05-21T20:23:36Z f6a6e7317c78e108176b74f1f67e12f5880e14fa   0.2 650893 0 b5d82a0887f7156ddd4ab1c1aab89345bd642162 7732816216bbb5d0c98946149c9f3b8dc54eb28f MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/137  
16622100 MDExOlB1bGxSZXF1ZXN0MTY2MjIxMDA= 144 closed 0 Use "equivalence" for all dictionary equality checks shoyer 1217238 This should fix a bug @mgarvert encountered with concatenating variables with different array attributes. In the process of fixing this issue, I encountered and fixed another bug with utils.remove_incompatible_items. 2014-06-02T21:01:35Z 2014-06-25T23:40:36Z 2014-06-02T21:20:15Z 2014-06-02T21:20:15Z 955027efe5822cdb1d3f48ee1260318e1af8c0a8   0.2 650893 0 eff435deecabd1ff9488ec640c126dde2fe4fca0 71137d1e50116e5cca63d9b1c169844b5737cec2 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/144  
16802020 MDExOlB1bGxSZXF1ZXN0MTY4MDIwMjA= 147 closed 0 Support "None" as a variable name and use it as a default shoyer 1217238 This makes the xray API a little more similar to pandas, which makes heavy use of `name = None` for objects that can but don't always have names like Series and Index. It will be a particular useful option to have around when we add a direct constructor for DataArray objects (#115). For now, arrays will probably only end up being named `None` if they are the result of some mathematical operation where the name could be ambiguous. 2014-06-06T02:26:57Z 2014-08-14T07:44:27Z 2014-06-09T06:17:55Z 2014-06-09T06:17:55Z 0674f9350b26eb604d7cb729d34abbf52fde2e20   0.2 650893 0 f448318ff7efc8e6c4e98140ecda0db7304fbfce 77dd0c38a4065ea815368f3ca9490157b530a9c4 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/147  
16873050 MDExOlB1bGxSZXF1ZXN0MTY4NzMwNTA= 149 closed 0 Data array constructor shoyer 1217238 Fixes #115. Related: #116, #117. Note: a remaining major task will be to rewrite/reorganize the docs to introduce `DataArray` first, entirely independently of `Dataset`. This will make it easier for new users to figure out how to get started with xray, since DataArray is much simpler. 2014-06-09T06:29:49Z 2014-06-12T20:38:27Z 2014-06-11T16:53:58Z 2014-06-11T16:53:58Z 467cf48090c5f3a7821f0b8bcda035e0bb26d1df   0.2 650893 0 31cbb2fafea5d9f0db647cd65674201df9c2d9c0 3af0e34b90b8ec5436047419ad3ed2402ad5ff24 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/149  
16896623 MDExOlB1bGxSZXF1ZXN0MTY4OTY2MjM= 150 closed 0 Fix DecodedCFDatetimeArray was being incorrectly indexed. akleeman 514053 This was causing an error in the following situation: ``` ds = xray.Dataset() ds['time'] = ('time', [np.datetime64('2001-05-01') for i in range(5)]) ds['variable'] = ('time', np.arange(5.)) ds.to_netcdf('test.nc') ds = xray.open_dataset('./test.nc') ss = ds.indexed(time=slice(0, 2)) ss.dumps() ``` Thanks @shoyer for the fix. 2014-06-09T17:25:05Z 2014-06-09T17:43:50Z 2014-06-09T17:43:50Z 2014-06-09T17:43:50Z 2ec8b7127f0d27683cb6d32da859a62e00ded6b9   0.2 650893 0 095e7070342a01ce5ee06a4cabd55087ad80395d 3af0e34b90b8ec5436047419ad3ed2402ad5ff24 CONTRIBUTOR   xarray 13221727 https://github.com/pydata/xarray/pull/150  
17117566 MDExOlB1bGxSZXF1ZXN0MTcxMTc1NjY= 161 closed 0 Rename "Coordinate", "labeled" and "indexed" shoyer 1217238 Fixes #142 Fixes #148 All existing code should still work but issue a `FutureWarning` if any of the old names are used. Full list of updates: | Old | New | | --- | --- | | `Coordinate` | `Index` | | `coordinates` | `indexes` | | `noncoordinates` | `nonindexes` | | `indexed` | `isel` | | `labeled` | `sel` | | `select` | `select_vars` | | `unselect` | `drop_vars` | Most of these are both `Dataset` and `DataArray` methods/properties. 2014-06-13T16:07:40Z 2014-06-22T00:44:28Z 2014-06-22T00:44:26Z 2014-06-22T00:44:26Z 9375aa280bb9254d9b83fe220baebed3526274da   0.2 650893 0 f51c7e8ca52e0d7cc5ec62a57c474c37d1debeb3 83ac662d3d90e31f6ee37262ebc85f059afa6751 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/161  
17158398 MDExOlB1bGxSZXF1ZXN0MTcxNTgzOTg= 163 closed 0 BUG: fix encoding issues (array indexing now resets encoding) shoyer 1217238 Fixes #156, #157 To elaborate on the changes: 1. When an array is indexed, its encoding will be reset. This takes care of the invalid chunksize issue. More generally, this seems like the right choice because it's not clear that the right encoding will be the same after slicing an array, anyways. 2. If an array has `encoding['dtype'] = np.dtype('S1')` (e.g., it was originally encoded in characters), it will be stacked up to be saved as a character array, even if it's being saved to a NetCDF4 file. Previously, the array would be cast to 'S1' without stacking, which would result in silent loss of data. 2014-06-16T01:29:22Z 2014-06-17T07:28:45Z 2014-06-16T04:52:43Z 2014-06-16T04:52:43Z 2d8751e9f80f6ade4240162d8b6c0668d4f00be8   0.2 650893 0 667f26fad6af902fb0508693326bc3c313d7847d 71226fb571e0b9cdc32cc476b333991eafebe466 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/163  
17281384 MDExOlB1bGxSZXF1ZXN0MTcyODEzODQ= 165 closed 0 WIP: cleanup conventions.encode_cf_variable shoyer 1217238 Almost ready, except for failing tests on Python 3. 2014-06-18T08:47:35Z 2014-06-22T00:36:01Z 2014-06-22T00:35:42Z 2014-06-22T00:35:42Z 4c8bda09fdd7a03bd0293ed663320420b3b099bd   0.2 650893 0 1675cc51e09b43cfeabbc34c6dac80976d26f28b 4fce6d2e4aca03687a40f9041db7bdc5a30f9e09 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/165  
17312904 MDExOlB1bGxSZXF1ZXN0MTczMTI5MDQ= 166 closed 0 Revert using __slots__ for Mapping subclasses in xray.utils shoyer 1217238 This recently added some complexity for a very nominal speed benefit. And it appears that it breaks joblib serialization, somehow (even though pickle works). So for now, revert it -- and consider filing a joblib bug if we can narrow it down. 2014-06-18T19:08:47Z 2014-06-18T19:24:50Z 2014-06-18T19:12:52Z 2014-06-18T19:12:52Z 57bba43983d48a9ba30b2770d375a742ba4c62cc   0.2 650893 0 3d6eab5e8e2774d006481234847f348427aa87eb 4fce6d2e4aca03687a40f9041db7bdc5a30f9e09 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/166  
17446066 MDExOlB1bGxSZXF1ZXN0MTc0NDYwNjY= 169 closed 0 Cleanups shoyer 1217238   2014-06-22T06:44:17Z 2014-06-22T06:56:22Z 2014-06-22T06:56:20Z 2014-06-22T06:56:20Z 2543892501760532042b84352b0919833794ad10   0.2 650893 0 c87d68bcb11bd0d6f19dcea863070bc8668895ca 420655dbf13282e2754ff1f681fae12978a78291 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/169  
17446667 MDExOlB1bGxSZXF1ZXN0MTc0NDY2Njc= 171 closed 0 Implementation of DatasetGroupBy summary methods shoyer 1217238 You can now do `ds.groupby('time.month').mean()` to apply the mean over all groups and variables in a dataset. It is not optimized like the DataArray.groupby summary methods but it should work. Thanks @jhamman for laying the groundwork for this! 2014-06-22T08:38:51Z 2014-06-23T07:25:10Z 2014-06-23T07:25:08Z 2014-06-23T07:25:08Z fd8c731f7d98ab0315c1b4f956246dbc1af6a2e3   0.2 650893 0 da3b0053eaa44e0526cf23a079804af6e08f7335 64d88a8537b8d107ab978410f47ea4e2280c6d89 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/171  
17513266 MDExOlB1bGxSZXF1ZXN0MTc1MTMyNjY= 172 closed 0 {DataArray,Dataset}.indexes no longer creates a new dict shoyer 1217238 According to the toy benchmark below, this shaves off between 20% (diff-indexes) to 40% (same-indexes) of xray's overhead for array math: ``` import numpy as np import xray x = np.random.randn(1000, 1000) y = np.random.randn(1000, 1000) dx = xray.DataArray(x) dy = xray.DataArray(y) %timeit x + x # raw-numpy %timeit dx + dx # same-indexes %timeit dx + dy # diff-indexes ``` 2014-06-24T05:10:25Z 2014-06-24T05:34:38Z 2014-06-24T05:34:36Z 2014-06-24T05:34:36Z 17097a127a67c9bd245e83ede8ccfe64475ee887   0.2 650893 0 3f0a87b9c2e29670b14a69e352ab5e1f26bc9a95 e0ffca26d30eab1731b6a5d380f2948c5f519dab MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/172  
17513759 MDExOlB1bGxSZXF1ZXN0MTc1MTM3NTk= 173 closed 0 Edge cases shoyer 1217238   2014-06-24T05:34:05Z 2014-06-24T17:55:16Z 2014-06-24T17:55:14Z 2014-06-24T17:55:14Z eb7d9a577fced96e63b035496afab186c0765bb5   0.2 650893 0 d0c1e95aaf265a79823b9bbe380276cf9bf54fbf e0ffca26d30eab1731b6a5d380f2948c5f519dab MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/173  
17574726 MDExOlB1bGxSZXF1ZXN0MTc1NzQ3MjY= 174 closed 0 Add isnull and notnull (wrapping pandas) shoyer 1217238   2014-06-25T07:07:42Z 2014-06-25T07:37:36Z 2014-06-25T07:37:35Z 2014-06-25T07:37:35Z 2cf59a28ff1b071ea2f57a50a9f550af036d3bca   0.2 650893 0 e6203c1d952e1a3f422cae8db99a816aa2f11012 3672599bc9e605dbb2df05237bfc5b0c142a3257 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/174  
17840241 MDExOlB1bGxSZXF1ZXN0MTc4NDAyNDE= 177 closed 0 Add python2.6 compatibility aykuznetsova 3344007 This change mainly involves an alternative import of OrderedDict, modified dict and set comprehensions, and using unittest2 for testing. 2014-07-01T16:19:21Z 2014-07-01T21:30:08Z 2014-07-01T19:57:30Z 2014-07-01T19:57:30Z 930b795420e3e024545298eb05f501f5ac6bc1c3   0.2 650893 0 16bfa99e9bc9165510758dde07a4e02617e2b108 7e0e7b1f2b3663c9fddb7b9f1767e4e7f744d19c NONE   xarray 13221727 https://github.com/pydata/xarray/pull/177  
18759550 MDExOlB1bGxSZXF1ZXN0MTg3NTk1NTA= 188 closed 0 Dataset context manager and close() method shoyer 1217238 With this PR, it is possible to close the data store from which a dataset was loaded via `ds.close()` or automatically when a dataset is used with a context manager: ``` python with xray.open_dataset('data.nc') as ds: ... ``` The ability to cleanly close files opened from disk is pretty essential -- we probably should have had this a while ago. It should not be necessary to use the low-level/unstable datastore API to get this functionality. **Implementation question**: With this current implementation, calling `ds.close()` on (and using a context manager with) a dataset not linked to any file objects is a no-op. Should we raise an exception instead? Something like `IOError('no file object to close')`? CC @ToddSmall 2014-07-23T07:03:49Z 2014-07-29T19:47:46Z 2014-07-29T19:44:30Z 2014-07-29T19:44:30Z 8e9c9ab7cd23507c0644207d5de1713d7a49c22c   0.2 650893 0 d1e739f27bec53f1c77d4625ffc5ddc44a2ac1e1 6c394b14ecc04a53d804893060ed33cadfde688e MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/188  
18879796 MDExOlB1bGxSZXF1ZXN0MTg4Nzk3OTY= 189 closed 0 Implementation of Dataset.apply method shoyer 1217238 Fixes #140 2014-07-25T06:18:29Z 2014-07-31T04:45:29Z 2014-07-31T04:45:29Z 2014-07-31T04:45:29Z 2bce568f2195f98beeb4f9aa0fb02cd192dbae99   0.2 650893 0 4548d1015c38dc7c1c324b157da5939f232f4b46 6c394b14ecc04a53d804893060ed33cadfde688e MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/189  
18947350 MDExOlB1bGxSZXF1ZXN0MTg5NDczNTA= 192 closed 0 Enhanced support for modifying Dataset & DataArray properties in place shoyer 1217238 With this patch, it is possible to perform the following operations: - `data_array.name = 'foo'` - `data_array.coordinates = ...` - `data_array.coordinates[0] = ...` - `data_array.coordinates['x'] = ...` - `dataset.coordinates['x'] = ...` - `dataset.rename(..., inplace=True)` It is no longer possible to set `data_array.variable = ....`, which was technically part of the public API but I would guess unused. 2014-07-28T02:14:00Z 2014-07-31T04:46:19Z 2014-07-31T04:46:16Z 2014-07-31T04:46:16Z 8624314f0d0893e64f818e778ae40c9ffbaf89e3   0.2 650893 0 a7f53516b31b49a841de2b67cfeb0027dfda5f71 6c394b14ecc04a53d804893060ed33cadfde688e MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/192  
19132736 MDExOlB1bGxSZXF1ZXN0MTkxMzI3MzY= 194 closed 0 Consistently use shorter names: always use 'attrs', 'coords' and 'dims' shoyer 1217238 Cleaned up a few cases where `attributes` was used instead of `attrs` in function signatures. Fixes: #190 - [x] Switch names in xray itself - [x] Switch names in tests - [x] Switch names in documentation 2014-07-31T05:11:12Z 2014-08-14T05:08:01Z 2014-08-14T05:07:58Z 2014-08-14T05:07:58Z a9b879898f3d5efffbfb0ee026e8cf2c1b4bac8e   0.2 650893 0 6f0fca3584d8d2e079dbd15607a9cda6e183a76b db292afdc68b4d8a1c7b17e5aacb8d9a67688de8 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/194  
19133368 MDExOlB1bGxSZXF1ZXN0MTkxMzMzNjg= 195 closed 0 .loc and .sel support indexing with boolean arrays shoyer 1217238 Fixes #182 2014-07-31T05:41:09Z 2014-07-31T06:52:43Z 2014-07-31T06:52:41Z 2014-07-31T06:52:41Z 4643cf790007c8c14ed6629ae3e4375552f03e66   0.2 650893 0 d2196ce4bd8f335ea252f358bcc93743084038ac 20d1939df8dcf016d85d3d71bd739494c586d4d9 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/195  
19135159 MDExOlB1bGxSZXF1ZXN0MTkxMzUxNTk= 196 closed 0 Raise NotImplementedError when attempting to use a pandas.MultiIndex shoyer 1217238 Related: #164 2014-07-31T06:53:04Z 2014-07-31T07:00:43Z 2014-07-31T07:00:40Z 2014-07-31T07:00:40Z 5798942b33531f0af6a0452a7885618c9bd97e36   0.2 650893 0 f2057b1da829f1a6cc04042b2e7a65fd5d87dc08 0c66a06e4a7cb64f71979f4f8bb494ad8a2a218e MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/196  
19248308 MDExOlB1bGxSZXF1ZXN0MTkyNDgzMDg= 198 closed 0 Cleanup of DataArray constructor / Dataset.__getitem__ shoyer 1217238 Now Dataset.**getitem** raises a KeyError when it can't find a variable. 2014-08-02T18:12:36Z 2014-08-02T18:28:54Z 2014-08-02T18:28:52Z 2014-08-02T18:28:52Z 5108fdd8dea210233a848ed87347e708d9d2201f   0.2 650893 0 d605857b9593c4765c6efaf77ccc1d9e5909969c 2debeb9313473a0664c79e213ef9a55a0229aaf1 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/198  
19261817 MDExOlB1bGxSZXF1ZXN0MTkyNjE4MTc= 201 closed 0 Fix renaming in-place bug with virtual variables shoyer 1217238 This is why mutating state is a bad idea. 2014-08-04T01:20:06Z 2014-08-04T01:24:32Z 2014-08-04T01:22:58Z 2014-08-04T01:22:58Z dbc78ad25e85b1268e62c34087a5d23320468b40   0.2 650893 0 e79ce168a694f54e191d97bfa5fe1fd3bcf5c57a 590aa9e7e3f10e6e690cfe8b75ae6f3588b6f47d MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/201  
19494597 MDExOlB1bGxSZXF1ZXN0MTk0OTQ1OTc= 207 closed 0 Raise an error when attempting to use a scalar variable as a dimension shoyer 1217238 If 'x' was a scalar variable in a dataset and you set a new variable with 'x' as a dimension, you could end up with a broken Dataset object. 2014-08-07T21:07:03Z 2014-08-07T21:13:12Z 2014-08-07T21:13:02Z 2014-08-07T21:13:02Z bfb96f9bbb25ec14b5d709523e308a7a5083c6eb   0.2 650893 0 81195ec7ce030315e8d953002aab96077c8a8b25 d432677c20b98aff2e48a43699233288c34efbdc MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/207  
19773281 MDExOlB1bGxSZXF1ZXN0MTk3NzMyODE= 213 closed 0 Checklist for v0.2.0 shoyer 1217238 Should resolve all remaining items in #183. 2014-08-14T08:08:25Z 2014-08-14T17:20:05Z 2014-08-14T17:20:02Z 2014-08-14T17:20:01Z 067ec9a104f019304ade3196b76882b40160485e   0.2 650893 0 7fa33d7dd4fb9476a0f3bd50fa9e2c442dc6f9f3 cd0ff19fbf1b57f443761b477bd6be01dd06c3f0 MEMBER   xarray 13221727 https://github.com/pydata/xarray/pull/213  

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