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| id ▼ | node_id | number | state | locked | title | user | body | created_at | updated_at | closed_at | merged_at | merge_commit_sha | assignee | milestone | draft | head | base | author_association | auto_merge | repo | url | merged_by |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 15798892 | MDExOlB1bGxSZXF1ZXN0MTU3OTg4OTI= | 126 | closed | 0 | Return numpy.datetime64 arrays for non-standard calendars | jhamman 2443309 | Fixes issues in #118 and #121 | 2014-05-13T00:22:51Z | 2015-07-27T05:38:06Z | 2014-05-16T00:21:08Z | 2014-05-16T00:21:08Z | e80836b9736fcfba1af500c08aab22bcda4e8912 | 0.1.1 664063 | 0 | e07bc93589bbd23fe3bfa1ae1e1daf15eebf83f2 | ed3143e3082ba339d35dc4678ddabc7e175dd6b8 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/126 | |||
| 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 | |||
| 16140780 | MDExOlB1bGxSZXF1ZXN0MTYxNDA3ODA= | 139 | closed | 0 | Enable keep attrs | jhamman 2443309 | Fixes #138 | 2014-05-21T00:48:47Z | 2015-07-27T05:38:13Z | 2014-05-21T21:43:21Z | cfc9de74d9dccfd61798e6f0db6fdd8cf47f4e7f | 0 | 1c08e190d2b3d05b7107d3d7a988c2afac37b911 | fd5268f7bbf932767b589169112efc2ee5a8a012 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/139 | |||||
| 16190479 | MDExOlB1bGxSZXF1ZXN0MTYxOTA0Nzk= | 141 | closed | 0 | Add keep_attrs to reduction methods | jhamman 2443309 | fixes #138 This is a much cleaner version of #139. | 2014-05-21T21:48:19Z | 2014-05-22T00:35:21Z | 2014-05-22T00:29:22Z | 2014-05-22T00:29:22Z | 70a6f9b29743e2b5480bdb25ced7c184c99df268 | 0 | 555def48f18e75246a91decd4a3b3c951e247ff1 | fd5268f7bbf932767b589169112efc2ee5a8a012 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/141 | ||||
| 30390417 | MDExOlB1bGxSZXF1ZXN0MzAzOTA0MTc= | 357 | closed | 0 | updated monthly mean averaging example using new virtual variable syntax | jhamman 2443309 | uses new virtual variable syntax discussed in #345 and applied in #351. Also see #337. | 2015-03-03T16:46:23Z | 2015-07-27T05:37:57Z | 2015-03-03T18:19:54Z | 2015-03-03T18:19:54Z | f6ef602975e20fc6b2558a8ff32fb9e7bace66e5 | 0 | ef124194e21db227112d75a9d4bf774e258a0651 | 52bbca3507081ec98360d844dc079d4dfbf0e152 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/357 | ||||
| 39720670 | MDExOlB1bGxSZXF1ZXN0Mzk3MjA2NzA= | 465 | closed | 0 | update monthly-means.rst using example data from xray-data repo | jhamman 2443309 | fixes #424 related: https://github.com/xray/xray-data/pull/1 | 2015-07-10T20:20:26Z | 2015-07-27T05:37:53Z | 2015-07-15T17:34:09Z | 2015-07-15T17:34:09Z | 68a024c4ca3ee41915782a74af1dc1ad09c0babd | 0 | 3f9b5d4409309c2be5aa49aa0e1103cdd9895834 | bf55bfd496e7fce55091bc760c8b6347211469e6 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/465 | ||||
| 39988955 | MDExOlB1bGxSZXF1ZXN0Mzk5ODg5NTU= | 474 | closed | 0 | add weighted seasonal means example ipython notebook | jhamman 2443309 | closes #424 related: #465 and https://github.com/xray/xray-data/issues/1 | 2015-07-15T05:21:00Z | 2015-07-27T05:37:54Z | 2015-07-15T17:33:05Z | 2015-07-15T17:33:05Z | 9083956533d511cc83431688f864b96b15b5472c | 0 | 5e7ccf73507c56c6f98a8ae58c55b64d2241043e | 0e77e5a86ffa2355f986ef165b5b6970411d5ef6 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/474 | ||||
| 40324635 | MDExOlB1bGxSZXF1ZXN0NDAzMjQ2MzU= | 481 | closed | 0 | Add pointwise indexing via isel_points method | jhamman 2443309 | This provides behavior equivalent to numpy slicing with multiple lists. ## Example ``` python >>> da = xray.DataArray(np.arange(56).reshape((7, 8)), dims=['x', 'y']) >>> da <xray.DataArray (x: 7, y: 8)> array([[ 0, 1, 2, 3, 4, 5, 6, 7], [ 8, 9, 10, 11, 12, 13, 14, 15], [16, 17, 18, 19, 20, 21, 22, 23], [24, 25, 26, 27, 28, 29, 30, 31], [32, 33, 34, 35, 36, 37, 38, 39], [40, 41, 42, 43, 44, 45, 46, 47], [48, 49, 50, 51, 52, 53, 54, 55]]) Coordinates: * x (x) int64 0 1 2 3 4 5 6 * y (y) int64 0 1 2 3 4 5 6 7 >>> da.isel_points(x=[0, 1, 6], y=[0, 1, 0]) <xray.DataArray (points: 3)> array([ 0, 9, 48]) Coordinates: y (points) int64 0 1 0 x (points) int64 0 1 6 * points (points) int64 0 1 2 ``` related: #475 | 2015-07-20T05:41:36Z | 2015-07-27T05:37:19Z | 2015-07-27T05:04:46Z | 2015-07-27T05:04:46Z | ca0d6d6dee86e11170363cc226ec13c553ad5232 | 0.6 1213895 | 0 | 5ab9d4b2f65584aac74e0e54050a84a1a0697773 | 1faf1b2cbf0cbed1d1b62b71df4aec8dbe63bb99 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/481 | |||
| 40856682 | MDExOlB1bGxSZXF1ZXN0NDA4NTY2ODI= | 496 | closed | 0 | fix typo in combine/concat warning | jhamman 2443309 | 2015-07-26T17:38:53Z | 2015-07-27T05:37:49Z | 2015-07-27T02:01:18Z | 2015-07-27T02:01:18Z | 938a818061d3481f9197a81c50b8c9bb53db9c4d | 0 | 3f39475e540f501c930847cf52358da34b0a43f9 | 0bee5e5fe41e5dbc74d953c3cb3b5335cfab1b3d | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/496 | |||||
| 41422864 | MDExOlB1bGxSZXF1ZXN0NDE0MjI4NjQ= | 509 | closed | 0 | Discrete colormap/colorbar option | jhamman 2443309 | This PR adds a discrete colormap / colorbar option to xray plots. closes #500 ``` python import matplotlib.pyplot as plt import numpy as np import xray # sample DataArray x = np.arange(start=0, stop=10, step=2) y = np.arange(start=9, stop=-7, step=-3) xy = np.dstack(np.meshgrid(x, y)) distance = np.linalg.norm(xy, axis=2) distance = xray.DataArray(distance, list(zip(('y', 'x'), (y, x)))) # Sample plots fig, axes = plt.subplots(2, 2, figsize=(8, 8), sharex=True, sharey=True) distance.plot(ax=axes[0, 0]) axes[0, 0].set_title('Default') distance.plot(vmin=0, vmax=12, levels=6, ax=axes[1, 0]) axes[1, 0].set_title('Setting with integer levels') distance.plot(levels=[1, 2, 4, 5, 7, 9], extend='both', cmap='Spectral', ax=axes[0, 1]) axes[0, 1].set_title('Setting with list of levels') flatui = ["#9b59b6", "#3498db", "#95a5a6", "#e74c3c", "#34495e", "#2ecc71"] distance.plot(levels=[1, 2, 4, 5, 7], cmap=flatui, extend='both', ax=axes[1, 1]) axes[1, 1].set_title('Using custom list of colors') ``` Produces these plots:  There are potential issues that I'd still like to look into a bit further. 1. Does discretizing `cmap` impact the `contour` and `contourf` plot types? We may need some logic to only discretize when the plot type is `imshow` or `pcolormesh`. 2. It is possible, in some cases, to end up masking out values equal to `vmax`: ``` python distance.plot(levels=6) ``` Produces this plot:  In the first example, we corrected for this by setting `extend='max'`. | 2015-08-02T19:17:31Z | 2015-08-06T19:53:17Z | 2015-08-06T16:06:33Z | 2015-08-06T16:06:33Z | 9edb6b0f5989431554b8dbf2e2758e2993c0faf1 | 0 | 1d60752d0ea977cea19a72ca30879a0f0bdfaf64 | 43489589958b2a7604e738c99f0b601b9601bef6 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/509 | ||||
| 41960189 | MDExOlB1bGxSZXF1ZXN0NDE5NjAxODk= | 520 | closed | 0 | added to_masked_array method and masked_array property | jhamman 2443309 | This PR adds convienience methods to convert DataArrays to numpy masked arrays. `DataArray.to_masked_array(copy=True)` returns a numpy Masked array `DataArray.masked_array` returns a masked array that is a view to the `DataArray.values.` closes #460 | 2015-08-08T20:47:41Z | 2015-08-12T18:34:17Z | 2015-08-12T18:34:16Z | 2015-08-12T18:34:16Z | 283940acff0b2d9eece93f3a423d4c0d510ce907 | 0.6 1213895 | 0 | 84ee4d0f61a3b9f7c45589568690fa10a67f87b8 | 200aeb006781528cf6d4ca2f118d7f9257bd191b | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/520 | |||
| 43195526 | MDExOlB1bGxSZXF1ZXN0NDMxOTU1MjY= | 549 | closed | 0 | cast DataArray name to string if not None | jhamman 2443309 | closes #533 | 2015-08-24T16:44:40Z | 2015-10-21T07:05:47Z | 2015-08-25T15:46:39Z | bc0e3f00652732f385216cde8b9ff4ce03ab9a3d | 0.6.1 1307323 | 0 | dfc2940d01797f69e5d1f5ed82c80b0b0e2402c1 | 8847ede760cc00c712a25dced49e6dc0158be966 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/549 | ||||
| 43302640 | MDExOlB1bGxSZXF1ZXN0NDMzMDI2NDA= | 551 | closed | 0 | raise error if dataarray.name is wrong type | jhamman 2443309 | closes #533 xref #549 | 2015-08-25T15:50:09Z | 2015-10-26T20:28:19Z | 2015-09-16T23:40:54Z | bd1bd8250f7387018f67ca6648ce338a9db28518 | 0.6.1 1307323 | 0 | 0b315eac39ad8e40cd8a6cebbec780ce8bfc3433 | 8847ede760cc00c712a25dced49e6dc0158be966 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/551 | ||||
| 45237492 | MDExOlB1bGxSZXF1ZXN0NDUyMzc0OTI= | 580 | closed | 0 | Raise an error if DataArray name is not able to be written to netCDF. | jhamman 2443309 | closes #533 xref #549, #551 | 2015-09-16T23:42:54Z | 2015-10-21T07:07:59Z | 2015-09-18T17:35:26Z | 2015-09-18T17:35:26Z | 82b2821a6099a99cd8cd564bcdc58362c3b76c58 | 0.6.1 1307323 | 0 | 2da0e7d8be49f944ef16d89e561d500cabea7782 | c13ee9875b31dceb505b4aead83272fbcbeef27e | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/580 | |||
| 45435627 | MDExOlB1bGxSZXF1ZXN0NDU0MzU2Mjc= | 583 | closed | 0 | Add Python 3.5 to Travis Builds | jhamman 2443309 | 2015-09-18T18:10:06Z | 2015-10-21T07:07:59Z | 2015-09-19T16:00:53Z | 2015-09-19T16:00:53Z | 95b359633ba927bca23f0ae7a3bba9a4dc555166 | 0.6.1 1307323 | 0 | 0a11b794b58fde21d8b979f13443c96422186983 | a2a3f21e92f9f32c9c4aed3f595856df43faa199 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/583 | ||||
| 46347492 | MDExOlB1bGxSZXF1ZXN0NDYzNDc0OTI= | 594 | closed | 0 | Spring cleaning | jhamman 2443309 | This is basically just a style/pep cleanup. I removed a bunch of unused variables from internal modules. I should say that I'm somewhat sheepishly submitting this PR, especially after seeing [this](https://youtu.be/wf-BqAjZb8M?list=PLP1xYYjBXksOm402NpkV1Ah5TRUKiQThn) talk by Raymond Hettinger. However, since my [linter](https://atom.io/packages/linter-flake8) was constantly complaining about many of these, I figured I'd knock off all of them at once. There are quite a few line changes here but none of them should result in different behavior. | 2015-09-29T23:59:14Z | 2015-10-21T07:08:00Z | 2015-09-30T17:36:16Z | 2015-09-30T17:36:16Z | f8442801c3b1088f0231cdf2fe298e3a5c917625 | 0.6.1 1307323 | 0 | b71022b12b0f3769c5252b63edce453ed94fb201 | d704524a030aef7e2029ec43d19099143b72f653 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/594 | |||
| 46363372 | MDExOlB1bGxSZXF1ZXN0NDYzNjMzNzI= | 595 | closed | 0 | unsorted integer indexing on netCDF4 objections on disk | jhamman 2443309 | add more informative error message when unsorted integer array is used to index netCDF4 variable on disk. Closes #593 | 2015-09-30T05:43:06Z | 2015-10-21T07:08:00Z | 2015-10-02T21:41:11Z | 2015-10-02T21:41:11Z | 462170a1ad08ba5cd52e7a3f6df884f4a28fc6e4 | 0.6.1 1307323 | 0 | fcddcee53c4f505c08cf4c73df1ebc66592d9fc1 | 4c35dcc008a064858a9c8ae11ae4e800a0ac4305 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/595 | |||
| 46467643 | MDExOlB1bGxSZXF1ZXN0NDY0Njc2NDM= | 596 | closed | 0 | add landscape.yml config file | jhamman 2443309 | @shoyer - we can ignore any warnings you don't like (e.g. `dangerous-default-value`). xref #594 | 2015-09-30T22:56:36Z | 2015-10-21T07:08:00Z | 2015-10-01T18:45:31Z | 2015-10-01T18:45:31Z | 80bdee536d7b1ef542e70304de544ed82285d13e | 0.6.1 1307323 | 0 | 2d213e5d822b6d876fea9fa7e8486a056f051175 | 1ec0e3592be5e9136824144809aa763499134ec7 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/596 | |||
| 46483378 | MDExOlB1bGxSZXF1ZXN0NDY0ODMzNzg= | 598 | closed | 0 | Fix colormap for facet grid plots | jhamman 2443309 | Fixes #592 Added test to check that all subplots in facet grid have same data range and colormap. This fixes two issues present in the existing code: 1) colormap was being selected for each subplot 2) range was being selected for each subplot and colorbar was the result of only the last subplot Some sample code: ``` Python data = (np.random.random(size=(20, 25, 12)) + np.linspace(-3, 3, 12)) # range is ~ -3 to 4 da = xray.DataArray(data, dims=['x', 'y', 'time'], name='data') fg = da.plot.pcolormesh(col='time', col_wrap=4) ``` previously yielded this plot:  and now yields this plot:  | 2015-10-01T04:15:04Z | 2015-10-21T07:08:00Z | 2015-10-01T17:10:31Z | 2015-10-01T17:10:31Z | e881473120221e89608c566f55f2aa4b9e013bf3 | 0.6.1 1307323 | 0 | ca5b1cbd52ddc210bf2a016522213dbdec499c9e | 1ec0e3592be5e9136824144809aa763499134ec7 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/598 | |||
| 46689632 | MDExOlB1bGxSZXF1ZXN0NDY2ODk2MzI= | 604 | closed | 0 | Add subplot_kws arg to plotting interfaces | jhamman 2443309 | This argument is only used in the FacetGrid class and allows users to pass arguments to subplot constructor. The api change is a pretty simple and just accepts a single new argument (`subplot_kws`). I think we need to think about how to tweak the subplots a bit more in terms of aspect. Here's some example code that produces the plot below: ``` Python import xray import cartopy.crs as ccrs ds = xray.open_dataset('xray-data/ncep_temperature_north-america_2013-14.nc') ds.lon -= 360 lon0 = ds.lon.values.mean() dss = ds.groupby('time.season').mean('time') g = dss.air.plot.pcolormesh(col='season', col_wrap=2, transform=ccrs.PlateCarree(), subplot_kws=dict(projection=ccrs.PlateCarree(lon0))) for ax in g.axes.flat: ax.coastlines() ax.gridlines() ax.set_extent((-161.25, -28.75, 20, 40)) ```  Obviously there are some issues with the grid lines too but that may end up getting fixed by a more flexible aspect. cc @clarkfitzg closes #603 xref: https://github.com/mwaskom/seaborn/pull/320 | 2015-10-02T22:36:04Z | 2016-11-30T08:00:48Z | 2015-10-06T15:10:01Z | 2015-10-06T15:10:00Z | b5749f006c11827562f6042afc7a83f3b2ccee2a | 0.6.1 1307323 | 0 | 98946aa7cd7338b0643b738e7c1c713d6d53bc3f | 89adda5e719a2bba6231310e3726185597f9beab | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/604 | |||
| 46709838 | MDExOlB1bGxSZXF1ZXN0NDY3MDk4Mzg= | 606 | closed | 0 | example of how to use cf convention to use 2d coordinates for plotting | jhamman 2443309 | This is one idea of how to handle 2d coordinate variables. Attribute names may need to change but this is working for my application. No test written and existing roundtrip tests will likely fail on this first commit. | 2015-10-03T17:53:07Z | 2015-10-26T20:28:26Z | 2015-10-06T15:56:15Z | 5fd548404f9005bfd7431aa75ae61f31fd6c636f | 0.6.1 1307323 | 0 | c6a61bdc4340099f6b1a2e00dc3d867396e2072e | 89adda5e719a2bba6231310e3726185597f9beab | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/606 | ||||
| 46720115 | MDExOlB1bGxSZXF1ZXN0NDY3MjAxMTU= | 608 | closed | 0 | allow passing coordinate names as x and y to plot methods | jhamman 2443309 | This allows us to use coordinate names as plotting arguments for `x` and `y`. I have a test for this that isn't quite working yet. | 2015-10-04T06:15:36Z | 2015-11-15T21:50:18Z | 2015-10-09T14:21:25Z | 2015-10-09T14:21:25Z | b52f8ebea2aff0fce517601b8523db391870c2ac | 0.6.1 1307323 | 0 | e25ac4b58dbe91b933bebc06d8d081e3f0c40339 | cb4e4138fdb52078d27341dadf0feedb15e1de80 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/608 | |||
| 47104188 | MDExOlB1bGxSZXF1ZXN0NDcxMDQxODg= | 612 | closed | 0 | keep coordinates encoding even when coordinates are decoded | jhamman 2443309 | fixes #610 | 2015-10-08T02:01:20Z | 2015-10-26T20:28:26Z | 2015-10-08T18:03:19Z | 2015-10-08T18:03:19Z | c63a72a821d6fc264e05b19d9af8433c4dad397b | 0.6.1 1307323 | 0 | e3508a8ee48ac1b1722df9ec1e932abd173502e7 | 0966b78003e3e25ef9d41f9e7f938bfaefeb7d22 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/612 | |||
| 47349510 | MDExOlB1bGxSZXF1ZXN0NDczNDk1MTA= | 618 | closed | 0 | numpy 1.10 compat fixes | jhamman 2443309 | fixes #617 @shoyer - can you take a look at `test_index_0d_not_a_time` and see if you can figure out why that test is failing? I couldn't sort it out. Also, we're now getting a ton of these warnings: `FutureWarning: numpy equal will not check object identity in the future. The comparison did not return the same result as suggested by the identity (`is`)) and will change.` I thought about trying to suppress the ones that come directly from xray but that seems tricky to do safely. matplotlib and numpy itself are raising the same warnings. err... | 2015-10-10T17:04:45Z | 2016-01-04T23:11:55Z | 2015-10-12T20:37:14Z | 2015-10-12T20:37:14Z | e45f0f730c879535320fa43635fb81fe9c644cd4 | 0.6.1 1307323 | 0 | 675578f982272fbf3eec99c1d3249f38397e8bdb | a2fa27004f6cac476a3dbec2fa0774716f05f198 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/618 | |||
| 48667587 | MDExOlB1bGxSZXF1ZXN0NDg2Njc1ODc= | 638 | closed | 0 | Feature/pytest | jhamman 2443309 | Uses `py.test` instead of `nosetests` for test collection and execution. I was mostly curious if this would work given xray's testing structure. Turns out it does (with one exception in Python 2.6). I much prefer the traceback that `py.test` returns when tests fail. | 2015-10-24T23:13:14Z | 2015-10-26T20:42:02Z | 2015-10-26T18:23:51Z | 2015-10-26T18:23:51Z | 056ea1726c0e13999eea5665f891852f3a26ece8 | 0 | 69878cf469437ce449512d84f9ef918caddffe86 | 187a9f7974a13e99c013117d00ea150128b3b040 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/638 | ||||
| 50156922 | MDExOlB1bGxSZXF1ZXN0NTAxNTY5MjI= | 650 | closed | 0 | Feature/average | jhamman 2443309 | closes #422 | 2015-11-09T18:11:35Z | 2016-05-11T04:25:04Z | 2016-05-11T04:25:04Z | 13609579644e5eb3919ff7a381e3ce05f546f65e | 0 | 2f5787520d850ac8520b048faa838c47b680dc52 | 44059471a1af4a3ad9ac665d2038c17c299451c0 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/650 | |||||
| 52455751 | MDExOlB1bGxSZXF1ZXN0NTI0NTU3NTE= | 668 | closed | 0 | Feature/rolling | jhamman 2443309 | This is an initial take at the rolling aggregation object and methods in xray. This PR implements: - A new `Rolling` class available in `DataArray` objects: ``` Python rolling_obj = da.rolling(time=7) ``` - `bottleneck.move_*` functions are wrapped and are available in the following manor: ``` Python rolling_obj.mean() ``` - generic reduce method ``` Python from numpy import nanpercentile rolling_obj.reduce(nanpercentile, q=5) ``` - iterating through the rolling object: ``` Python for label, da_window in rolling_obj: # da_window is a view of da ``` TODO: - [x] Documentation - [x] Cleanup `_setup_windows` - [x] Inject bottleneck methods in some generic way - [x] ~~Possibly create a `Window` object to hold windowed `DataArray`s~~ closes #641 #130 xref pydata/pandas#11603, pydata/pandas#11704 cc @shoyer @bartnijssen | 2015-12-02T21:20:34Z | 2016-02-20T02:37:52Z | 2016-02-20T02:32:33Z | 2016-02-20T02:32:33Z | e28d39c6c2106fb6b5f3e8e84f27e77d42581fb8 | 0 | 68ba033b699d2e4dc36e5fb0659a26233f9d1f64 | 44059471a1af4a3ad9ac665d2038c17c299451c0 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/668 | ||||
| 60034784 | MDExOlB1bGxSZXF1ZXN0NjAwMzQ3ODQ= | 772 | closed | 0 | update rolling doc string | jhamman 2443309 | minor update of `rolling` doc string. Missed this update after @shoyer's last review. xref: #668 | 2016-02-20T02:46:32Z | 2016-02-20T21:34:00Z | 2016-02-20T17:01:45Z | 2016-02-20T17:01:45Z | 4a6a7785a7441a5878d2270750a3940ac19524ea | 0 | a829c0bce3754475d31f20b9779cb866253fa5bd | a59e6ddb450530640b5d641c4a7f26c3cf9807d0 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/772 | ||||
| 60054139 | MDExOlB1bGxSZXF1ZXN0NjAwNTQxMzk= | 774 | closed | 0 | fix/update math with dataset docs | jhamman 2443309 | Fixes the build failure in the docs here: http://xarray.pydata.org/en/latest/computation.html#math-with-datasets | 2016-02-20T17:22:04Z | 2016-02-20T21:08:50Z | 2016-02-20T21:08:50Z | 2016-02-20T21:08:50Z | 390e64566a9f50f5cf37d8b85a238facc4ac768f | 0 | 3fea1e1a49b7847aaaf4ac65484b11a0126d6fb9 | 4242f700102284b8d69aae19faf07fc9a22e14dd | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/774 | ||||
| 60059840 | MDExOlB1bGxSZXF1ZXN0NjAwNTk4NDA= | 775 | closed | 0 | remove extra line from rolling doc string | jhamman 2443309 | (sorry about this...) | 2016-02-20T20:48:50Z | 2016-02-27T01:40:21Z | 2016-02-27T01:40:21Z | 2016-02-27T01:40:21Z | c2e948f1daf80953a7e14d54c48648174b93617b | 0 | 9135b5062e6bb4206352f127c8c627338ac9b940 | 4242f700102284b8d69aae19faf07fc9a22e14dd | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/775 | ||||
| 60062707 | MDExOlB1bGxSZXF1ZXN0NjAwNjI3MDc= | 777 | closed | 0 | minor refactor of Rolling.reduce to handle nans | jhamman 2443309 | fixes #776 ~~Still need to add a regression test~~ | 2016-02-20T22:13:51Z | 2016-03-01T08:10:11Z | 2016-03-01T08:10:09Z | 2016-03-01T08:10:09Z | ac8e186abd143572c4aaf2c97c0dfd59aa2628b8 | 0 | 72e2d185961a40c459f5acc3d0d99a94c134efbe | b15f0ee759248ef52b9a53d410090133b86216ee | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/777 | ||||
| 61515856 | MDExOlB1bGxSZXF1ZXN0NjE1MTU4NTY= | 782 | closed | 0 | dont infer interval breaks in pcolormesh when ax is a cartopy axis | jhamman 2443309 | This PR chooses not to infer interval breaks in pcolormesh if the axis is a Cartopy axis. Below is an example of a plot using the new behavior - compare to https://github.com/pydata/xarray/issues/781#issuecomment-191595449.  I'll come up with a few tests here. closes #781. | 2016-03-03T06:24:00Z | 2016-03-11T18:59:02Z | 2016-03-11T18:59:01Z | 2016-03-11T18:59:01Z | 34d082b02e427ff8602917f345658db6d10e0bcb | 0 | e3c17ead98debbfaaab41a41501303adc961c4a9 | 660d29d33cfc647324543e338d0b03ce7be1383b | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/782 | ||||
| 70302527 | MDExOlB1bGxSZXF1ZXN0NzAzMDI1Mjc= | 849 | closed | 0 | roundtrip boolean datatype | jhamman 2443309 | This PR allows boolean datatypes to be faithfully roundtripped. My approach follows @shoyer's suggestions in https://github.com/pydata/xarray/pull/401#issuecomment-96085330. closes #401 cc @klapo, @khaeru | 2016-05-17T05:42:53Z | 2016-05-23T04:54:42Z | 2016-05-23T04:54:40Z | 2016-05-23T04:54:40Z | c9cde62c764251b7d39269e860a4a0553c79630f | 0 | e4bd6a1dc93b766996c69aac05c4849b677bbd7b | b9fab55e19d78c52090e41538753bd5d4ce54df7 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/849 | ||||
| 70998690 | MDExOlB1bGxSZXF1ZXN0NzA5OTg2OTA= | 856 | closed | 0 | drop python 2.6 support | jhamman 2443309 | closes #855. There is still a code base of work-arounds for Python 2.6 (examples below). I'm not sure if we want to remove those now or just stop testing with 2.6 in this PR. Thoughts from @shoyer and @MaximilianR? - [tests](https://github.com/pydata/xarray/blob/master/xarray/test/__init__.py#L110-L120) - [backends](https://github.com/pydata/xarray/blob/master/xarray/backends/api.py#L196-L197) | 2016-05-23T02:45:12Z | 2016-05-23T19:38:09Z | 2016-05-23T19:38:07Z | 2016-05-23T19:38:07Z | 765f17d3b31af1228c6c8def8e108f62a27d7260 | 0 | f21fe2b68350e3d62bddc905b16dd2bbf12daf3b | b9fab55e19d78c52090e41538753bd5d4ce54df7 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/856 | ||||
| 80024579 | MDExOlB1bGxSZXF1ZXN0ODAwMjQ1Nzk= | 941 | closed | 0 | add faq on how to cite xarray | jhamman 2443309 | closes #290 closes #931 | 2016-08-04T06:28:14Z | 2016-08-04T21:17:55Z | 2016-08-04T21:17:53Z | 2016-08-04T21:17:53Z | b0727412fd32e1110d20dbad001292bde856656e | 0 | c5f6e513f46730bfa9e548c7ae8a2bf071e4593e | 9d8bb1325b2d5992574622273bc379bb51fa663c | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/941 | ||||
| 82424747 | MDExOlB1bGxSZXF1ZXN0ODI0MjQ3NDc= | 982 | closed | 0 | update rasm example - ipython notebook and rst | jhamman 2443309 | xref: https://github.com/pydata/xarray-data/pull/5 | 2016-08-23T19:20:46Z | 2016-08-23T19:37:13Z | 2016-08-23T19:37:11Z | 2016-08-23T19:37:11Z | ea26738e01db357c4b3d886914e49dc7b344af74 | 0 | 3c46ebbc121711fe5e5d8c6dd8adf49be05055cf | 584e70378c64e3fa861e5b4b4fd61d21639661c6 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/982 | ||||
| 82449206 | MDExOlB1bGxSZXF1ZXN0ODI0NDkyMDY= | 983 | closed | 0 | Update the Multimension coordinate groupby example | jhamman 2443309 | cc @rabernat @shoyer now using `ds = xr.tutorial.load_dataset('rasm')` | 2016-08-23T22:01:33Z | 2016-08-27T19:06:49Z | 2016-08-27T19:04:51Z | 2016-08-27T19:04:51Z | fda00bd246f8a1ac282efd8d4ca41c6bb5413777 | 0 | 1ac459b847fbf2d76a3847914407aa54adc4edd4 | ea26738e01db357c4b3d886914e49dc7b344af74 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/983 | ||||
| 84765407 | MDExOlB1bGxSZXF1ZXN0ODQ3NjU0MDc= | 1000 | closed | 0 | update how to cite xarray | jhamman 2443309 | 2016-09-10T19:30:09Z | 2016-09-12T00:03:15Z | 2016-09-12T00:03:13Z | 2016-09-12T00:03:13Z | 64b4f35f1ff220b5fd54e19490fc7cbab543ecee | 0 | 98a49efa16d3afef1900ce3a61fe9ba17fddf49e | f00ab9b8f55cd630a2dca905ad07ac1a8093a256 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1000 | |||||
| 87374389 | MDExOlB1bGxSZXF1ZXN0ODczNzQzODk= | 1021 | closed | 0 | Add colorbar object to FacetGrid object. | jhamman 2443309 | 2016-09-29T19:07:49Z | 2016-09-30T17:17:09Z | 2016-09-30T17:17:07Z | 2016-09-30T17:17:07Z | 38930f02145b453fdd7a04e273760cf070b223b0 | 0 | 99e6b04dfb04f004fc86f4f224ddad5225bb4131 | fbb4f0618eade20981bd5cfb9771b82fd88a8db5 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1021 | |||||
| 98427057 | MDExOlB1bGxSZXF1ZXN0OTg0MjcwNTc= | 1170 | closed | 0 | Dataset.encoding and unlimited dimensions for to_netcdf | jhamman 2443309 | Add `Dataset.encoding` attribute and support unlimited dimensions for scipy/netcdf4 backends. closes #992 | 2016-12-17T01:13:04Z | 2017-01-24T06:43:33Z | 2017-01-24T06:38:49Z | 2017-01-24T06:38:49Z | 6d5ad44e4666a50ed91a201ce28ad0b4e3d727a4 | 0 | cb22ba139d7adbfaab5d5340dcdb412f9b2ea766 | c5146e8f82ae8387a24b99b27fb8b7e623b38778 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1170 | ||||
| 98873849 | MDExOlB1bGxSZXF1ZXN0OTg4NzM4NDk= | 1176 | closed | 0 | add info method to dataset | jhamman 2443309 | I don't know if this is exactly what we want but here's an idea that emulates `ncdump -h`. I'm sure people will have thoughts on the implementation and output so I'll just throw this first cut up and let people discuss. closes #1150 fixes #244 xref: #1044, #820 | 2016-12-21T05:23:22Z | 2016-12-23T17:36:58Z | 2016-12-23T17:36:54Z | 2016-12-23T17:36:54Z | 81921900fe208c33fcdc74f1a8ce36ecf4a5d006 | 0 | 74df621815e32c8bad7a8b01d194d205a9d0b901 | aec3e8e8208f557864feb8f3e6a1c8c6cc200bc5 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1176 | ||||
| 99281642 | MDExOlB1bGxSZXF1ZXN0OTkyODE2NDI= | 1183 | closed | 0 | Test with Python 3.6 | jhamman 2443309 | Updated tests to use Python 3.6 for base test and development version tests. closes #1182 | 2016-12-23T21:09:51Z | 2017-01-22T04:31:08Z | 2017-01-22T04:31:04Z | 2017-01-22T04:31:04Z | 80fbc6e46c5a36bd4bfe24c667bd44d1f4e8e53a | 0 | b616fca994aed00f56a3c939e3e33ee774b94376 | 601c26250745eb1d032d867ea970067a7756b594 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1183 | ||||
| 99497806 | MDExOlB1bGxSZXF1ZXN0OTk0OTc4MDY= | 1187 | closed | 0 | add quantile method to DataArray | jhamman 2443309 | This PR adds the `quantile` method to the DataArray. There may be a way to better fit this in with `.apply` or `reduce` it wasn't immediately clear to me how to do that. It uses `np.nanpercentile` under the hood so this shouldn't be expected to work well with dask. The main advantage to this method, over using `apply(np.nanpercentile)` is the handling of the `quantile` coordinate. example usage: ```Python In [12]: x = np.random.random(size=(2, 3, 800)) In [13]: da = xr.DataArray(x, dims=('x', 'y', 'time')) In [14]: da.quantile([1, 5, 10, 25, 50, 75, 90, 95, 99], dim='time', interpolation='lower') Out[14]: <xarray.DataArray (quantile: 9, x: 2, y: 3)> array([[[ 0.00835474, 0.01126747, 0.00778847], [ 0.00803924, 0.00919259, 0.01150164]], [[ 0.04902814, 0.05346976, 0.04493341], [ 0.04236611, 0.05273082, 0.05858802]], [[ 0.09370776, 0.09976448, 0.09256707], [ 0.08943787, 0.09331907, 0.08832309]], [[ 0.25416402, 0.22577298, 0.24407393], [ 0.25386087, 0.23052584, 0.24621966]], [[ 0.534169 , 0.46017551, 0.49817391], [ 0.50968059, 0.49427688, 0.51573855]], [[ 0.76633412, 0.73405412, 0.77210754], [ 0.76759837, 0.74243892, 0.76703357]], [[ 0.90832116, 0.89495854, 0.91818434], [ 0.91492771, 0.88063773, 0.91416636]], [[ 0.95260527, 0.95132871, 0.95979701], [ 0.95988286, 0.93137055, 0.95941658]], [[ 0.98597133, 0.98883232, 0.99013424], [ 0.98951238, 0.97550784, 0.99224201]]]) Coordinates: * quantile (quantile) float64 1.0 5.0 10.0 25.0 50.0 75.0 90.0 95.0 99.0 o x (x) - o y (y) - ``` closes #303 fixes #561 | 2016-12-28T01:06:51Z | 2017-01-23T18:23:06Z | 2017-01-23T18:22:14Z | 2017-01-23T18:22:14Z | d5f4af50d14de165e6d5a5be4826910540384fc7 | 0 | d8ba5694351b6948dee89748a8b4a38dfaa7f2bd | 80fbc6e46c5a36bd4bfe24c667bd44d1f4e8e53a | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1187 | ||||
| 99609843 | MDExOlB1bGxSZXF1ZXN0OTk2MDk4NDM= | 1190 | closed | 0 | only use bottleneck version 1.0 and later | jhamman 2443309 | closes #808 | 2016-12-29T01:36:24Z | 2017-01-07T07:43:37Z | 2017-01-07T07:43:34Z | 2017-01-07T07:43:34Z | 417797e602f8d5a1463a9923968c3cb2f3e4b1f1 | 0 | 88b47104ac3d436bb638506bb955ba54af50844b | 27d04a15e27645e3c0d2db93ed7a8c983f5818a4 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1190 | ||||
| 103973581 | MDExOlB1bGxSZXF1ZXN0MTAzOTczNTgx | 1242 | closed | 0 | Cleanup | jhamman 2443309 | This is just a quick PR to clean up a few style violations that have crept in. I also removed a number of unused imports. - [ ] closes #xxxx - [x] tests passed - [x] passes ``git diff upstream/master | flake8 --diff`` - [ ] whatsnew entry | 2017-01-31T16:37:34Z | 2017-01-31T20:07:21Z | 2017-01-31T19:07:55Z | 2017-01-31T19:07:55Z | 93d6963315026f87841c7cf39cc39bb78f555345 | 0 | 4d9485884221a21f45247227acb8f0c655a7f462 | 176cd4f81ffa7c849ddd9c4592addf331a616e9f | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1242 | ||||
| 103977310 | MDExOlB1bGxSZXF1ZXN0MTAzOTc3MzEw | 1243 | closed | 0 | use latest doi badge for zenodo | jhamman 2443309 | Quick update to docs to use latest zenodo doi | 2017-01-31T16:55:05Z | 2017-01-31T18:38:07Z | 2017-01-31T18:38:04Z | 2017-01-31T18:38:04Z | 588339cd40bdefb9f33c534b1f1a320c2437f802 | 0 | 1821e426b62398e7ada4a1aeea67b77012d6c1c8 | 176cd4f81ffa7c849ddd9c4592addf331a616e9f | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1243 | ||||
| 104709202 | MDExOlB1bGxSZXF1ZXN0MTA0NzA5MjAy | 1250 | closed | 0 | add DataArray.pipe to api docs | jhamman 2443309 | - [ ] closes #xxxx - [ ] tests added / passed - [ ] passes ``git diff upstream/master | flake8 --diff`` - [ ] whatsnew entry | 2017-02-05T18:28:52Z | 2017-02-05T21:15:02Z | 2017-02-05T21:15:02Z | 2017-02-05T21:15:02Z | 7761c4b801437e6a092a778a0c9cd154b1e505c0 | 0 | 50308359998325b16ef35ff06788c729fda79540 | 93d6963315026f87841c7cf39cc39bb78f555345 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1250 | ||||
| 106945192 | MDExOlB1bGxSZXF1ZXN0MTA2OTQ1MTky | 1278 | closed | 0 | Feature/support bn 1 1 | jhamman 2443309 | Bottleneck added support for rolling variance calculations (`bn.move_var`) as well as a few other functions in version 1.1. This PR conditionally uses those new functions, when they are available. - [x] closes #1276 - [x] tests added / passed - [x] passes ``git diff upstream/master | flake8 --diff`` - [x] whatsnew entry cc @shoyer and @d-chambers | 2017-02-20T06:12:07Z | 2017-03-06T01:32:38Z | 2017-03-06T01:32:14Z | 2017-03-06T01:32:14Z | e92a8079d119d6f65936657be721605156c8bfbd | 0 | 0f2e1014dae8c6e99d5b237dc732ef3a802ca94f | 7f71e4087147938afa503e1460a05631f07c5c24 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1278 | ||||
| 114629774 | MDExOlB1bGxSZXF1ZXN0MTE0NjI5Nzc0 | 1355 | closed | 0 | update docs to reflect recently published paper on xarray | jhamman 2443309 | - [x] closes #931 and #290 (already closed) A few doc updates to reflect the newly published status of our xarray paper. | 2017-04-06T15:30:09Z | 2017-04-11T18:08:39Z | 2017-04-06T19:05:31Z | 2017-04-06T19:05:31Z | 61bb71db1753fd3192dfbe2ba29bdc43fda5e657 | 0 | 70e4496dfa596b5c9cf920b12b75dd0cc5592d5e | 94790388c273c0c1ce2c203940a706d331deb14f | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1355 | ||||
| 125936835 | MDExOlB1bGxSZXF1ZXN0MTI1OTM2ODM1 | 1457 | closed | 0 | Feature/benchmark | jhamman 2443309 | - [x] Closes #1257 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [ ] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API This is a very bare bones addition of the [asv](https://github.com/spacetelescope/asv/) benchmarking tool to xarray. I have added four very rudimentary benchmarks in the `dataset_io.py` module. Usage of `asv` is pretty straightforward but I'll outline the steps for those who want to try this out: ``` cd xarray conda install asv -c conda-forge asv run # this will install some conda environments in ./.asv/envs asv publish # this collates the results asv preview # this will launch a web server so you can visually compare the tests ``` Before I go any further, I want to get some input from @pydata/xarray on what we want to see in this PR. In previous projects, I have found designing tests after the fact can end up being fairly arbitrary and I want to avoid that if at all possible. I'm guessing that we will want to focus our efforts for now on I/O and dask related performance but how we do that is up for discussion. cc @shoyer, @rabernat, @MaximilianR, @Zac-HD | 2017-06-16T00:11:52Z | 2017-11-13T04:09:53Z | 2017-07-26T16:17:34Z | 2017-07-26T16:17:34Z | 96e6e8f7ad8dd493c9d15df2951999c6dd04e8c9 | 0.10 2415632 | 0 | 6c058083bfa7e4e044e50ea7e048c60c35686e22 | 5d245b22e9500a7eb805193ba5c65bb5474a5ae1 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1457 | |||
| 131816195 | MDExOlB1bGxSZXF1ZXN0MTMxODE2MTk1 | 1485 | closed | 0 | add ISSUE_TEMPLATE for github and xr.show_versions() | jhamman 2443309 | - [x] xref #986 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API This PR adds a new module level function `xr.show_versions()` and a new Github Issue Template to help with debugging user issues. Hopefully, we stop having to ask "what version of dask are you using?" Functionality is copied from [pandas](https://github.com/pandas-dev/pandas/blob/e99f56e43ab65710a34440067efe372d5f74280b/pandas/util/_print_versions.py). | 2017-07-21T16:54:29Z | 2017-10-28T01:24:08Z | 2017-10-28T01:24:02Z | 2017-10-28T01:24:02Z | 3a995294a99a00a62fb451c8dc3f0c404c8e92f5 | 0.10 2415632 | 0 | 97ee679446ca3941a2ec9098142623d2bba8be2d | 63902306176da07cf3db52805f3a90a62e18ad46 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1485 | |||
| 137864749 | MDExOlB1bGxSZXF1ZXN0MTM3ODY0NzQ5 | 1529 | closed | 0 | raise TypeError in Variable.quantile if data is a dask array | jhamman 2443309 | - [x] Closes #1524 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API | 2017-08-28T03:19:11Z | 2017-08-28T17:31:57Z | 2017-08-28T17:31:57Z | 2017-08-28T17:31:57Z | 174bad061dc5ac37a4b5e849ad2afa957127745f | 0 | c40336d5a06cf0c803998f75f249dbb0483b5b16 | bcd608101133c0cb84c74d341d22edef71ef4818 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1529 | ||||
| 138539001 | MDExOlB1bGxSZXF1ZXN0MTM4NTM5MDAx | 1538 | closed | 0 | Fix/1120 | jhamman 2443309 | - [x] Closes #1120 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API | 2017-08-30T22:02:52Z | 2017-09-06T00:07:11Z | 2017-09-06T00:07:08Z | 2017-09-06T00:07:08Z | 216bb6720dbe22b67fc6194f4f9525ae0f8924e2 | 0.10 2415632 | 0 | 59039a9213c116821ca0697f2fb5f4a9077a035e | 5472fb585b9bfda7b0ce5b54d0182d608199df35 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1538 | |||
| 138552535 | MDExOlB1bGxSZXF1ZXN0MTM4NTUyNTM1 | 1539 | closed | 0 | remove warning and raise error when dataset constructor is called wit… | jhamman 2443309 | …h coords dict and not dims - [x] Closes #1197 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API | 2017-08-30T23:42:57Z | 2017-08-31T19:17:32Z | 2017-08-31T19:17:29Z | 2017-08-31T19:17:29Z | 4571d60859850ec121fbaae04d717754f5a35dd1 | 0 | a2bf80b0c107dcacc7961d49aad29af2817506ce | 0b2424a1813bf1af712780c360a94a5588523adf | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1539 | ||||
| 138758173 | MDExOlB1bGxSZXF1ZXN0MTM4NzU4MTcz | 1543 | closed | 0 | pass dask compute/persist args through from load/compute/perist | jhamman 2443309 | - [x] Closes #1523 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API cc @crusaderky - putting this up in case its useful to you. I'm frankly not sure if my tests are doing what they need to but everything seems to be playing nicely. | 2017-08-31T20:24:50Z | 2017-09-05T19:55:50Z | 2017-09-05T19:55:46Z | 2017-09-05T19:55:46Z | 5472fb585b9bfda7b0ce5b54d0182d608199df35 | 0 | a879214ad6fe9b513c8f41e91ff190dd5098266f | d1ab8051bd4ae42a2e197a7175db1aa915363107 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1543 | ||||
| 138789324 | MDExOlB1bGxSZXF1ZXN0MTM4Nzg5MzI0 | 1544 | closed | 0 | allow positional indexing with unsigned integer types | jhamman 2443309 | - [x] Fixes #1405, Closes #1406 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API cc @gerritholl | 2017-08-31T23:42:52Z | 2017-09-01T14:18:51Z | 2017-09-01T14:18:51Z | 9a045768de9d0077420e12dfdede5bbccc524f57 | 0 | 46dd7c7cd0a9980572bcfd8f8362d5fb32c7444f | 4571d60859850ec121fbaae04d717754f5a35dd1 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1544 | |||||
| 138793278 | MDExOlB1bGxSZXF1ZXN0MTM4NzkzMjc4 | 1545 | closed | 0 | Concat retain encoding | jhamman 2443309 | - [x] Closes #1438, Fixes #1299 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API cc @gerritholl | 2017-09-01T00:21:41Z | 2017-09-05T04:10:05Z | 2017-09-05T04:10:02Z | 2017-09-05T04:10:02Z | d1ab8051bd4ae42a2e197a7175db1aa915363107 | 0 | 5e210b2b43278371efadb2d2dfe5c96148384c5b | 4571d60859850ec121fbaae04d717754f5a35dd1 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1545 | ||||
| 138954907 | MDExOlB1bGxSZXF1ZXN0MTM4OTU0OTA3 | 1546 | closed | 0 | return bytes from DataArray.to_netcdf when path is not provided | jhamman 2443309 | - [x] Closes #1410 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API | 2017-09-01T19:06:38Z | 2017-09-05T13:51:00Z | 2017-09-05T13:50:55Z | 2017-09-05T13:50:55Z | d11a4b1063d492b431952507836f2c991b59e8db | 0 | 59ef8a91a94e8cfd54d2829cb027392eac7804ef | d1ab8051bd4ae42a2e197a7175db1aa915363107 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1546 | ||||
| 139705782 | MDExOlB1bGxSZXF1ZXN0MTM5NzA1Nzgy | 1556 | closed | 0 | raise error if objects other than datasets are passed to save_mfdataset | jhamman 2443309 | - [x] Closes #1555 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API | 2017-09-07T02:50:41Z | 2017-09-07T07:38:49Z | 2017-09-07T07:38:46Z | 2017-09-07T07:38:46Z | 98a05f11c6f38489c82e86c9e9df796e7fb65fd2 | 0 | af08f696aec83752c932f814354292b2d126dbb5 | 216bb6720dbe22b67fc6194f4f9525ae0f8924e2 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1556 | ||||
| 139715643 | MDExOlB1bGxSZXF1ZXN0MTM5NzE1NjQz | 1557 | closed | 0 | fix unintentional skipped tests | jhamman 2443309 | - [x] Closes #1531 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API As @crusaderky pointed out, just moving the `@requires_pynio` decorator inside the `TestPyNio` class seems to fix the problems described in #1531. It looks like `requires_pynio` is nullifying `CFEncodedDataTest, Only32BitTypes, TestCase` in addition to `TestPyNio`, hence the propagation. This PR also includes a cleanup of `tests/__init__.py`. | 2017-09-07T04:47:27Z | 2017-10-04T23:12:52Z | 2017-10-04T23:12:48Z | 2017-10-04T23:12:48Z | e7136689751059619fe3aa07cd6f1469fd4a0ad4 | 0 | 993992def9afc075f52bedc2423bca03ac744672 | 24643ecee2eab04d0f84c41715d753e829f448e6 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1557 | ||||
| 139738491 | MDExOlB1bGxSZXF1ZXN0MTM5NzM4NDkx | 1558 | closed | 0 | stop skipping test_bivariate_ufunc in test_dask.py | jhamman 2443309 | - [x] Closes #1090 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` The fix for this issue went into dask v.0.13 (Jan 2, 2017). xrefs https://github.com/dask/dask/pull/1799, https://github.com/dask/dask/issues/1764 | 2017-09-07T07:55:04Z | 2017-09-07T20:04:15Z | 2017-09-07T20:04:07Z | 2017-09-07T20:04:07Z | 3a81942eb0cc38129208a52c391f7150af6f2538 | 0 | 4dc57c8d99ba74b921a5581e3017981b5582ecd3 | 98a05f11c6f38489c82e86c9e9df796e7fb65fd2 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1558 | ||||
| 140484541 | MDExOlB1bGxSZXF1ZXN0MTQwNDg0NTQx | 1568 | closed | 0 | support dask arrays in rolling computations using bottleneck functions | jhamman 2443309 | - [x] Closes #1279 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API cc @shoyer, @darothen, @arbennett, @vnoel | 2017-09-12T04:11:31Z | 2017-09-14T17:19:55Z | 2017-09-14T17:19:51Z | 2017-09-14T17:19:51Z | ae4df1d8304ccd1eebec2c50e66f1671c1682ef8 | 0 | 59455721d584b948d9958f286c3bab7dc772575f | fa6a7bee082332108d49fbbf452d04f8e7285172 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1568 | ||||
| 144724548 | MDExOlB1bGxSZXF1ZXN0MTQ0NzI0NTQ4 | 1607 | closed | 0 | fix nc4 shuffle option roundtrip | jhamman 2443309 | - [x] Closes #1606 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API | 2017-10-04T17:04:51Z | 2017-10-05T00:12:41Z | 2017-10-05T00:12:38Z | 2017-10-05T00:12:38Z | c748062ef4353f5e249553b06a198a44c71083c4 | 0 | 635f9d7bf4ffd0416e80ba93d8e31b00c22005d1 | e7136689751059619fe3aa07cd6f1469fd4a0ad4 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1607 | ||||
| 144733698 | MDExOlB1bGxSZXF1ZXN0MTQ0NzMzNjk4 | 1608 | closed | 0 | Fix resample/interpolate for non-upsampling case | jhamman 2443309 | - [x] Closes #1605 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - ~[ ] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API~ cc @darothen | 2017-10-04T17:49:10Z | 2017-10-05T16:57:03Z | 2017-10-05T16:34:14Z | 2017-10-05T16:34:14Z | 8710e0872533ccb82ac9716c24aa6e91f24113d0 | 0 | 9c5601384fb4500daf2d8cabd74377312e5d1a1b | 24643ecee2eab04d0f84c41715d753e829f448e6 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1608 | ||||
| 144775591 | MDExOlB1bGxSZXF1ZXN0MTQ0Nzc1NTkx | 1609 | closed | 0 | fix to_netcdf append bug (GH1215) | jhamman 2443309 | - [x] Closes #1215 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API ~TODO: Additional tests needed to verify this works for all the write backends and that the correct errors are raised when dims are different between writes.~ | 2017-10-04T21:05:29Z | 2017-10-25T05:09:10Z | 2017-10-25T05:09:10Z | 2017-10-25T05:09:10Z | f01d69802d9fd37d28817f77ad3cb9b6344268a3 | 0 | 09101d63db0ece7e66b0fcee8082a13783733708 | 423d3902ae432989a8a28bf9608621805d7095c5 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1609 | ||||
| 145761497 | MDExOlB1bGxSZXF1ZXN0MTQ1NzYxNDk3 | 1622 | closed | 0 | Improved netcdf4 error message when opening non existent file | jhamman 2443309 | - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` This is particularly helpful when using `open_mfdataset` with a list of files. For example: Current behavior (unclear which file is causing open_dataset to choke): ```Python-traceback In [2]: xr.open_mfdataset(['foo.nc', 'bar.nc'], engine='netcdf4') --------------------------------------------------------------------------- OSError Traceback (most recent call last) <ipython-input-2-12b24f38f025> in <module>() ----> 1 xr.open_mfdataset(['foo.nc', 'bar.nc'], engine='netcdf4') ... /Users/jhamman/Dropbox/src/xarray/xarray/backends/netCDF4_.py in _open_netcdf4_group(filename, mode, group, **kwargs) 183 import netCDF4 as nc4 184 --> 185 ds = nc4.Dataset(filename, mode=mode, **kwargs) 186 187 with close_on_error(ds): netCDF4/_netCDF4.pyx in netCDF4._netCDF4.Dataset.__init__() netCDF4/_netCDF4.pyx in netCDF4._netCDF4._ensure_nc_success() OSError: No such file or directory ``` And the new behavior ```Python-traceback In [2]: xr.open_mfdataset(['foo.nc', 'bar.nc'], engine='netcdf4') ... /Users/jhamman/Dropbox/src/xarray/xarray/backends/netCDF4_.py in _open_netcdf4_group(filename, mode, group, **kwargs) 186 ds = nc4.Dataset(filename, mode=mode, **kwargs) 187 except OSError as e: --> 188 raise OSError("Error opening %r" % filename, e) 189 190 with close_on_error(ds): OSError: [Errno Error opening '/Users/jhamman/Dropbox/src/xarray/foo.nc'] No such file or directory | 2017-10-10T18:03:16Z | 2017-10-20T19:35:11Z | 2017-10-20T19:35:11Z | 6b74f020418e31a52144e1e79359f739af91b947 | 0 | e864567484b2b484ff6c35614289880eb2ce2dd5 | b46fcd656391d786b8d25b0615f6d4bd30b524b7 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1622 | |||||
| 146944492 | MDExOlB1bGxSZXF1ZXN0MTQ2OTQ0NDky | 1634 | closed | 0 | catch/supress seaborn import warning | jhamman 2443309 | - [x] Closes #1633 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API | 2017-10-17T05:07:07Z | 2017-10-23T15:58:12Z | 2017-10-23T15:58:09Z | 2017-10-23T15:58:09Z | 2c83e5496f7cf9984c8eb70a88ef5d30d278c673 | 0 | 2c3792422e2f42b80e11707cd392eaadac707e24 | 2949558b75a65404a500a237ec54834fd6946d07 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1634 | ||||
| 147133026 | MDExOlB1bGxSZXF1ZXN0MTQ3MTMzMDI2 | 1637 | closed | 0 | Add unlim dims for h5netcdf | jhamman 2443309 | - [x] Closes #1636 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API (*these tests will fail until conda-forge get's an updated version of h5netcdf*) | 2017-10-17T19:35:40Z | 2017-10-18T19:56:46Z | 2017-10-18T19:56:43Z | 2017-10-18T19:56:43Z | 4c3c3328a7ea8269e1411c5119dd0b3d4d972cc4 | 0 | 6efca5265f36a9ba8dd9c931848de2d8932e2ac5 | 2949558b75a65404a500a237ec54834fd6946d07 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1637 | ||||
| 147695311 | MDExOlB1bGxSZXF1ZXN0MTQ3Njk1MzEx | 1640 | closed | 0 | WIP: Feature/interpolate | jhamman 2443309 | - [x] Closes #1631 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API Rough draft of interpolate method for filling of arbitrary nans. cc @darothen | 2017-10-20T00:26:25Z | 2017-12-30T06:58:52Z | 2017-12-30T06:21:42Z | 2017-12-30T06:21:42Z | 783b527b8ed2a79fbb1439c9a87db144edc55cf7 | 0 | d3220f3324b215cd0b1c8041f642f5ddf3c6c0ae | 6eac8574f85623b18b59ba1ac9cf95e09c87980b | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1640 | ||||
| 148568774 | MDExOlB1bGxSZXF1ZXN0MTQ4NTY4Nzc0 | 1657 | closed | 0 | fixes for warnings related to unit tests and nan comparisons | jhamman 2443309 | - [x] Closes #1652 - [x] Tests added / passed - [x] Passes ``git diff upstream/master | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API This first commit just includes the fixes for the warnings issued in our unit tests. I've temporarily added `-W error` to the travis builds so we can see the warnings/errors for all environments. Next step is to address the warnings in the xarray code itself. | 2017-10-25T04:38:09Z | 2017-10-29T18:19:44Z | 2017-10-29T18:19:06Z | 2017-10-29T18:19:05Z | d016ea7d925d3d53796b7c68b6d377bdb7497a8e | 0 | c2126fc0bced0e78d9ac3d0a240e2e25a329c943 | c58d1426401a1f7b6ad14a14a67afe25189e4ff3 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1657 | ||||
| 148724400 | MDExOlB1bGxSZXF1ZXN0MTQ4NzI0NDAw | 1660 | closed | 0 | fix CI builds (pytest/hypothesis) | jhamman 2443309 | - [x] Closes #1655 - [x] Tests added / passed | 2017-10-25T16:54:34Z | 2017-10-25T17:59:52Z | 2017-10-25T17:59:49Z | 2017-10-25T17:59:48Z | 888b383b844fedae8b04095d0cb0d08066b19de9 | 0 | 2d3c7d1ba719c60806775b393bc34f382ef71ec8 | f01d69802d9fd37d28817f77ad3cb9b6344268a3 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1660 | ||||
| 150448641 | MDExOlB1bGxSZXF1ZXN0MTUwNDQ4NjQx | 1685 | closed | 0 | fix bugs in is_scalar and as_variable for dask arrays | jhamman 2443309 | - [x] Closes #1684 - [x] Tests added / passed - [x] Passes ``git diff upstream/master **/*py | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API xref: #1674 cc @shoyer, @mrocklin | 2017-11-03T03:18:30Z | 2017-11-05T11:04:43Z | 2017-11-05T01:29:45Z | 2017-11-05T01:29:45Z | acae757d869af776a4b2bd980fb77a1873f4c510 | 0 | e94bd8d9d29efd1082fc4182c2b12694ce50e743 | f83361c76b6aa8cdba8923080bb6b98560cf3a96 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1685 | ||||
| 156877513 | MDExOlB1bGxSZXF1ZXN0MTU2ODc3NTEz | 1767 | closed | 0 | use pandas Grouper instead of TimeGrouper | jhamman 2443309 | - [x] Closes #1766 - [ ] Tests added (for all bug fixes or enhancements) - [x] Tests passed (for all non-documentation changes) - [x] Passes ``git diff upstream/master **/*py | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API | 2017-12-07T00:43:05Z | 2017-12-07T01:33:33Z | 2017-12-07T01:33:29Z | 2017-12-07T01:33:28Z | 3a28b611e40f2a09c05f982242f638cc3f7d94bf | 0 | c5e338335296b1752c99c4d284aa7437b53691da | c2b205f29467a4431baa80b5c07fe31bda67fbef | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1767 | ||||
| 159286994 | MDExOlB1bGxSZXF1ZXN0MTU5Mjg2OTk0 | 1793 | closed | 0 | fix distributed writes | jhamman 2443309 | - [x] Closes #1464 - [x] Tests added - [x] Tests passed - [x] Passes ``git diff upstream/master **/*py | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API Right now, I've just modified the dask distributed integration tests so we can all see the [failing tests](https://travis-ci.org/jhamman/xarray/jobs/317603224#L4400-L4571). I'm happy to push this further but I thought I'd see if either @shoyer or @mrocklin have an idea where to start? | 2017-12-19T22:24:41Z | 2018-03-13T15:32:54Z | 2018-03-10T15:43:18Z | 2018-03-10T15:43:18Z | 2f590f7d7f34c7dfddea4d1d4f8877bca081b601 | 0.10.3 3008859 | 0 | 3c2ffbf5b85299a59e0fa12fdec8dff03346527f | 870e4eaf1895cfeffdc27dab61ad739e67133777 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1793 | |||
| 159582273 | MDExOlB1bGxSZXF1ZXN0MTU5NTgyMjcz | 1797 | closed | 0 | fix to docs and update print_versions with distributed/zarr | jhamman 2443309 | - [x] Tests passed (for all non-documentation changes) - [x] Passes ``git diff upstream/master **/*py | flake8 --diff`` | 2017-12-21T06:09:41Z | 2017-12-21T06:41:09Z | 2017-12-21T06:41:06Z | 2017-12-21T06:41:06Z | 4a9c1e313037ccadd6d4b1251de8d8f943443270 | 0 | da877b2e3797be90bee06c00541381bfd1c771b5 | eeb109d9181c84dfb93356c5f14045d839ee64cb | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1797 | ||||
| 159735727 | MDExOlB1bGxSZXF1ZXN0MTU5NzM1NzI3 | 1799 | closed | 0 | move backend append logic to the prepare_variable methods | jhamman 2443309 | - [x] Closes #1798 - [ ] Tests added (ideas for how to test that load is not called? Regression tests from #1609 are passing) - [x] Tests passed - [x] Passes ``git diff upstream/master **/*py | flake8 --diff`` (remove if you did not edit any Python files) - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API | 2017-12-21T19:44:54Z | 2017-12-28T05:40:21Z | 2017-12-28T05:40:17Z | 2017-12-28T05:40:16Z | 6eac8574f85623b18b59ba1ac9cf95e09c87980b | 0 | ec5172e2a6b9aea2f1d3326fa5370b64dc453a9c | 4a9c1e313037ccadd6d4b1251de8d8f943443270 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1799 | ||||
| 160165627 | MDExOlB1bGxSZXF1ZXN0MTYwMTY1NjI3 | 1800 | closed | 0 | WIP: Performance improvements for zarr backend | jhamman 2443309 | - [x] Closes #https://github.com/pangeo-data/pangeo/issues/48 - [x] Tests added (for all bug fixes or enhancements) - [x] Tests passed (for all non-documentation changes) - [x] Passes ``git diff upstream/master **/*py | flake8 --diff`` (remove if you did not edit any Python files) - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later) This is building on top of #1799. Based on the suggestion from @alimanfoo in https://github.com/pangeo-data/pangeo/issues/48#issuecomment-353807691, I have reworked the handling of attributes in the zarr backend. There is more to do here, particularly in the `set_dimensions` arena but this is giving almost a 2x speedup in writing to GCP. cc @rabernat, @mrocklin and @alimanfoo | 2017-12-26T20:37:45Z | 2018-01-24T14:56:57Z | 2018-01-24T14:55:52Z | 2018-01-24T14:55:52Z | 0a0593d78fad6c0b776d4c3c6b32a24b2bdfba35 | 0.10.3 3008859 | 0 | 96996eff5fbbd07ea87003762bc27befd70bbf58 | f3deb2f2495220af819021b199a5305b0d62ef36 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1800 | |||
| 161508331 | MDExOlB1bGxSZXF1ZXN0MTYxNTA4MzMx | 1811 | closed | 0 | WIP: Compute==False for to_zarr and to_netcdf | jhamman 2443309 | review of this can wait until after #1800 is merged. - [x] Closes #1784 - [x] Tests added (for all bug fixes or enhancements) - [x] Tests passed (for all non-documentation changes) - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later) cc @mrocklin | 2018-01-07T05:01:42Z | 2018-05-16T15:06:51Z | 2018-05-16T15:05:03Z | 2018-05-16T15:05:03Z | 8ef194f2e6f2e68f1f818606d6362ddfe801df1e | 0 | 75b2431beaf077f2a237f234de436b81d1f07b4f | 9f58d509a432f18d9ceb69bdc0808f2cb9b77f6c | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1811 | ||||
| 161953502 | MDExOlB1bGxSZXF1ZXN0MTYxOTUzNTAy | 1814 | closed | 0 | Fix/plot error and warning | jhamman 2443309 | - [x] Closes #1813 ~[ ] Tests added~ - [x] Tests passed - [x] Passes ``git diff upstream/master **/*py | flake8 --diff`` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later) | 2018-01-09T19:16:31Z | 2018-01-10T07:13:53Z | 2018-01-10T07:13:53Z | 2018-01-10T07:13:53Z | b6300ea9d9e84e24fc2e03bdff06d8d0659e2344 | 0 | e59fcf66d7e7d5c80a3d26c13425471ba4ace485 | ab0db05a58fd47fe895d1a85c09c37d96263d3b7 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1814 | ||||
| 165877425 | MDExOlB1bGxSZXF1ZXN0MTY1ODc3NDI1 | 1868 | closed | 0 | add h5py to show_versions() | jhamman 2443309 | - [x] Closes #1867 - [x] Tests passed (for all non-documentation changes) | 2018-01-30T03:25:13Z | 2018-01-30T15:33:14Z | 2018-01-30T06:21:15Z | 2018-01-30T06:21:15Z | e7e2778a4c6b2d41d98481b8cef94032eff9ebc2 | 0 | e9c0c139901d5b406842ef5d6c9b8f27336e32a2 | 015daca45bd7be32377bdf429c02117d5955452c | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1868 | ||||
| 166163249 | MDExOlB1bGxSZXF1ZXN0MTY2MTYzMjQ5 | 1871 | closed | 0 | add warning stating that xarray will drop python 2 support at the end of 2018 | jhamman 2443309 | - [x] Closes #1830 (remove if there is no corresponding issue, which should only be the case for minor changes) - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API | 2018-01-31T04:25:14Z | 2018-02-01T06:04:12Z | 2018-02-01T06:04:08Z | 2018-02-01T06:04:08Z | 55257b86fcfedba1c4be35183e55fa1f2de13667 | 0 | 11e5cce26820bfc0116c3ec0fee4ad484fac4c00 | 7b17b4f42abf90f7300a4865839fe6f6faae16ca | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1871 | ||||
| 166177839 | MDExOlB1bGxSZXF1ZXN0MTY2MTc3ODM5 | 1872 | closed | 0 | added contributing guide | jhamman 2443309 | - [x] Closes #640 - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API This is something we've talked about for a while and I'm capitalizing on a moment of inspiration. Full disclosure, I've taken most of this from Pandas and edited it just where it makes sense for Xarray. If others would like specific changes to this, please comment only on `doc/contributing.rst`, ~`CONTRIBUTING.md` is auto generated with `pandoc`~. @pydata/xarray, feel free to push directly to this branch if there are larger edits you'd like to add. | 2018-01-31T06:41:34Z | 2018-02-23T06:16:00Z | 2018-02-05T21:00:02Z | 2018-02-05T21:00:01Z | 7357a07806d2493c7cb2765f01d54ec9a8f2c87d | 0 | 2008f301237d79403ea552088d8439c7ed59a00b | 23866d0447da2765a0d655138edeefa454d99af1 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1872 | ||||
| 168927473 | MDExOlB1bGxSZXF1ZXN0MTY4OTI3NDcz | 1907 | closed | 0 | drop zarr variable name from the dask chunk name | jhamman 2443309 | - [x] Closes #1894 - [ ] Tests added (for all bug fixes or enhancements) - [x] Tests passed (for all non-documentation changes) - [ ] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API cc @mrocklin | 2018-02-13T18:55:33Z | 2018-02-17T04:40:18Z | 2018-02-17T04:40:15Z | 2018-02-17T04:40:15Z | e0621c7d66c13b486b1890f67a126caec2990da7 | 0 | ed60c914b02c0f9a55001014bfd45c881890180b | 33660b76057b7dc5b9c7dac77e286bb755b1d68e | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1907 | ||||
| 168942588 | MDExOlB1bGxSZXF1ZXN0MTY4OTQyNTg4 | 1908 | closed | 0 | Build documentation on TravisCI | jhamman 2443309 | - [x] Closes #1898 (remove if there is no corresponding issue, which should only be the case for minor changes) - [x] Tests added (for all bug fixes or enhancements) - [ ] Tests passed (for all non-documentation changes) - [ ] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later) | 2018-02-13T20:04:07Z | 2018-02-15T23:20:34Z | 2018-02-15T23:20:31Z | 2018-02-15T23:20:31Z | 174fe5d28b94147ecb0cb88d5301ca9479c6d7ad | 0 | 0f669670f864a52d046786069e4e62bc7859d635 | 2aa5b8a5c094593569f5bd9ae220d1f2fc0ecda0 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1908 | ||||
| 169737884 | MDExOlB1bGxSZXF1ZXN0MTY5NzM3ODg0 | 1920 | closed | 0 | Add netcdftime as an optional dependency. | jhamman 2443309 | - [x] Helps with #1084 - [x] Tests added (for all bug fixes or enhancements) - [x] Tests passed (for all non-documentation changes) - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later) I've added a temporary travis build with the master branch of `netcdftime`. After a while, we can probably remove that. This is helping us move towards https://github.com/Unidata/netcdf4-python/issues/601 and #1252 cc @jswhit and @spencerkclark | 2018-02-16T22:12:01Z | 2018-02-22T03:23:25Z | 2018-02-19T21:25:57Z | 2018-02-19T21:25:57Z | e544e0db42819076dc4a0c70f513b726fe8da511 | 0 | c2b35c1adee869d2c77680b305e83ac0679e421c | e0621c7d66c13b486b1890f67a126caec2990da7 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1920 | ||||
| 170385828 | MDExOlB1bGxSZXF1ZXN0MTcwMzg1ODI4 | 1933 | closed | 0 | Use conda-forge netcdftime wherever netcdf4 was tested | jhamman 2443309 | - [x] Closes #1920 - [x] Tests added (for all bug fixes or enhancements) - [x] Tests passed (for all non-documentation changes) - [x] Fully documented: see #1920 | 2018-02-21T06:22:08Z | 2018-03-09T19:22:34Z | 2018-03-09T19:22:20Z | 2018-03-09T19:22:19Z | 8c6a28435282b1fd988e3984ecec539de94b10ca | 0 | 493c262c5e6318dfce1a931c6a19c99e3bf4aec2 | 33095885e6a4d7b2504ced5d9d4d34f1d6e872e2 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1933 | ||||
| 171238397 | MDExOlB1bGxSZXF1ZXN0MTcxMjM4Mzk3 | 1939 | closed | 0 | Fix/dask isnull | jhamman 2443309 | - [x] Closes #1937 - [x] Tests added (for all bug fixes or enhancements) - [x] Tests passed (for all non-documentation changes) - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API Thanks @fujiisoup for the report. | 2018-02-25T16:32:47Z | 2018-02-25T20:52:17Z | 2018-02-25T20:52:16Z | 2018-02-25T20:52:16Z | ec6e1603680ffa5a975baf890953cf2605394f0c | 0 | 6a18a1c5b58603301194754dcb3016f4475f4b10 | fc7fe4875289778014fc1ea04b6b09be12f9750a | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1939 | ||||
| 174185429 | MDExOlB1bGxSZXF1ZXN0MTc0MTg1NDI5 | 1980 | closed | 0 | Fix for failing zarr test | jhamman 2443309 | - [x] Closes #1979 and #1955 - [x] Tests added - [x] Tests passed | 2018-03-10T19:26:37Z | 2018-03-12T05:37:09Z | 2018-03-12T05:37:02Z | 2018-03-12T05:37:02Z | aa83d0ec5a0da9e8880d3194864ff212d5990d6b | 0 | f755975813f324dbf9df18fa5f2877799b1a1d4c | 2f590f7d7f34c7dfddea4d1d4f8877bca081b601 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1980 | ||||
| 174531572 | MDExOlB1bGxSZXF1ZXN0MTc0NTMxNTcy | 1983 | closed | 0 | Parallel open_mfdataset | jhamman 2443309 | - [x] Closes #1981 - [x] Tests added - [x] Tests passed - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API I'm sharing this in the hopes of getting comments from @mrocklin and @pydata/xarray. What this does: - implements a `dask.bag` map/apply on the xarray `open_dataset` and `preprocess` steps in `open_mfdataset` - adds a new `parallel` option to `open_mfdataset` - provides about a 40% speedup in opening a multifile dataset when using the distributed scheduler (I tested on 1000 netcdf files that took about 9 seconds to open/concatenate in the default configuration) What it does not do (yet): - check that `autoclose=True` when multiple processes are being use (multiprocessing/distributed scheduler) - provide any speedup with the multiprocessing backend (I do not understand why this is) ------ ### Benchmark Example ```Python In [1]: import xarray as xr ...: import dask ...: import dask.threaded ...: import dask.multiprocessing ...: from dask.distributed import Client ...: In [2]: c = Client() ...: c ...: Out[2]: <Client: scheduler='tcp://127.0.0.1:59576' processes=4 cores=4> In [4]: %%time ...: with dask.set_options(get=dask.multiprocessing.get): ...: ds = xr.open_mfdataset('../test_files/test_netcdf_*nc', autoclose=True, parallel=True) ...: CPU times: user 4.76 s, sys: 201 ms, total: 4.96 s Wall time: 7.74 s In [5]: %%time ...: with dask.set_options(get=c.get): ...: ds = xr.open_mfdataset('../test_files/test_netcdf_*nc', autoclose=True, parallel=True) ...: ...: CPU times: user 1.88 s, sys: 60.6 ms, total: 1.94 s Wall time: 4.41 s In [6]: %%time ...: with dask.set_options(get=dask.threaded.get): ...: ds = xr.open_mfdataset('../test_files/test_netcdf_*nc') ...: CPU times: user 7.77 s, sys: 247 ms, total: 8.02 s Wall time: 8.17 s In [7]: %%time ...: with dask.set_options(get=dask.threaded.get): ...: ds = xr.open_mfdataset('../… | 2018-03-13T00:44:35Z | 2018-04-20T12:04:31Z | 2018-04-20T12:04:23Z | 2018-04-20T12:04:23Z | 093518207f4a3210ec692308da2b181a646115d6 | 0 | b0a794822b1d717a2ca2d473c96d61ce6d930fbe | 68090bbfc6ce3ea72f8166375441d31f830de1ea | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/1983 | ||||
| 187978886 | MDExOlB1bGxSZXF1ZXN0MTg3OTc4ODg2 | 2131 | closed | 0 | Feature/pickle rasterio | jhamman 2443309 | - [x] Closes #2121 - [x] Tests added - [x] Tests passed - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API cc @rsignell-usgs | 2018-05-14T23:38:59Z | 2018-06-08T05:00:59Z | 2018-06-07T18:02:56Z | 2018-06-07T18:02:56Z | 21a9f3d7e3a5dd729aeafd08dda966c365520965 | 0 | 8d7c7689063c4b23fd2baa5db4023989bae03afe | bc52f8aa64833d8c97f9ef5253b6a78c7033f521 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/2131 | ||||
| 188518786 | MDExOlB1bGxSZXF1ZXN0MTg4NTE4Nzg2 | 2141 | closed | 0 | expose CFTimeIndex to public API | jhamman 2443309 | - [x] Closes #2140 ~- [ ] Tests added (for all bug fixes or enhancements)~ - [ ] Tests passed - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API cc @spencerkclark and @shoyer | 2018-05-16T18:19:59Z | 2018-05-16T19:48:00Z | 2018-05-16T19:48:00Z | 2018-05-16T19:48:00Z | 4972dfd84d4e7ed31875b4257492ca84939eda4a | 0 | bac56d1b94b2175af82b3f0d4361687e39dab6b9 | 8ef194f2e6f2e68f1f818606d6362ddfe801df1e | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/2141 | ||||
| 188875457 | MDExOlB1bGxSZXF1ZXN0MTg4ODc1NDU3 | 2154 | closed | 0 | fix unlimited dims bug | jhamman 2443309 | - [x] Closes #2134 - [x] Tests added - [x] Tests passed - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API | 2018-05-17T22:13:51Z | 2018-05-25T00:32:02Z | 2018-05-18T14:48:11Z | 2018-05-18T14:48:11Z | ecb10e347bbe0f0e4bab8a358f406923e5468dcf | 0 | a03bcf32fa4271f309bdee1a5e5f21b2c1fccc66 | 7bab27cc637a60bff2b510d4f4a419c9754eeaa3 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/2154 | ||||
| 189128764 | MDExOlB1bGxSZXF1ZXN0MTg5MTI4NzY0 | 2163 | closed | 0 | Versioneer | jhamman 2443309 | - [x] Closes #1300 (in a more portable way) - [x] Tests passed (for all non-documentation changes) - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later) This eliminates the need to edit `setup.py` before / after release and is a nice step towards simplifying xarray's release process. | 2018-05-18T20:35:39Z | 2018-05-20T23:14:03Z | 2018-05-20T23:14:03Z | 2018-05-20T23:14:03Z | 585b9a7913d98e26c28b4f1da599c1c6db551362 | 0 | b278cd9c7571bdfdd5cceb6b4470ab8df7045030 | c346d3b7bcdbd6073cf96fdeb0710467a284a611 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/2163 | ||||
| 191585858 | MDExOlB1bGxSZXF1ZXN0MTkxNTg1ODU4 | 2204 | closed | 0 | update minimum versions and associated code cleanup | jhamman 2443309 | - [x] closes #2200, closes #1829, closes #2203 - [x] Tests passed (for all non-documentation changes) - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later) This updates the following minimum versions: - numpy: 1.11 (Mar 27, 2016) --> 1.12 (Jan 15, 2017) - pandas: 0.18 (Mar 11, 2016) --> 0.19 (Oct 2, 2016) - dask: 0.9 (May 10, 2016) --> 0.16 and drops our tests for python 3.4. | 2018-05-30T21:27:14Z | 2018-07-08T00:55:36Z | 2018-07-08T00:55:32Z | 2018-07-08T00:55:31Z | 1688a59803786a9d88eeb43aa4c935f7052d6a80 | 0.11 2856429 | 0 | b8aa4c082095d30c0a116c4d0fea0c9d39999328 | 448c3f1ae919f94a2b594eaeb91c6fd950eca43f | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/2204 | |||
| 194407359 | MDExOlB1bGxSZXF1ZXN0MTk0NDA3MzU5 | 2228 | closed | 0 | fix zarr chunking bug | jhamman 2443309 | - [x] Closes #2225 - [x] Tests added - [x] Tests passed - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API | 2018-06-12T21:04:10Z | 2018-06-13T13:07:58Z | 2018-06-13T05:51:36Z | 2018-06-13T05:51:36Z | 66be9c5db7d86ea385c3a4cd4295bfce67e3f25b | 0 | 97dcc9476dc0f05b89a84babe4e0210a8e6fff73 | 6c3abedf906482111b06207b9016ea8493c42713 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/2228 | ||||
| 199925487 | MDExOlB1bGxSZXF1ZXN0MTk5OTI1NDg3 | 2271 | closed | 0 | dev/test build for python 3.7 | jhamman 2443309 | - [x] Tests added - [x] Tests passed (for all non-documentation changes) - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API | 2018-07-08T05:02:19Z | 2018-09-22T23:09:43Z | 2018-09-22T20:13:28Z | 2018-09-22T20:13:28Z | 04253f271c66a12366a82d357c2a889dd3eea42f | 0 | ffcfc9d1512b2958856780e2a64bdcc89f6b9a34 | 4577ed891f9839722fd9e606e4f3bdb8e6acef4f | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/2271 | ||||
| 200888374 | MDExOlB1bGxSZXF1ZXN0MjAwODg4Mzc0 | 2282 | closed | 0 | fix dask get_scheduler warning | jhamman 2443309 | - [x] Closes #2238 - [ ] Tests added (for all bug fixes or enhancements) - [x] Tests passed (for all non-documentation changes) - [ ] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API | 2018-07-12T05:01:02Z | 2018-07-14T16:19:58Z | 2018-07-14T16:19:53Z | 2018-07-14T16:19:53Z | afee350789cacecc689c63fe580c98025e29d3db | 0 | 20330b36b1593072ce7f7cabac172b9334def8c6 | 1688a59803786a9d88eeb43aa4c935f7052d6a80 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/2282 | ||||
| 204488426 | MDExOlB1bGxSZXF1ZXN0MjA0NDg4NDI2 | 2320 | closed | 0 | Fix for zarr encoding bug | jhamman 2443309 | - [x] Closes #2278 - [x] Tests added - [ ] Tests passed - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API | 2018-07-27T17:05:27Z | 2018-08-14T03:46:37Z | 2018-08-14T03:46:34Z | 2018-08-14T03:46:34Z | df4a4b145b68c11d50576c961cf33c09b5bb9905 | 0 | 6b74e5254e99dd5ca97eddd63cf57b6538ccb460 | 4df048c146b8da7093faf96b3e59fb4d56945ec5 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/2320 | ||||
| 213668183 | MDExOlB1bGxSZXF1ZXN0MjEzNjY4MTgz | 2403 | closed | 0 | add some blurbs about numfocus sponsorship to docs | jhamman 2443309 | Xarray is now a fiscally sponsored project of NumFOCUS. This PR adds a few blurbs of text highlighting that on the main readme and index page of the docs. TODO: - Update flipcause to xarray specific donation page | 2018-09-06T15:54:06Z | 2018-09-19T05:37:34Z | 2018-09-11T02:14:18Z | 2018-09-11T02:14:18Z | 59bf7a7c13d8b01fd9600cb76c82b35b465f5707 | 0 | 01c359fcf5ab0339a5d0d9c05e7018ccb9ca6b31 | 66a8f8dd7f5a2997ff614f3966d1951587915e7e | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/2403 | ||||
| 214500699 | MDExOlB1bGxSZXF1ZXN0MjE0NTAwNjk5 | 2409 | closed | 0 | Numfocus | jhamman 2443309 | followup PR fixing two small typos in my previous PR. | 2018-09-11T03:15:52Z | 2018-09-11T05:13:51Z | 2018-09-11T05:13:51Z | 2018-09-11T05:13:51Z | 4de8dbc3b1de461c0c9d3b002e55d60b46d2e6d2 | 0 | ba468a1c868dbe32da6c9483b3f681e8542c96f0 | 59bf7a7c13d8b01fd9600cb76c82b35b465f5707 | MEMBER | xarray 13221727 | https://github.com/pydata/xarray/pull/2409 |
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