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  • xarray · 17 ✖
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
83324817 MDExOlB1bGxSZXF1ZXN0MzY1OTk5MDI= 414 Doc updates 3 shoyer 1217238 closed 0   0.5 987654 0 2015-06-01T05:30:50Z 2015-06-01T05:33:24Z 2015-06-01T05:33:17Z MEMBER   0 pydata/xarray/pulls/414 
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83266863 MDExOlB1bGxSZXF1ZXN0MzY1OTQ3NTE= 413 More doc updates for 0.5 shoyer 1217238 closed 0   0.5 987654 0 2015-06-01T02:09:49Z 2015-06-01T02:12:29Z 2015-06-01T02:12:27Z MEMBER   0 pydata/xarray/pulls/413 
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83029667 MDExOlB1bGxSZXF1ZXN0MzY1Nzg0MDk= 412 Doc updates shoyer 1217238 closed 0   0.5 987654 0 2015-05-31T07:41:07Z 2015-05-31T23:45:06Z 2015-05-31T23:45:04Z MEMBER   0 pydata/xarray/pulls/412 
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75454929 MDExOlB1bGxSZXF1ZXN0MzUxOTIwNzQ= 410 ENH: Add .sel() method to Dataset and DataArray shoyer 1217238 closed 0   0.5 987654 0 2015-05-12T04:17:36Z 2015-05-14T02:27:45Z 2015-05-14T02:27:43Z MEMBER   0 pydata/xarray/pulls/410

sel() now supports the method parameter, which works like the paramter of the same name on reindex(). It provides a simple interface for doing nearest- neighbor interpolation:

``` In [12]: ds.sel(x=1.1, method='nearest') Out[12]: <xray.Dataset> Dimensions: () Coordinates: x int64 1 Data variables: y int64 2

In [13]: ds.sel(x=[1.1, 2.1], method='pad') Out[13]: <xray.Dataset> Dimensions: (x: 2) Coordinates: * x (x) int64 1 2 Data variables: y (x) int64 2 3 ```

 
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74529471 MDExOlB1bGxSZXF1ZXN0MzUwNTUyNTE= 409 Add display_width option shoyer 1217238 closed 0   0.5 987654 0 2015-05-08T23:27:55Z 2015-05-12T04:19:28Z 2015-05-12T04:17:22Z MEMBER   0 pydata/xarray/pulls/409

Example usage:

``` In [12]: ds = xray.Dataset({'x': np.arange(1000)})

In [13]: with xray.set_options(display_width=40): ....: print(ds) ....: <xray.Dataset> Dimensions: (x: 1000) Coordinates: * x (x) int64 0 1 2 3 4 5 6 ... Data variables: empty

In [14]: with xray.set_options(display_width=60): ....: print(ds) ....: <xray.Dataset> Dimensions: (x: 1000) Coordinates: * x (x) int64 0 1 2 3 4 5 6 7 8 9 10 11 12 13 ... Data variables: empty ```

 
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72946694 MDExOlB1bGxSZXF1ZXN0MzQ2MjAwMTQ= 408 Improved docs for dask integration shoyer 1217238 closed 0   0.5 987654 0 2015-05-04T07:40:49Z 2015-05-04T08:12:59Z 2015-05-04T08:12:57Z MEMBER   0 pydata/xarray/pulls/408 
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72227526 MDExOlB1bGxSZXF1ZXN0MzQ0ODIyMTU= 407 Support reading and writing milliseconds/microseconds shoyer 1217238 closed 0   0.5 987654 0 2015-04-30T17:28:26Z 2015-05-01T20:33:53Z 2015-05-01T20:33:10Z MEMBER   0 pydata/xarray/pulls/407

Fixes #406.

 
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71994342 MDExOlB1bGxSZXF1ZXN0MzQ0MDc4MDE= 405 Add robust retry logic when accessing remote datasets shoyer 1217238 closed 0   0.5 987654 3 2015-04-29T21:25:47Z 2015-05-01T20:33:46Z 2015-05-01T20:33:45Z MEMBER   0 pydata/xarray/pulls/405

Accessing data from remote datasets now has retrying logic (with exponential backoff) that should make it robust to occasional bad responses from DAP servers.

 
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71747677 MDExOlB1bGxSZXF1ZXN0MzQzMjU5MDE= 403 Fix indexing remote datasets with pydap shoyer 1217238 closed 0   0.5 987654 0 2015-04-29T00:50:32Z 2015-04-29T00:55:17Z 2015-04-29T00:55:16Z MEMBER   0 pydata/xarray/pulls/403 
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70295909 MDExOlB1bGxSZXF1ZXN0MzM5MjE1OTc= 400 H5nc cleanup shoyer 1217238 closed 0   0.5 987654 0 2015-04-23T03:33:44Z 2015-04-23T03:41:19Z 2015-04-23T03:41:15Z MEMBER   0 pydata/xarray/pulls/400

Fixes #369 

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70015421 MDExOlB1bGxSZXF1ZXN0MzM4MjQzMDc= 399 Dataset.to_array and DataArray.to_dataset methods shoyer 1217238 closed 0   0.5 987654 0 2015-04-22T03:59:56Z 2015-04-22T04:34:56Z 2015-04-22T04:34:54Z MEMBER   0 pydata/xarray/pulls/399

These methods make it easy to switch back and forth between data arrays and datasets:

``` In [4]: ds = xray.Dataset({'a': 1, 'b': ('x', [1, 2, 3])}, ...: coords={'c': 42}, attrs={'Conventions': 'None'}) ...:

In [5]: ds.to_array() Out[5]: <xray.DataArray (variables: 2, x: 3)> array([[1, 1, 1], [1, 2, 3]]) Coordinates: c int64 42 * x (x) int64 0 1 2 * variables (variables) |S1 'a' 'b' Attributes: Conventions: None

In [6]: ds.to_array().to_dataset(dim='variables') Out[6]: <xray.Dataset> Dimensions: (x: 3) Coordinates: c int64 42 * x (x) int64 0 1 2 Data variables: a (x) int64 1 1 1 b (x) int64 1 2 3 Attributes: Conventions: None ```

Fixes #132

CC @IamJeffG 

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69972951 MDExOlB1bGxSZXF1ZXN0MzM4MTIxMzQ= 398 Rename .load_data() to the more succinct .load() shoyer 1217238 closed 0   0.5 987654 0 2015-04-21T23:01:46Z 2015-04-22T00:46:09Z 2015-04-22T00:46:08Z MEMBER   0 pydata/xarray/pulls/398

Also rename .chunk_data() -> .chunk() (but nobody is using that, yet).

 
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69767364 MDExOlB1bGxSZXF1ZXN0MzM3MzUyOTY= 397 Simplify load_data now that dask bugs have been fixed shoyer 1217238 closed 0   0.5 987654 0 2015-04-21T07:30:12Z 2015-04-21T07:35:49Z 2015-04-21T07:35:47Z MEMBER   0 pydata/xarray/pulls/397 
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69763046 MDExOlB1bGxSZXF1ZXN0MzM3MzQ0NTQ= 396 Add nbytes property shoyer 1217238 closed 0   0.5 987654 0 2015-04-21T07:14:00Z 2015-04-21T07:20:25Z 2015-04-21T07:20:23Z MEMBER   0 pydata/xarray/pulls/396 
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69714060 MDExOlB1bGxSZXF1ZXN0MzM3MjA0NTg= 395 Update xray to use updated dask.array and h5netcdf on pypi shoyer 1217238 closed 0   0.5 987654 0 2015-04-21T00:54:35Z 2015-04-21T01:07:03Z 2015-04-21T01:07:02Z MEMBER   0 pydata/xarray/pulls/395

This involves a big internal rename: block -> chunk

 
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67246147 MDExOlB1bGxSZXF1ZXN0MzI5MTM4MjA= 384 Fixes for dataset formatting shoyer 1217238 closed 0   0.5 987654 0 2015-04-08T23:53:40Z 2015-04-09T02:21:03Z 2015-04-09T02:21:00Z MEMBER   0 pydata/xarray/pulls/384

The previous tests were actually not being run because I named the test method incorrectly :(

 
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64206762 MDExOlB1bGxSZXF1ZXN0MzE5MDAxOTE= 381 WIP: support dask.array in xray objects shoyer 1217238 closed 0   0.5 987654 1 2015-03-25T08:00:50Z 2015-04-08T03:44:08Z 2015-04-08T03:44:08Z MEMBER   0 pydata/xarray/pulls/381

xref #328

 
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     xarray 13221727 pull

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