pull_requests: 40324635
This data as json
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 |
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40324635 | MDExOlB1bGxSZXF1ZXN0NDAzMjQ2MzU= | 481 | closed | 0 | Add pointwise indexing via isel_points method | 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 | 1213895 | 0 | 5ab9d4b2f65584aac74e0e54050a84a1a0697773 | 1faf1b2cbf0cbed1d1b62b71df4aec8dbe63bb99 | MEMBER | 13221727 | https://github.com/pydata/xarray/pull/481 |
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