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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
143107776 MDU6SXNzdWUxNDMxMDc3NzY= 801 dictionaries in labeled indexing with letter values nedlrichards 11950875 closed 0     2 2016-03-23T23:44:02Z 2016-03-24T16:05:23Z 2016-03-24T16:05:11Z CONTRIBUTOR      

An exception is raised when a letter is used in a dictionary as a labelled index. I believe this use of letter values is acceptable according to #291.

The error is:

ValueError: invalid literal for int() with base 10: 'b'

The work around is simple at least, the .loc keyword works as expected with dictionary labelled indexing.

``` test = np.random.randn(3, 3) test_xr = xr.DataArray(test, coords=[[1, 2, 3], ['a', 'b', 'c']], dims=['inter', 'alpha']) test_xr.loc[dict(inter=1)] test_xr[dict(inter=1)] test_xr.loc[dict(alpha='b')]

Throws a ValueError exception

test_xr[dict(alpha='b')] ```

 
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   completed xarray 13221727 issue
132535802 MDU6SXNzdWUxMzI1MzU4MDI= 753 creating DataArray from list of complex DataArray nedlrichards 11950875 closed 0     3 2016-02-09T21:13:50Z 2016-02-11T16:11:52Z 2016-02-11T16:11:52Z CONTRIBUTOR      

The DataArray constructor fails with a TypeError in the following case:

c1 = xr.DataArray(np.array((1, 2), dtype=np.complex)) c2 = xr.DataArray(np.array((3, 4), dtype=np.complex)) test = xr.DataArray([c1, c2])

The constructor works fine if c1 and c2 are np.arrays:

c1 = np.array((1, 2), dtype=np.complex) c2 = np.array((3, 4), dtype=np.complex) test = xr.DataArray([c1,c2])

and constructing the array with concatenation also works:

c1 = xr.DataArray(np.array((1, 2), dtype=np.complex)) c2 = xr.DataArray(np.array((3, 4), dtype=np.complex)) test = xr.concat([c1, c2], 'new')

Any thoughts on how to fix this?

 
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   completed xarray 13221727 issue
130767608 MDExOlB1bGxSZXF1ZXN0NTgwMjY4NjY= 743 BUG: reindexing an array with complex values should keep dtype=complex nedlrichards 11950875 closed 0     6 2016-02-02T18:11:48Z 2016-02-04T23:13:09Z 2016-02-04T23:12:37Z CONTRIBUTOR   0 pydata/xarray/pulls/743

Fixes #738

I have added a simple behaviour for complex numbers in _maybe_promote. This fix means that _maybe_promote does indeed return (dtype, np.nan + 0j) for complex dtypes, and the complex -> object conversion shown in #738 does not occur.

 
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     xarray 13221727 pull
130504978 MDU6SXNzdWUxMzA1MDQ5Nzg= 738 reindex_like with tolerance changes the type of returned DataArray nedlrichards 11950875 closed 0     1 2016-02-01T22:30:36Z 2016-02-04T23:12:37Z 2016-02-04T23:12:37Z CONTRIBUTOR      

I am really excited about all of the new changes to xarray! reindexing with tolerance has great potential to clean up some sort of nasty stuff that I use a lot but have tucked away into a corner of my code. I am not sure I am 100% comfortable with it at the moment, however, because it seems to be changing the types of my data in unexpected ways.

Bei:

``` test = xr.DataArray([1,2,3], coords=[[0.1, 0.2, 0.3]]) test_i = xr.DataArray([5,6,7,8], coords=[[0.21, 0.31, 0.41, 0.51]])

test.dtype test.reindex_like(test_i, method='pad', tolerance=0.2).dtype ```

the reindexed output has changed from int64 to float64!

Even more concerning is the complex example:

``` test = xr.DataArray(np.array([1,2,3], dtype=np.complex), coords=[[0.1, 0.2, 0.3]])

test.dtype test.reindex_like(test_i, method='pad', tolerance=0.2).dtype ```

Conversion from complex to object? Oh no.

Hope this isn't anything too big, let me know if I can help. Thank

 
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   completed xarray 13221727 issue

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