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  • ENH: finite difference method `diff` · 8 ✖

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133518318 https://github.com/pydata/xarray/pull/495#issuecomment-133518318 https://api.github.com/repos/pydata/xarray/issues/495 MDEyOklzc3VlQ29tbWVudDEzMzUxODMxOA== shoyer 1217238 2015-08-21T18:13:00Z 2015-08-21T18:13:00Z MEMBER

OK, merging.

Thank you!

 
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   ENH: finite difference method `diff` 97237275
133056424 https://github.com/pydata/xarray/pull/495#issuecomment-133056424 https://api.github.com/repos/pydata/xarray/issues/495 MDEyOklzc3VlQ29tbWVudDEzMzA1NjQyNA== shoyer 1217238 2015-08-20T15:45:01Z 2015-08-20T15:45:01Z MEMBER

Could you try doing rebase -i master to pick out your commits? Otherwise github shows everything since the merge (look at the commit tab on this PR).

 
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   ENH: finite difference method `diff` 97237275
133055400 https://github.com/pydata/xarray/pull/495#issuecomment-133055400 https://api.github.com/repos/pydata/xarray/issues/495 MDEyOklzc3VlQ29tbWVudDEzMzA1NTQwMA== shoyer 1217238 2015-08-20T15:41:07Z 2015-08-20T15:41:07Z MEMBER 
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   ENH: finite difference method `diff` 97237275
132761093 https://github.com/pydata/xarray/pull/495#issuecomment-132761093 https://api.github.com/repos/pydata/xarray/issues/495 MDEyOklzc3VlQ29tbWVudDEzMjc2MTA5Mw== shoyer 1217238 2015-08-19T20:00:27Z 2015-08-19T20:00:27Z MEMBER

@andreas-h we're going to release v0.6 in the next day or two. I'd love to include this enhancement in it if you have the time to finish it up :).

 
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   ENH: finite difference method `diff` 97237275
125450222 https://github.com/pydata/xarray/pull/495#issuecomment-125450222 https://api.github.com/repos/pydata/xarray/issues/495 MDEyOklzc3VlQ29tbWVudDEyNTQ1MDIyMg== shoyer 1217238 2015-07-28T05:17:16Z 2015-07-28T05:17:16Z MEMBER

This could also use a bit of documentation -- at least mention on "What's New" and in the API docs.

 
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   ENH: finite difference method `diff` 97237275
125327122 https://github.com/pydata/xarray/pull/495#issuecomment-125327122 https://api.github.com/repos/pydata/xarray/issues/495 MDEyOklzc3VlQ29tbWVudDEyNTMyNzEyMg== shoyer 1217238 2015-07-27T20:02:03Z 2015-07-27T20:02:03Z MEMBER

Just made a PR against your branch with my suggestion: https://github.com/andreas-h/xray/pull/1

It looks like it's working now.

 
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   ENH: finite difference method `diff` 97237275
125302068 https://github.com/pydata/xarray/pull/495#issuecomment-125302068 https://api.github.com/repos/pydata/xarray/issues/495 MDEyOklzc3VlQ29tbWVudDEyNTMwMjA2OA== shoyer 1217238 2015-07-27T18:45:06Z 2015-07-27T18:45:06Z MEMBER

I don't see how 'mean' could work, as the coord might be of dtype str. But I'm implementing 'upper' and 'lower'. If the user wants something different, she can always just swap the coord manually.

Indeed, this would fail for string dtypes. I can see some possible utility in centered coordinates, especially for second order differences. We can certainly leave this for later, though.

 
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   ENH: finite difference method `diff` 97237275
125068381 https://github.com/pydata/xarray/pull/495#issuecomment-125068381 https://api.github.com/repos/pydata/xarray/issues/495 MDEyOklzc3VlQ29tbWVudDEyNTA2ODM4MQ== shoyer 1217238 2015-07-27T02:55:50Z 2015-07-27T02:55:50Z MEMBER

This looks very nice -- thanks for putting together the PR!

allow numeric axis instead of dim for DataArray objects.

I wouldn't bother with this. It's not so elegant, and dim already takes care of all the desired functionality.

allow specifying the new coordinate array explicitly via a coord kwarg instead of just taking the coordinate values of the upper bounds.

I wouldn't allow full control here, but maybe a keyword argument for choosing whether to take the "lower", "upper" or "mean" labels would be appropriate.

Actually, the current implementation leads to 0.0 for arrays inside a Dataset which don't have dim as a dimension. I personally would find it more intuitive if those arrays would not be touched at all.

I agree. It would be better to skip those variables entirely, like the current behavior for aggregation functions like mean.

 
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   ENH: finite difference method `diff` 97237275

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