Transpose some but not all dimensions

Hi, all

Sorry to bother. Maybe it is a kind of stupid question for others, but I cannot figure it out at this moment.

I want to swap dims in xarray, like swapaxes in numpy. I found both dataarray and dataset has method swap_dims, but I don’t understand its arguments: dims_dict : dict-like Dictionary whose keys are current dimension names and whose values are new names. Each value must already be a coordinate on this array.

Here is my example:

data = np.random.rand(4,3)
lon = [1,2,3]
lat = [4,3,2,1]
foo = xr.DataArray(data,coords=[lat,lon])
foo
foo = xr.DataArray(data,coords=[lat,lon],dims=['lat','lon'])
foo
foo.swap_dims({'lat':'lon'})

The error message:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-47-c8aa4311b27e> in <module>()
----> 1 foo.swap_dims({'lat':'lon'})

/glade/u/home/che43/miniconda2/lib/python2.7/site-packages/xarray/core/dataarray.pyc in swap_dims(self, dims_dict)
    794         Dataset.swap_dims
    795         """
--> 796         ds = self._to_temp_dataset().swap_dims(dims_dict)
    797         return self._from_temp_dataset(ds)
    798

/glade/u/home/che43/miniconda2/lib/python2.7/site-packages/xarray/core/dataset.pyc in swap_dims(self, dims_dict, inplace)
   1293                 raise ValueError('replacement dimension %r is not a 1D '
   1294                                  'variable along the old dimension %r'
-> 1295                                  % (v, k))
   1296
   1297         result_dims = set(dims_dict.get(dim, dim) for dim in self.dims)

ValueError: replacement dimension 'lon' is not a 1D variable along the old dimension 'lat'

Sorry to bother.

[crusaderky]

From personal experience I find that 99% of the time, I want to push some known dimensions either to the front or to the back of the array while I don’t care about the order of the others. I’d love to have this syntax:

transpose(..., "x", "y")

or

transpose("x", "y", ...)

where the ellipsis expands to all dimensions not explicitly listed, in their original order. There can be at most one ellipsis.

[shoyer]

There’s one edge case that might be worth thinking carefully about here: Consider a dataset with two variables with dimensions ('w', 'x', 'y', 'z') and ('x', 'w', 'y', 'z'). Now we write .transpose(..., 'z', 'y'). What should the dimensions of variables on the resulting dataset be?

1. Both ('w', 'x', 'z', 'y'), with ... filled in based on the order of dimensions in the overall dataset.
2. ('w', 'x', 'y', 'z') and ('x', 'w', 'y', 'z'), with ... filled in for each variable separately.