issue_comments: 427195935

I just got bit with this as well. I was basically using tuples of indices as coordinates in order to implement a multidimensional sparse array .

My workaround is to use plain dimension index_dim to index the points in the N-dimensional space that I actually populate, and to have several coordinates (say X,Y) that all have index_dim as their only dimension. It's easy enough to see what the coordinates are once you select a value along index_dim, but I have to go outside xarray to locate a populated point based on it's X,Y-coordinates, because I can't slice along those arrays as (A) they aren't aliased to a dimension (B) they have non-unique values.

I've come up with an ugly method for selecting by tuples of X,Y-coordinates:

pairs = zip(x_wanted,y_wanted)

pair2index = {(dataset.x[i].item(), dataset.y[i].item()):i for i in dataset.index_dim.data}

try:

     found_indices = [pair2index[p] for p in pairs]

     found = dataset.isel(index_dim=found_indices)

except KeyError:

     print "Coordinate {} not found in dataset.".format(p)

     raise