Python xarray index return

Question

I have a multidimensional xarray like:

testarray = xr.DataArray([[1,-2,3],[4,5,-6]])

and i want to get the indices for a specific condition, eg. where testarray is smaller then 0. So the expected result should be an array like:

result = [[1,2],[0,1]]

Or any other format that let me get these indices for further calculations. Can't imagine, that there is no option within xarray for such an elementary problem, but i can't find it. Things like

testarray.where(testarray<0)

do some very ???suspicious??? stuff. Whats the use of an array thats the same but with nan's where conditions not met???

Thanks alot for your help :)

did you looked here ? xarray.pydata.org/en/stable/generated/… — woblob
– woblob, Commented Sep 24, 2020 at 19:51
Yes, but i think i'm to stupid to get it work ;) There is well explaine how to change values that match to a specific condition. But i have no idea how to get the indices of the values that match a specific condition. — Christian
– Christian, Commented Sep 24, 2020 at 21:09

Maximilian · Accepted Answer · 2020-09-26 22:51:03Z

2

To get the indices, you could use np.argwhere:

In [3]: da= xr.DataArray([[1,-2,3],[4,5,-6]])

In [4]: da
Out[4]:
<xarray.DataArray (dim_0: 2, dim_1: 3)>
array([[ 1, -2,  3],
       [ 4,  5, -6]])
Dimensions without coordinates: dim_0, dim_1


In [14]: da.where(da<0,0)
Out[14]:
<xarray.DataArray (dim_0: 2, dim_1: 3)>
array([[ 0, -2,  0],
       [ 0,  0, -6]])
Dimensions without coordinates: dim_0, dim_1

# Note you'd need to handle the case of a 0 value here

In [13]: np.argwhere(da.where(da<0,0).values)
Out[13]:
array([[0, 1],
       [1, 2]])

I agree this would be useful function to have natively in xarray; I'm not sure of the best way of doing it natively at the moment. Open to ideas!

answered Sep 26, 2020 at 22:51

Maximilian

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1 Comment

Christian Over a year ago

Hi, thanks for that solution. Well, as far as i have figured out combining numpy with xarray is simple. numpy.where does exactly what i want, but it is a very fragile and often easy error-prone, because it always depends on the type and mixing types liky run into broadcasting errors driving me as a beginner crazy. And in mor complex functions you tend to get those crazy lines like xarray(np.array(xarray(np.arrray....))) .. .. well, not that nice to handle sometimes ;)

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