issues

The following code will not run with current version of the xarray

``` import numpy as np import xarray as xr p_data = np.array([('John', 180), ('Stacy', 150), ('Dick',200)], dtype=[('name', '|S256'), ('height', int)]) p_data_1 = np.array([('John', 180), ('Stacy', 150), ('Dick',200)], dtype=[('name', '|S256'), ('height', int)]) weights_0 = xr.DataArray([80,56,120], dims=['participant'], coords={'participant':p_data}) weights_1 = xr.DataArray([81,52,115], dims=['participant'], coords={'participant':p_data_1})

print weights_1-weights_0 ```

It will crash with the error

ValueError: index 'participant' not aligned

The real cause is the isnull function from pandas that throws TypeError exception when called on e.g. numpy recarray or numpy structured array

A quick fix involves replacing array_equiv function in xarray.core.ops.py with the following implementation

``` def array_equiv(arr1, arr2): """Like np.array_equal, but also allows values to be NaN in both arrays """ arr1, arr2 = as_like_arrays(arr1, arr2) if arr1.shape != arr2.shape: return False

flag_array = (arr1 == arr2)

# isnull fcn from pandas will throw TypeError when run on numpy structured array
# therefore for dims that are np structured arrays we skip testing for nan
try:

    flag_array |= (isnull(arr1) & isnull(arr2))

except TypeError:
    pass

return bool(flag_array.all())

```