issues: 133136274

I recently tried to apply the argmin function on a dataset that I opened using xr.open_mfdataset and encountered an unexpected error. Applying argmin on the same dataset opened using xr.open_dataset works fine. Below is an example with some toy data. Could this be a bug, or is there something I'm doing wrong? I appreciate your help.

``` ipython In [1]: import xarray as xr In [2]: import numpy as np In [3]: xr.DataArray(np.random.rand(2, 3, 4), coords=[np.arange(2), np.arange(3), np.arange(4)], dims=['x', 'y', 'z']).to_dataset(name='test').to_netcdf('test_mfdataset.nc') In [4]: xr.open_dataset('test_mfdataset.nc').test.argmin('x').values Out[4]: array([[1, 1, 1, 1], [1, 0, 1, 0], [1, 1, 0, 1]])

In [5]: xr.open_mfdataset('test_mfdataset.nc').test.argmin('x').values

IndexError Traceback (most recent call last) <ipython-input-8-ccac9ca40874> in <module>() ----> 1 xr.open_mfdataset('test_mfdataset.nc').test.argmin('x').values

//anaconda/lib/python2.7/site-packages/xarray/core/dataarray.py in values(self) 353 def values(self): 354 """The array's data as a numpy.ndarray""" --> 355 return self.variable.values 356 357 @values.setter

//anaconda/lib/python2.7/site-packages/xarray/core/variable.py in values(self) 286 def values(self): 287 """The variable's data as a numpy.ndarray""" --> 288 return _as_array_or_item(self._data_cached()) 289 290 @values.setter

//anaconda/lib/python2.7/site-packages/xarray/core/variable.py in _data_cached(self) 252 def _data_cached(self): 253 if not isinstance(self._data, (np.ndarray, PandasIndexAdapter)): --> 254 self._data = np.asarray(self._data) 255 return self._data 256

//anaconda/lib/python2.7/site-packages/numpy/core/numeric.pyc in asarray(a, dtype, order) 472 473 """ --> 474 return array(a, dtype, copy=False, order=order) 475 476 def asanyarray(a, dtype=None, order=None):

//anaconda/lib/python2.7/site-packages/dask/array/core.py in array(self, dtype, kwargs) 852 853 def array(self, dtype=None, kwargs): --> 854 x = self.compute() 855 if dtype and x.dtype != dtype: 856 x = x.astype(dtype)

//anaconda/lib/python2.7/site-packages/dask/base.py in compute(self, kwargs) 35 36 def compute(self, kwargs): ---> 37 return compute(self, **kwargs)[0] 38 39 @classmethod

//anaconda/lib/python2.7/site-packages/dask/base.py in compute(args, kwargs) 108 for opt, val in groups.items()]) 109 keys = [var._keys() for var in variables] --> 110 results = get(dsk, keys, *kwargs) 111 112 results_iter = iter(results)

//anaconda/lib/python2.7/site-packages/dask/threaded.py in get(dsk, result, cache, num_workers, kwargs) 55 results = get_async(pool.apply_async, len(pool._pool), dsk, result, 56 cache=cache, queue=queue, get_id=_thread_get_id, ---> 57 kwargs) 58 59 return results

//anaconda/lib/python2.7/site-packages/dask/async.py in get_async(apply_async, num_workers, dsk, result, cache, queue, get_id, raise_on_exception, rerun_exceptions_locally, callbacks, **kwargs) 479 _execute_task(task, data) # Re-execute locally 480 else: --> 481 raise(remote_exception(res, tb)) 482 state['cache'][key] = res 483 finish_task(dsk, key, state, results, keyorder.get)

IndexError: shape mismatch: indexing arrays could not be broadcast together with shapes (3,4) (4,1) (1,3)

Traceback

File "//anaconda/lib/python2.7/site-packages/dask/async.py", line 264, in execute_task result = _execute_task(task, data) File "//anaconda/lib/python2.7/site-packages/dask/async.py", line 246, in _execute_task return func(*args2) File "//anaconda/lib/python2.7/site-packages/toolz/functoolz.py", line 381, in call ret = f(ret) File "//anaconda/lib/python2.7/site-packages/dask/array/reductions.py", line 450, in arg_agg return _arg_combine(data, axis, argfunc)[0] File "//anaconda/lib/python2.7/site-packages/dask/array/reductions.py", line 416, in _arg_combine arg = (arg + offsets)[tuple(inds)] ```