issues: 144037264

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id node_id number title user state locked assignee milestone comments created_at updated_at closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
144037264 MDU6SXNzdWUxNDQwMzcyNjQ= 807 cumprod returns errors 4295853 closed 0     3 2016-03-28T17:50:13Z 2016-03-31T23:39:55Z 2016-03-31T23:39:55Z CONTRIBUTOR      

The xarray implementation of cumprod returns an assertion error, presumably because of bottleneck, e.g., https://github.com/pydata/xarray/blob/master/xarray/core/ops.py#L333. The error is

``` └─▪ ./test_cumprod.py [ 0.8841785 0.54181236 0.29075258 0.28883015 0.1137352 0.09909713 0.03570122 0.0304542 0.01578143 0.01496195 0.01442681 0.00980845] Traceback (most recent call last): File "./test_cumprod.py", line 13, in <module> foo.cumprod() File "/Users/pwolfram/anaconda/lib/python2.7/site-packages/xarray/core/common.py", line 16, in wrapped_func skipna=skipna, allow_lazy=True, kwargs) File "/Users/pwolfram/anaconda/lib/python2.7/site-packages/xarray/core/dataarray.py", line 991, in reduce var = self.variable.reduce(func, dim, axis, keep_attrs, kwargs) File "/Users/pwolfram/anaconda/lib/python2.7/site-packages/xarray/core/variable.py", line 871, in reduce axis=axis, **kwargs) File "/Users/pwolfram/anaconda/lib/python2.7/site-packages/xarray/core/ops.py", line 346, in f assert using_numpy_nan_func AssertionError

```

If bottleneck is uninstalled then a value error is returned:

└─▪ ./test_cumprod.py [ 2.99508768e-01 2.80142920e-01 1.56389242e-01 1.10791301e-01 4.58372649e-02 4.10865622e-02 9.91362500e-03 6.76033435e-03 3.83574249e-03 9.54972340e-04 1.56846616e-04 6.44088547e-05] Traceback (most recent call last): File "./test_cumprod.py", line 13, in <module> foo.cumprod() File "/Users/pwolfram/anaconda/lib/python2.7/site-packages/xarray/core/common.py", line 16, in wrapped_func skipna=skipna, allow_lazy=True, **kwargs) File "/Users/pwolfram/anaconda/lib/python2.7/site-packages/xarray/core/dataarray.py", line 991, in reduce var = self.variable.reduce(func, dim, axis, keep_attrs, **kwargs) File "/Users/pwolfram/anaconda/lib/python2.7/site-packages/xarray/core/variable.py", line 880, in reduce return Variable(dims, data, attrs=attrs) File "/Users/pwolfram/anaconda/lib/python2.7/site-packages/xarray/core/variable.py", line 213, in __init__ self._dims = self._parse_dimensions(dims) File "/Users/pwolfram/anaconda/lib/python2.7/site-packages/xarray/core/variable.py", line 321, in _parse_dimensions % (dims, self.ndim)) ValueError: dimensions () must have the same length as the number of data dimensions, ndim=1

No error occurs if the data array is converted to a numpy array prior to use of cumprod.

This can easily be reproduced by https://gist.github.com/c32f231b773ecc4b0ccf, excerpted below

``` import numpy as np import pandas as pd import xarray as xr

data = np.random.rand(4, 3) locs = ['IA', 'IL', 'IN'] times = pd.date_range('2000-01-01', periods=4) foo = xr.DataArray(data, coords=[times, locs], dims=['time', 'space']) print foo.values.cumprod() foo.cumprod() ```

 
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