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PYTHON=3.6 NUMPY=1.14.1 PANDAS=0.22.0 TEST='true' LINT='true' COVERAGE='true' PARALLEL='false' XTRATESTARGS= TEST_IMPORTS='true'

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jakirkham 
Fixed mean() and moment() on sparse arrays (#4525)

* Fixed mean() and moment() on sparse arrays

For proper creation of sparse auxiliary arrays, a dispatcher for ones_like has
been added. However, sparse arrays created from ones_like cause sparse
reductions to fail, as it would result in a dense array. To fix that, the arrays
have first to be converted to dense before, which ends up requiring a new
dispatcher for that purpose, and for already dense arrays must be bypassed, that
is here implemented as numpy.ndarray.view() to simply return a shallow copy of
the array.

This commit fixes https://github.com/dask/dask/issues/4523 and adds the tests
suggested in that issue.

* Reductions' numel() won't create ones() for unmasked arrays

* Add tests for new numel() implementation

* Fix numel() test, previously failing in Python 2.7.

* Remove ones_like_lookup() for sparse matrices

* remove todense_lookup

* Call correct sum() function in moment_chunk()

* Remove xfail from mean() sparse test

* Add sparse std() test back

* Test sparse moment()

* Test sparse var()

* Build also against sparse upstream

* Fix condition for CI upstream sparse installation

* Attempt to fix upstream sparse installation once more

* Enable __array_function__ in Python 3.7 build

* Remove leftover export from run_tests.sh

* Workaround for mkl.fft failures in test_array_function.py

* Minor reductions readability/code consistency changes

* Increase coverage of numel()

* Remove unnecessary for loop in numel() test

* Reenable development build, uses upstream libraries

* Revert "Reenable development build, uses upstream libraries"

This reverts commit 1705689db.

17319 of 18932 relevant lines covered (91.48%)

0.91 hits per line

Source Files on job 11233.7 (PYTHON=3.6 NUMPY=1.14.1 PANDAS=0.22.0 TEST='true' LINT='true' COVERAGE='true' PARALLEL='false' XTRATESTARGS= TEST_IMPORTS='true')