hgrecco / pint / 782
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bors[bot] 
Merge #630

630: Fix unit tests errors with numpy >=1.13 (Fix 577) r=cpascual a=cpascual

This PR fixes the 4 test errors/failiures reported in #577 and adds new travis builds with numpy 1.14

3 of the 4 problems are relatively trivial to solve.

The remaining one (`test_isreal`) is not so trivial because it  involves allowing to compare a *non-dimensionless* quantity against zero. The reason is that `numpy.isreal(x)` essentially does `x.imag !=0` if the `imag` method is implemented in x... and since Quantity reimplements .imag to return units (see #171), the check always returns False if x is a non-dimensionless quantity.

As mentioned, this can be solved by allowing comparisons against zero. Actually, this has already been requested in #194, but it was not implemented.

In this PR, I implemented the comparison-to-zero feature and provide several new unit tests for it. AFAIK this implementation takes into account the concerns expressed by @hgrecco in #194. But if the feature is not wanted, we can just revert the last 3 commits of this PR and then `test_isreal` will left with an expected failure flag.

The rules that I implemented for the comparison-with-zero are:
```    
    a) comparing against (non-quantity) zero is allowed for any quantity
    b) comparing against zero-magnitude quantities of incompatible
    dimensionality raises a Dimensionality error, except for the case
    of equality, for which it always returns False
    
    Notes:
    1.- Numpy arrays of zeros are also supported and the comparison rules
    apply elementwise
    2.- In the case of non-multiplicative units, the rules above
    apply after converting to base units if the autoconvert offset flag
    is set. Otherwise they raise an OffsetUnitCalculusError.
```

Fixes #577


Co-authored-by: Carlos Pascual <cpascual@cells.es>

2834 of 3202 relevant lines covered (88.51%)

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1 782.1 (UNCERTAINTIES="N" PYTHON="3.3" NUMPY_VERSION=1.9.2) 0
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2 782.2 (UNCERTAINTIES="N" PYTHON="3.4" NUMPY_VERSION=1.11.2) 0
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3 782.3 (UNCERTAINTIES="N" PYTHON="3.5" NUMPY_VERSION=1.11.2) 0
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4 782.4 (UNCERTAINTIES="Y" PYTHON="3.5" NUMPY_VERSION=1.11.2) 0
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5 782.5 (UNCERTAINTIES="N" PYTHON="3.6" NUMPY_VERSION=1.11.2) 0
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6 782.6 (UNCERTAINTIES="N" PYTHON="2.7" NUMPY_VERSION=0) 0
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7 782.7 (UNCERTAINTIES="N" PYTHON="3.5" NUMPY_VERSION=0) 0
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8 782.8 (UNCERTAINTIES="N" PYTHON="2.7" NUMPY_VERSION=1.14) 0
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9 782.9 (UNCERTAINTIES="N" PYTHON="3.4" NUMPY_VERSION=1.14) 0
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10 782.10 (UNCERTAINTIES="N" PYTHON="3.5" NUMPY_VERSION=1.14) 0
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11 782.11 (UNCERTAINTIES="Y" PYTHON="3.5" NUMPY_VERSION=1.14) 0
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12 782.12 (UNCERTAINTIES="N" PYTHON="3.6" NUMPY_VERSION=1.14) 0
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