issue_comments

Okay - that worked. I think we're good with numpy 1.10 here. There is still one failing test related to pandas/numpy. This may be more of a travis thing.

ugh indeed. I'll figure out how to coerce the datetime64 object into something that works for now.

I'm actually going to paste the traceback from one of the test results (using py.test) to show how nonsensical this is:

``` =========================================================================================================== FAILURES ============================================================================================================ _____________ TestVariable.test_index_0d_not_a_time _____________

self = <xray.test.test_variable.TestVariable testMethod=test_index_0d_not_a_time>

def test_index_0d_not_a_time(self):
    d = np.datetime64('NaT')
    x = self.cls(['x'], [d])
    # Wasn't able to figure out why this was failing.
    # AssertionError: numpy.datetime64('NaT') != numpy.datetime64('NaT')

  self.assertIndexedLikeNDArray(x, d, None)

xray/test/test_variable.py:115:

xray/test/test_variable.py:61: in assertIndexedLikeNDArray self.assertEqual(variable.values[0], expected_value0)

self = <xray.test.test_variable.TestVariable testMethod=test_index_0d_not_a_time>, a1 = numpy.datetime64('NaT'), a2 = numpy.datetime64('NaT')

def assertEqual(self, a1, a2):

  assert a1 == a2 or (a1 != a1 and a2 != a2)

E AssertionError: assert (numpy.datetime64('NaT') == numpy.datetime64('NaT') or (numpy.datetime64('NaT') != numpy.datetime64('NaT')))

xray/test/init.py:154: AssertionError ```

I don't get how neither of these are true:

(numpy.datetime64('NaT') == numpy.datetime64('NaT') or\ (numpy.datetime64('NaT') != numpy.datetime64('NaT')))

Previously, NaT == NaT was true. Now it's false, like how NaN works.

@shoyer - I don't think this is true.

``` Python In [9]: import numpy as np

In [10]: t = np.datetime64('NaT')

In [11]: t == t Out[11]: True

In [12]: n = np.nan

In [13]: n == n Out[13]: False

In [14]: np.version Out[14]: '1.10.0' ```

I'll figure out something to do with the NaT comparison.

I think we're okay on Travis. We just have one failing test.

As for the verbosity of the numpy warnings. It is now just showing up in a lot more places (https://travis-ci.org/xray/xray/jobs/84683346#L665-L702). It seems like matplotlib and numpy itself haven't dealt with the warnings on their end yet.