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Fixed a bug that showed when trying to establish equivalence of two a… #837

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Fixed a bug that showed when trying to establish equivalence of two a… #837

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f9c51b7
Fixed a bug that showed when trying to establish equivalence of two a…
maciekswat Apr 27, 2016
6635f9c
Fixed a bug that showed when trying to establish equivalence of two a…
maciekswat May 2, 2016
ee3a23e
fixed formatting according to PEP8 recommendation
maciekswat May 2, 2016
16a7c37
removed commented out code. simplified test_struct_array_dims
maciekswat May 2, 2016
96af68c
added a comment explaining the need to catch TypeError when calling i…
maciekswat May 3, 2016
b8beca4
Merge branch 'master' of https://github.com/pydata/xarray
maciekswat May 25, 2016
c0b97b1
Added issue number to the bugfix code
maciekswat May 25, 2016
693d019
updated bugfix entry in "what's new" document
maciekswat May 26, 2016
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13 changes: 12 additions & 1 deletion xarray/core/ops.py
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Expand Up @@ -187,7 +187,18 @@ def array_equiv(arr1, arr2):
arr1, arr2 = as_like_arrays(arr1, arr2)
if arr1.shape != arr2.shape:
return False
return bool(((arr1 == arr2) | (isnull(arr1) & isnull(arr2))).all())

flag_array = (arr1 == arr2)
try:

flag_array |= (isnull(arr1) & isnull(arr2))

except TypeError:
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could you add a brief comment explaining why we allow TypeError here? a reference to this issue (e.g., GH837)` could be nice, too.

pass

return bool(flag_array.all())

# return bool(((arr1 == arr2) | (isnull(arr1) & isnull(arr2))).all())
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remove commented out lines



def _call_possibly_missing_method(arg, name, args, kwargs):
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66 changes: 65 additions & 1 deletion xarray/test/test_dataarray.py
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Expand Up @@ -8,7 +8,10 @@
Coordinate, Variable)
from xarray.core.pycompat import iteritems, OrderedDict
from xarray.core.common import _full_like
from . import (TestCase, ReturnItem, source_ndarray, unittest, requires_dask,
# from . import (TestCase, ReturnItem, source_ndarray, unittest, requires_dask,
# requires_bottleneck)

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remove this commented out code.

from xarray.test import (TestCase, ReturnItem, source_ndarray, unittest, requires_dask,
requires_bottleneck)


Expand Down Expand Up @@ -63,6 +66,67 @@ def test_data_property(self):
self.assertArrayEqual(2 * np.ones((3, 4)), actual.data)
self.assertArrayEqual(actual.data, actual.values)

def test_struct_array_dims(self):
# -----------------test 1
p_data = np.array([('John', 180), ('Stacy', 150), ('Dick', 200)],
dtype=[('name', '|S256'), ('height', object)])
p_data_1 = np.array([('John', 180), ('Stacy', 150), ('Dick', 200)],
dtype=[('name', '|S256'), ('height', object)])

weights_0 = DataArray([80, 56, 120], dims=['participant'],
coords={'participant': p_data})
weights_1 = DataArray([81, 52, 115], dims=['participant'],
coords={'participant': p_data_1})

actual = weights_1 - weights_0

expected = DataArray([1, -4, -5], dims=['participant'],
coords={'participant': p_data})

self.assertDataArrayIdentical(actual, expected)

# -----------------test 2
p_data = np.array([('John', 180), ('Stacy', 150), ('Dick', 200)],
dtype=[('name', '|S256'), ('height', object)])
p_data_1 = np.array([('John', 180), ('Stacy', 151), ('Dick', 200)],
dtype=[('name', '|S256'), ('height', object)])

p_data_2 = np.array([('John', 180), ('Dick', 200)],
dtype=[('name', '|S256'), ('height', object)])

weights_0 = DataArray([80, 56, 120], dims=['participant'],
coords={'participant': p_data})
weights_1 = DataArray([81, 52, 115], dims=['participant'],
coords={'participant': p_data_1})

actual = weights_1 - weights_0

expected = DataArray([1, -5], dims=['participant'],
coords={'participant': p_data_2})

self.assertDataArrayIdentical(actual, expected)

# -----------------test 3 - np.nan
p_data = np.array([('John', 180), ('Stacy', 150), ('Dick', 200)],
dtype=[('name', '|S256'), ('height', object)])
p_data_1 = np.array([('John', 180), ('Stacy', np.nan), ('Dick', 200)],
dtype=[('name', '|S256'), ('height', object)])

p_data_2 = np.array([('John', 180), ('Dick', 200)],
dtype=[('name', '|S256'), ('height', object)])

weights_0 = DataArray([80, 56, 120], dims=['participant'],
coords={'participant': p_data})
weights_1 = DataArray([81, 52, 115], dims=['participant'],
coords={'participant': p_data_1})

actual = weights_1 - weights_0

expected = DataArray([1, -5], dims=['participant'],
coords={'participant': p_data_2})

self.assertDataArrayIdentical(actual, expected)

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I think the tests you've written are overly verbose. I don't think you need to recreate p_data* and weights* for each of your tests. The way it is written now, I'm not sure what the differences between your three tests are (at least test1 and test2).

def test_name(self):
arr = self.dv
self.assertEqual(arr.name, 'foo')
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