def test_dict_equiv(self):
x = OrderedDict()
x['a'] = 3
x['b'] = np.array([1, 2, 3])
y = OrderedDict()
y['b'] = np.array([1.0, 2.0, 3.0])
y['a'] = 3
self.assertTrue(utils.dict_equiv(x, y)) # two nparrays are equal
y['b'] = [1, 2, 3] # np.array not the same as a list
self.assertTrue(utils.dict_equiv(x, y)) # nparray == list
x['b'] = [1.0, 2.0, 3.0]
self.assertTrue(utils.dict_equiv(x, y)) # list vs. list
x['c'] = None
self.assertFalse(utils.dict_equiv(x, y)) # new key in x
x['c'] = np.nan
y['c'] = np.nan
self.assertTrue(utils.dict_equiv(x, y)) # as intended, nan is nan
x['c'] = np.inf
y['c'] = np.inf
self.assertTrue(utils.dict_equiv(x, y)) # inf == inf
y = dict(y)
self.assertTrue(utils.dict_equiv(
x, y)) # different dictionary types are fine
y['b'] = 3 * np.arange(3)
self.assertFalse(utils.dict_equiv(x,
y)) # not equal when arrays differ
def assertDatasetIdentical(self, d1, d2):
# this method is functionally equivalent to `assert d1.identical(d2)`,
# but it checks each aspect of equality separately for easier debugging
assert utils.dict_equiv(d1.attrs, d2.attrs), (d1.attrs, d2.attrs)
self.assertEqual(sorted(d1.vars, key=str), sorted(d2.vars, key=str))
self.assertEqual(sorted(d1.coords, key=str), sorted(d2.coords,
key=str))
for k in d1:
v1 = d1._arrays[k]
v2 = d2._arrays[k]
self.assertVariableIdentical(v1, v2)
def assertDatasetIdentical(self, d1, d2):
# this method is functionally equivalent to `assert d1.identical(d2)`,
# but it checks each aspect of equality separately for easier debugging
assert utils.dict_equiv(d1.attrs, d2.attrs), (d1.attrs, d2.attrs)
self.assertEqual(sorted(d1.vars, key=str),
sorted(d2.vars, key=str))
self.assertEqual(sorted(d1.coords, key=str),
sorted(d2.coords, key=str))
for k in d1:
v1 = d1._arrays[k]
v2 = d2._arrays[k]
self.assertVariableIdentical(v1, v2)
def test_dict_equiv(self):
x = OrderedDict()
x['a'] = 3
x['b'] = np.array([1, 2, 3])
y = OrderedDict()
y['b'] = np.array([1.0, 2.0, 3.0])
y['a'] = 3
self.assertTrue(utils.dict_equiv(x, y)) # two nparrays are equal
y['b'] = [1, 2, 3] # np.array not the same as a list
self.assertTrue(utils.dict_equiv(x, y)) # nparray == list
x['b'] = [1.0, 2.0, 3.0]
self.assertTrue(utils.dict_equiv(x, y)) # list vs. list
x['c'] = None
self.assertFalse(utils.dict_equiv(x, y)) # new key in x
x['c'] = np.nan
y['c'] = np.nan
self.assertTrue(utils.dict_equiv(x, y)) # as intended, nan is nan
x['c'] = np.inf
y['c'] = np.inf
self.assertTrue(utils.dict_equiv(x, y)) # inf == inf
y = dict(y)
self.assertTrue(utils.dict_equiv(x, y)) # different dictionary types are fine
y['b'] = 3 * np.arange(3)
self.assertFalse(utils.dict_equiv(x, y)) # not equal when arrays differ
