| 1150 | assert v.values == np.timedelta64(10**9, "ns") |
| 1151 | |
| 1152 | def test_equals_and_identical(self): |
| 1153 | d = np.random.rand(10, 3) |
| 1154 | d[0, 0] = np.nan |
| 1155 | v1 = Variable(("dim1", "dim2"), data=d, attrs={"att1": 3, "att2": [1, 2, 3]}) |
| 1156 | v2 = Variable(("dim1", "dim2"), data=d, attrs={"att1": 3, "att2": [1, 2, 3]}) |
| 1157 | assert v1.equals(v2) |
| 1158 | assert v1.identical(v2) |
| 1159 | |
| 1160 | v3 = Variable(("dim1", "dim3"), data=d) |
| 1161 | assert not v1.equals(v3) |
| 1162 | |
| 1163 | v4 = Variable(("dim1", "dim2"), data=d) |
| 1164 | assert v1.equals(v4) |
| 1165 | assert not v1.identical(v4) |
| 1166 | |
| 1167 | v5 = deepcopy(v1) |
| 1168 | v5.values[:] = np.random.rand(10, 3) |
| 1169 | assert not v1.equals(v5) |
| 1170 | |
| 1171 | assert not v1.equals(None) |
| 1172 | assert not v1.equals(d) |
| 1173 | |
| 1174 | assert not v1.identical(None) |
| 1175 | assert not v1.identical(d) |
| 1176 | |
| 1177 | def test_broadcast_equals(self): |
| 1178 | v1 = Variable((), np.nan) |