def test_instance_attribute():
iattr = InstanceAttribute('type_array', dim='atom', dtype='str')
eq_(iattr.size, 0)
# Now we initialize as empty
iattr.empty(10)
eq_(iattr.size, 10)
# We get another one
iattr = InstanceAttribute('type_array', dim='atom', dtype='str')
iattr.value = ['A', 'B', 'C', 'D']
# Automatic casting
ok_(isinstance(iattr.value, np.ndarray))
assert_npequal(iattr.value, ['A', 'B', 'C', 'D'])
# Reordering
iattr2 = iattr.reorder([1, 0, 3, 2], inplace=False)
assert_npequal(iattr2.value, ['B', 'A', 'D', 'C'])
iattr.reorder([1, 0, 3, 2])
assert_npequal(iattr.value, ['B', 'A', 'D', 'C'])
# Reordering with wrong input raises ValueError
assert_raises(ValueError, iattr.reorder, [1, 2])
assert_raises(ValueError, iattr.reorder, [0, 1, 2, 100])
def test_concatenate_attributes():
a1 = InstanceAttribute('type_array', dim='atom', dtype='str')
newattr = concatenate_attributes([a1, a1, a1])
eq_(newattr.size, 0)
a2 = a1.empty(10, inplace=False)
newattr = concatenate_attributes([a1, a2, a2])
eq_(newattr.size, 20)
# Shape parameter
r_array = InstanceAttribute('r_array', shape=(3,), dtype='f', dim='atom')
r_array.value = [[0, 1, 2]]
newattr = concatenate_attributes([r_array, r_array, r_array])
eq_(newattr.size, 3)
assert_npequal(newattr.value, [[0, 1, 2], [0, 1, 2], [0, 1, 2]])
