def test_convert_all(self):
for cuba in CUBA:
# given
original_value = dummy_cuba_value(cuba)
# when
file_value = convert_to_file_type(original_value, cuba)
# then
assert_array_equal(original_value,
convert_from_file_type(file_value, cuba))
def test_convert_all(self):
for cuba in CUBA:
# given
original_value = dummy_cuba_value(cuba)
# when
file_value = convert_to_file_type(original_value, cuba)
# then
assert_array_equal(original_value,
convert_from_file_type(file_value, cuba))
def _populate(self, row, value):
""" Populate the row from the DataContainer.
"""
positions = self._cuba_to_position
mask = numpy.zeros(
shape=self._table.coldtypes['mask'].shape, dtype=numpy.bool)
data = list(row['data'])
for key in value:
if key in positions:
data[positions[key]] = convert_to_file_type(value[key], key)
mask[positions[key]] = True
row['mask'] = mask
row['data'] = tuple(data)
def _create_rec_array(self, value):
""" Create a rec_array row from a DataContainer
"""
positions = self._cuba_to_position
rec_array = numpy.zeros(shape=1, dtype=self._table._v_dtype)[0]
data = rec_array['data']
mask = rec_array['mask']
for key in value:
if key in positions:
position = positions[key]
# special case array valued cuba keys
# see numpy issue https://github.com/numpy/numpy/issues/3126
if numpy.isscalar(data[position]):
data[position] = convert_to_file_type(value[key], key)
else:
data[position][:] = convert_from_file_type(value[key], key)
mask[position] = True
return rec_array
