def data(self):
if not self._structure_calculated:
self._calculate_structure()
if self._data_cache is None:
stack = np.empty(self.vector_dims_shape, 'object')
for nd_index, field in zip(np.ndindex(self.vector_dims_shape),
self.fields):
stack[nd_index] = as_lazy_data(field._data)
self._data_cache = multidim_lazy_stack(stack)
return self._data_cache
def data(self):
if not self._structure_calculated:
self._calculate_structure()
if self._data_cache is None:
stack = np.empty(self.vector_dims_shape, 'object')
for nd_index, field in zip(np.ndindex(self.vector_dims_shape),
self.fields):
stack[nd_index] = as_lazy_data(field._data)
self._data_cache = multidim_lazy_stack(stack)
return self._data_cache
def _check(self, stack_shape):
vals = np.arange(np.prod(stack_shape)).reshape(stack_shape)
stack = np.empty(stack_shape, 'object')
# Define the shape of each element in the stack.
stack_element_shape = (4, 5)
expected = np.empty(stack_shape + stack_element_shape, dtype=int)
for index, val in np.ndenumerate(vals):
stack[index] = as_lazy_data(val * np.ones(stack_element_shape))
expected[index] = val
result = multidim_lazy_stack(stack)
self.assertEqual(result.shape, stack_shape + stack_element_shape)
self.assertIsInstance(result, da.core.Array)
result = as_concrete_data(result)
self.assertArrayAllClose(result, expected)
def _check(self, stack_shape):
vals = np.arange(np.prod(stack_shape)).reshape(stack_shape)
stack = np.empty(stack_shape, 'object')
# Define the shape of each element in the stack.
stack_element_shape = (4, 5)
expected = np.empty(stack_shape + stack_element_shape,
dtype=int)
for index, val in np.ndenumerate(vals):
stack[index] = as_lazy_data(val * np.ones(stack_element_shape))
expected[index] = val
result = multidim_lazy_stack(stack)
self.assertEqual(result.shape, stack_shape + stack_element_shape)
self.assertIsInstance(result, da.core.Array)
result = as_concrete_data(result)
self.assertArrayAllClose(result, expected)