hpcflow.sdk.core.loop_cache.LoopCache#

class hpcflow.sdk.core.loop_cache.LoopCache(element_dependents, elements, zeroth_iters, data_idx, iterations, task_iterations)#

Bases: object

Class to store a cache for use in Workflow.add_empty_loop and WorkflowLoop.add_iterations.

Parameters:

element_dependents (Dict[int, Dict]) –
elements (Dict[int, Dict]) –
zeroth_iters (Dict[int, Tuple]) –
data_idx (Dict[int, Dict]) –
iterations (Dict[int, Tuple]) –
task_iterations (Dict[int, List[int]]) –

element_dependents#

Keys are element IDs, values are dicts whose keys are element IDs that depend on the key element ID (via Element.get_dependent_elements_recursively), and whose values are dicts with keys: group_names, which is a tuple of the string group names associated with the dependent element’s element set.

Type:: Dict[int, Dict]

elements#

Keys are element IDs, values are dicts with keys: input_statuses, input_sources, and task_insert_ID.

Type:: Dict[int, Dict]

zeroth_iters#

Keys are element IDs, values are data associated with the zeroth iteration of that element, namely a tuple of iteration ID and ElementIteration.data_idx.

Type:: Dict[int, Tuple]

data_idx#

Keys are element IDs, values are data associated with all iterations of that element, namely a dict whose keys are the iteration loop index as a tuple, and whose values are data indices via ElementIteration.get_data_idx().

Type:: Dict[int, Dict]

iterations#

Keys are iteration IDs, values are tuples of element ID and iteration index within that element.

Type:: Dict[int, Tuple]

task_iterations#

Keys are task insert IDs, values are list of all iteration IDs associated with that task.

Type:: Dict[int, List[int]]

Methods

`add_iteration`	Update the cache to include a newly added iteration.
`build`	Build a cache of data for use in adding loops and iterations.
`get_iter_IDs`	Retrieve a list of iteration IDs belonging to a given loop.
`get_iter_loop_indices`
`update_loop_indices`

Attributes

`element_dependents`
`elements`
`zeroth_iters`
`data_idx`
`iterations`
`task_iterations`

add_iteration(iter_ID, task_insert_ID, element_ID, loop_idx, data_idx)#: Update the cache to include a newly added iteration.

classmethod build(workflow, loops=None)#

Build a cache of data for use in adding loops and iterations.

Parameters:

workflow (Workflow) –
loops (List[Loop] | None) –

data_idx: Dict[int, Dict]#

element_dependents: Dict[int, Dict]#

elements: Dict[int, Dict]#

get_iter_IDs(loop)#

Retrieve a list of iteration IDs belonging to a given loop.

Parameters:: loop (Loop) –
Return type:: List[int]

get_iter_loop_indices(iter_IDs)#

Parameters:: iter_IDs (List[int]) –
Return type:: List[Dict[str, int]]

iterations: Dict[int, Tuple]#

task_iterations: Dict[int, List[int]]#

update_loop_indices(new_loop_name, iter_IDs)#

Parameters:

new_loop_name (str) –
iter_IDs (List[int]) –

zeroth_iters: Dict[int, Tuple]#