8.1.1.10. dispatch¶
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Dispatcher.dispatch(inputs=None, outputs=None, cutoff=None, inputs_dist=None, wildcard=False, no_call=False, shrink=False, rm_unused_nds=False, select_output_kw=None, _wait_in=None, stopper=None, executor=False, sol_name=())[source] Evaluates the minimum workflow and data outputs of the dispatcher model from given inputs.
Parameters: - inputs (dict[str, T], list[str], iterable, optional) – Input data values.
- outputs (list[str], iterable, optional) – Ending data nodes.
- cutoff (float, int, optional) – Depth to stop the search.
- inputs_dist (dict[str, int | float], optional) – Initial distances of input data nodes.
- wildcard (bool, optional) – If True, when the data node is used as input and target in the ArciDispatch algorithm, the input value will be used as input for the connected functions, but not as output.
- no_call (bool, optional) – If True data node estimation function is not used and the input values are not used.
- shrink (bool, optional) –
If True the dispatcher is shrink before the dispatch.
See also
- rm_unused_nds (bool, optional) – If True unused function and sub-dispatcher nodes are removed from workflow.
- select_output_kw (dict, optional) – Kwargs of selector function to select specific outputs.
- _wait_in (dict, optional) – Override wait inputs.
- stopper (multiprocess.Event, optional) – A semaphore to abort the dispatching.
- executor (str, optional) – A pool executor id to dispatch asynchronously or in parallel.
- sol_name (tuple[str], optional) – Solution name.
Returns: Dictionary of estimated data node outputs.
Return type: ——————————————————————–
Example:
A dispatcher with a function \(log(b - a)\) and two data a and b with default values:
Dispatch without inputs. The default values are used as inputs:
>>> outputs = dsp.dispatch() >>> outputs Solution([('a', 0), ('b', 5), ('d', 1), ('c', 0), ('e', 0.0)])
Dispatch until data node c is estimated:
>>> outputs = dsp.dispatch(outputs=['c']) >>> outputs Solution([('a', 0), ('b', 5), ('c', 0)])
Dispatch with one inputs. The default value of a is not used as inputs:
>>> outputs = dsp.dispatch(inputs={'a': 3}) >>> outputs Solution([('a', 3), ('b', 5), ('d', 1), ('c', 3)])