def __init__(self, metrics_params=[]):
"""
Init the class, adding metrics_params to the
stuff to compute if a list of metrics parameters (dictionaries) is passed.
Metrics parameters are checked for correctness, an assertion error will interrupt
the program if any incorrectness is met.
:param metrics_params: List of metrics, each metric is a dictionary mapping params of
the metric to a value, as in the json config file.
:type metrics_params: list
"""
Config._process_metrics(metrics_params)
self._metrics = metrics_params
def add(self, input):
"""
Adds more metrics to the task, the input can be of:
- a _Task class or any class extending it
- a dict containing metric params, or a list of those
:param input: a _Task class or a class inheriting from it, a list of metrics params or a single metric param
:type input dict/list/Task
:return: Returns a reference to this instance of _Task, for chaining.
"""
if type(input) is list:
Config._process_metrics(input)
self._metrics.extend(input)
elif type(input) is dict:
Config._process_metrics([input])
self._metrics.append(input)
elif isinstance(input, _Task):
# metrics should already have been processed, no need to check here
self._metrics.extend(input._metrics)
else:
"Input must be either a list of dicts, a dict or another Task instance"
exit()
return self