def process(self, element, *args, **kwargs):
"""Produces various recidivism metric combinations.
Sends the calculator the StatePerson entity and their corresponding
ReleaseEvents for mapping all recidivism combinations.
Args:
element: Tuple containing a StatePerson and their ReleaseEvents
**kwargs: This should be a dictionary with values for the
following keys:
- age_bucket
- gender
- stay_length_bucket
- release_facility
- race
- ethnicity
Yields:
Each recidivism metric combination, tagged by metric type.
"""
person, release_events = element
# Calculate recidivism metric combinations for this person and events
metric_combinations = \
calculator.map_recidivism_combinations(person,
release_events, kwargs)
# Return each of the recidivism metric combinations
for metric_combination in metric_combinations:
metric_key, value = metric_combination
metric_type = metric_key.get('metric_type')
# Converting the metric key to a JSON string so it is hashable
serializable_dict = json_serializable_metric_key(metric_key)
json_key = json.dumps(serializable_dict, sort_keys=True)
if metric_type == MetricType.RATE:
yield beam.pvalue.TaggedOutput('rates',
(json_key, value))
elif metric_type == MetricType.COUNT:
yield beam.pvalue.TaggedOutput('counts',
(json_key, value))
elif metric_type == MetricType.LIBERTY:
yield beam.pvalue.TaggedOutput('liberties',
(json_key, value))
def process(self, element, metric_inclusions):
"""Produces various recidivism metric combinations.
Sends the calculator the StatePerson entity and their corresponding ReleaseEvents for mapping all recidivism
combinations.
Args:
element: Tuple containing a StatePerson and their ReleaseEvents
metric_inclusions: A dictionary where the keys are each ReincarcerationRecidivismMetricType, and the values
are boolean flags for whether or not to include that metric type in the calculations
Yields:
Each recidivism metric combination.
"""
person, release_events = element
# Calculate recidivism metric combinations for this person and events
metric_combinations = calculator.map_recidivism_combinations(person, release_events, metric_inclusions)
# Return each of the recidivism metric combinations
for metric_combination in metric_combinations:
yield metric_combination