def test_add_demographic_characteristics_RaceEthnicity(self):
characteristics = {}
person = StatePerson.new_with_defaults(
person_id=12345,
birthdate=date(1984, 8, 31),
gender=Gender.FEMALE,
races=[StatePersonRace.new_with_defaults(race=Race.ASIAN)],
ethnicities=[
StatePersonEthnicity.new_with_defaults(
ethnicity=Ethnicity.HISPANIC)
])
event_date = date(2010, 9, 1)
updated_characteristics = add_demographic_characteristics(
characteristics, person, event_date)
expected_output = {
'age_bucket': '25-29',
'race': [Race.ASIAN],
'gender': Gender.FEMALE,
'ethnicity': [Ethnicity.HISPANIC]
}
self.assertEqual(updated_characteristics, expected_output)
def characteristics_dict(person: StatePerson,
program_event: ProgramEvent) -> Dict[str, Any]:
"""Builds a dictionary that describes the characteristics of the person and event.
Args:
person: the StatePerson we are picking characteristics from
program_event: the ProgramEvent we are picking characteristics from
Returns:
A dictionary populated with all relevant characteristics.
"""
characteristics: Dict[str, Any] = {}
event_date = program_event.event_date
if isinstance(program_event, ProgramReferralEvent):
if program_event.supervision_type:
characteristics['supervision_type'] = program_event.supervision_type
if program_event.assessment_score and program_event.assessment_type:
assessment_bucket = assessment_score_bucket(
assessment_score=program_event.assessment_score,
assessment_level=None,
assessment_type=program_event.assessment_type)
if assessment_bucket and include_assessment_in_metric(
'program', program_event.state_code, program_event.assessment_type):
characteristics['assessment_score_bucket'] = assessment_bucket
characteristics['assessment_type'] = program_event.assessment_type
if program_event.participation_status:
characteristics['participation_status'] = program_event.participation_status
if program_event.supervising_officer_external_id:
characteristics['supervising_officer_external_id'] = program_event.supervising_officer_external_id
if program_event.supervising_district_external_id:
characteristics['supervising_district_external_id'] = program_event.supervising_district_external_id
elif isinstance(program_event, ProgramParticipationEvent):
characteristics['date_of_participation'] = event_date
if program_event.supervision_type:
characteristics['supervision_type'] = program_event.supervision_type
if program_event.program_location_id:
characteristics['program_location_id'] = program_event.program_location_id
if program_event.program_id:
characteristics['program_id'] = program_event.program_id
characteristics = add_demographic_characteristics(characteristics, person, event_date)
characteristics_with_person_details = characteristics_with_person_id_fields(
characteristics, program_event.state_code, person, 'program')
return characteristics_with_person_details
def test_add_demographic_characteristics_NoAttributes(self):
characteristics = {}
person = StatePerson.new_with_defaults(person_id=12345)
event_date = date(2010, 9, 1)
updated_characteristics = add_demographic_characteristics(
characteristics, person, event_date)
expected_output = {}
self.assertEqual(updated_characteristics, expected_output)
def characteristics_dict(
person: StatePerson, event: ReleaseEvent,
metric_type: ReincarcerationRecidivismMetricType) -> Dict[str, Any]:
"""Builds a dictionary that describes the characteristics of the person and the release event.
Release cohort, follow-up period, and methodology are not included in the output here. They are added into
augmented versions of these combinations later.
Args:
person: the StatePerson we are picking characteristics from
event: the ReleaseEvent we are picking characteristics from
metric_type: The ReincarcerationRecidivismMetricType provided determines which fields should be added to the
characteristics dictionary
Returns:
A dictionary populated with all relevant characteristics.
"""
characteristics: Dict[str, Any] = {}
if event.county_of_residence:
characteristics['county_of_residence'] = event.county_of_residence
if event.release_facility is not None:
characteristics['release_facility'] = event.release_facility
event_stay_length = stay_length_from_event(event)
event_stay_length_bucket = stay_length_bucket(event_stay_length)
characteristics['stay_length_bucket'] = event_stay_length_bucket
characteristics = add_demographic_characteristics(
characteristics, person, event.original_admission_date)
if isinstance(
event, RecidivismReleaseEvent
) and metric_type == ReincarcerationRecidivismMetricType.COUNT:
time_at_liberty = days_at_liberty(event)
characteristics['days_at_liberty'] = time_at_liberty
characteristics = characteristics_with_person_id_fields(
characteristics, event.state_code, person, 'recidivism')
return characteristics
def test_add_demographic_characteristics_MultipleRaces(self):
characteristics = {}
person = StatePerson.new_with_defaults(
person_id=12345,
birthdate=date(1984, 8, 31),
gender=Gender.FEMALE,
races=[
StatePersonRace.new_with_defaults(race=Race.ASIAN),
StatePersonRace.new_with_defaults(race=Race.BLACK)
])
event_date = date(2010, 9, 1)
updated_characteristics = add_demographic_characteristics(
characteristics, person, event_date)
expected_output = {
'age_bucket': '25-29',
'race': [Race.ASIAN, Race.BLACK],
'gender': Gender.FEMALE
}
self.assertEqual(updated_characteristics, expected_output)
def characteristics_dict(person: StatePerson,
supervision_time_bucket: SupervisionTimeBucket,
metric_type: SupervisionMetricType) -> Dict[str, Any]:
"""Builds a dictionary that describes the characteristics of the person and supervision_time_bucket.
Args:
person: the StatePerson we are picking characteristics from
supervision_time_bucket: the SupervisionTimeBucket we are picking characteristics from
metric_type: The SupervisionMetricType provided determines which fields should be added to the characteristics
dictionary
Returns:
A dictionary populated with all relevant characteristics.
"""
characteristics: Dict[str, Any] = {}
include_revocation_dimensions = _include_revocation_dimensions_for_metric(
metric_type)
include_assessment_dimensions = _include_assessment_dimensions_for_metric(
metric_type)
include_demographic_dimensions = _include_demographic_dimensions_for_metric(
metric_type)
include_person_level_dimensions = _include_person_level_dimensions_for_metric(
metric_type)
if (metric_type == SupervisionMetricType.POPULATION
and isinstance(supervision_time_bucket,
(RevocationReturnSupervisionTimeBucket,
NonRevocationReturnSupervisionTimeBucket))):
if supervision_time_bucket.most_severe_violation_type:
characteristics[
'most_severe_violation_type'] = supervision_time_bucket.most_severe_violation_type
if supervision_time_bucket.most_severe_violation_type_subtype:
characteristics['most_severe_violation_type_subtype'] = \
supervision_time_bucket.most_severe_violation_type_subtype
if supervision_time_bucket.response_count is not None:
characteristics[
'response_count'] = supervision_time_bucket.response_count
if include_revocation_dimensions and \
isinstance(supervision_time_bucket,
RevocationReturnSupervisionTimeBucket):
if supervision_time_bucket.revocation_type:
characteristics[
'revocation_type'] = supervision_time_bucket.revocation_type
if supervision_time_bucket.source_violation_type:
characteristics[
'source_violation_type'] = supervision_time_bucket.source_violation_type
if metric_type in [
SupervisionMetricType.REVOCATION_ANALYSIS,
SupervisionMetricType.REVOCATION_VIOLATION_TYPE_ANALYSIS
]:
if supervision_time_bucket.most_severe_violation_type:
characteristics[
'most_severe_violation_type'] = supervision_time_bucket.most_severe_violation_type
if supervision_time_bucket.most_severe_violation_type_subtype:
characteristics['most_severe_violation_type_subtype'] = \
supervision_time_bucket.most_severe_violation_type_subtype
if metric_type in [SupervisionMetricType.REVOCATION_ANALYSIS]:
if supervision_time_bucket.most_severe_response_decision:
characteristics['most_severe_response_decision'] = \
supervision_time_bucket.most_severe_response_decision
if supervision_time_bucket.response_count is not None:
characteristics[
'response_count'] = supervision_time_bucket.response_count
if isinstance(supervision_time_bucket, SupervisionTerminationBucket):
if supervision_time_bucket.termination_reason:
characteristics[
'termination_reason'] = supervision_time_bucket.termination_reason
if supervision_time_bucket.supervision_type:
characteristics[
'supervision_type'] = supervision_time_bucket.supervision_type
if supervision_time_bucket.case_type:
characteristics['case_type'] = supervision_time_bucket.case_type
if not include_revocation_dimensions and supervision_time_bucket.supervision_level:
characteristics[
'supervision_level'] = supervision_time_bucket.supervision_level
if include_assessment_dimensions:
# TODO(2853): Figure out more robust solution for not assessed people. Here we don't set assessment_type when
# someone is not assessed. This only works as desired because BQ doesn't rely on assessment_type at all.
characteristics['assessment_score_bucket'] = 'NOT_ASSESSED'
if supervision_time_bucket.assessment_score and supervision_time_bucket.assessment_type:
assessment_bucket = assessment_score_bucket(
supervision_time_bucket.assessment_score,
supervision_time_bucket.assessment_level,
supervision_time_bucket.assessment_type)
if assessment_bucket and include_assessment_in_metric(
'supervision', supervision_time_bucket.state_code,
supervision_time_bucket.assessment_type):
characteristics['assessment_score_bucket'] = assessment_bucket
characteristics[
'assessment_type'] = supervision_time_bucket.assessment_type
if supervision_time_bucket.supervising_officer_external_id:
characteristics[
'supervising_officer_external_id'] = supervision_time_bucket.supervising_officer_external_id
if supervision_time_bucket.supervising_district_external_id:
characteristics[
'supervising_district_external_id'] = supervision_time_bucket.supervising_district_external_id
if isinstance(supervision_time_bucket,
RevocationReturnSupervisionTimeBucket):
event_date = supervision_time_bucket.revocation_admission_date
elif isinstance(supervision_time_bucket, SupervisionTerminationBucket):
event_date = supervision_time_bucket.termination_date
else:
year = supervision_time_bucket.year
month = supervision_time_bucket.month
event_date = date(year, month, 1)
if include_demographic_dimensions:
characteristics = add_demographic_characteristics(
characteristics, person, event_date)
if include_person_level_dimensions:
characteristics = characteristics_with_person_id_fields(
characteristics, person, 'supervision')
if not include_revocation_dimensions and supervision_time_bucket.supervision_level_raw_text:
characteristics['supervision_level_raw_text'] = \
supervision_time_bucket.supervision_level_raw_text
if metric_type == SupervisionMetricType.POPULATION:
if isinstance(supervision_time_bucket,
(RevocationReturnSupervisionTimeBucket,
NonRevocationReturnSupervisionTimeBucket)):
characteristics['is_on_supervision_last_day_of_month'] = \
supervision_time_bucket.is_on_supervision_last_day_of_month
if metric_type == SupervisionMetricType.REVOCATION_ANALYSIS:
if isinstance(supervision_time_bucket, RevocationReturnSupervisionTimeBucket) \
and supervision_time_bucket.violation_history_description:
characteristics['violation_history_description'] = \
supervision_time_bucket.violation_history_description
if include_revocation_dimensions and isinstance(
supervision_time_bucket,
RevocationReturnSupervisionTimeBucket):
characteristics['revocation_admission_date'] = \
supervision_time_bucket.revocation_admission_date
if metric_type == SupervisionMetricType.ASSESSMENT_CHANGE:
if isinstance(supervision_time_bucket, SupervisionTerminationBucket) \
and supervision_time_bucket.termination_date:
characteristics[
'termination_date'] = supervision_time_bucket.termination_date
return characteristics
def characteristics_dict(
person: StatePerson,
incarceration_event: IncarcerationEvent) -> Dict[str, Any]:
"""Builds a dictionary that describes the characteristics of the person and event.
Args:
person: the StatePerson we are picking characteristics from
incarceration_event: the IncarcerationEvent we are picking characteristics from
Returns:
A dictionary populated with all relevant characteristics.
"""
characteristics: Dict[str, Any] = {}
# Add characteristics that will be used to generate dictionaries with unique combinations.
if isinstance(incarceration_event, IncarcerationAdmissionEvent):
characteristics['admission_date'] = incarceration_event.event_date
if incarceration_event.admission_reason:
characteristics[
'admission_reason'] = incarceration_event.admission_reason
if incarceration_event.supervision_type_at_admission:
characteristics[
'supervision_type_at_admission'] = incarceration_event.supervision_type_at_admission
# TODO(3275): Rename to purpose_for_incarceration
if incarceration_event.specialized_purpose_for_incarceration:
characteristics['specialized_purpose_for_incarceration'] = \
incarceration_event.specialized_purpose_for_incarceration
if isinstance(incarceration_event, IncarcerationReleaseEvent):
characteristics['release_date'] = incarceration_event.event_date
if incarceration_event.release_reason:
characteristics[
'release_reason'] = incarceration_event.release_reason
if incarceration_event.release_reason_raw_text:
characteristics[
'release_reason_raw_text'] = incarceration_event.release_reason_raw_text
if incarceration_event.purpose_for_incarceration:
characteristics[
'purpose_for_incarceration'] = incarceration_event.purpose_for_incarceration
if incarceration_event.supervision_type_at_release:
characteristics[
'supervision_type_at_release'] = incarceration_event.supervision_type_at_release
if incarceration_event.admission_reason:
characteristics[
'admission_reason'] = incarceration_event.admission_reason
# Have to explicitly check if this is not None because 0 is a valid value and evaluates to False
if incarceration_event.total_days_incarcerated is not None:
characteristics[
'total_days_incarcerated'] = incarceration_event.total_days_incarcerated
if isinstance(incarceration_event, IncarcerationStayEvent):
characteristics['date_of_stay'] = incarceration_event.event_date
if incarceration_event.admission_reason:
characteristics[
'admission_reason'] = incarceration_event.admission_reason
if incarceration_event.supervision_type_at_admission:
characteristics[
'supervision_type_at_admission'] = incarceration_event.supervision_type_at_admission
if incarceration_event.judicial_district_code:
characteristics[
'judicial_district_code'] = incarceration_event.judicial_district_code
# Always include facility as a dimension
if incarceration_event.facility:
characteristics['facility'] = incarceration_event.facility
# Always include county_of_residence as a dimension
if incarceration_event.county_of_residence:
characteristics[
'county_of_residence'] = incarceration_event.county_of_residence
event_date = incarceration_event.event_date
characteristics = add_demographic_characteristics(characteristics, person,
event_date)
characteristics_with_person_details = add_person_level_characteristics(
person, incarceration_event, characteristics)
return characteristics_with_person_details
