def test_max_risk(self):
goal = Fixture1.goal1()
settings = Fixture1.settings1()
client = goal.account.primary_owner
# Add the weights for the risk factors
Fixture1.populate_risk_profile_questions() # Also populates all possible answers.
Fixture1.populate_risk_profile_responses()
# we haven't set a net worth or a target, so worth_score isn't a factor
# An all-9s account will have a max_risk of 1
self.assertEqual(max_risk(settings), 1.0)
# and if they are low risk behavior, high Ability + Sophistication
# the max risk is still 1
client.risk_profile_responses.clear()
client.risk_profile_responses.add(Fixture1.risk_profile_answer1c())
client.risk_profile_responses.add(Fixture1.risk_profile_answer2c())
self.assertEqual(max_risk(settings), 1.0)
# but if they are risky, new and unskilled, recommend no risk
client.risk_profile_responses.clear()
client.risk_profile_responses.add(Fixture1.risk_profile_answer1d())
client.risk_profile_responses.add(Fixture1.risk_profile_answer2d())
self.assertAlmostEqual(recommend_risk(settings), 0.1, 1)
self.assertAlmostEqual(max_risk(settings), 0.1, 1)
def test_put_settings_with_risk_too_high(self):
url = '/api/v1/goals/{}/selected-settings'.format(Fixture1.goal1().id)
self.client.force_authenticate(user=Fixture1.client1().user)
rsm = self.risk_score_metric.copy()
rsm['configured_val'] = 0.9
new_settings = {
"metric_group": {"metrics": [rsm]},
}
self.assertLess(max_risk(Fixture1.goal1().selected_settings), 0.9)
response = self.client.put(url, new_settings)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
def test_fully_answered_zero_max(self):
goal = Fixture1.goal1()
setting = Fixture1.settings1()
risk_metric = setting.metric_group.metrics.get(type=GoalMetric.METRIC_TYPE_RISK_SCORE)
q = RiskProfileQuestionFactory.create(group=goal.account.primary_owner.risk_profile_group)
a = RiskProfileAnswerFactory.create(b_score=0, a_score=0, s_score=0, question=q)
client = goal.account.primary_owner
client.risk_profile_responses.add(a)
self.assertGreater(risk_metric.configured_val, 0.01)
with self.assertRaises(ValidationError) as ex:
validate_risk_score(setting)
risk_metric.configured_val = 0
risk_metric.save()
self.assertEqual(validate_risk_score(setting), None) # Should now complete OK.
self.assertEqual(max_risk(setting), 0.0)
self.assertEqual(recommend_risk(setting), 0.0)