def test_hiv_expose(make_model, make_agent):
model = make_model()
model.run_random = FakeRandom(0.0) # always less than param
a = make_agent()
p = make_agent()
a.partners["Sex"] = set()
p.partners["Sex"] = set()
rel = Relationship(a, p, 10, bond_type="Sex")
HIV.expose(model, "sex", rel, 10)
assert a.hiv.active is False
assert p.hiv.active is False
a.hiv.active = True
p.hiv.active = True
# test nothing happens
HIV.expose(model, "sex", rel, 10)
assert a.hiv.active
assert p.hiv.active
p.hiv.active = False
# test conversion happens
HIV.expose(model, "sex", rel, 10)
assert a.hiv.active
assert p.hiv.active
def test_update_all_agents(make_model, make_agent):
# make agent 0
model = make_model()
assert model.params.agent_zero.interaction_type == "injection"
a = make_agent(race="white", DU="Inj")
p = make_agent(race="white", DU="Inj")
# make sure at least 1 relationship is compatible with agent 0 type
Relationship(a, p, 10, bond_type="Inj")
model.time = 1
# update all agents passes with agent 0
model.update_all_agents()
assert a.knowledge.active is False
# remove all bonds compatible with agent 0. agent 0 fails
for rel in copy(model.pop.relationships):
if rel.bond_type in ["Inj", "SexInj"]:
rel.unbond()
model.pop.remove_relationship(rel)
# no target partners available
for agent in model.pop.all_agents:
for k in agent.target_partners.keys():
agent.target_partners[k] = 0
model.reset_trackers()
with pytest.raises(ValueError) as excinfo:
model.update_all_agents()
assert "No agent zero!" in str(excinfo)
def test_sex_num_acts(make_model, make_agent, make_relationship, params):
params.hiv.dx.risk_reduction.sex = 1.0
model = make_model()
model.time = model.params.hiv.start_time
model.np_random = FakeRandom(1.0)
a = make_agent()
p = make_agent()
a.partners["Sex"] = set()
p.partners["Sex"] = set()
rel_Sex = Relationship(a, p, 10, bond_type="Sex")
assert Sex.get_num_acts(model, rel_Sex) > 0
a.hiv.active = True
a.hiv.dx = True
# test nothing happens
assert Sex.get_num_acts(model, rel_Sex) == 0
a.location.params.partnership.sex.frequency = (
p.location.params.partnership.sex.frequency) = ObjMap({
"Sex": {
"type": "distribution",
"distribution": {
"dist_type": "set_value",
"vars": {
1: {
"value": 0,
"value_type": "int"
}
},
},
}
})
assert Sex.get_num_acts(model, rel_Sex) == 0
def test_pca_interaction(make_model, make_agent):
model = make_model()
a = make_agent()
p = make_agent()
a.knowledge.opinion = 4
p.knowledge.opinion = 2
a.knowledge.active = True
a.partners["SexInj"] = set()
p.partners["SexInj"] = set()
rel = Relationship(a, p, 10, bond_type="SexInj")
model.run_random = FakeRandom(-0.1)
model.pop.graph.add_edge(a, p)
model.pop.graph.add_edge(a, "edge")
model.time = 5
# make partner aware via dissemination
PCA.interact(model, rel)
assert p.knowledge.active
# influence partner's opinion
model.time += 1
PCA.interact(model, rel)
assert p.knowledge.opinion == 3
def test_injection_num_acts(make_model, make_agent):
model = make_model()
model.np_random = FakeRandom(0.5)
a = make_agent()
p = make_agent()
a.drug_type = "Inj"
p.drug_type = "Inj"
rel = Relationship(a, p, 10, bond_type="Inj")
# set to a high number to ensure above zero
a.location.params.demographics[a.race].sex_type[
a.sex_type].injection.num_acts = 100
p.location.params.demographics[p.race].sex_type[
p.sex_type].injection.num_acts = 200
assert Injection.get_num_acts(model, rel) > 0
a.syringe_services.active = True
SyringeServices.enrolled_risk = 0.0
assert Injection.get_num_acts(model, rel) == 0
a.syringe_services.active = False
a.hiv.active = True
a.hiv.dx = True
model.params.hiv.dx.risk_reduction.injection = 1.0
assert Injection.get_num_acts(model, rel) == 0
assert p.hiv
def test_knolwedge_transmission_probability(make_model, make_agent):
model = make_model()
a = make_agent()
p = make_agent()
rel = Relationship(a, p, 10, bond_type="Social")
# knowledge transmission
assert a.knowledge.get_transmission_probability(model, "pca", p, 0) == 0
assert (
a.knowledge.get_transmission_probability(model, "pca", p, 1)
== model.params.knowledge.prob
)
assert a.knowledge.get_transmission_probability(
model, "pca", p, 2
) == 1.0 - utils.binom_0(2, model.params.knowledge.prob)
# opinion transmission
a.knowledge.active = True
p.knowledge.active = True
assert a.knowledge.get_transmission_probability(model, "pca", p, 0) == 0
assert (
a.knowledge.get_transmission_probability(model, "pca", p, 1)
== model.params.knowledge.opinion.prob
)
assert a.knowledge.get_transmission_probability(
model, "pca", p, 2
) == 1.0 - utils.binom_0(2, model.params.knowledge.opinion.prob)
def test_incarcerate_not_hiv(make_model, make_agent):
model = make_model()
a = make_agent(SO="HM", race="white")
p = make_agent(SO="HF", race="white")
rel = Relationship(a, p, 10, "Sex")
a.location.params.demographics.white.sex_type.HM.incar.prob = 1.0
a.incar.update_agent(model)
assert a.incar.active
def test_pca_num_acts_bins(make_model, make_agent):
model = make_model()
model.run_random = FakeRandom(-0.1)
a = make_agent()
p = make_agent()
rel = Relationship(a, p, 10, bond_type="Social")
assert (PCA.get_num_acts(
model,
rel) == model.params.partnership.pca.frequency.Social.bins[1].min)
def test_injection_get_num_acts_do_nothing(make_model, make_agent):
model = make_model()
model.time = model.params.hiv.start_time + 2
a = make_agent(race="white", DU="Inj", SO="HM")
p_inj = make_agent(race="white", DU="Inj", SO="HF")
rel_Inj = Relationship(a, p_inj, 10, bond_type="Inj")
model.run_random = FakeRandom(-0.1)
assert Injection.get_num_acts(model, rel_Inj) > 0
model.run_random = FakeRandom(1.1)
assert Injection.get_num_acts(model, rel_Inj) == 0
def test_injection_transmission(make_model, make_agent):
model = make_model()
model.np_random = FakeRandom(1.0)
model.run_random = FakeRandom(-0.1)
model.time = model.params.hiv.start_time + 2
a = make_agent(race="black", DU="Inj", SO="HM")
p = make_agent(race="black", DU="Inj", SO="HF")
rel = Relationship(a, p, 10, bond_type="Inj")
Injection.interact(model, rel)
assert a.hiv.active is False
assert p.hiv.active is False
a.hiv.active = True
a.hiv.time = model.time - 1 # acute
Injection.interact(model, rel)
assert p.hiv.active
def test_incarcerate_not_diagnosed(make_model, make_agent):
model = make_model()
model.time = model.params.partner_tracing.start_time + 1
a = make_agent(SO="HM", race="white") # incarceration only for HM and HF?
a.hiv.active = True
a.hiv.time = model.time - 1
a.partners["Sex"] = set()
p = make_agent(SO="HF")
p.partners["Sex"] = set()
rel = Relationship(a, p, 10, bond_type="Sex")
model.run_random = FakeRandom(0.0) # always less than params
a.incar.update_agent(model)
assert a.incar.active
assert a.incar.release_time == model.time + 1
assert a.hiv.dx
def test_initiate_prep_eligible_racial(make_model, make_agent):
model = make_model()
# make sure there's room to add more prep agents
a = make_agent(SO="HF") # model is "CDCwomen"
p = make_agent(DU="Inj")
a.partners["Sex"] = set()
p.partners["Sex"] = set()
p.hiv.dx = True
p.external_exposure.active = True
model.time = 10
a.location.params.prep.cap = 1.0
a.location.params.prep.target_model = ["Racial"]
rel = Relationship(a, p, 10, bond_type="Sex")
# non-forcing, adherant, inj
model.run_random = FakeRandom(-0.1)
a.prep.initiate(model)
assert a.prep.active
assert a.prep.adherent is True
assert a.prep.last_dose_time == 10
assert a.prep.time == 10
def test_get_random_sex_partner_valid(make_population, make_agent, params):
empty_pop = make_population()
hm_agent = make_agent(SO="HM")
hf_partner = make_agent(SO="HF")
for bond in params.classes.bond_types:
hm_agent.target_partners[bond] = 0
hf_partner.target_partners[bond] = 0
hm_agent.partners[bond] = set()
hf_partner.partners[bond] = set()
empty_pop.add_agent(hm_agent)
empty_pop.add_agent(hf_partner)
hm_agent.target_partners = 10
hf_partner.target_partners = 10
partner = select_partner(
hm_agent,
empty_pop.all_agents.members,
empty_pop.sex_partners,
empty_pop.pwid_agents,
params,
FakeRandom(1.0),
"Sex",
)
assert partner == hf_partner
rel = Relationship(partner, hm_agent, 10, "Sex")
empty_pop.add_relationship(rel)
# no match after bonded
partner = select_partner(
hm_agent,
empty_pop.all_agents.members,
empty_pop.sex_partners,
empty_pop.pwid_agents,
params,
FakeRandom(1.0),
"Sex",
)
assert partner is None
def test_pca_num_acts_dist(make_model, make_agent):
model = make_model()
model.params.partnership.pca.frequency = ObjMap({
"Social": {
"type": "distribution",
"distribution": {
"dist_type": "set_value",
"vars": {
1: {
"value": 0,
"value_type": "int"
}
},
},
}
})
a = make_agent()
p = make_agent()
rel = Relationship(a, p, 10, bond_type="Social")
model.run_random = FakeRandom(-0.1)
assert PCA.get_num_acts(model, rel) == 0
def _make_relationship(id1, id2, bond_type="Sex", duration=2):
return Relationship(id1, id2, duration, bond_type)
def test_sex_transmission(make_model, make_agent):
model = make_model()
model.time = model.params.hiv.start_time
a = make_agent()
a.sex_role = "insertive"
p = make_agent()
p.sex_role = "receptive"
a.partners["Sex"] = set()
p.partners["Sex"] = set()
rel = Relationship(a, p, 10, bond_type="Sex")
a.hiv.active = True
a.hiv.time = model.time # acute
rel.total_sex_acts = 0
model.params.calibration.acquisition = 10
model.params.calibration.acquisition = 5
model.params.calibration.sex.act = 10
model.run_random = FakeRandom(0.6)
a.location.params.partnership.sex.frequency = ObjMap({
"Sex": {
"type": "bins",
"bins": {
1: {
"prob": 1.0,
"min": 10,
"max": 37
}
}
}
})
p.location.params.partnership.sex.frequency = ObjMap({
"Sex": {
"type": "bins",
"bins": {
1: {
"prob": 1.0,
"min": 10,
"max": 37
}
}
}
})
# test partner becomes
Sex.interact(model, rel)
assert p.hiv.active
p.hiv.active = False
a.location.params.partnership.sex.frequency = (
p.location.params.partnership.sex.frequency) = ObjMap({
"Sex": {
"type": "distribution",
"distribution": {
"dist_type": "set_value",
"vars": {
1: {
"value": 1,
"value_type": "int"
}
},
},
}
})
Sex.interact(model, rel)
assert p.hiv.active
# before hiv start time
p.hiv.active = False
model.time = model.params.hiv.start_time - 1
Sex.interact(model, rel)
assert not p.hiv.active