46 lines
1.3 KiB
Python
46 lines
1.3 KiB
Python
from multi_swarm.agents.adversarial import AdversarialReport, Finding, Severity
|
|
from multi_swarm.agents.falsification import FalsificationReport
|
|
from multi_swarm.ga.fitness import compute_fitness
|
|
|
|
|
|
def make_falsification(
|
|
dsr: float = 0.7, max_dd: float = 0.2, n_trades: int = 30
|
|
) -> FalsificationReport:
|
|
return FalsificationReport(
|
|
sharpe=1.5,
|
|
dsr=dsr,
|
|
dsr_pvalue=0.05,
|
|
max_drawdown=max_dd,
|
|
total_return=0.3,
|
|
n_trades=n_trades,
|
|
n_bars=500,
|
|
)
|
|
|
|
|
|
def test_fitness_zero_trades_is_zero() -> None:
|
|
f = make_falsification(n_trades=0)
|
|
a = AdversarialReport()
|
|
assert compute_fitness(f, a) == 0.0
|
|
|
|
|
|
def test_fitness_increases_with_dsr() -> None:
|
|
a = AdversarialReport()
|
|
f1 = make_falsification(dsr=0.5)
|
|
f2 = make_falsification(dsr=0.9)
|
|
assert compute_fitness(f2, a) > compute_fitness(f1, a)
|
|
|
|
|
|
def test_fitness_decreases_with_drawdown() -> None:
|
|
a = AdversarialReport()
|
|
f1 = make_falsification(max_dd=0.1)
|
|
f2 = make_falsification(max_dd=0.4)
|
|
assert compute_fitness(f1, a) > compute_fitness(f2, a)
|
|
|
|
|
|
def test_fitness_zeroed_by_high_severity_finding() -> None:
|
|
f = make_falsification()
|
|
a = AdversarialReport(
|
|
findings=[Finding(name="degenerate", severity=Severity.HIGH, detail="x")]
|
|
)
|
|
assert compute_fitness(f, a) == 0.0
|