jshbrmn/irt-service
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just update the Target drift attribute to so we dont have to inject the drift_percent every single time

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This commit is contained in:
Adrian Manteza 2022-03-17 22:48:22 +00:00
parent e4f51b8a3f
commit bd61fb7e81
3 changed files with 15 additions and 8 deletions
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6
app/models/objective_function.py
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@ -30,6 +30,12 @@ class ObjectiveFunction(BaseModel):
print(self.tcc_targets) print(self.tcc_targets)
return amount return amount
def update_targets_drift(self, amount: float = 0.0):
for target in self.tif_targets:
target.drift = round(amount, 2)
for target in self.tcc_targets:
target.drift = round(amount, 2)
def minimum_drift(self) -> float: def minimum_drift(self) -> float:
minimum_drift = 0.0 minimum_drift = 0.0

8
app/models/target.py
View File

@ -15,8 +15,8 @@ class Target(BaseModel):
def max_drift_increment(cls) -> int: def max_drift_increment(cls) -> int:
return 1 # 10% return 1 # 10%
def minimum(self, drift_percent = 0.0) -> float: def minimum(self) -> float:
return self.value - (self.value * drift_percent) return self.value - (self.value * self.drift)
def maximum(self, drift_percent = 0.0) -> float: def maximum(self) -> float:
return self.value + (self.value * drift_percent) return self.value + (self.value * self.drift)

9
app/services/loft_service.py
View File

@ -80,6 +80,7 @@ class LoftService(Base):
while current_drift <= Target.max_drift(): while current_drift <= Target.max_drift():
drift_percent = current_drift / 100 drift_percent = current_drift / 100
self.solver_run.objective_function.update_targets_drift(drift_percent)
# create problem # create problem
problem = LpProblem('ata-form-generate', LpMinimize) problem = LpProblem('ata-form-generate', LpMinimize)
@ -120,7 +121,7 @@ class LoftService(Base):
item.iif(self.solver_run, tif_target.theta) * items[item.id] item.iif(self.solver_run, tif_target.theta) * items[item.id]
for item in self.solver_run.unbundled_items() for item in self.solver_run.unbundled_items()
] ]
) >= tif_target.minimum(drift_percent), f'Min TIF theta({tif_target.theta}) at target {tif_target.value} drift at {current_drift}%' ) >= tif_target.minimum(), f'Min TIF theta({tif_target.theta}) at target {tif_target.value} drift at {current_drift}%'
problem += lpSum( problem += lpSum(
[ [
bundle.tif(self.solver_run.irt_model, tif_target.theta) * bundles[bundle.id] bundle.tif(self.solver_run.irt_model, tif_target.theta) * bundles[bundle.id]
@ -130,7 +131,7 @@ class LoftService(Base):
item.iif(self.solver_run, tif_target.theta) * items[item.id] item.iif(self.solver_run, tif_target.theta) * items[item.id]
for item in self.solver_run.unbundled_items() for item in self.solver_run.unbundled_items()
] ]
) <= tif_target.maximum(drift_percent), f'Max TIF theta({tif_target.theta}) at target {tif_target.value} drift at {current_drift}%' ) <= tif_target.maximum(), f'Max TIF theta({tif_target.theta}) at target {tif_target.value} drift at {current_drift}%'
for tcc_target in self.solver_run.objective_function.tcc_targets: for tcc_target in self.solver_run.objective_function.tcc_targets:
problem += lpSum( problem += lpSum(
@ -142,7 +143,7 @@ class LoftService(Base):
item.irf(self.solver_run, tcc_target.theta) * items[item.id] item.irf(self.solver_run, tcc_target.theta) * items[item.id]
for item in self.solver_run.unbundled_items() for item in self.solver_run.unbundled_items()
] ]
) >= tcc_target.minimum(drift_percent), f'Min TCC theta({tcc_target.theta}) at target {tcc_target.value} drift at {current_drift}%' ) >= tcc_target.minimum(), f'Min TCC theta({tcc_target.theta}) at target {tcc_target.value} drift at {current_drift}%'
problem += lpSum( problem += lpSum(
[ [
bundle.trf(self.solver_run.irt_model, tcc_target.theta) * bundles[bundle.id] bundle.trf(self.solver_run.irt_model, tcc_target.theta) * bundles[bundle.id]
@ -152,7 +153,7 @@ class LoftService(Base):
item.irf(self.solver_run, tcc_target.theta) * items[item.id] item.irf(self.solver_run, tcc_target.theta) * items[item.id]
for item in self.solver_run.unbundled_items() for item in self.solver_run.unbundled_items()
] ]
) <= tcc_target.maximum(drift_percent), f'Max TCC theta({tcc_target.theta}) at target {tcc_target.value} drift at {current_drift}%' ) <= tcc_target.maximum(), f'Max TCC theta({tcc_target.theta}) at target {tcc_target.value} drift at {current_drift}%'
logging.info(f'Solving for Form {form_number} with a drift of {current_drift}%') logging.info(f'Solving for Form {form_number} with a drift of {current_drift}%')
problem.solve() problem.solve()