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refactor in prep for enemies

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This commit is contained in:
Joshua Burman
2023-11-09 16:12:26 -05:00
parent 49178380a4
commit 11979193de
7 changed files with 159 additions and 115 deletions
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117
app/services/form_generation_service.py
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@ -8,6 +8,7 @@ from lib.errors.item_generation_error import ItemGenerationError
from models.solver_run import SolverRun
from models.solution import Solution
from models.problem import Problem
from models.form import Form
from models.target import Target
@ -71,24 +72,6 @@ class FormGenerationService(Base):
form_number = form_count + 1
current_drift = 0 # FF Tokyo Drift
# adding an element of randomness to the items and bundles used
# may need to change impl based on limit of items available
selected_items = self.solver_run.select_items_by_percent(30)
selected_bundles = self.solver_run.select_bundles_by_percent(
30)
# setup common Solver variables
items = LpVariable.dicts("Item",
[item.id for item in selected_items],
lowBound=0,
upBound=1,
cat='Binary')
bundles = LpVariable.dicts("Bundle",
[bundle.id for bundle in selected_bundles],
lowBound=0,
upBound=1,
cat='Binary')
logging.info(f'Generating Solution for Form {form_number} using the {self.solver_run.irt_model.model} IRT model')
while current_drift <= Target.max_drift():
@ -97,99 +80,11 @@ class FormGenerationService(Base):
drift_percent)
# create problem
problem = LpProblem('ata-form-generate', LpMinimize)
# objective function
problem += lpSum([
bundle.count * bundles[bundle.id]
for bundle in selected_bundles
] + [
items[item.id]
for item in selected_items
])
# Form Constraints
problem += lpSum(
[
bundle.count * bundles[bundle.id]
for bundle in selected_bundles
] + [
1 * items[item.id]
for item in selected_items
]
) == self.solver_run.total_form_items, f'Total bundle form items for form {form_number}'
# Dynamic constraints.. currently we only support Metadata and Bundles(Cases/Passages)
problem = solver_helper.build_constraints(
self.solver_run, problem, items, bundles, selected_items, selected_bundles)
# form uniqueness constraints
# for form in solution.forms:
# form_item_options = [
# bundles[bundle.id]
# for bundle in selected_bundles
# ] + [
# items[item.id]
# for item in selected_items
# ]
# problem += len(
# set(form.solver_variables)
# & set(form_item_options)) / float(
# len(
# set(form.solver_variables)
# | set(form_item_options))) * 100 >= 10
logging.info('Creating TIF and TCC Elastic constraints')
# Behold our very own Elastic constraints!
for tif_target in self.solver_run.objective_function.tif_targets:
problem += lpSum([
bundle.tif(self.solver_run.irt_model, tif_target.theta)
* bundles[bundle.id]
for bundle in selected_bundles
] + [
item.iif(self.solver_run, tif_target.theta) *
items[item.id]
for item in selected_items
]) >= tif_target.minimum(
), f'Min TIF theta({tif_target.theta}) at target {tif_target.value} drift at {current_drift}%'
problem += lpSum([
bundle.tif(self.solver_run.irt_model, tif_target.theta)
* bundles[bundle.id]
for bundle in selected_bundles
] + [
item.iif(self.solver_run, tif_target.theta) *
items[item.id]
for item in selected_items
]) <= 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:
problem += lpSum([
bundle.trf(self.solver_run.irt_model, tcc_target.theta)
* bundles[bundle.id]
for bundle in selected_bundles
] + [
item.irf(self.solver_run, tcc_target.theta) *
items[item.id]
for item in selected_items
]) >= tcc_target.minimum(
), f'Min TCC theta({tcc_target.theta}) at target {tcc_target.value} drift at {current_drift}%'
problem += lpSum([
bundle.trf(self.solver_run.irt_model, tcc_target.theta)
* bundles[bundle.id]
for bundle in selected_bundles
] + [
item.irf(self.solver_run, tcc_target.theta) *
items[item.id]
for item in selected_items
]) <= 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}%'
)
problem.solve()
problem_handler = Problem(items = self.solver_run.items, bundles = self.solver_run.bundles, problem = LpProblem('ata-form-generate', LpMinimize))
problem_handler.generate(solution, self.solver_run)
problem_handler.generate_constraints(self.solver_run, current_drift)
problem = problem_handler.solve()
if LpStatus[problem.status] == 'Infeasible':
logging.info(