just save the body parameter externally in my gist
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Adrian Manteza
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ef04373bd4
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98922bfc4c
@ -67,101 +67,113 @@ class LoftService(Base):
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solution = Solution(response_id=random.randint(100, 5000), forms=[]) # unsolved solution
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# setup common Solver variables
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items = LpVariable.dicts("Item", [item.id for item in self.solver_run.items], cat='Binary')
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items = LpVariable.dicts("Item", [item.id for item in self.solver_run.items], cat='Binary')
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bundles = LpVariable.dicts("Bundle", [bundle.id for bundle in self.solver_run.bundles], cat='Binary')
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form_count = 0 # counter for number of forms
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# iterate for number of forms that require creation
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while form_count < self.solver_run.total_forms:
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form_number = form_count + 1
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logging.info('Generating Solution for Form %s...', form_number)
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for form_count in range(self.solver_run.total_forms):
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form_number = form_count + 1
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current_drift = 0 # FF Tokyo Drift
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# create problem
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problem = LpProblem("ata-form-generate", LpMinimize)
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problem_objective_functions = []
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logging.info(f'Generating Solution for Form {form_number}')
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# dummy objective function, because it just makes things easier™
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problem += lpSum([items[item.id] for item in self.solver_run.items])
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while current_drift <= Target.max_drift():
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drift_percent = current_drift / 100
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# constraints
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problem += lpSum([items[item.id]
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for item in self.solver_run.items]) == self.solver_run.total_form_items, f'Total form items for form {form_number}'
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problem += lpSum(
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[
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bundle.count * bundles[bundle.id]
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for bundle in self.solver_run.bundles
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] + [
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1 * items[item.id]
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for item in self.solver_run.unbundled_items()
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]
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) == self.solver_run.total_form_items, f'Total bundle form items for form {form_number}'
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# create problem
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problem = LpProblem('ata-form-generate', LpMinimize)
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# Dynamic constraints.. currently we only support Metadata and Bundles(Cases/Passages)
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problem = solver_helper.build_constraints(self.solver_run, problem, items, bundles)
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# objective function
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problem += lpSum(
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[item.iif_irf_sum(self.solver_run) * items[item.id] for item in self.solver_run.items]
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+
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[bundle.tif_trf_sum(self.solver_run) * bundles[bundle.id] for bundle in self.solver_run.bundles]
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)
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# multi-objective constraints
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logging.info('Creating TIF and TCC constraints')
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for target in self.solver_run.objective_function.tif_targets:
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tif = lpSum([
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bundle.tif(self.solver_run.irt_model, target.theta) *
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bundles[bundle.id] for bundle in self.solver_run.bundles
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] + [
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item.iif(self.solver_run, target.theta) * items[item.id]
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for item in self.solver_run.items
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]) <= target.value, f'min tif theta {target.theta} target for form {form_number}'
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# Form Constraints
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problem += lpSum(
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[items[item.id] for item in self.solver_run.items]
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) == self.solver_run.total_form_items, f'Total form items for form {form_number}'
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problem += tif
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problem_objective_functions.append(tif)
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problem += lpSum(
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[
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bundle.count * bundles[bundle.id] for bundle in self.solver_run.bundles
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] +
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[
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1 * items[item.id] for item in self.solver_run.unbundled_items()
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]
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) == self.solver_run.total_form_items, f'Total bundle form items for form {form_number}'
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e = LpAffineExpression(
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[(bundles[bundle.id],
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bundle.tif(self.solver_run.irt_model, target.theta))
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for bundle in self.solver_run.bundles] +
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[(items[item.id], item.iif(self.solver_run, target.theta))
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for item in self.solver_run.items])
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constraint = LpConstraint(
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e=e,
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sense=0,
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name=f'tif theta ({target.theta}) @{target.value}',
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rhs=target.value)
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# Dynamic constraints.. currently we only support Metadata and Bundles(Cases/Passages)
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problem = solver_helper.build_constraints(self.solver_run, problem, items, bundles)
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elasticized_constraint = solver_helper.elasticize_constraint(constraint)
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problem.extend(elasticized_constraint)
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# if int(target.value) == 20: print(elasticized_constraint)
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for target in self.solver_run.objective_function.tcc_targets:
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tcc = lpSum([
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bundle.trf(self.solver_run.irt_model, target.theta) *
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bundles[bundle.id] for bundle in self.solver_run.bundles
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] + [
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item.irf(self.solver_run, target.theta) * items[item.id]
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for item in self.solver_run.items
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]) <= target.value, f'min tcc theta {target.theta} target for form {form_number}'
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logging.info('Creating TIF and TCC Elastic constraints')
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problem += tcc
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problem_objective_functions.append(tcc)
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# Behold our very own Elastic constraints!
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for tif_target in self.solver_run.objective_function.tif_targets:
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problem += lpSum(
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[
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bundle.tif(self.solver_run.irt_model, tif_target.theta) * bundles[bundle.id]
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for bundle in self.solver_run.bundles
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] +
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[
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item.iif(self.solver_run, tif_target.theta) * items[item.id]
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for item in self.solver_run.items
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]
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) >= tif_target.value - (tif_target.value * drift_percent)
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e = LpAffineExpression(
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[(bundles[bundle.id],
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bundle.trf(self.solver_run.irt_model, target.theta))
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for bundle in self.solver_run.bundles] +
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[(items[item.id], item.irf(self.solver_run, target.theta))
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for item in self.solver_run.items])
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constraint = LpConstraint(
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e=e,
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sense=-1,
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name=f'tcc theta ({target.theta}) @{target.value} for form {form_number}',
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rhs=target.value)
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problem += lpSum(
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[
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bundle.tif(self.solver_run.irt_model, tif_target.theta) * bundles[bundle.id]
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for bundle in self.solver_run.bundles
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] +
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[
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item.iif(self.solver_run, tif_target.theta) * items[item.id]
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for item in self.solver_run.items
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]
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) <= tif_target.value + (tif_target.value * drift_percent)
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elasticized_constraint = solver_helper.elasticize_constraint(constraint)
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# problem.extend(elasticized_constraint)
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for tcc_target in self.solver_run.objective_function.tcc_targets:
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problem += lpSum(
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[
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bundle.trf(self.solver_run.irt_model, tcc_target.theta) * bundles[bundle.id]
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for bundle in self.solver_run.bundles
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] +
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[
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item.irf(self.solver_run, tcc_target.theta) * items[item.id]
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for item in self.solver_run.items
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]
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) >= tcc_target.value - (tcc_target.value * drift_percent)
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# solve problem
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logging.info('Solving for Form %s...', form_number)
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problem += lpSum(
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[
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bundle.trf(self.solver_run.irt_model, tcc_target.theta) * bundles[bundle.id]
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for bundle in self.solver_run.bundles
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] +
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[
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item.irf(self.solver_run, tcc_target.theta) * items[item.id]
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for item in self.solver_run.items
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]
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) <= tcc_target.value + (tcc_target.value * drift_percent)
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print(problem)
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problem.solve()
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# problem.sequentialSolve(problem_objective_functions)
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# solve problem
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logging.info(f'Solving for Form {form_number}')
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problem.solve()
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if LpStatus[problem.status] == 'Infeasible':
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logging.info(f'attempt infeasible for drift of {current_drift}%')
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for v in problem.variables():
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print(v.name, "=", v.varValue)
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print(problem.objective.value())
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print(problem.objective)
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current_drift += Target.max_drift_increment()
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else:
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logging.info(f'solution found with drift of {current_drift}%!')
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break
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logging.info(f'Solved for Form {form_number}...generating form and adding to solution')
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@ -173,11 +185,8 @@ class LoftService(Base):
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logging.info('Form generated and added to solution...')
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# successfull form, increment
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form_count += 1
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logging.info('Solution Generated.')
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# print(problem)
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return solution
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def stream_to_s3_bucket(self, error=None):
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@ -14,8 +14,7 @@ from pulp import LpProblem, LpVariable, LpInteger, LpMinimize, LpMaximize, LpAff
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from services.loft_service import LoftService
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class SolverSandbox:
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def loft_service():
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body = {'Records': [{'eventVersion': '2.1', 'eventSource': 'aws:s3', 'awsRegion': 'us-east-1', 'eventTime': '2022-03-09T14:40:04.115Z', 'eventName': 'ObjectCreated:Put', 'userIdentity': {'principalId': 'AIDAJDPLRKLG7UEXAMPLE'}, 'requestParameters': {'sourceIPAddress': '127.0.0.1'}, 'responseElements': {'x-amz-request-id': '4629a38d', 'x-amz-id-2': 'eftixk72aD6Ap51TnqcoF8eFidJG9Z/2'}, 's3': {'s3SchemaVersion': '1.0', 'configurationId': 'testConfigRule', 'bucket': {'name': 'measure-local-solver-ingest', 'ownerIdentity': {'principalId': 'A3NL1KOZZKExample'}, 'arn': 'arn:aws:s3:::measure-local-solver-ingest'}, 'object': {'key': 'baf511b0-81e4-013a-6e98-0242ac120010_solver_run.tar.gz', 'size': 509, 'eTag': '"4c0911a335c6feca5493d63b58654e3a"', 'versionId': None, 'sequencer': '0055AED6DCD90281E5'}}}]}
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def loft_service(body):
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LoftService(body).process()
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def yosh_loop():
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