1 files changed, 180 insertions, 0 deletions
diff --git a/pipeline.py b/pipeline.py
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+++ b/pipeline.py
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+# -- In the sum of squares library -------------------------------------------------------
+from abc import ABC, abstractmethod
+from enum import Enum, auto
+from typing import Callable, Self
+from dataclasses import dataclass, field
+from itertools import cycle
+from functools import wraps
+
+try:
+	from typing import override
+except ImportError:
+	from typing_extensions import override
+
+
+class Solver(Enum):
+	""" Enum to select a solver """
+	CVXOPT = auto()
+
+
+@dataclass(frozen=True)
+class OptResult(ABC):
+	""" Generic result from optimization problem """
+	success: bool # last problem was solved successfully
+	
+
+class Problem(ABC):
+	""" Optimization Problem. """
+	
+	@abstractmethod
+	def solve(self, solver: Solver) -> OptResult:
+		""" Solve the optimization problem """
+		
+		
+class SOSProblem(Problem):
+	@override
+	def solve(self, solver: Solver) -> OptResult:
+		raise NotImplementedError
+
+	
+Stage			 = Callable[[OptResult], Problem]
+SolvableStage    = Callable[[OptResult, Solver], OptResult]
+
+@dataclass
+class HaltingPredicate:
+	""" This wrapper is sadly necessary because otherwise we can't use
+	`isinstance(stage, HaltingPredicate)` in the class below. """
+	check: Callable[[OptResult], bool]
+	
+	def __str__(self):
+		return self.check.__name__
+	
+	def __call__(self, res: OptResult):
+		return self.check(res)
+
+
+@dataclass
+class MultiStageProblem(Problem):
+	""" Pipeline for multi-state optimization problems.
+	
+	The pipeline is made of stages and halting predicates. If there are no halting
+	predicates, the pipeline runs the stages by passing the result of each stage to the
+	next. If there are halting predicates, the pipeline is repeated until one of the
+	halting predicates tells it to stop.
+	"""
+	initial: OptResult
+	solver: Solver = Solver.CVXOPT
+	stages: list[Stage | HaltingPredicate] = field(default_factory=list)
+	iterations: int = 0
+	
+	# Magic methods
+	
+	def __str__(self):
+		i, lines = 0, ["Multi-Stage Problem:"]
+		for stage in self.stages:
+			if isinstance(stage, HaltingPredicate):
+				lines.append(f"    halt? {stage}")
+			else:
+				lines.append(f" {i:02d} stage {stage.__name__}")
+				i += 1
+		return "\n".join(lines)
+	
+	# Problem behaviour
+	
+	@override
+	def solve(self) -> OptResult:
+		""" Solve the multistage problem """
+		if HaltingPredicate in map(type, self.stages):
+			return self._solve_repeating()
+		return self._solve_once()
+	
+	def _solve_once(self) -> OptResult:
+		self.iterations, result = 0, self.initial
+		for stage in self.stages:
+			result = stage(result, self.solver)
+			self.iterations += 1
+		return result
+		
+	def _solve_repeating(self) -> OptResult:
+		self.iterations, result = 0, self.initial
+		for stage in cycle(self.stages):
+			if isinstance(stage, HaltingPredicate):
+				if stage(result):
+					break
+			else:
+				result = stage(result, self.solver)
+		return result
+		
+	# Wrappers
+
+	@staticmethod
+	def stage(fn: Stage) -> SolvableStage:
+		""" Make a stage / step for the pipeline.  """
+		@wraps(fn)
+		def wrapper(res: OptResult, solver: Solver) -> OptResult:
+			return fn(res).solve(solver)
+			
+		return wrapper
+		
+	@staticmethod
+	def halt(fn: Callable[[OptResult], bool]) -> HaltingPredicate:
+		return HaltingPredicate(fn)
+		
+	# Pipeline construction (plumbing)
+	
+	def and_then(self, fn: SolvableStage) -> Self:
+		""" Add a stage to the pipeline that runs only if the previous stage
+		completed with success. """
+		@wraps(fn)
+		def wrapper(res: OptResult, solver: Solver) -> OptResult:
+			if not res.success:
+				return res # do nothing
+			return fn(res, solver)
+			
+		self.stages.append(fn)
+		return self
+		
+	def or_else(self, fn: SolvableStage) -> Self:
+		""" Add a stage to the pipeline, that runs only if the previous stage
+		failed.  """
+		@wraps(fn)
+		def wrapper(res: OptResult, solver: Solver) -> OptResult:
+			if res.success:
+				return res # do nothing
+			return fn(res, solver)
+			
+		self.stages.append(wrapper)
+		return self
+		
+	def stop_if(self, predicate: HaltingPredicate) -> Self:
+		""" Add a predicate to stop the pipeline. """
+		self.stages.append(predicate)
+		return self
+			
+# -- In the user script -----------------------------------------------------------------
+# from sumofsquares import MultiStageProblem
+
+# Define stages
+@MultiStageProblem.stage
+def solve_controller(result: OptResult) -> Problem:
+	return SOSProblem()
+	
+@MultiStageProblem.stage
+def solve_cbf_clf(result: OptResult) -> Problem:
+	return SOSProblem()
+
+@MultiStageProblem.halt
+def good_op_region(result: OptResult) -> bool:
+	return abs(result.roi) < 1e-3
+
+
+# Initialize multi-stage problem and define order
+power_converter_prob = (
+	MultiStageProblem(initial=OptResult) # Pass initialization in constructor
+		.and_then(solve_controller)
+		.stop_if(good_op_region)
+		.and_then(solve_cbf_clf)
+)
+
+print(power_converter_prob)
+# res: OptResult = power_converter_prob.solve()