def test_interval_storage_with_two_intervals_and_midpoint_get(self): interval_storage = IntervalStorage() interval_storage.add_interval("1", 0.0, 0.5) interval_storage.add_interval("2", 0.5, 1.0) self.assertEqual("1", interval_storage.get_entry(0.25)) self.assertEqual("2", interval_storage.get_entry(0.5)) self.assertEqual("2", interval_storage.get_entry(0.8))
def test_initializing_interval_storage_with_a_map(self): interval_storage = IntervalStorage({ "1": (0.0, 0.3), "2": (0.3, 0.6), "3": (0.6, 1.0) }) self.assertEqual("1", interval_storage.get_entry(0.0)) self.assertEqual("1", interval_storage.get_entry(0.2)) self.assertEqual("2", interval_storage.get_entry(0.3)) self.assertEqual("2", interval_storage.get_entry(0.5)) self.assertEqual("3", interval_storage.get_entry(0.6)) self.assertEqual("3", interval_storage.get_entry(0.85))
def __init__(self, settings, stages=None): self.settings = settings if stages == None: stages = self.settings.get("optimization_algorithm.default_stages") for key in stages.iterkeys(): if not issubclass(key, OptimizationAlgorithmStage): raise ValueError( "OptimizationAlgorithmStageHandler must contain OptimizationAlgorithmStage subclasses." ) self.stage_storage = IntervalStorage(stages) self.stages_used = []
def test_interval_storage_for_completely_containing_intervals(self): interval_storage = IntervalStorage() interval_storage.add_interval("1", 0.5, 0.7) with self.assertRaises(ValueError): interval_storage.add_interval("2", 0.55, 0.65) with self.assertRaises(ValueError): interval_storage.add_interval("3", 0.45, 0.75)
def test_interval_storage_with_a_single_interval(self): interval_storage = IntervalStorage() self.assertFalse(interval_storage.has_intersection(0.0, 1.0)) interval_storage.add_interval("1", 0.0, 1.0) self.assertEqual("1", interval_storage.get_entry(0.5)) with self.assertRaises(ValueError): interval_storage.get_entry(1.5)
def test_interval_storage_for_invalid_intervals(self): interval_storage = IntervalStorage() with self.assertRaises(ValueError): interval_storage.add_interval("1", 0.0, 1.2) with self.assertRaises(ValueError): interval_storage.add_interval("1", -3.2, 0.8) with self.assertRaises(ValueError): interval_storage.add_interval("1", -3.2, 1.4)
def test_interval_storage_for_has_entry(self): interval_storage = IntervalStorage() self.assertFalse(interval_storage.has_entry(0.5)) self.assertFalse(interval_storage.has_entry(1.5)) interval_storage.add_interval("1", 0.3, 0.7) self.assertTrue(interval_storage.has_entry(0.5)) self.assertFalse(interval_storage.has_entry(0.8)) self.assertFalse(interval_storage.has_entry(0.2)) self.assertFalse(interval_storage.has_entry(-0.2))
def test_initializing_interval_storage_with_a_map_with_invalid_intervals( self): with self.assertRaises(ValueError): interval_storage = IntervalStorage({ "1": (0.0, 0.5), "2": (0.4, 1.0) }) with self.assertRaises(ValueError): interval_storage = IntervalStorage({ "1": (-10.0, 20.5), "2": (0.4, 1.0) }) with self.assertRaises(ValueError): interval_storage = IntervalStorage({ "1": (0.0, 0.5), "2": (0.5, 1.2) })
def __init__(self, settings, stages=None): self.settings = settings if stages == None: stages = self.settings.get("optimization_algorithm.default_stages") for key in stages.iterkeys(): if not issubclass(key, OptimizationAlgorithmStage): raise ValueError("OptimizationAlgorithmStageHandler must contain OptimizationAlgorithmStage subclasses.") self.stage_storage = IntervalStorage(stages) self.stages_used = []
class OptimizationAlgorithmStageHandler(object): def __init__(self, settings, stages=None): self.settings = settings if stages == None: stages = self.settings.get("optimization_algorithm.default_stages") for key in stages.iterkeys(): if not issubclass(key, OptimizationAlgorithmStage): raise ValueError("OptimizationAlgorithmStageHandler must contain OptimizationAlgorithmStage subclasses.") self.stage_storage = IntervalStorage(stages) self.stages_used = [] def add_stage(self, stage, start_percentage, end_percentage): self.stage_storage.add_interval(stage, start_percentage, end_percentage) def has_stage(self, current_step, total_steps=None): step_percentage = self._get_step_percentage(current_step, total_steps) return self.stage_storage.has_entry(step_percentage) def get_stage(self, current_step, total_steps=None): step_percentage = self._get_step_percentage(current_step, total_steps) return self.stage_storage.get_entry(step_percentage) # TODO: its possible that an optimization step won't get run if stage == None and # on_step doesn't run. Need some way to fix that. def run_stage(self, current_step, total_steps=None, payload=None): stage = None if self.has_stage(current_step, total_steps): stage = self.get_stage(current_step, total_steps) # If we've started using a new stage, check to see if we have to run the # `after_stage` method. if (stage == None) or not self._is_used_stage(stage): if len(self.stages_used) > 0: last_stage, has_run_after_stage = self.stages_used[-1] if not has_run_after_stage: last_stage(self.settings).after_stage(payload) self.stages_used[-1] = (last_stage, True) # If this is the first time we've seen the stage, then run the `before_stage` # method if (stage != None) and not self._is_used_stage(stage): stage(self.settings).before_stage(payload) self.stages_used.append((stage, False)) # Run the stage if it exists if stage != None: stage(self.settings).on_step(payload=payload) # If this is the last step, then we need to run the after_stage total_steps = self._get_total_steps(total_steps) if stage != None and (current_step >= total_steps - 1): print "Running after stage" stage(self.settings).after_stage(payload) def _is_used_stage(self, stage): for used_stage, _ in self.stages_used: if stage == used_stage: return True return False def _get_step_percentage(self, current_step, total_steps=None): total_steps = self._get_total_steps(total_steps) return float(current_step) / total_steps def _get_total_steps(self, total_steps=None): if total_steps == None: return self.settings.get("optimization_algorithm.finishing_criteria.max_steps") else: return total_steps
class OptimizationAlgorithmStageHandler(object): def __init__(self, settings, stages=None): self.settings = settings if stages == None: stages = self.settings.get("optimization_algorithm.default_stages") for key in stages.iterkeys(): if not issubclass(key, OptimizationAlgorithmStage): raise ValueError( "OptimizationAlgorithmStageHandler must contain OptimizationAlgorithmStage subclasses." ) self.stage_storage = IntervalStorage(stages) self.stages_used = [] def add_stage(self, stage, start_percentage, end_percentage): self.stage_storage.add_interval(stage, start_percentage, end_percentage) def has_stage(self, current_step, total_steps=None): step_percentage = self._get_step_percentage(current_step, total_steps) return self.stage_storage.has_entry(step_percentage) def get_stage(self, current_step, total_steps=None): step_percentage = self._get_step_percentage(current_step, total_steps) return self.stage_storage.get_entry(step_percentage) # TODO: its possible that an optimization step won't get run if stage == None and # on_step doesn't run. Need some way to fix that. def run_stage(self, current_step, total_steps=None, payload=None): stage = None if self.has_stage(current_step, total_steps): stage = self.get_stage(current_step, total_steps) # If we've started using a new stage, check to see if we have to run the # `after_stage` method. if (stage == None) or not self._is_used_stage(stage): if len(self.stages_used) > 0: last_stage, has_run_after_stage = self.stages_used[-1] if not has_run_after_stage: last_stage(self.settings).after_stage(payload) self.stages_used[-1] = (last_stage, True) # If this is the first time we've seen the stage, then run the `before_stage` # method if (stage != None) and not self._is_used_stage(stage): stage(self.settings).before_stage(payload) self.stages_used.append((stage, False)) # Run the stage if it exists if stage != None: stage(self.settings).on_step(payload=payload) # If this is the last step, then we need to run the after_stage total_steps = self._get_total_steps(total_steps) if stage != None and (current_step >= total_steps - 1): print "Running after stage" stage(self.settings).after_stage(payload) def _is_used_stage(self, stage): for used_stage, _ in self.stages_used: if stage == used_stage: return True return False def _get_step_percentage(self, current_step, total_steps=None): total_steps = self._get_total_steps(total_steps) return float(current_step) / total_steps def _get_total_steps(self, total_steps=None): if total_steps == None: return self.settings.get( "optimization_algorithm.finishing_criteria.max_steps") else: return total_steps
def test_interval_storage_with_three_intervals(self): interval_storage = IntervalStorage() interval_storage.add_interval("1", 0.0, 0.3) interval_storage.add_interval("2", 0.3, 0.6) interval_storage.add_interval("3", 0.6, 1.0) self.assertEqual("1", interval_storage.get_entry(0.0)) self.assertEqual("1", interval_storage.get_entry(0.2)) self.assertEqual("2", interval_storage.get_entry(0.3)) self.assertEqual("2", interval_storage.get_entry(0.5)) self.assertEqual("3", interval_storage.get_entry(0.6)) self.assertEqual("3", interval_storage.get_entry(0.85)) with self.assertRaises(ValueError): interval_storage.get_entry(1.0) with self.assertRaises(ValueError): interval_storage.get_entry(-0.01)