qbahn /
grortir
| Total Complexity | 10 |
| Total Lines | 37 |
| Duplicated Lines | 0 % |
| Coverage | 100% |
| Changes | 2 | ||
| Bugs | 0 | Features | 0 |
| 1 | """Basic optimizer.""" |
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| 8 | 1 | class Optimizer(object): |
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| 9 | """Optimizer is object which optimize process.""" |
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| 10 | |||
| 11 | 1 | def __init__(self, process): |
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| 12 | 1 | self.process = process |
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| 13 | 1 | self.ordered_stages = nx.topological_sort(self.process) |
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| 14 | 1 | self.swarm_size = 40 |
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| 15 | |||
| 16 | 1 | def set_custom_optimizing_order(self, ordered_stages): |
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| 17 | """Set custom order.""" |
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| 18 | 1 | if set(self.ordered_stages) == set(ordered_stages) and len( |
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| 19 | self.ordered_stages) == len(ordered_stages): |
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| 20 | 1 | self.ordered_stages = ordered_stages |
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| 21 | else: |
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| 22 | 1 | raise ValueError("List of stages must contain all stages.") |
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| 23 | |||
| 24 | 1 | def optimize_process(self): |
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| 25 | """Optimize process. |
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| 26 | Returns: |
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| 27 | True if success, False otherwise.""" |
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| 28 | 1 | for stage in self.ordered_stages: |
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| 29 | 1 | if not self.process.predecessors(stage): |
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| 30 | 1 | self.run_pso(stage) |
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| 31 | 1 | elif len(self.process.predecessors(stage)) == 1: |
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| 32 | 1 | predecessor = self.process.predecessors(stage)[0] |
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| 33 | 1 | stage.input_vector = predecessor.get_output_of_stage() |
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| 34 | 1 | self.run_pso(stage) |
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| 35 | else: |
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| 36 | 1 | raise AttributeError('Incorrect process structure.') |
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| 37 | |||
| 38 | 1 | if stage.optimization_status != OptimizationStatus.success: |
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| 39 | 1 | return False |
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| 40 | 1 | return True |
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| 41 | |||
| 42 | 1 | def run_pso(self, stage): |
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| 43 | """Run pso with predefined parameters.""" |
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| 44 | pso(stage, swarmsize=self.swarm_size) |
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| 45 |
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