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Update hyperopt.py
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@ -414,30 +414,33 @@ class Hyperopt:
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# Store non-trimmed data - will be trimmed after signal generation.
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dump(preprocessed, self.data_pickle_file)
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def get_asked_points(self, n_points: int) -> List[Any]:
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def get_asked_points(self, n_points: int) -> List[List[Any]]:
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'''
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Enforce points returned from `self.opt.ask` have not been already evaluated
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Steps:
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1. Try to get points using `self.opt.ask` first
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2. Discard the points that have already been evaluated
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3. Retry using `self.opt.ask` up to 3 times
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4. If still some points are missing in respect to `n_points`, random sample some points
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5. Repeat until at least `n_points` points in the `asked_non_tried` list
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6. Return a list with legth truncated at `n_points`
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6. Return a list with length truncated at `n_points`
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'''
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i = 0
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asked_non_tried = []
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while i < 100:
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if len(asked_non_tried) < n_points:
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if i < 3:
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asked = self.opt.ask(n_points=n_points)
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else:
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# use random sample if `self.opt.ask` returns points points already tried
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asked = self.opt.space.rvs(n_samples=n_points * 5)
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asked_non_tried += [x for x in asked if x not in self.opt.Xi and x not in asked_non_tried]
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i += 1
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asked_non_tried: List[List[Any]] = []
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while i < 100 and len(asked_non_tried) < n_points:
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if i < 3:
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asked = self.opt.ask(n_points=n_points)
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else:
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break
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return asked_non_tried[:n_points]
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asked = self.opt.space.rvs(n_samples=n_points * 5)
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asked_non_tried += [x for x in asked
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if x not in self.opt.Xi
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and x not in asked_non_tried]
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i += 1
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if asked_non_tried:
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return asked_non_tried[:n_points]
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else:
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return self.opt.ask(n_points=n_points)
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def start(self) -> None:
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self.random_state = self._set_random_state(self.config.get('hyperopt_random_state', None))
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