Add dna to hyperactive csv.
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@@ -124,6 +124,7 @@ class Optimizer():
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# save the score in the copy of the dictionary
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parameter_dict["score"] = score
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parameter_dict["dna"] = jh.hp_to_dna(self.strategy_hp, hp.para_dict)
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# if score:
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# # save the daily_returns in the copy of the dictionary
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@@ -183,6 +184,7 @@ class Optimizer():
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if jh.file_exists(self.path):
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with open(self.path, "r") as f:
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mem = pd.read_csv(f, sep=";", na_values='nan')
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mem.drop('dna', axis=1, inplace=True)
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if not mem.empty and not click.confirm(
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f'Previous optimization results for {self.study_name} exists. Continue?',
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default=True,
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@@ -251,7 +253,7 @@ class Optimizer():
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if mem is None or mem.empty:
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# init empty pandas dataframe
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# search_data = pd.DataFrame(columns=list(self.search_space.keys()) + ["score", "daily_balance"])
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search_data = pd.DataFrame(columns=list(self.search_space.keys()) + ["score"])
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search_data = pd.DataFrame(columns=list(self.search_space.keys()) + ["score", "dna"])
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with open(self.path, "w") as f:
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search_data.to_csv(f, sep=";", index=False, na_rep='nan')
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