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Merge components more efficiently
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@@ -180,13 +180,20 @@ class WarmStartComponent(Component):
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self.predictors[category] = deepcopy(self.predictor_prototype)
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self.predictors[category].fit(x_train, y_train)
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def merge(self, other):
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for c in other.x_train.keys():
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if c not in self.x_train:
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self.x_train[c] = other.x_train[c]
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self.y_train[c] = other.y_train[c]
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else:
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self.x_train[c] = np.vstack([self.x_train[c], other.x_train[c]])
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self.y_train[c] = np.vstack([self.y_train[c], other.y_train[c]])
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if (c in other.predictors.keys()) and (c not in self.predictors.keys()):
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self.predictors[c] = other.predictors[c]
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def merge(self, other_components):
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keys = set(self.x_train.keys())
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for comp in other_components:
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keys = keys.union(set(comp.x_train.keys()))
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for key in keys:
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x_train_submatrices = [comp.x_train[key]
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for comp in other_components
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if key in comp.x_train.keys()]
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y_train_submatrices = [comp.y_train[key]
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for comp in other_components
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if key in comp.y_train.keys()]
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if key in self.x_train.keys():
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x_train_submatrices += [self.x_train[key]]
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y_train_submatrices += [self.y_train[key]]
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self.x_train[key] = np.vstack(x_train_submatrices)
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self.y_train[key] = np.vstack(y_train_submatrices)
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