src/text_clustering.py [114:125]:
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        self.id2cluster = {
            index: label for index, label in enumerate(self.cluster_labels)
        }
        self.label2docs = defaultdict(list)
        for i, label in enumerate(self.cluster_labels):
            self.label2docs[label].append(i)

        self.cluster_centers = {}
        for label in self.label2docs.keys():
            x = np.mean([self.projections[doc, 0] for doc in self.label2docs[label]])
            y = np.mean([self.projections[doc, 1] for doc in self.label2docs[label]])
            self.cluster_centers[label] = (x, y)
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src/text_clustering.py [280:291]:
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        self.id2cluster = {
            index: label for index, label in enumerate(self.cluster_labels)
        }
        self.label2docs = defaultdict(list)
        for i, label in enumerate(self.cluster_labels):
            self.label2docs[label].append(i)

        self.cluster_centers = {}
        for label in self.label2docs.keys():
            x = np.mean([self.projections[doc, 0] for doc in self.label2docs[label]])
            y = np.mean([self.projections[doc, 1] for doc in self.label2docs[label]])
            self.cluster_centers[label] = (x, y)
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