def _fit_local(self, data):
from sklearn.decomposition import FastICA
from numpy import random
random.seed(self.seed)
model = FastICA(n_components=self.k, fun="cube", max_iter=self.max_iter, tol=self.tol, random_state=self.seed)
signals = model.fit_transform(data)
return signals, model.mixing_.T
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