neurosynth/analysis/cluster.py
def transform(self, transformer, transpose=False):
        ''' Apply a transformation to the Clusterable instance. Accepts any
        scikit-learn-style class that implements a fit_transform() method. '''
        data = self.data.T if transpose else self.data
        data = transformer.fit_transform(data)
        self.data = data.T if transpose else data
        return self
def transform(self, transformer, transpose=False):
        ''' Apply a transformation to the Clusterable instance. Accepts any
        scikit-learn-style class that implements a fit_transform() method. '''
        data = self.data.T if transpose else self.data
        data = transformer.fit_transform(data)
        self.data = data.T if transpose else data
        return self
def transform ( self , transformer , transpose = False ) : data = self . data . T if transpose else self . data data = transformer . fit_transform ( data ) self . data = data . T if transpose else data return self
Apply a transformation to the Clusterable instance. Accepts any
        scikit-learn-style class that implements a fit_transform() method.
Apply a transformation to the Clusterable instance . Accepts any scikit - learn - style class that implements a fit_transform () method .