neurosynth/base/dataset.py
def trim(self, ids):
        """ Trim ImageTable to keep only the passed studies. This is a
        convenience method, and should generally be avoided in favor of
        non-destructive alternatives that don't require slicing (e.g.,
            matrix multiplication). """
        self.data = self.get_image_data(ids, dense=False)  # .tocoo()
        idxs = np.where(np.in1d(np.array(self.ids), np.array(ids)))[0]
        self.ids = [self.ids[i] for i in idxs]
def trim(self, ids):
        """ Trim ImageTable to keep only the passed studies. This is a
        convenience method, and should generally be avoided in favor of
        non-destructive alternatives that don't require slicing (e.g.,
            matrix multiplication). """
        self.data = self.get_image_data(ids, dense=False)  # .tocoo()
        idxs = np.where(np.in1d(np.array(self.ids), np.array(ids)))[0]
        self.ids = [self.ids[i] for i in idxs]
Trim ImageTable to keep only the passed studies. This is a
        convenience method, and should generally be avoided in favor of
        non-destructive alternatives that don't require slicing (e.g.,
            matrix multiplication).