neurosynth/base/dataset.py
def create_image_table(self, r=None):
        """ Create and store a new ImageTable instance based on the current
        Dataset. Will generally be called privately, but may be useful as a
        convenience method in cases where the user wants to re-generate the
        table with a new smoothing kernel of different radius.

        Args:
            r (int): An optional integer indicating the radius of the smoothing
                kernel. By default, this is None, which will keep whatever
                value is currently set in the Dataset instance.
        """
        logger.info("Creating image table...")
        if r is not None:
            self.r = r
        self.image_table = ImageTable(self)
def create_image_table(self, r=None):
        logger.info("Creating image table...")
        if r is not None:
            self.r = r
        self.image_table = ImageTable(self)
def create_image_table ( self , r = None ) : logger . info ( "Creating image table..." ) if r is not None : self . r = r self . image_table = ImageTable ( self )
Create and store a new ImageTable instance based on the current
        Dataset. Will generally be called privately, but may be useful as a
        convenience method in cases where the user wants to re-generate the
        table with a new smoothing kernel of different radius.

        Args:
            r (int): An optional integer indicating the radius of the smoothing
                kernel. By default, this is None, which will keep whatever
                value is currently set in the Dataset instance.
Create and store a new ImageTable instance based on the current Dataset . Will generally be called privately but may be useful as a convenience method in cases where the user wants to re - generate the table with a new smoothing kernel of different radius .