(self, dimension)
return np.array(intervals_result)
This function returns the persistence intervals of the complex in a
        specific dimension.
        :param dimension: The specific dimension.
        :type dimension: int.
        :returns: The persistence intervals.
        :rtype:  numpy array of dimension 2
        :note: intervals_in_dim function requires persistence function to be
            launched first.
This function returns the persistence intervals of the complex in a
        specific dimension.
        :param dimension: The specific dimension.
        :type dimension: int.
        :returns: The persistence intervals.
        :rtype:  numpy array of dimension 2
        :note: intervals_in_dim function requires persistence function to be
            launched first.
This function returns the persistence intervals of the complex in a specific dimension . : param dimension : The specific dimension . : type dimension : int . : returns : The persistence intervals . : rtype : numpy array of dimension 2 : note : intervals_in_dim function requires persistence function to be launched first .
def persistence_intervals_in_dimension(self, dimension):
        """This function returns the persistence intervals of the complex in a
        specific dimension.
        :param dimension: The specific dimension.
        :type dimension: int.
        :returns: The persistence intervals.
        :rtype:  numpy array of dimension 2
        :note: intervals_in_dim function requires persistence function to be
            launched first.
        """
        intervals_result = []
        if self.pcohptr is not None:
            intervals_result = self.pcohptr.intervals_in_dimension(dimension)
        else:
            print("intervals_in_dim function requires persistence function"
                  " to be launched first.")
        return np.array(intervals_result)
def persistence_intervals_in_dimension ( self , dimension ) : intervals_result = [ ] if self . pcohptr is not None : intervals_result = self . pcohptr . intervals_in_dimension ( dimension ) else : print ( "intervals_in_dim function requires persistence function" " to be launched first." ) return np . array ( intervals_result )