code: def _check_validity_of_inputs(data, input_arg, input_name, grid_plot, dimension):
      
      if input_arg is not None:
          if grid_plot is True:
              if isinstance(input_arg, list):
                  if numpy.shape(input_arg)[:dimension] != numpy.shape(data)[:dimension]:
                      raise RuntimeError("The shape of " + input_name + " does not match with data "
                                         "input.")
  
              else:
                  raise RuntimeError("The specified data type of " + input_name +
                                     " field is not valid. Input must be a list.")
          else:
              if not isinstance(input_arg, str):
                  raise RuntimeError("Taking into account that only one time-series had been "
                                     "specified at 'data', the " + input_name + " field must be a "
                                     "string")
      elif grid_plot is True:
          input_arg = numpy.ndarray(shape=numpy.shape(data)[:dimension], dtype=numpy.object)
  
      return input_arg
docs: Function that verifies when an input ('input_arg') of function 'plot' has a valid structure.
  
      ----------
      Parameters
      ----------
      data : list or list of lists
          Structure with the data that will be plotted.
  
      input_arg : list or list of lists
          The input data to be verified.
  
      input_name : str
          Name of the input_arg variable.
  
      grid_plot : bool
          A flag that identifies when the input_arg is a matrix or not.
  
      dimension : int
          Level of verification in the matrix format structure.
  
      Returns
      -------
      out : list or list of lists
          Returns the same value as input_arg or a modified version.