Loads error values from `scipy_data_fitting.Data.path` using [`numpy.genfromtxt`][1]
        and returns a two element tuple where each element is of a form described by
        cases 3 and 4 in `scipy_data_fitting.Data.error`.

        The columns to import are set by `scipy_data_fitting.Data.error_columns`.

        Values are scaled according to `scipy_data_fitting.Data.scale`.

        Arguments to [`numpy.genfromtxt`][1] are controlled
        by `scipy_data_fitting.Data.genfromtxt_args_error`.

        [1]: http://docs.scipy.org/doc/numpy/reference/generated/numpy.genfromtxt.html

def load_error(self):
        """
        Loads error values from `scipy_data_fitting.Data.path` using [`numpy.genfromtxt`][1]
        and returns a two element tuple where each element is of a form described by
        cases 3 and 4 in `scipy_data_fitting.Data.error`.

        The columns to import are set by `scipy_data_fitting.Data.error_columns`.

        Values are scaled according to `scipy_data_fitting.Data.scale`.

        Arguments to [`numpy.genfromtxt`][1] are controlled
        by `scipy_data_fitting.Data.genfromtxt_args_error`.

        [1]: http://docs.scipy.org/doc/numpy/reference/generated/numpy.genfromtxt.html
        """
        usecols = []
        for v in self.error_columns:
            if v is None:
                pass
            elif isinstance(v, int):
                usecols.append(v)
            elif len(v) is 2:
                for n in v: usecols.append(n)
        self.genfromtxt_args_error['usecols'] = tuple(usecols)

        array = numpy.genfromtxt(self.path, **self.genfromtxt_args_error)

        error = []
        for n, v in enumerate(self.error_columns):
            if v is None:
                error.append(None)
            elif isinstance(v, int):
                if len(usecols) is 1:
                    error.append(array * self.scale[n])
                else:
                    error.append(array[0] * self.scale[n])
                    array = numpy.delete(array, (0), axis=(0))
            elif len(v) is 2:
                error.append(array[0:2] * self.scale[n])
                array = numpy.delete(array, (0, 1), axis=(0))

        return tuple(error)