Returns a dictionary with the keys `data` and `fit`.

        `data` is just `scipy_data_fitting.Data.array`.

        `fit` is a two row [`numpy.ndarray`][1], the first row values correspond
        to the independent variable and are generated using [`numpy.linspace`][2].
        The second row are the values of `scipy_data_fitting.Fit.fitted_function`
        evaluated on the linspace.

        For both `fit` and `data`, each row will be scaled by the corresponding
        inverse prefix if given in `scipy_data_fitting.Fit.independent`
        or `scipy_data_fitting.Fit.dependent`.

        Any keyword arguments are passed to [`numpy.linspace`][2].

        [1]: http://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.html
        [2]: http://docs.scipy.org/doc/numpy/reference/generated/numpy.linspace.html

def pointspace(self, **kwargs):
        """
        Returns a dictionary with the keys `data` and `fit`.

        `data` is just `scipy_data_fitting.Data.array`.

        `fit` is a two row [`numpy.ndarray`][1], the first row values correspond
        to the independent variable and are generated using [`numpy.linspace`][2].
        The second row are the values of `scipy_data_fitting.Fit.fitted_function`
        evaluated on the linspace.

        For both `fit` and `data`, each row will be scaled by the corresponding
        inverse prefix if given in `scipy_data_fitting.Fit.independent`
        or `scipy_data_fitting.Fit.dependent`.

        Any keyword arguments are passed to [`numpy.linspace`][2].

        [1]: http://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.html
        [2]: http://docs.scipy.org/doc/numpy/reference/generated/numpy.linspace.html
        """
        scale_array = numpy.array([
            [prefix_factor(self.independent)**(-1)],
            [prefix_factor(self.dependent)**(-1)]
        ])

        linspace = numpy.linspace(self.limits[0], self.limits[1], **kwargs)
        return {
          'data': self.data.array * scale_array,
          'fit': numpy.array([linspace, self.fitted_function(linspace)]) * scale_array
        }