Return x,y values evaluated with a given pixel step.

        The returned values are computed within the corresponding
        bounding box of the line.

        Parameters
        ----------
        start : float
            Minimum pixel coordinate to evaluate the independent
            variable.
        stop : float
            Maximum pixel coordinate to evaluate the independent
            variable.
        pixel_step : float
            Pixel step employed to evaluate the independent variable.
        y_vs_x : bool
            If True, the polynomial fit is assumed to be Y vs X.
            Otherwise, X vs Y is employed.

        Returns
        -------
        x : 1d numpy array
            X coordinates.
        y : 1d numpy array
            Y coordinates.

def linspace_pix(self, start=None, stop=None, pixel_step=1, y_vs_x=None):
        """Return x,y values evaluated with a given pixel step.

        The returned values are computed within the corresponding
        bounding box of the line.

        Parameters
        ----------
        start : float
            Minimum pixel coordinate to evaluate the independent
            variable.
        stop : float
            Maximum pixel coordinate to evaluate the independent
            variable.
        pixel_step : float
            Pixel step employed to evaluate the independent variable.
        y_vs_x : bool
            If True, the polynomial fit is assumed to be Y vs X.
            Otherwise, X vs Y is employed.

        Returns
        -------
        x : 1d numpy array
            X coordinates.
        y : 1d numpy array
            Y coordinates.
        """

        if y_vs_x:
            if start is None:
                xmin = self.bb_nc1_orig
            else:
                xmin = start
            if stop is None:
                xmax = self.bb_nc2_orig
            else:
                xmax = stop
            num = int(float(xmax-xmin+1)/float(pixel_step)+0.5)
            x = np.linspace(start=xmin, stop=xmax, num=num)
            y = self.poly_funct(x)
        else:
            if start is None:
                ymin = self.bb_ns1_orig
            else:
                ymin = start
            if stop is None:
                ymax = self.bb_ns2_orig
            else:
                ymax = stop
            num = int(float(ymax-ymin+1)/float(pixel_step)+0.5)
            y = np.linspace(start=ymin, stop=ymax, num=num)
            x = self.poly_funct(y)

        return x, y