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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def find_surface_sites_by_height(self, slab, height=0.9, xy_tol=0.05):
 """ This method finds surface sites by determining which sites are within a threshold value in height from the topmost site in a list of sites Args: site_list (list):
 list of sites from which to select surface sites height (float):
 threshold in angstroms of distance from topmost site in slab along the slab c-vector to include in surface site determination xy_tol (float):
 if supplied, will remove any sites which are within a certain distance in the miller plane. Returns: list of sites selected to be within a threshold of the highest """


        # Get projection of coordinates along the miller index
        m_projs = np.array([np.dot(site.coords, self.mvec)
                            for site in slab.sites])

        # Mask based on window threshold along the miller index.
        mask = (m_projs - np.amax(m_projs)) >= -height
        surf_sites = [slab.sites[n] for n in np.where(mask)[0]]
        if xy_tol:
            # sort surface sites by height
            surf_sites = [s for (h, s) in zip(m_projs[mask], surf_sites)]
            surf_sites.reverse()
            unique_sites, unique_perp_fracs = [], []
            for site in surf_sites:
                this_perp = site.coords - np.dot(site.coords, self.mvec)
                this_perp_frac = slab.lattice.get_fractional_coords(this_perp)
                if not in_coord_list_pbc(unique_perp_fracs, this_perp_frac):
                    unique_sites.append(site)
                    unique_perp_fracs.append(this_perp_frac)
            surf_sites = unique_sites

        return surf_sites