@classmethod
def preload_SAM(cls, h5_file, sites, unscale=True, hsds=False, str_decode=
    True, group=None, tech='pv', clearsky=False, means=False):
    """
        Pre-load project_points for SAM

        Parameters
        ----------
        h5_file : str
            h5_file to extract resource from
        sites : list
            List of sites to be provided to SAM
        unscale : bool
            Boolean flag to automatically unscale variables on extraction
        hsds : bool
            Boolean flag to use h5pyd to handle .h5 'files' hosted on AWS
            behind HSDS
        str_decode : bool
            Boolean flag to decode the bytestring meta data into normal
            strings. Setting this to False will speed up the meta data read.
        group : str
            Group within .h5 resource file to open
        tech : str, optional
            Technology to be run by SAM, by default 'pv'
        clearsky : bool
            Boolean flag to pull clearsky instead of real irradiance
        means : bool
            Boolean flag to compute mean resource when res_array is set

        Returns
        -------
        SAM_res : SAMResource
            Instance of SAMResource pre-loaded with Solar resource for sites
            in project_points
        """
    kwargs = {'unscale': unscale, 'hsds': hsds, 'str_decode': str_decode,
        'group': group}
    with cls(h5_file, **kwargs) as res:
        SAM_res = res._preload_SAM(sites, tech=tech, clearsky=clearsky,
            means=means)
    return SAM_res
