Map samples defined in input file to pipelines to run.

def _pair_samples_with_pipelines(run_info_yaml, config):
    """Map samples defined in input file to pipelines to run.
    """
    samples = config_utils.load_config(run_info_yaml)
    if isinstance(samples, dict):
        resources = samples.pop("resources")
        samples = samples["details"]
    else:
        resources = {}
    ready_samples = []
    for sample in samples:
        if "files" in sample:
            del sample["files"]
        # add any resources to this item to recalculate global configuration
        usample = copy.deepcopy(sample)
        usample.pop("algorithm", None)
        if "resources" not in usample:
            usample["resources"] = {}
        for prog, pkvs in resources.items():
            if prog not in usample["resources"]:
                usample["resources"][prog] = {}
            if pkvs is not None:
                for key, val in pkvs.items():
                    usample["resources"][prog][key] = val
        config = config_utils.update_w_custom(config, usample)
        sample["resources"] = {}
        ready_samples.append(sample)
    paired = [(x, _get_pipeline(x)) for x in ready_samples]
    d = defaultdict(list)
    for x in paired:
        d[x[1]].append([x[0]])
    return d, config