def print_percent_identification_success(testres):
    '\n        Prints names identified (at rank 1) / names queried.\n        This combines results over multiple queries of a particular name using\n        max\n\n        OLD, MAYBE DEPRIATE\n\n        Example:\n            >>> # DISABLE_DOCTEST\n            >>> from wbia.expt.test_result import *  # NOQA\n        '
    ibs = testres.ibs
    qaids = testres.get_test_qaids()
    (unique_nids, groupxs) = ut.group_indices(ibs.get_annot_nids(qaids))
    qx2_gt_raw_score = testres.get_infoprop_mat('qx2_gt_raw_score', qaids=qaids)
    qx2_gf_raw_score = testres.get_infoprop_mat('qx2_gf_raw_score', qaids=qaids)
    nx2_gt_raw_score = np.array([np.nanmax(scores, axis=0) for scores in vt.apply_grouping(qx2_gt_raw_score, groupxs)])
    nx2_gf_raw_score = np.array([np.nanmax(scores, axis=0) for scores in vt.apply_grouping(qx2_gf_raw_score, groupxs)])
    cfgx2_success = (nx2_gt_raw_score > nx2_gf_raw_score).T
    logger.info('Identification success (names identified / names queried)')
    for (cfgx, success) in enumerate(cfgx2_success):
        pipelbl = testres.cfgx2_lbl[cfgx]
        percent = ((100 * success.sum()) / len(success))
        logger.info(('%2d) success = %r/%r = %.2f%% -- %s' % (cfgx, success.sum(), len(success), percent, pipelbl)))
Prints names identified (at rank 1) / names queried.
This combines results over multiple queries of a particular name using
max

OLD, MAYBE DEPRIATE

Example:
    >>> # DISABLE_DOCTEST
    >>> from wbia.expt.test_result import *  # NOQA
def print_percent_identification_success(testres):
    '\n        Prints names identified (at rank 1) / names queried.\n        This combines results over multiple queries of a particular name using\n        max\n\n        OLD, MAYBE DEPRIATE\n\n        Example:\n            >>> # DISABLE_DOCTEST\n            >>> from wbia.expt.test_result import *  # NOQA\n        '
    ibs = testres.ibs
    qaids = testres.get_test_qaids()
    (unique_nids, groupxs) = ut.group_indices(ibs.get_annot_nids(qaids))
    qx2_gt_raw_score = testres.get_infoprop_mat('qx2_gt_raw_score', qaids=qaids)
    qx2_gf_raw_score = testres.get_infoprop_mat('qx2_gf_raw_score', qaids=qaids)
    nx2_gt_raw_score = np.array([np.nanmax(scores, axis=0) for scores in vt.apply_grouping(qx2_gt_raw_score, groupxs)])
    nx2_gf_raw_score = np.array([np.nanmax(scores, axis=0) for scores in vt.apply_grouping(qx2_gf_raw_score, groupxs)])
    cfgx2_success = (nx2_gt_raw_score > nx2_gf_raw_score).T
    logger.info('Identification success (names identified / names queried)')
    for (cfgx, success) in enumerate(cfgx2_success):
        pipelbl = testres.cfgx2_lbl[cfgx]
        percent = ((100 * success.sum()) / len(success))
        logger.info(('%2d) success = %r/%r = %.2f%% -- %s' % (cfgx, success.sum(), len(success), percent, pipelbl)))