Python utool.flatten函数代码示例

 def get_column_keys(metadata):
     unflat_colname_list = [
         [cols.keys() for cols in qaid2_cols.values()]
         for qaid2_cols in six.itervalues(metadata.dictstore)
     ]
     colname_list = ut.unique_keep_order(ut.flatten(ut.flatten(unflat_colname_list)))
     return colname_list

def delete_contributors(ibs, contrib_rowid_list):
    r"""
    deletes contributors from the database and all information associated

    RESTful:
        Method: DELETE
        URL:    /api/contributor/
    """
    # TODO: FIXME TESTME
    if not ut.QUIET:
        print('[ibs] deleting %d contributors' % len(contrib_rowid_list))

    config_rowid_list = ut.flatten(ibs.get_contributor_config_rowids(contrib_rowid_list))
    # Delete configs (UNSURE IF THIS IS CORRECT)
    ibs.delete_configs(config_rowid_list)
    # CONTRIBUTORS SHOULD NOT DELETE IMAGES
    # Delete encounters
    #eid_list = ibs.get_valid_eids()
    #eid_config_list = ibs.get_encounter_configid(eid_list)
    #valid_list = [config in config_rowid_list for config in eid_config_list ]
    #eid_list = ut.compress(eid_list, valid_list)
    #ibs.delete_encounters(eid_list)
    # Remote image contributors ~~~Delete images~~~~
    gid_list = ut.flatten(ibs.get_contributor_gids(contrib_rowid_list))
    ibs.set_image_contributor_rowid(gid_list, [None] * len(gid_list))
    #ibs.delete_images(gid_list)
    # Delete contributors
    ibs.db.delete_rowids(const.CONTRIBUTOR_TABLE, contrib_rowid_list)

def get_varied_acfg_labels(acfg_list, mainkey='_cfgname', checkname=False):
    """
        >>> from ibeis.expt.annotation_configs import *  # NOQA

    """
    #print(ut.list_str(varied_acfg_list, nl=2))
    for acfg in acfg_list:
        assert acfg['qcfg'][mainkey] == acfg['dcfg'][mainkey], (
            'should be the same for now')
    cfgname_list = [acfg['qcfg'][mainkey] for acfg in acfg_list]
    if checkname and ut.allsame(cfgname_list):
        cfgname_list = [None] * len(cfgname_list)

    # Hack to make common params between q and d appear the same
    _acfg_list = [compress_aidcfg(acfg) for acfg in acfg_list]

    flat_acfg_list = flatten_acfg_list(_acfg_list)
    nonvaried_dict, varied_acfg_list = ut.partition_varied_cfg_list(
        flat_acfg_list)

    SUPER_HACK = True
    if SUPER_HACK:
        # SUPER HACK, recompress remake the varied list after knowing what is varied
        _varied_keys = list(set(ut.flatten(
            [list(ut.flatten(
                [list(x.keys())
                 for x in unflatten_acfgdict(cfg).values()]
            )) for cfg in varied_acfg_list]
        )))
        _acfg_list = [
            compress_aidcfg(acfg, force_noncommon=_varied_keys)
            for acfg in acfg_list]
        flat_acfg_list = flatten_acfg_list(_acfg_list)
        nonvaried_dict, varied_acfg_list = ut.partition_varied_cfg_list(
            flat_acfg_list)

    shortened_cfg_list = [
        #{shorten_to_alias_labels(key): val for key, val in _dict.items()}
        ut.map_dict_keys(shorten_to_alias_labels, _dict)
        for _dict in varied_acfg_list]
    nonlbl_keys = ut.INTERNAL_CFGKEYS
    nonlbl_keys = [prefix +  key for key in nonlbl_keys
                   for prefix in ['', 'q', 'd']]
    # hack for sorting by q/d stuff first

    def get_key_order(cfg):
        keys = [k for k in cfg.keys() if k not in nonlbl_keys]
        sortorder = [2 * k.startswith('q') + 1 * k.startswith('d')
                     for k in keys]
        return ut.sortedby(keys, sortorder)[::-1]

    cfglbl_list = [
        ut.get_cfg_lbl(cfg, name, nonlbl_keys, key_order=get_key_order(cfg))
        for cfg, name in zip(shortened_cfg_list, cfgname_list)]

    if checkname:
        cfglbl_list = [x.lstrip(':') for x in cfglbl_list]
    return cfglbl_list

def _build_inverted_descriptor_index(aid_list, desc_list):
    """
    Stacks descriptors into a flat structure and returns inverse mapping from
    flat database descriptor indexes (dx) to annotation ids (aid) and feature
    indexes (fx). Feature indexes are w.r.t. annotation indexes.

    Output:
        dx2_desc - flat descriptor stack
        dx2_aid  - inverted index into annotations
        dx2_fx   - inverted index into features

    # Example with 2D Descriptors
    >>> from ibeis.model.hots.hots_nn_index import *  # NOQA
    >>> from ibeis.model.hots.hots_nn_index import _build_inverted_descriptor_index
    >>> DESC_TYPE = np.uint8
    >>> aid_list  = [1, 2, 3, 4, 5]
    >>> desc_list = [
    ...     np.array([[0, 0], [0, 1]], dtype=DESC_TYPE),
    ...     np.array([[5, 3], [2, 30], [1, 1]], dtype=DESC_TYPE),
    ...     np.empty((0, 2), dtype=DESC_TYPE),
    ...     np.array([[5, 3], [2, 30], [1, 1]], dtype=DESC_TYPE),
    ...     np.array([[3, 3], [42, 42], [2, 6]], dtype=DESC_TYPE),
    ...     ]
    >>> dx2_desc, dx2_aid, dx2_fx = _build_inverted_descriptor_index(aid_list, desc_list)
    >>> print(repr(dx2_desc.T))
    array([[ 0,  0,  5,  2,  1,  5,  2,  1,  3, 42,  2],
           [ 0,  1,  3, 30,  1,  3, 30,  1,  3, 42,  6]], dtype=uint8)
    >>> print(repr(dx2_aid))
    array([1, 1, 2, 2, 2, 4, 4, 4, 5, 5, 5])
    >>> print(repr(dx2_fx))
    array([0, 1, 0, 1, 2, 0, 1, 2, 0, 1, 2])

    cdef:
        list aid_list, desc_list
        long nFeat, aid
        iter aid_nFeat_iter, nFeat_iter, _ax2_aid, _ax2_fx
        np.ndarray dx2_aid, dx2_fx, dx2_desc

    """
    # Build inverted index of (aid, fx) pairs
    aid_nFeat_iter = zip(aid_list, map(len, desc_list))
    nFeat_iter = map(len, desc_list)
    # generate aid inverted index for each feature in each annotation
    _ax2_aid = ([aid] * nFeat for (aid, nFeat) in aid_nFeat_iter)
    # Avi: please test the timing of the lines neighboring this statement.
    #_ax2_aid = ([aid] * nFeat for (aid, nFeat) in aid_nFeat_iter)
    # generate featx inverted index for each feature in each annotation
    _ax2_fx  = (range(nFeat) for nFeat in nFeat_iter)
    # Flatten generators into the inverted index
    #dx2_aid = np.array(list(chain.from_iterable(_ax2_aid)))
    #dx2_fx  = np.array(list(chain.from_iterable(_ax2_fx)))
    dx2_aid = np.array(utool.flatten(_ax2_aid))
    dx2_fx  = np.array(utool.flatten(_ax2_fx))
    # Stack descriptors into numpy array corresponding to inverted inexed
    # This might throw a MemoryError
    dx2_desc = np.vstack(desc_list)
    return dx2_desc, dx2_aid, dx2_fx

def get_varied_params_list(test_cfg_name_list):
    vary_dicts = get_vary_dicts(test_cfg_name_list)
    dict_comb_list = [utool.all_dict_combinations(dict_) for dict_ in vary_dicts]
    dict_comb_lbls = [utool.all_dict_combinations_lbls(dict_) for dict_ in vary_dicts]
    # Append testname
    dict_comb_lbls = [[name_lbl + lbl for lbl in comb_lbls] for name_lbl, comb_lbls in izip(test_cfg_name_list, dict_comb_lbls)]
    varied_params_list = utool.flatten(dict_comb_list)  # [comb for dict_comb in dict_comb_list for comb in dict_comb]
    varied_param_lbls = utool.flatten(dict_comb_lbls)
    return varied_params_list, varied_param_lbls

def test_incremental_add(ibs):
    r"""
    Args:
        ibs (IBEISController):

    CommandLine:
        python -m ibeis.algo.hots._neighbor_experiment --test-test_incremental_add

    Example:
        >>> # DISABLE_DOCTEST
        >>> from ibeis.algo.hots.neighbor_index_cache import *  # NOQA
        >>> import ibeis
        >>> ibs = ibeis.opendb('PZ_MTEST')
        >>> result = test_incremental_add(ibs)
        >>> print(result)
    """
    import ibeis
    sample_aids = ibeis.testdata_aids(a='default:pername=1,mingt=2')
    aids1 = sample_aids[::2]
    aids2 = sample_aids[0:5]
    aids3 = sample_aids[:-1]  # NOQA
    daid_list = aids1  # NOQA
    qreq_ = ibs.new_query_request(aids1, aids1)
    nnindexer1 = neighbor_index_cache.request_ibeis_nnindexer(ibs.new_query_request(aids1, aids1))  # NOQA
    nnindexer2 = neighbor_index_cache.request_ibeis_nnindexer(ibs.new_query_request(aids2, aids2))  # NOQA

    # TODO: SYSTEM use visual uuids
    #daids_hashid = qreq_.ibs.get_annot_hashid_visual_uuid(daid_list)  # get_internal_data_hashid()
    items = ibs.get_annot_visual_uuids(aids3)
    uuid_map_fpath = neighbor_index_cache.get_nnindexer_uuid_map_fpath(qreq_)
    candidate_uuids = neighbor_index_cache.read_uuid_map(uuid_map_fpath, 0)
    candidate_sets = candidate_uuids
    covertup = ut.greedy_max_inden_setcover(candidate_sets, items)
    uncovered_items, covered_items_list, accepted_keys = covertup
    covered_items = ut.flatten(covered_items_list)

    covered_aids = sorted(ibs.get_annot_aids_from_visual_uuid(covered_items))
    uncovered_aids = sorted(ibs.get_annot_aids_from_visual_uuid(uncovered_items))

    nnindexer3 = neighbor_index_cache.request_ibeis_nnindexer(ibs.new_query_request(uncovered_aids, uncovered_aids))  # NOQA

    # TODO: SYSTEM use visual uuids
    #daids_hashid = qreq_.ibs.get_annot_hashid_visual_uuid(daid_list)  # get_internal_data_hashid()
    items = ibs.get_annot_visual_uuids(sample_aids)
    uuid_map_fpath = neighbor_index_cache.get_nnindexer_uuid_map_fpath(qreq_)
    #contextlib.closing(shelve.open(uuid_map_fpath)) as uuid_map:
    candidate_uuids = neighbor_index_cache.read_uuid_map(uuid_map_fpath, 0)
    candidate_sets = candidate_uuids
    covertup = ut.greedy_max_inden_setcover(candidate_sets, items)
    uncovered_items, covered_items_list, accepted_keys = covertup
    covered_items = ut.flatten(covered_items_list)

    covered_aids = sorted(ibs.get_annot_aids_from_visual_uuid(covered_items))  # NOQA
    uncovered_aids = sorted(ibs.get_annot_aids_from_visual_uuid(uncovered_items))

 def __init__(fstack, ibs, aid_list, config=None):
     ax2_vecs = ibs.depc_annot.d.get_feat_vecs(aid_list, config=config)
     fstack.config = config
     fstack.ibs = ibs
     fstack.ax2_aid = aid_list
     fstack.ax2_nFeat = [len(vecs) for vecs in ax2_vecs]
     fstack.idx2_fxs = ut.flatten([list(range(num)) for num in fstack.ax2_nFeat])
     fstack.idx2_axs = ut.flatten([[ax] * num for ax, num in enumerate(fstack.ax2_nFeat)])
     fstack.idx2_vec = np.vstack(ax2_vecs)
     #fstack.idx2_fxs = vt.atleast_nd(fstack.idx2_fxs, 2)
     #fstack.idx2_axs = vt.atleast_nd(fstack.idx2_axs, 2)
     fstack.num_feat = sum(fstack.ax2_nFeat)

    def intersect_hack():
        failed = testres.rank_mat > 0
        colx2_failed = [np.nonzero(failed_col)[0] for failed_col in failed.T]
        #failed_col2_only = np.setdiff1d(colx2_failed[1], colx2_failed[0])
        #failed_col2_only_aids = ut.take(testres.qaids, failed_col2_only)
        failed_col1_only = np.setdiff1d(colx2_failed[0], colx2_failed[1])
        failed_col1_only_aids = ut.take(testres.qaids, failed_col1_only)
        gt_aids1 = ibs.get_annot_groundtruth(failed_col1_only_aids, daid_list=testres.cfgx2_qreq_[0].daids)
        gt_aids2 = ibs.get_annot_groundtruth(failed_col1_only_aids, daid_list=testres.cfgx2_qreq_[1].daids)

        qaids_expt = failed_col1_only_aids
        gt_avl_aids1 = ut.flatten(gt_aids1)
        gt_avl_aids2 = list(set(ut.flatten(gt_aids2)).difference(gt_avl_aids1))

        ibs.print_annotconfig_stats(qaids_expt, gt_avl_aids1)
        ibs.print_annotconfig_stats(qaids_expt, gt_avl_aids2)
        #jsontext = ut.to_json({
        #    'qaids': list(qaids_expt),
        #    'dinclude_aids1': list(gt_aids_expt1),
        #    'dinclude_aids2': list(gt_aids_expt2),
        #})
        #annotation_configs.varysize_pzm
        #from ibeis.expt import annotation_configs

        acfg = testres.acfg_list[0]
        import copy
        acfg1 = copy.deepcopy(acfg)
        acfg2 = copy.deepcopy(acfg)
        acfg1['qcfg']['min_pername'] = None
        acfg2['qcfg']['min_pername'] = None
        acfg1['dcfg']['min_pername'] = None
        acfg2['dcfg']['min_gt_per_name'] = None

        acfg1['qcfg']['default_aids'] = qaids_expt
        acfg1['dcfg']['gt_avl_aids'] = gt_avl_aids1
        acfg2['qcfg']['default_aids'] = qaids_expt
        acfg2['dcfg']['gt_avl_aids'] = gt_avl_aids2

        from ibeis.init import filter_annots
        from ibeis.expt import experiment_helpers

        annots1 = filter_annots.expand_acfgs(ibs, acfg1, verbose=True)
        annots2 = filter_annots.expand_acfgs(ibs, acfg2, verbose=True)

        acfg_name_list = dict(  # NOQA
            acfg_list=[acfg1, acfg2],
            expanded_aids_list=[annots1, annots2],
        )
        test_cfg_name_list = ['candidacy_k']
        cfgdict_list, pipecfg_list = experiment_helpers.get_pipecfg_list(test_cfg_name_list, ibs=ibs)

        t1, t2 = testres_list  # NOQA

 def parse_all_fname_tags(fname):
     _tags = [splitext(fname)[0]]
     _tags = ut.flatten([t.split('_') for t in _tags])
     _tags = ut.flatten([t.split('.') for t in _tags])
     _tags = [t.lower() for t in _tags]
     _tags = [tag_alias_map.get(t, t) for t in _tags]
     for key, vals in regex_alias_map.items():
         pat = ut.regex_or(vals)
         _tags = [key if re.match(pat, t) else t for t in _tags]
     pat = ut.regex_or(invalid_tag_patterns)
     _tags = [t for t in _tags if not re.match(pat, t)]
     _tags = ut.unique_ordered(_tags)
     return _tags

def make_ibeis_matching_graph(ibs, qaid_list, daids_list, scores_list):
    print('make_ibeis_matching_graph')
    aid1_list = ut.flatten([[qaid] * len(daids) for qaid, daids in zip(qaid_list, daids_list)])
    aid2_list = ut.flatten(daids_list)
    unique_aids = list(set(aid2_list + qaid_list))
    score_list = ut.flatten(scores_list)

    # Make a graph between the chips
    nodes = list(zip(unique_aids))
    edges = list(zip(aid1_list, aid2_list, score_list))
    node_lbls = [('aid', 'int')]
    edge_lbls = [('weight', 'float')]
    netx_graph = make_netx_graph(nodes, edges, node_lbls, edge_lbls)
    return netx_graph

def get_name_imgsetids(ibs, nid_list):
    r"""

    RESTful:
        Method: GET
        URL:    /api/name/imgsetids/
    """
    import utool as ut
    name_aids_list = ibs.get_name_aids(nid_list)
    name_aid_list  = ut.flatten(name_aids_list)
    name_gid_list  = ibs.get_annot_gids(name_aid_list)
    name_imgsetids_list = ibs.get_image_imgsetids(name_gid_list)
    name_imgsetid_list  = ut.flatten(name_imgsetids_list)
    name_imgsetids      = list(set(name_imgsetid_list))
    return name_imgsetids

 def unnest_data(data):
     unnested_cols = list(zip(ut.take(data, idxs2)))
     nested_cols = ut.take(data, idxs1)
     grouped_items = [nested_cols, unnested_cols]
     groupxs = [idxs1, idxs2]
     unflat = ut.ungroup(grouped_items, groupxs, nested_nCols - 1)
     return tuple(ut.flatten(unflat))

 def get_set_groundfalse(ibs, qaids):
     # get groundfalse annots relative to the entire set
     valid_nids = ibs.get_valid_nids()
     qnids = ibs.get_annot_nids(qaids)
     nid_list = list(set(valid_nids) - set(qnids))
     aids_list = ibs.get_name_aids(nid_list)
     return ut.flatten(aids_list)

def test_vsone_verified(ibs):
    """
    hack in vsone-reranking

    Example:
        >>> # DISABLE_DOCTEST
        >>> from ibeis.all_imports import *  # NOQA
        >>> #reload_all()
        >>> from ibeis.algo.hots.automated_matcher import *  # NOQA
        >>> import ibeis
        >>> ibs = ibeis.opendb('PZ_MTEST')
        >>> test_vsone_verified(ibs)
    """
    import plottool as pt
    #qaids = ibs.get_easy_annot_rowids()
    nids = ibs.get_valid_nids(filter_empty=True)
    grouped_aids_ = ibs.get_name_aids(nids)
    grouped_aids = list(filter(lambda x: len(x) > 1, grouped_aids_))
    items_list = grouped_aids

    sample_aids = ut.flatten(ut.sample_lists(items_list, num=2, seed=0))
    qaid2_qres, qreq_ = query_vsone_verified(ibs, sample_aids, sample_aids)
    for cm in ut.InteractiveIter(list(six.itervalues(qaid2_qres))):
        pt.close_all_figures()
        fig = cm.ishow_top(ibs)
        fig.show()

def group_review():
    prefill = request.args.get('prefill', '')
    if len(prefill) > 0:
        ibs = current_app.ibs
        aid_list = ibs.get_valid_aids()
        bad_species_list, bad_viewpoint_list = ibs.validate_annot_species_viewpoint_cnn(aid_list)

        GROUP_BY_PREDICTION = True
        if GROUP_BY_PREDICTION:
            grouped_dict = ut.group_items(bad_viewpoint_list, ut.get_list_column(bad_viewpoint_list, 3))
            grouped_list = grouped_dict.values()
            regrouped_items = ut.flatten(ut.sortedby(grouped_list, map(len, grouped_list)))
            candidate_aid_list = ut.get_list_column(regrouped_items, 0)
        else:
            candidate_aid_list = [ bad_viewpoint[0] for bad_viewpoint in bad_viewpoint_list]
    elif request.args.get('aid_list', None) is not None:
        aid_list = request.args.get('aid_list', '')
        if len(aid_list) > 0:
            aid_list = aid_list.replace('[', '')
            aid_list = aid_list.replace(']', '')
            aid_list = aid_list.strip().split(',')
            candidate_aid_list = [ int(aid_.strip()) for aid_ in aid_list ]
        else:
            candidate_aid_list = ''
    else:
        candidate_aid_list = ''

    return appf.template(None, 'group_review', candidate_aid_list=candidate_aid_list, mode_list=appf.VALID_TURK_MODES)