d7b2db3c5262c82c44958afc2500efe0838f0884,osmnx/utils_graph.py,,_update_edge_keys,#,536

Before Change


    // for each set of duplicate edges
    for _, group in groups:

        if len(group) > 2:
            // if there are more than 2 edges here, make sure to compare all
            li = group["geometry"].tolist()
            li.append(li[0])
            geom_pairs = list(zip(li[:-1], li[1:]))
        else:
            // otherwise, just compare the first edge to the second edge
            geom_pairs = [(group["geometry"].iloc[0], group["geometry"].iloc[1])]

        // for each pair of edges to compare
        for geom1, geom2 in geom_pairs:
            // if they don"t have the same geometry, flag them as different streets
            if not _is_same_geometry(geom1, geom2):
                // add edge uvk, but not edge vuk, otherwise we"ll iterate both their keys

After Change


                different_streets.append(group.index[0])

    // for each unique different street, give it a unique key
    set_different_streets = set(different_streets)
    utils.log(f"Found {len(set_different_streets)} different streets")
    for u, v, k in set(different_streets):
        new_key = max(list(G[u][v]) + list(G[v][u])) + 1
        G.add_edge(u, v, key=new_key, **G.get_edge_data(u, v, k))
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 4

Instances


Project Name: gboeing/osmnx
Commit Name: d7b2db3c5262c82c44958afc2500efe0838f0884
Time: 2020-12-02
Author: boeing@usc.edu
File Name: osmnx/utils_graph.py
Class Name:
Method Name: _update_edge_keys


Project Name: AlexEMG/DeepLabCut
Commit Name: 0ef2bfb1adda578c45e9c56412f86c02b950c0a3
Time: 2020-06-18
Author: saveliy.m.yusufov@gmail.com
File Name: deeplabcut/utils/make_labeled_video.py
Class Name:
Method Name: CreateVideoSlow


Project Name: commonsense/conceptnet5
Commit Name: 79d149dd39dc7e7d22c623c0a4a4d3ab99e61c76
Time: 2017-06-15
Author: joanna.teresa.duda@gmail.com
File Name: conceptnet5/vectors/transforms.py
Class Name:
Method Name: choose_small_vocabulary