def far_interaction_same_kitchen_visually_dissimilar()

in build_graph/localization_network/dataset.py [0:0]

• 19 lines of code
• 10 McCabe index (conditional complexity)

    def far_interaction_same_kitchen_visually_dissimilar(self, indexA, T, pdist, threshold):
        entryA = self.data[indexA]
        candidates = [entry for entry in self.data if entryA['v_id'].split('_')[0] in entry['v_id']]
        indexA_new = [idx for idx in range(len(candidates)) if candidates[idx]['uid']==entryA['uid']][0] 
        if len(candidates)<2*T+2:
            # print ('Not enough candidates: OOPS')
            return self.far_interaction(indexA, T)

        uidxA = pdist['uid_to_idx'][self.data[indexA]['uid']]
        timeout = 100
        for t in range(timeout):
            indexB = self.get_far_idx(indexA_new, T, len(candidates))
            uidxB = pdist['uid_to_idx'][self.data[indexB]['uid']]
            if pdist['pdist'][uidxA, uidxB] == 0 or pdist['pdist'][uidxA, uidxB]>threshold:
                break
        if t==timeout-1:
            # print ('Timeout: OOPS')
            return self.far_interaction(indexA, T)

        entryB = candidates[indexB]
        frameB = self.rs.randint(0, len(entryB['frames']))
        frameB = entryB['frames'][frameB]
        return frameB, f'T: {pdist["pdist"][uidxA, uidxB]:3f}'