class_docstr: Unit tests for the
  :func:`~networkx.algorithms.matching.max_weight_matching` function.
docstr: Create S-blossom, relabel as T-blossom, use for augmentation:
docstr_tok: ["Create","S-blossom",",","relabel","as","T-blossom",",","use","for","augmentation",":"]
code: def test_s_t_blossom(self):
      """Create S-blossom, relabel as T-blossom, use for augmentation:"""
      G = nx.Graph()
      G.add_weighted_edges_from(
          [
              (1, 2, 9),
              (1, 3, 8),
              (2, 3, 10),
              (1, 4, 5),
              (4, 5, 4),
              (1, 6, 3),
          ]
      )
      answer = matching_dict_to_set(
          {1: 6, 2: 3, 3: 2, 4: 5, 5: 4, 6: 1}
      )
      assert edges_equal(nx.max_weight_matching(G), answer)
      assert edges_equal(nx.min_weight_matching(G), answer)
  
      G.add_edge(4, 5, weight=3)
      G.add_edge(1, 6, weight=4)
      assert edges_equal(nx.max_weight_matching(G), answer)
      assert edges_equal(nx.min_weight_matching(G), answer)
  
      G.remove_edge(1, 6)
      G.add_edge(3, 6, weight=4)
      answer = matching_dict_to_set(
          {1: 2, 2: 1, 3: 6, 4: 5, 5: 4, 6: 3}
      )
      assert edges_equal(nx.max_weight_matching(G), answer)
      assert edges_equal(nx.min_weight_matching(G), answer)
  
imports: import math
  from itertools import permutations
  from pytest import raises
  import networkx
  from networkx.algorithms.matching import matching_dict_to_set
  from networkx.utils import edges_equal
label_desc: Use image node_id 11 for calling the TestMaxWeightMatching obj's underlying member method code with example usage: obj.test_s_t_blossom() without return types