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トップネットワークに関する質問重み付き隣接行列の作り方

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回答編集履歴

4

修正

2020/07/19 14:48

投稿

tiitoi
tiitoi

スコア21956

test CHANGED
@@ -18,7 +18,9 @@
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- n_nodes = df[["node_1", "node_2"]].values.ravel().max() + 1
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+ name_to_node = {name: i for i, name in enumerate(np.unique(df[["node_1", "node_2"]].values))}
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+
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+ n_nodes = len(name_to_node)
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  A = np.zeros((n_nodes, n_nodes))
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@@ -26,7 +28,13 @@
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28
 
27
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  for row in df.itertuples():
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30
 
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+ n1 = name_to_node[row.node_1]
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+
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+ n2 = name_to_node[row.node_2]
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+
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- A[row.node_1, row.node_2] += row.weight
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+ A[n1, n2] += row.weight
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+
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+ A[n2, n1] += row.weight
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32
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@@ -38,22 +46,22 @@
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  ```
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- [[ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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- [ 0. 0. 0. 0. 35. 30. 30. 0. 0.]
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- [ 0. 0. 0. 0. 0. 0. 0. 20. 0.]
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+ [[ 0. 0. 0. 35. 30. 30. 0. 0.]
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- [ 0. 0. 0. 0. 0. 0. 0. 0. 15.]
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+ [ 0. 0. 0. 0. 0. 0. 20. 0.]
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- [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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+ [ 0. 0. 0. 0. 0. 0. 0. 15.]
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- [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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+ [35. 0. 0. 0. 0. 0. 0. 0.]
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- [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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+ [30. 0. 0. 0. 0. 0. 0. 0.]
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- [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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+ [30. 0. 0. 0. 0. 0. 0. 0.]
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+ [ 0. 20. 0. 0. 0. 0. 0. 0.]
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+
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- [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]]
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+ [ 0. 0. 15. 0. 0. 0. 0. 0.]]
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  ```

3

修正

2020/07/19 14:48

投稿

tiitoi
tiitoi

スコア21956

test CHANGED
@@ -28,8 +28,6 @@
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  A[row.node_1, row.node_2] += row.weight
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- A[row.node_2, row.node_1] += row.weight
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-
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34
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  print(A)
@@ -48,14 +46,14 @@
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  [ 0. 0. 0. 0. 0. 0. 0. 0. 15.]
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48
 
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- [ 0. 35. 0. 0. 0. 0. 0. 0. 0.]
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+ [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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- [ 0. 30. 0. 0. 0. 0. 0. 0. 0.]
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+ [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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- [ 0. 30. 0. 0. 0. 0. 0. 0. 0.]
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+ [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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- [ 0. 0. 20. 0. 0. 0. 0. 0. 0.]
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+ [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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- [ 0. 0. 0. 15. 0. 0. 0. 0. 0.]]
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+ [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]]
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  ```

2

修正

2020/07/19 14:27

投稿

tiitoi
tiitoi

スコア21956

test CHANGED
@@ -28,26 +28,34 @@
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  A[row.node_1, row.node_2] += row.weight
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+ A[row.node_2, row.node_1] += row.weight
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+
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  print(A)
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- # [[ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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+ ```
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- # [ 0. 0. 0. 0. 35. 30. 30. 0. 0.]
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- # [ 0. 0. 0. 0. 0. 0. 0. 20. 0.]
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-
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- # [ 0. 0. 0. 0. 0. 0. 0. 0. 15.]
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-
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- # [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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-
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- # [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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-
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- # [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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-
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- # [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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-
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- # [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]]
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40
 
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  ```
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+
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+ [[ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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+
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+ [ 0. 0. 0. 0. 35. 30. 30. 0. 0.]
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+
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+ [ 0. 0. 0. 0. 0. 0. 0. 20. 0.]
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+
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+ [ 0. 0. 0. 0. 0. 0. 0. 0. 15.]
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+
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+ [ 0. 35. 0. 0. 0. 0. 0. 0. 0.]
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+
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+ [ 0. 30. 0. 0. 0. 0. 0. 0. 0.]
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+
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+ [ 0. 30. 0. 0. 0. 0. 0. 0. 0.]
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+
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+ [ 0. 0. 20. 0. 0. 0. 0. 0. 0.]
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+
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+ [ 0. 0. 0. 15. 0. 0. 0. 0. 0.]]
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+
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+ ```

1

修正

2020/07/19 14:27

投稿

tiitoi
tiitoi

スコア21956

test CHANGED
@@ -18,9 +18,9 @@
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- n_nodes = df[["node_1", "node_2"]].values.ravel().max()
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+ n_nodes = df[["node_1", "node_2"]].values.ravel().max() + 1
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- A = np.zeros((n_nodes + 1, n_nodes + 1))
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+ A = np.zeros((n_nodes, n_nodes))
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