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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 @@
18
18
 
19
19
 
20
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21
- 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)
22
24
 
23
25
  A = np.zeros((n_nodes, n_nodes))
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26
 
@@ -26,7 +28,13 @@
26
28
 
27
29
  for row in df.itertuples():
28
30
 
31
+ 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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+
29
- A[row.node_1, row.node_2] += row.weight
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+ A[n1, n2] += row.weight
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+
37
+ A[n2, n1] += row.weight
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31
39
 
32
40
 
@@ -38,22 +46,22 @@
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46
 
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  ```
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48
 
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- [[ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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49
 
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- [ 0. 0. 0. 0. 35. 30. 30. 0. 0.]
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50
 
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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.]
46
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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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54
 
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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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56
 
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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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60
 
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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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66
 
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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 @@
28
28
 
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  A[row.node_1, row.node_2] += row.weight
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30
 
31
- A[row.node_2, row.node_1] += row.weight
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-
33
31
 
34
32
 
35
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  print(A)
@@ -48,14 +46,14 @@
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46
 
49
47
  [ 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.]
52
50
 
53
- [ 0. 30. 0. 0. 0. 0. 0. 0. 0.]
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+ [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
54
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55
- [ 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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54
 
57
- [ 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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56
 
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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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58
 
61
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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 @@
28
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29
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  A[row.node_1, row.node_2] += row.weight
30
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31
+ A[row.node_2, row.node_1] += row.weight
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+
31
33
 
32
34
 
33
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  print(A)
34
36
 
35
- # [[ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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+ ```
36
38
 
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- # [ 0. 0. 0. 0. 35. 30. 30. 0. 0.]
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39
 
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- # [ 0. 0. 0. 0. 0. 0. 0. 20. 0.]
40
-
41
- # [ 0. 0. 0. 0. 0. 0. 0. 0. 15.]
42
-
43
- # [ 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.]
46
-
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- # [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
48
-
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- # [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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-
51
- # [ 0. 0. 0. 0. 0. 0. 0. 0. 0.]]
52
40
 
53
41
  ```
42
+
43
+ [[ 0. 0. 0. 0. 0. 0. 0. 0. 0.]
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+
45
+ [ 0. 0. 0. 0. 35. 30. 30. 0. 0.]
46
+
47
+ [ 0. 0. 0. 0. 0. 0. 0. 20. 0.]
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+
49
+ [ 0. 0. 0. 0. 0. 0. 0. 0. 15.]
50
+
51
+ [ 0. 35. 0. 0. 0. 0. 0. 0. 0.]
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+
53
+ [ 0. 30. 0. 0. 0. 0. 0. 0. 0.]
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+
55
+ [ 0. 30. 0. 0. 0. 0. 0. 0. 0.]
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+
57
+ [ 0. 0. 20. 0. 0. 0. 0. 0. 0.]
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+
59
+ [ 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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19
19
 
20
20
 
21
- 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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22
 
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- A = np.zeros((n_nodes + 1, n_nodes + 1))
23
+ A = np.zeros((n_nodes, n_nodes))
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24
 
25
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