回答編集履歴
2
修正
answer
CHANGED
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@@ -13,6 +13,9 @@
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# (6, 1) x (1, 6)
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c = a.reshape(-1, 1) @ b.reshape(1, -1)
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16
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# c = a[:, np.newaxis] @ b[np.newaxis] でも同じ
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print(c)
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# [[ 100 200 300]
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# [ 200 400 600]
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1
修正
answer
CHANGED
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@@ -20,4 +20,39 @@
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# [ 400 800 1200]
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# [ 500 1000 1500]
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# [ 600 1200 1800]]
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-
```
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```
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## `a.reshape(-1, 1) * b.reshape(1, -1)` で同じ結果が計算できた理由
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```python
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[[1]
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[2]
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[3]
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[4]
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[5]
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[6]]
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```
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と
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```python
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[[100 200 300]]
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```
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39
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を演算しようとしたときにブロードキャストされて、
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40
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```python
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[[1, 1, 1],
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[2, 2, 2],
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[3, 3, 3],
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[4, 4, 4],
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[5, 5, 5],
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[6, 6, 6]]
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```
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と
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```python
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array([[100, 200, 300],
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[100, 200, 300],
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[100, 200, 300],
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[100, 200, 300],
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[100, 200, 300],
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[100, 200, 300]])
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```
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58
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の要素同士の積になって、たまたま行列積と同じ結果になりました。
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