November 2018
Intermediate to advanced
272 pages
6h 51m
Japanese
book
エレガントなSciPy ―Pythonによる科学技術計算
by Juan Nunez-Iglesias, Stéfan van der Walt, Harriet Dashnow, 山崎 邦子, 山崎 康宏
Content preview from エレガントなSciPy ―Pythonによる科学技術計算
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220
付録 演習の解答
A.11
解答：必要なメモリ容量を減らす
以下は「
5.4.1
演習：必要なメモリ容量を減らす」の解答です。
作成する
np.ones
配列は読み出し専用です。
coo_matrix
が和を取る値としてのみ使われます。
broadcast_to
を使えば、要素が
1
つだけの類似した配列を「仮想的に」
n
回反復したものを作成
できます。
def confusion_matrix(pred, gt):
n = pred.size
ones = np.broadcast_to(1., n) # virtual array of 1s of size n
値が
1
でサイズが
n
の仮想配列
cont = sparse.coo_matrix((ones, (pred, gt)))
return cont
予想通りに動作するか、確認してみましょう。
cont = confusion_matrix(pred, gt)
print(cont.toarray())
図
A-4
図
5-1
を原点を中心に回転
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