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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11
1.3 遺伝子発現データセットの探索
すべての
(i, j)
で、
outer[i, j] = x[i] * y[j]
であることがおわかりいただけると思います。
上の結果は、
NumPy
のブロードキャスティングのルール（
http://bit.ly/2sFpZ3H
）により達成
されました。一方の配列で大きさが
1
である次元は、もう一方の配列の対応する次元の大きさと
一致するように非明示的に拡張されるのです。このルールについてはのちほど詳しく解説しますの
で、心配無用です。
本章の後半で本物のデータを試してみればよくわかりますが、ブロードキャスティングは、実際
に使われているデータ配列の数値計算にとって大変重要なものです。これにより、複雑な演算を簡
潔に効率よく表現することが可能になります。
1.3
遺伝子発現データセットの探索
ここでは、がんゲノムアトラス（
TCGA
）プロジェクト（
http://cancergenome.nih.gov
）の皮
膚がん標本を使った
RNA
シーケンシング実験のデータセットを使用します。データはクリーニン
グとソートを適用済みなので、本書のリポジトリにある
data/counts.txt
をそのまま使えます。
「
2
章
NumPy
と
SciPy
を用いた分位数正規化」では、この遺伝子発現データを使って皮膚が
ん患者の死亡率を予測し、
TCGA
コンソーシアムの論文（
http://bit.ly/2sFAwfa
）の図
5A
と
5B
（
http://bit.ly/2sFCegE
）の簡易版を再現してみましょう。その前に、データのバイアスを吟味し ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.