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NumPyで配列プログラミング
Charles R Harris1, K Jarrod Millman2,3,4, Stéfan J van der Walt5,6,7
1Independent researcher, Logan, UT, USA.
Nature
|September 17, 2020
まとめ
配列プログラミングのための基本的な Python ライブラリである NumPy は,様々な分野における科学的データ分析のための強力なパラダイムを提供します. その広範な採用と相互運用能力が 科学的・産業的な計算の未来を形作っています
科学分野:
- 科学的コンピューティング
- データ分析
- Python プログラミング
背景:
- データ操作のコンパクトな構文を提供します.
- NumPyはPythonの主要な配列プログラミングライブラリです.
- それは様々な科学分野の研究に不可欠です.
研究 の 目的:
- 科学的なデータ分析のための基本的な配列の概念を見直す.
- 科学的なPythonのエコシステムにおける NumPyの基本的役割を強調する.
- NumPyの相互運用性層としての機能について説明します.
主な方法:
- 配列プログラミングのコンセプトのレビュー
- NumPyの科学研究における役割と影響の検討
- NumPyのAPIと将来のアプリケーションのためのその枠組みの分析.
主要な成果:
- NumPyは強力でコンパクトで表現的なデータ操作を可能にします.
- 物理学,天文学,生物学の研究パイプラインに不可欠です.
- NumPyは,さまざまな配列計算ライブラリ間の相互運用を容易にする.
結論:
- NumPyの配列プログラミングパラダイムは 科学的なデータ探査と分析を簡素化します
- サイエンティフィック・パイソン・エコシステムの 基礎となるものです
- NumPyは将来の科学および産業分析のための柔軟な枠組みを提供します.
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