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IMSL Python Numerical Library (PyNL) 提供數學和統計功能，用于在 Python 中構建各種應用程序。PyNL建立在 IMSL C Numerical Library之上，為 Python 環境帶來了 40 多年的數值知識、嚴格的測試和本機性能。
IMSL Python Library具有用于各種應用的可嵌入數學和統計算法，包括：飛機飛行動力學建模、天氣預報、人類基因組的創新研究、股票市場行為預測和投資組合優化。
PyNL 是針對各種開發環境的一系列數值庫中的一員。PyNL 專門針對 Python (CPython) 的 C 實現。對于 Cython 項目，建議使用IMSL Library for C。對于 Jython，我們建議使用IMSL Library for Java。
IMSL Python Library特點
IMSL Library，包括 IMSL Python Library，被認為是當今的主流編程環境中可用于數值分析的復雜、靈活、可擴展和高度可訪問的技術。
可訪問、直觀、一致
IMSL Python Library具有描述性和一致的函數名稱，對于開發人員和數據科學家來說都是可訪問且直觀的。
降低開發成本
使用經過驗證的 IMSL 算法和功能，在設計、開發、文檔編制、測試和維護方面節省時間和金錢。
高性能和可擴展
IMSL Python Library支持多線程進程和經過全面測試的函數和算法，已為高性能做好準備。
清除診斷錯誤消息
通過提供信息豐富且清晰的錯誤消息，開發人員可以快速著手解決問題，而不需要浪費時間找問題。
【英文介紹】
The IMSL Python Numerical Library (PyNL) provides mathematical and statistical functionality for building advanced a wide range of applications in Python. Built on the IMSL C Numerical Library, PyNL brings over 40 years of numerical expertise, rigorous testing, and native performance to the Python environment.
The IMSL Python Library features advanced embeddable mathematical and statistical algorithms used across a wide variety of applications, including: modeling airplane flight dynamics, weather prediction, innovative study of the human genome, stock market behavior forecasts, and investment portfolio optimization.
The IMSL Library for Python is a library of Python functions useful for programming in a wide range of applications ranging from scientific, to engineering, to business.
IMSL Python Library Key Features
The IMSL Libraries, including the IMSL Python Library, are regarded as the most sophisticated, flexible, scalable and highly accessible technology available for numerical analysis in the most important mainstream programming environments in use today.
Accessible, Intuitive, Consistent
With descriptive and consistent function names, the IMSL Python Library is accessible and intuitive for developers and data scientists alike.
Reduce Development Costs
Save time and money on design, development, documentation, testing, and maintenance with proven IMSL algorithms and functions.
Performant and Scalable
With support for multi-thread processes and thoroughly tested functions and algorithms, the IMSL Python Library is high performance ready.
Clear Diagnostic Error Messaging
With informative and clear error messaging, developers can quickly get to work on fixing the issue instead of trying to find it.
