IMSL Python Library - 高效、可靠的数值计算库

IMSL Python Numerical Library (PyNL) 提供数学和统计功能，用于在 Python 中构建各种应用程序。PyNL建立在 IMSL C Numerical Library之上，为 Python 环境带来了 40 多年的数值知识、严格的测试和本机性能。

IMSL Python Library具有用于各种应用的高级可嵌入数学和统计算法，包括：飞机飞行动力学建模、天气预报、人类基因组的创新研究、股票市场行为预测和投资组合优化。

PyNL 是针对各种开发环境的一系列数值库中的一员。PyNL 专门针对 Python (CPython) 的 C 实现。对于 Cython 项目，建议使用IMSL Library for C。对于 Jython，我们建议使用IMSL Library for Java。

IMSL Python Library特点

IMSL Library，包括 IMSL Python Library，被认为是当今的主流编程环境中可用于数值分析的复杂、灵活、可扩展和高度可访问的技术。

• 可访问、直观、一致

IMSL Python Library具有描述性和一致的函数名称，对于开发人员和数据科学家来说都是可访问且直观的。

• 降低开发成本

使用经过验证的 IMSL 算法和功能，在设计、开发、文档编制、测试和维护方面节省时间和金钱。

• 高性能和可扩展

IMSL Python Library支持多线程进程和经过全面测试的函数和算法，已为高性能做好准备。

• 清除诊断错误消息

通过提供信息丰富且清晰的错误消息，开发人员可以快速着手解决问题，而不需要浪费时间找问题。

【英文介绍】

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.