IMSL Python Numerical Library (PyNL) 提供数学和统计职能，用于在 Python 中构建各类利用法式

。PyNL成立在 IMSL C Numerical Library之上，为 Python 环境带来了 40 多年的数值知识、严格的测试和本机机能

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IMSL Python Library拥有效于各类利用的高级可嵌入数学和统推算法，蕴含：飞机飞行动力学建模、气象预报、人类基因组的创新钻延注股票市场行为预测和投资组合优化

。

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PyNL 是针对各类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

。

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IMSL Python Library特点

IMSL Library，蕴含 IMSL Python Library，被以为是当今的主流编程环境中可用于数值分析的复杂、矫捷、可扩大和高度可接见的技术

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• 可接见、直观、一致

IMSL Python Library拥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接见且直观的

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• 降低开发成本

使用经过验证的 IMSL 算法和职能，在设计、开发、文档假造、测试和守护方面节俭功夫和金钱

。

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• 高机能和可扩大

IMSL Python Library支持多线程过程和经过全面测试的函数和算法，已为高机能做好筹备

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• 断根诊断谬误新闻

通过提供信息丰硕且清澈的谬误新闻，开发人员能够急剧着手解决问题，而不必要浪费功夫找问题

。

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【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.

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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.

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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.

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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.

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Accessible, Intuitive, Consistent

With descriptive and consistent function names, the IMSL Python Library is accessible and intuitive for developers and data scientists alike.

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Reduce Development Costs

Save time and money on design, development, documentation, testing, and maintenance with proven IMSL algorithms and functions.

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Performant and Scalable

With support for multi-thread processes and thoroughly tested functions and algorithms, the IMSL Python Library is high performance ready.

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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.

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