用python替换Matlab [英] replacing Matlab with python

问题描述

我是一名工程专业的学生，​​我必须做大量的数值处理，绘图，模拟等工作.我目前使用的工具是Matlab.我在大学计算机上使用它来完成大部分任务.但是，我想知道有哪些可用的免费选项.

我已经做过一些研究，许多人说python在各种情况下都可以替代matlab.我想知道如何用python做所有这些事情.我使用的是Mac，如何安装不同的python软件包.那些包是什么?这真的是可行的选择吗?使用此python设置我可以做什么和不能做什么?

解决方案

在Mac上，最简单的入门方法是(无特定顺序):

• Python发行版，其中包括您可能需要的大多数科学软件包.免费用于学术/非商业用途.
• Macports -是最新版本，因此sudo port install py26-numpy py26-scipy py26-matplotlib py26-ipython应该可以帮助您入门. li>
• Scipy Superpack -用于安装所有重要软件包的最新svn版本的脚本.

大约2年前，我已经做到了这一点(用Python替换了Matlab)，并且没有回头.使用Python进行广播，更直观的内存模型和Numpy的其他优点使数值工作变得非常愉快.与f2py和cython一起使用，可以很容易地将内部循环放入另一种语言中. 这是一个不错的起点-其他令人振奋的页面是 ParallelProgramming .一定要了解Python的变量是对对象的引用"的语义……在进行了这种调整之后，一切都是一帆风顺的.击败matlab的最酷的事情之一是我在8个内核上运行了2条线... p = Pool(8); res = p.map(analysis_function,list_of_data)-MATLAB并行工具箱是如此昂贵，以至于我还没有看到实际上拥有它们的大学.

i am a engineering student and i have to do a lot of numerical processing, plots, simulations etc. The tool that i use currently is Matlab. I use it in my university computers for most of my assignments. However, i want to know what are the free options available.

i have done some research and many have said that python is a worthy replacement for matlab in various scenarios. i want to know how to do all this with python. i am using a mac so how do i install the different python packages. what are those packages? is it really a viable alternative? what are the things i can and cannot do using this python setup?

解决方案

On a Mac the easiest ways to get started are (in no particular order):

• Enthought Python Distribution which includes most scientific packages you are likely to need. Free for academic/non-commercial use.
• Macports - up to date with latest releases, so sudo port install py26-numpy py26-scipy py26-matplotlib py26-ipython should get you started.
• Scipy Superpack - script to install recent svn versions of all the important packages.

I've done exactly this (replace Matlab with Python) about 2 years ago and haven't looked back. The broadcasting in Python, more intuitive memory model and other Numpy advantages make numerical work a complete pleasure. Plus with f2py, cython it is incredibly easy to put inner loops in another language. This is a good place to start - other impressive pages to provide motiviation are PerformancePython and ParallelProgramming. Be sure to understand Pythons "variable is a reference to an object" semantics... after that adjustment everything is plain sailing. One of the coolest things that beats matlab is in 2 lines I run over 8 cores... p = Pool(8); res = p.map(analysis_function,list_of_data) - MATLAB parallels toolboxes are so expensive I've yet to see a University that actually has them.

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