Introduction to scipy and matplotlib [Z]

The mature function library on Matlab facilitates numerical calculation and drawing, and is widely used in China. But authorization is also a big problem, so there are a lot of alternative open source implementation, in Python, I have been in touch with scipy (www.scipy.org) and matplotlib (http://matplotlib.sourceforge.net/) two projects.
"Scipy is a python-based project designed to reproduce all functions of Matlab, optimize its performance, and simplify integration with other software, at the same time, it remains completely free and at least as easy to use as MATLAB. "
Http://www-128.ibm.com/developerworks/cn/linux/l-oslab/index.html)
Scipy has scipy Conference every year. The current version is 0.3.2 of 04, and python2.3 wxpython2.4 numeric23 is required. The structure of scipy is two parts: scipy_core and scipy_lib. However, it is troublesome to compile by yourself. C and FORTRAN compilers are required. If you need more complete MATLAB Functions, you can choose it. It is recommended to install enhanced Python (http://www.enthought.com/python/), one installation, all have.
"Matplotlib is a python module developed by John Hunter and others to draw two-dimensional images. It uses the numeric computing modules numeric and numarray in Python to clone many MATLAB functions to help users easily obtain high-quality 2D images. Matplotlib can be used to draw various forms of graphs, including common line charts, histograms, pie charts, scatter plots, and error line charts. It is convenient to customize the types and colors of different attributes of a graph, width, font size, etc. It can well support some Tex typographical commands, and can display mathematical formulas in graphs in a more beautiful way. Matplotlib is easy to master. Most of matplotlib's functions have the same name as the corresponding functions in MATLAB, And the meanings of various parameters are the same in usage, this makes users familiar with MATLAB feel comfortable to use. For users who are not familiar with MATLAB, the significance of these functions is often clear at a glance, so they can be mastered with little time ." (Http://www-128.ibm.com/developerworks/cn/linux/l-matplotlib? CA = dwcn-newsletter-Linux)
Matplotlib/pylab is a lightweight, quasi-MATLAB implementation with fast version updates. Currently, the latest version is 2.3, which was released in September this year of python2.4/0.84, compatible with Python 2.4 wxpython2.6u and other new versions. numeric computation supports numeric and numarray. I suggest using numarray. If it is numeric, it is best to use 23 instead of 24 versions. If you want to use Python 2.4 and mainly develop 2D images, matplotlib is suitable for you.
The combination of scipy, matplotlib, numeric, and numarray has become a powerful tool for python in numerical computation and drawing. It is worth noting that they all have some common developers, for example, John Hunter, Jay t Miller and others, so they are very compatible. Another thing worth noting is the newly released scipy_core0.4 in numpy (http://sourceforge.net/projects/numpy), I guess, because it will be used to replace the new version of scipy and numarray, compare the core of scipy0.32 Code And scipy_core0.4. If you modify the code, scipy0.32 _ lib + scipy_core0.4 can be used on python2.4.

 

Original: http://www.cnblogs.com/WWW-1/archive/2005/10/21/259023.html