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Scientific Analysis in Python Scientific Analysis in Python Python based scientific analysis cookbook James Battat Created: October 3, 2006 Last Modified: July 12, 2010 I find Python very user-friendly. Therefore I often reach for it when tasked to solve small or large scripting problems. I have been rather frustrated, though, with the level of support for scientific analysis packages. With scipy and matplotlib, of course, the tools are all there and success is just around the corner... But if you're like me and you're at a loss when trying to do something in Python because you're used to using other languages (IDL) for scientific analysis then you may find this page useful.
NumPy for MATLAB users – Mathesaurus NumPy for MATLAB users – Mathesaurus Help Searching available documentation Using interactively Operators Arithmetic operators Relational operators
In order to compliment my linear regression in google docs post (and because I keep forgetting how to do it), here is a quick and dirty guide to linear regression using python and pylab. First some notes. One, there is some good info on this online (how else do you think I find this stuff?). Here is a great link: SciPy Cookbook on linear regression. Second, remember that I do things the ‘hard way’ sometimes. Linear regression with pylab | Wired Science  Linear regression with pylab | Wired Science 
Python/Unix Course Peter Shearer (x42260, pshearer@ucsd.edu) Website for class at http://mahi.ucsd.edu/class233/ We meet MWF from 10 to 10:50 in the IGPP Munk Lab Conference Room. There will be no final. Grades will be based on homework. To participate, you should install on a Mac:gfortran (64-bit version) (also see NetOps wiki) XCode: Macs Developer's environment. Python/Unix Course
Simplicity, Flexibility, Beauty!, Kiwi PyCon 2011, August 27-28, 2011, Wellington, New Zealand
Python for Scientists Python for Scientists In reaction to several colleagues asking about Python , I thought a webpage would be more useful than giving an exhaustive rundown on Python verbally. Python is a script based language that allows programmers/scientists to get their algorithms and functions working in little or no time. A large number of modules and wrappers are being built for Python, like RPy and Scipy , to allow advanced tools and faster processing speeds to be implemented.
Welcome! Geany is a text editor using the GTK2 toolkit with basic features of an integrated development environment. It was developed to provide a small and fast IDE, which has only a few dependencies from other packages. It supports many filetypes and has some nice features. Geany : Home Page

Geany : Home Page

matplotlib: python plotting — Matplotlib v1.0.1 documentation

matplotlib: python plotting — Matplotlib v1.0.1 documentation matplotlib is a python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. matplotlib can be used in python scripts, the python and ipython shell (ala MATLAB®* or Mathematica®†), web application servers, and six graphical user interface toolkits. matplotlib tries to make easy things easy and hard things possible. You can generate plots, histograms, power spectra, bar charts, errorcharts, scatterplots, etc, with just a few lines of code. For a sampling, see the screenshots, thumbnail gallery, and examples directory For example, using "ipython --pylab" to provide an interactive environment, to generate 10,000 gaussian random numbers and plot a histogram with 100 bins, you simply need to type x = randn(10000) hist(x, 100)
VPython VPython VPython is the Python programming language plus a 3D graphics module called "visual" originated by David Scherer in 2000. VPython makes it easy to create navigable 3D displays and animations, even for those with limited programming experience. Because it is based on Python, it also has much to offer for experienced programmers and researchers. For a quick introduction, see youtube.com/vpythonvideos Descriptions of the options available in the left margin: Documentation: Overview, tutorials, and detailed documentation Download: Free downloads for Windows, Macintosh, and Linux What's new in VPython 6: New mouse/keyboard handling; native buttons, sliders, etc.
NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object sophisticated (broadcasting) functions tools for integrating C/C++ and Fortran code useful linear algebra, Fourier transform, and random number capabilities Scientific Computing Tools For Python — Numpy

Scientific Computing Tools For Python — Numpy

Get Started Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Start with our Beginner’s Guide Download Python Programming Language – Official Website

Python Programming Language – Official Website