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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)

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Open Book Project by Peter Wentworth, Jeffrey Elkner, Allen B. Downey, and Chris Meyers 3rd Edition (last updated 10/6/12)2nd Edition (last updated 4/21/12) What's the difference among these versions? color example code: — Matplotlib 1.3.0 documentation (Source code) """Reference for colormaps included with Matplotlib. This reference example shows all colormaps included with Matplotlib. Note thatany colormap listed here can be reversed by appending "_r" (e.g., "pink_r").These colormaps are divided into the following categories: Sequential: These colormaps are approximately monochromatic colormaps varying smoothly between two color tones---usually from low saturation (e.g. white) to high saturation (e.g. a bright blue). Sequential colormaps are ideal for representing most scientific data since they show a clear progression from low-to-high values.

NumPy, SciPy, and the Intel Compiler Suite - Iceweasel 30 Aug 2009 I spent a lot of time trying to get NumPy and SciPy to work with the Intel Compiler Suite, but it finally works. Here is how I did it on Ubuntu 9.04/AMD64 on an Intel Core 2 Duo using the versions specified. Monte Carlo method Monte Carlo methods (or Monte Carlo experiments) are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results; typically one runs simulations many times over in order to obtain the distribution of an unknown probabilistic entity. They are often used in physical and mathematical problems and are most useful when it is difficult or impossible to obtain a closed-form expression, or infeasible to apply a deterministic algorithm. Monte Carlo methods are mainly used in three distinct problem classes: optimization, numerical integration and generation of draws from a probability distribution.

BeginnersGuide New to programming? Python is free and easy to learn if you know where to start! This guide will help you to get started quickly. Chinese Translation New to Python? Read BeginnersGuide/Overview for a short explanation of what Python is.

pylab_examples example code: — Matplotlib 1.3.0 documentation Navigation This Page Show Source Quick search Enter search terms or a module, class or function name. Chapter 12: Classes and objects Warning: the HTML version of this document is generated from Latex and may contain translation errors. In particular, some mathematical expressions are not translated correctly. 12.1 User-defined compound types

The Python Tutorial — Python v2.7.1 documentation Python is an easy to learn, powerful programming language. It has efficient high-level data structures and a simple but effective approach to object-oriented programming. Python’s elegant syntax and dynamic typing, together with its interpreted nature, make it an ideal language for scripting and rapid application development in many areas on most platforms. Minesweeper in Matplotlib Lately I've been playing around with interactivity in matplotlib. A couple weeks ago, I discussed briefly how to use event callbacks to implement simple 3D visualization and later used this as a base for creating a working 3D Rubik's cube entirely in matplotlib. Today I have a different goal: re-create minesweeper, that ubiquitous single-player puzzle game that most of us will admit to having binged on at least once or twice in their lives.

Style Guide for Python Code Code should be written in a way that does not disadvantage other implementations of Python (PyPy, Jython, IronPython, Cython, Psyco, and such).For example, do not rely on CPython's efficient implementation of in-place string concatenation for statements in the form a += b or a = a + b. This optimization is fragile even in CPython (it only works for some types) and isn't present at all in implementations that don't use refcounting. In performance sensitive parts of the library, the ''.join() form should be used instead. This will ensure that concatenation occurs in linear time across various implementations.Comparisons to singletons like None should always be done with is or is not, never the equality operators.Also, beware of writing if x when you really mean if x is not None -- e.g. when testing whether a variable or argument that defaults to None was set to some other value.

BeginnersGuide/Programmers Please Note Because this is a Wiki page, users can edit it. You are therefore free to add details of material that other Python users will find useful. It is not an advertising page, and is here to serve the whole Python community. Users who continually edit pages to give their own materials (particularly commercial materials) prominence, or spam the listing with multiple entries which point to resources with only slightly altered material, may therefore find their accounts are disabled. Python beginner's mistakes Every Python programmer had to learn the language at one time, and started out as a beginner. Beginners make mistakes. This article highlights a few common mistakes, including some I made myself. Beginner's mistakes are not Python's fault, nor the beginner's. They're merely a result of misunderstanding the language. However, there is a difference between misunderstanding (often subtle) language features, vs misunderstanding the language as a whole, and what can (and cannot) be done with it.

Python Course: Modular Programming and Modules Modular Programming If you want to develop programs which are readable, reliable and maintainable without too much effort, you have use some kind of modular software design. Especially if your application has a certain size. There exists a variety of concepts to design software in modular form. Modular programming is a software design technique to split your code into separate parts. These parts are called modules. Python For Beginners Welcome! Are you completely new to programming? If not then we presume you will be looking for information about why and how to get started with Python. Fortunately an experienced programmer in any programming language (whatever it may be) can pick up Python very quickly.