Difference between revisions of "Python"
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is a handy starting point for someone used to Matlab/Octave to get into | is a handy starting point for someone used to Matlab/Octave to get into | ||
NumpPy/Scipy. | NumpPy/Scipy. | ||
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| + | * [http://mathesaurus.sourceforge.net/matlab-numpy.html Numpy/SciPy for Matlab/Octave users]. Like a Rosetta stone. | ||
| + | * [http://www.scipy-lectures.org/ More detailed SciPy lectures] | ||
Plotting is done using the [http://matplotlib.sourceforge.net/ matplotlib] library. The website contains | Plotting is done using the [http://matplotlib.sourceforge.net/ matplotlib] library. The website contains | ||
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* [http://www.scipy.org/Cookbook/FittingData Fitting data] | * [http://www.scipy.org/Cookbook/FittingData Fitting data] | ||
* [http://www.scipy.org/Cookbook/LoktaVolterraTutorial Numerical integration of ODEs] | * [http://www.scipy.org/Cookbook/LoktaVolterraTutorial Numerical integration of ODEs] | ||
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| + | The department also maintains a small [https://github.com/alchemyst/chemengcookbook cookbook notebook]. | ||
=== Thermo-Physical Properties of Materials === | === Thermo-Physical Properties of Materials === | ||
Revision as of 13:21, 28 July 2016
Contents
Python
Python is a popular scripting language. It is on the top 10 of the TIOBE index, and is often used in scientific programming outside of the major commercial platforms like Matlab or Mathematica.
- Check out the Python website for more information
Installation
- Windows: The MPR module uses Python(x,y). This is a distribution which supplies a full scientific programming environment. If that local link does not work, look for a Python(x,y) executable installer here or download directly from the Python(x,y) website. Note that the Anaconda distribution is probably a lot better. There is a local mirror of that here. Use Anaconda3.
- Linux: Install python along with Matplotlib and Numpy/Scipy
- Mac: Use Anaconda.
Python 2 vs Python 3
Python 3 came out in 2008. The problem was that it was not backwards compatible with all Python 2 programs. This delayed adoption, especially in the scientific community. There is probably no reason to use Python 2 any more.
Scientific computing
Numeric calculations are done using the NumPy or SciPy modules. Here is a handy starting point for someone used to Matlab/Octave to get into NumpPy/Scipy.
- Numpy/SciPy for Matlab/Octave users. Like a Rosetta stone.
- More detailed SciPy lectures
Plotting is done using the matplotlib library. The website contains documentation as well as a large gallery of examples.
The SciPy website also has a lot of examples in their Cookbook. Topical ones include
The department also maintains a small cookbook notebook.
Thermo-Physical Properties of Materials
Have a look at CoolProp. It is a thermo-physical property database with properties of many common pure substances. It has a python package as well as an Excel add-in.
Symbolic computing
The sympy module is a very capable symbolic module for Python. It plays well with the IPython notebook
