Python Scientific Computing Library Demo

base of Number value calculation

NumPy to Python provides a high-speed multidimensional array processing capability. and SciPy on the basis of the numpy to add a lot of scientific computing needs of the various tools, with these two libraries, Python has almost the same as MATLAB processing data and computing capabilities.

NumPy and SciPy official website: http://www.scipy.org

NumPy brings true multidimensional array functionality to Python. It also provides a rich library of functions to handle these arrays.

It will often use mathematical functions are arrays, so that these mathematical functions can be directly in the array operation, will be required at the Python level of the loop. Into the operations of the C language. Obviously, the computational speed of the program is improved.

The core calculations of SCIPY are some of the tried and tested Fortran numerical computing libraries, such as:

• Linear algebra using Lapack libraries

• High-speed Fourier transform using Fftpack Library

• Ordinary differential equation solving using Odepack library

• Using Minpack library for solving nonlinear equations and solving the minimum value

Symbol Calculation Library

SymPy is a set of Python function libraries for symbolic math operations. Although it has not reached the 1.0 version number at the moment, it is good enough to help us with the formula derivation and the symbolic solution.

SymPy Official website: http://code.google.com/p/sympy

Interface Design

The production interface has always been a very complex work, using the Traits Library. You will never spend a lot of effort on interface design, so you can focus on how to handle the data.

Traits official website: http://code.enthought.com/projects/traits

The traits library is divided into two parts, traits and Traitsui, traits adds a type-defined function to Python, and uses it to define the traits attribute with initialization, validation, proxy, event, and many more.

The Traitsui library is based on the traits library. Using the MVC architecture to define the user interface at a high speed, in the simplest case, you don't even have to write a code about the interface to get a working user interface through the traits attribute definition.

Programs written using the Traitsui library actively support the Wxpython and PYQT two classic interface libraries.

Drawing and Visualization

Chaco and matplotlib are very good 2D drawing libraries, and the Chaco library and the traits library are closely connected to create dynamic interactive charting functions.

The Matplotlib library can be used to draw beautiful charts and output them in many formats at high speed. And with a simple 3D drawing function.

Chaco Official Website: Http://code.enthought.com/projects/chaco

Matplotlib Official website: http://matplotlib.sourceforge.net

The TVTK Library is encapsulated with a traits library on top of the standard VTK library. Assuming you want to use VTK under Python, using TVTK is a good choice. Mayavi2 on the basis of TVTK added a set of application-oriented convenience tools. It can be used alone as a 3D visualizer, and can be embedded in the user's program at high speed.

MAYAVI2 Official website: Http://code.enthought.com/projects/mayavi

VTK (visualization Toolkit)

The visualizer library (VTK, visualization Toolkit) is an open source, cross-platform, support parallel processing (VTK was used to process data in the size of nearly 1 petabyte, the platform for the US Los Graphics Application Library for all Alamos National Labs with 1024 processor-sized large systems. 2005 was used by the United States Army Research Laboratory to simulate the Russian anti-missile vehicle zsu23-4 by plane wave attack, its compute nodes up to 2.5 trillion. --Excerpt from Wikipedia

In addition Use the Visual Library to make 3D animated presentations fast and easy, making your data results more convincing.

Visual Official Website: http://vpython.org

image processing and computer vision

OpenCV is initiated and developed by Intel Corporation and is licensed for distribution under the BSD license. Can be used free of charge in commercial and research areas. The OPENCV can be used to develop real-time image processing, computer vision, and pattern recognition programs. The Python API provided by OPENCV allows us to implement algorithms at high speed. View the results and exchange data with other libraries.

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Python Scientific Computing Library Demo