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An example plotting Bessel functions and finding their local maxima.
|Developer(s)||community project sponsored and supported by Enthought|
|Stable release||0.7.1 / 2009-07-11-04-9|
|Operating system||Cross-platform (list)|
SciPy contains modules for optimization, linear algebra, integration, interpolation special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering. It has a similar audience to applications as MATLAB, GNU Octave, and Scilab.
The basic data structure in SciPy is a multidimensional array provided by the NumPy module. Older versions of SciPy used Numeric as an array type, which is now deprecated in favor of the newer NumPy array code. 
- constants: physical constants and conversion factors (since version 0.7.0)
- cluster: hierarchical clustering, vector quantization, K-means
- fftpack: Discrete Fourier Transform algorithms
- integrate: numerical integration routines
- interpolate: interpolation tools
- io: data input and output
- lib: Python wrappers to external libraries
- linalg: linear algebra routines
- misc: miscellaneous utilities (e.g. image reading/writing)
- optimize: optimization algorithms including linear programming
- signal: signal processing tools
- sparse: sparse matrix and related algorithms
- spatial: KD-trees, nearest neighbors, distance functions
- special: special functions
- stats: statistical functions
- weave: tool for writing C/C++ code as Python multiline strings
SciPy's core feature set is extended by many other dedicated software tools. For example,
- Plotting. The currently recommended 2-D plotting package is Matplotlib, however, there are many other plotting packages such as HippoDraw, Chaco, and Biggles. Other popular graphics tools include Python Imaging Library and MayaVi (for 3D visualization).
- Optimization. While SciPy has its own optimization package, OpenOpt has access to more optimization solvers and can involve Automatic differentiation.
- Advanced Data Analysis. Via RPy, SciPy can interface to the R statistical package for advanced data analysis.
- Database. SciPy can interface with  PyTables, a hierarchical database package designed to efficiently manage large amounts of data using HDF5.
- Interactive shell. IPython is an interactive environment that offers debugging and coding features similar to what MATLAB offers.
- Symbolic Mathematics. There are several Python libraries--such as PyDSTool Symbolic and SymPy--that offer symbolic mathematics.
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