NumPy, Matplotlib, SciPy
NumPy, Matplotlib, and SciPy are packages that are fundamental to many applications of Python, particularly in numerically-oriented programming. They are not part of the set of base Python packages, can be easily added to a Python environment.
The NumPy package adds many features important or useful to scientific and numeric computing. These include
- True multidimensional arrays
- Linear algebra functions
- Fast Fourier Transform (FFT) Functions
- Random number generators
- Tools for integrating Fortran, C, and C++ libraries.
Matplotlib is a Python package that can be used to produce high-quality plots similar to those of MATLABTM. Its homepage and documentation can be found at matplotlib.org. A full complement of plot types is available, including
- line plots
- scatter plots
- histograms
- bar charts
- pie charts
- contour plots
NumPy and SciPy (Scientific Python) are closely linked and frequently are used together. Both provide a large selection of built-in functions.
SciPy builds on NumPy to provide a set of modules and packages that add functions for data analysis and numerical computations. These include
- special functions
- optimizations
- linear algebra
- quadrature (numerical integration)
- interpolation
- signal processing
- basic statistics