Python is a nice programming language for scientific programming. Many high quality libraries are available as building block in a wide variety of scientific domains. In this training we will concentrate on the core libraries, and give some examples of domain specific libraries.
Program
- multi-dimensional arrrays and algorithms on these data structures: numpy
- methods & algorithms useful for scientific programming, e.g., linear algebra, Fourier transforms, statistics, optimization, root finding, signal processing: scipy
- symbolic computing: sympy
- creating many types of plots: matplotlib
- portable file formats for scientific data: e.g., HDF5
- image processing: scikit-image