| Hilfe-Text | python_scipy (Version 0.16.1)
provides many user-friendly and efficient numerical routinesfor numerical integration and optimization
SciPy - Scientific Computing Tools For Python
compiled with python 3.5.7, numpy 1.11.2, icc 17.0 and mkl 2017
The SciPy library is one of the core packages that make up the SciPy stack. It provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization.
SciPy is a collection of mathematical algorithms and convenience functions built on the Numpy extension of Python. It adds significant power to the interactive Python session by providing the user with high-level commands and classes for manipulating and visualizing data. With SciPy an interactive Python session becomes a data-processing and system-prototyping environment rivaling sytems such as MATLAB, IDL, Octave, R-Lab, and SciLab.
The additional benefit of basing SciPy on Python is that this also makes a powerful programming language available for use in developing sophisticated programs and specialized applications. Scientific applications using SciPy benefit from the development of additional modules in numerous niches of the software landscape by developers across the world. Everything from parallel programming to web and data-base subroutines and classes have been made available to the Python programmer. All of this power is available in addition to the mathematical libraries in SciPy.
to use scipy, inside python type
import scipy
to obtain help about sub-modules of scipy type
help("scipy");
see also http://numpy.scipy.org/
In case of problems, please contact 'bwunicluster@hlrs.de'. |