开源软件名称(OpenSource Name):stefanengblom/stenglib开源软件地址(OpenSource Url):https://github.com/stefanengblom/stenglib开源编程语言(OpenSource Language):MATLAB 54.1%开源软件介绍(OpenSource Introduction):stenglibStefan Engblom's Matlab libraries - packages for daily use. License statement for stenglibYou may download all of stenglib and use, modify and redistribute it in any way you like. A redistributor must fully attribute the authorship and make a good effort to cite the original location of the software. A researcher making critical use of the software in research is requested to acknowledge this in publications related to the research. A company may use the code in software products provided that the original location and the author is clearly cited. All code provided here comes with absolutely no warranty and no support whatsoever is given. There are a lot of freeware available on the net. Do not download unless you agree to the above license. About stenglibstenglib is loosely divided into 5 sub-packages, with few dependencies in between them:
For contact details, see stenglib.org. I welcome bug reports and comments. Please do not send support requests. TensorOriginally, I made the Tensor package because I had the need to easily, efficiently and consistently manage multi-dimensional arrays in Matlab. Examples: given a matrix and a vector, how do you scale each row in the matrix by the vector? How can you multiply a 3-D array with a matrix? The package is useful to anyone who writes code for (pseudo-) spectral methods, FEM, or who uses multi-dimensional arrays or tensor notation a lot.
There is also a make.m available. It will work on several, but not all, platforms. FastThe routines in the Fast package exist because some things just take too much time in Matlab. Examples: replicate a data set in different dimensions (a.k.a. repmat), assemble a sparse matrix, or evaluate set operations. These routines should be of general interest to programmer in the scientific computing community.
There is now a parallel fsparse version available. A paper describing the algorithm is S. Engblom, D. Lukarski: Fast Matlab compatible sparse assembly on multicore computers, in Parallel Comput. 56:1--17 (2016) (doi). Fact: the fsparse-code has been selected as the base for the sparse assembly routines in PARALUTION.
As before there is a make.m available which you will probably have to modify. ScicompIn Scicomp I've assembled some solvers from different areas within scientific computing: two solvers for nonlinear problems and an implementation of the Nelder-Mead simplex algorithm. I have also put three routines for Gaussian quadratures with respect to discrete measures in this package.
UtilsIn the package Utils I've collected various routines for performing everyday tasks. Examples include generating LaTeX-arrays from matrices, .gif-animations, small perfect hash functions and removing files ending with a tilde (!).
MiscI'll put amusing routines in Misc. For now, this humble package contains a sudoku solver and a short function which I personally believe is the most beautiful Matlab-code ever written.
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