BinSeqPy

Reference : BinSeqPy


	Document type :	Computer developments : Software
	Discipline(s) :	Physical, chemical, mathematical & earth Sciences : Mathematics Engineering, computing & technology : Computer science
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/38864

Title :	BinSeqPy
Language :	English
Author, co-author :	Atashpendar, Arash [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	2014
Keywords :	[en] Binary sequences ; Subsequence ; Supersequence ; Information entropy ; Combinatorics ; Probability distribution ; Hidden Word Statistics ; Subsequence embeddings ; Dynamic programming ; Entropy Extremization
Abstract :	[en] BinSeqPy is a library for the Python programming language, aimed at performing experiments and analyses of combinatorial structures dealing with binary (sub/super)-sequences. It provides an array of low-level as well as high-level mathematical functions for addressing a variety of information theory and combinatorial problems involving binary subsequences and their embeddings in supersequences. These range from bitstring transformations, information entropy analysis routines, plotting functions and algorithms related to subsequence embeddings to functions dedicated to hidden word statistics.
Permalink :	http://hdl.handle.net/10993/38864
Commentary :	Source code available upon request.

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