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An SLF4J log provider that directly implements the SLF4J API and provides logging output suitable for console output (i.e. not to a file). The width of the output is restricted to the terminal width, with the possibility to split the width into multiple sections, each which may be a fixed width, or 'auto' which divides all remaining space amongst other automative sections. Any log attribute fields may then be placed in any of the sections with a particular alignment. Text will not overflow out of its section. Sections may be colour or styled with other text attributes, including hyperlinks for supported termins. Emoticons and other graphical sequences may be used in place of log levels. Configuration is achieved via 'ini' type files, which are reload automatically when changed.

This module allows you to enable suppressions for turning off warnings about Restricted APIs. !!!WARNING!!! Classes are marked as @Restricted for a reason and this module should not be used lightly! It implies that the author does not intend for them to be used outside their defined scope and as such they may be changed/modified/removed at any stage without warning. A simple upgrade of the dependency may break your module. Use at your own risk. You should try to not use @Restricted classes in the first place, but if you _must_ use them, this is a less-brutal approach than just disabling the access-modifier-checker entirely

Extension of BestFirst. Takes a restricted number of k attributes into account. Fixed-set selects a fixed number k of attributes, whereas k is increased in each step when fixed-width is selected. The search uses either the initial ordering to select the top k attributes, or performs a ranking (with the same evalutator the search uses later on). The search direction can be forward, or floating forward selection (with opitional backward search steps). For more information see: Martin Guetlein (2006). Large Scale Attribute Selection Using Wrappers. Freiburg, Germany.

This module contains a more general approach to construct AlignmentAlgorithms by relying on the theoretical concept of Algebraic Dynamic Programming (ADP) as developed by Giegerich et al. ADP defines four ingredients for an alignment algorithm: 1.) A signature that defines the permitted alignment operations. Operations are just function templates with an associated arity, meaning the number of arguments it takes from the left sequence and from the right sequence. In the TCSAlignmentToolbox we have a fixed signature with the following operations: REPLACEMENT(1, 1), DELETION(1, 0), INSERTION(0, 1), SKIPDELETION(1, 0) and SKIPINSERTION(0, 1) 2.) A regular tree grammar that produces alignments, that is: sequences of operations, in a restricted fashion. 3.) An algebra that can translate such trees to a cost. In the TCSAlignmentToolbox this is a Comparator. 4.) A choice function, in case of the TCSAlignmentToolbox: the strict minimum or the soft minimum. An alignment algorithm in the TCSAlignmentToolbox sense of the word then is the combination of choice function and grammar. While we provide hardcoded versions of these combinations in the main package, the adp package allows you to create your own grammars. You can combine them with a choice function by instantiating one of the Algorithm classes provided in this package with a grammar of your choice. For example: AlignmentAlgorithm algo = new SoftADPScoreAlgorithm(my_grammar, comparator); creates an alignment algorithm that implicitly produces all possible alignments your grammar can construct with the given input, translates them to a cost using the algebra/comparator you provided and applies the soft minimum to return the score. This all gets efficient by dynamic programming. Note that there is runtime overhead when using this method in comparison with the hardcoded algorithms. But for complicated grammars this is a much easier way to go. For more information on the theory, please refer to my master's thesis: "Adaptive Affine Sequence Alignment using Algebraic Dynamic Programming"