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algorithms from group de.cit-ec.tcs.alignment (version 3.1.1)

This module defines the interface for AlignmentAlgorithms as well as some helper classes. An AlignmentAlgorithm computes an Alignment of two given input sequences, given a Comparator that works in these sequences. More details on the AlignmentAlgorithm can be found in the respective interface. More information on Comparators can be found in the comparators module. The resulting 'Alignment' may be just a real-valued dissimilarity between the input sequence or may incorporate additional information, such as a full Alignment, a PathList, a PathMap or a CooptimalModel. If those results support the calculation of a Gradient, they implement the DerivableAlignmentDistance interface. In more detail, the Alignment class represents the result of a backtracing scheme, listing all Operations that have been applied in one co-optimal Alignment. A classic AlignmentAlgorithm does not result in a differentiable dissimilarity, because the minimum function is not differentiable. Therefore, this package also contains utility functions for a soft approximation of the minimum function, namely Softmin. For faster (parallel) computation of many different alignments or gradients we also provide the ParallelProcessingEngine, the SquareParallelProcessingEngine and the ParallelGradientEngine.

Group: de.cit-ec.tcs.alignment Artifact: algorithms
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algorithms from group de.cit-ec.tcs.alignment (version 3.1.0)

This module defines the interface for AlignmentAlgorithms as well as some helper classes. An AlignmentAlgorithm computes an Alignment of two given input sequences, given a Comparator that works in these sequences. More details on the AlignmentAlgorithm can be found in the respective interface. More information on Comparators can be found in the comparators module. The resulting 'Alignment' may be just a real-valued dissimilarity between the input sequence or may incorporate additional information, such as a full Alignment, a PathList, a PathMap or a CooptimalModel. If those results support the calculation of a Gradient, they implement the DerivableAlignmentDistance interface. In more detail, the Alignment class represents the result of a backtracing scheme, listing all Operations that have been applied in one co-optimal Alignment. A classic AlignmentAlgorithm does not result in a differentiable dissimilarity, because the minimum function is not differentiable. Therefore, this package also contains utility functions for a soft approximation of the minimum function, namely Softmin. For faster (parallel) computation of many different alignments or gradients we also provide the ParallelProcessingEngine, the SquareParallelProcessingEngine and the ParallelGradientEngine.

Group: de.cit-ec.tcs.alignment Artifact: algorithms
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algorithms from group de.cit-ec.tcs.alignment (version 3.0.1)

This module defines the interface for AlignmentAlgorithms as well as some helper classes. An AlignmentAlgorithm computes an Alignment of two given input sequences, given a Comparator that works in these sequences. More details on the AlignmentAlgorithm can be found in the respective interface. More information on Comparators can be found in the comparators module. The resulting 'Alignment' may be just a real-valued dissimilarity between the input sequence or may incorporate additional information, such as a full Alignment, a PathList, a PathMap or a CooptimalModel. If those results support the calculation of a Gradient, they implement the DerivableAlignmentDistance interface. In more detail, the Alignment class represents the result of a backtracing scheme, listing all Operations that have been applied in one co-optimal Alignment. A classic AlignmentAlgorithm does not result in a differentiable dissimilarity, because the minimum function is not differentiable. Therefore, this package also contains utility functions for a soft approximation of the minimum function, namely Softmin. For faster (parallel) computation of many different alignments or gradients we also provide the ParallelProcessingEngine, the SquareParallelProcessingEngine and the ParallelGradientEngine.

Group: de.cit-ec.tcs.alignment Artifact: algorithms
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algorithms from group de.cit-ec.tcs.alignment (version 3.0.0)

This module defines the interface for AlignmentAlgorithms as well as some helper classes. An AlignmentAlgorithm computes an Alignment of two given input sequences, given a Comparator that works in these sequences. More details on the AlignmentAlgorithm can be found in the respective interface. More information on Comparators can be found in the comparators module. The resulting 'Alignment' may be just a real-valued dissimilarity between the input sequence or may incorporate additional information, such as a full Alignment, a PathList, a PathMap or a CooptimalModel. If those results support the calculation of a Gradient, they implement the DerivableAlignmentDistance interface. In more detail, the Alignment class represents the result of a backtracing scheme, listing all Operations that have been applied in one co-optimal Alignment. A classic AlignmentAlgorithm does not result in a differentiable dissimilarity, because the minimum function is not differentiable. Therefore, this package also contains utility functions for a soft approximation of the minimum function, namely Softmin. For faster (parallel) computation of many different alignments or gradients we also provide the ParallelProcessingEngine, the SquareParallelProcessingEngine and the ParallelGradientEngine.

Group: de.cit-ec.tcs.alignment Artifact: algorithms
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algorithms from group de.cit-ec.tcs.alignment (version 2.1.2)

This module defines the interface for AlignmentAlgorithms as well as some helper classes. An AlignmentAlgorithm computes an alignment of two given input sequences, given an AlignmentSpecification. An AlignmentSpecification in turn is a vector of Comparators (refer to the respective module for more information), such that the distance between two elements of the input sequences can be computed. In that sense all an AlignmentAlgorithm has to do is to implement the computation of an Alignment, under the assumption that a distance between sequence elements is given as the weighted sum of comparator distances, as specified in the AlignmentSpecification. An AlignmentAlgorithm does not need to calculate just a real-valued distance between the input sequences but may also provide additional information about the alignment in order to calculate a derivative. To store such additional information this module contains the AlignmentDerivativeAlgorithm. A usual implementation of this is classic backtracing, which can be stored in an AlignmentPath object. If an AlignmentAlgorithm returns several possible AlignmentPaths, they can be stored in the PathList or PathMap datastructure. To make an alignment distance differentiable, we usually employ the Softmin approximation of the strict minimum. A standard implementation is provided in the Softmin class. For faster (parallel) computation of many different alignments or derivatives we also provide the ParallelProcessingEngine, the ParallelDerivativeEngine and the ParallelWeightDerivativeEngine.

Group: de.cit-ec.tcs.alignment Artifact: algorithms
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algorithms from group de.cit-ec.tcs.alignment (version 2.1.1)

This module defines the interface for AlignmentAlgorithms as well as some helper classes. An AlignmentAlgorithm computes an alignment of two given input sequences, given an AlignmentSpecification. An AlignmentSpecification in turn is a vector of Comparators (refer to the respective module for more information), such that the distance between two elements of the input sequences can be computed. In that sense all an AlignmentAlgorithm has to do is to implement the computation of an Alignment, under the assumption that a distance between sequence elements is given as the weighted sum of comparator distances, as specified in the AlignmentSpecification. An AlignmentAlgorithm does not need to calculate just a real-valued distance between the input sequences but may also provide additional information about the alignment in order to calculate a derivative. To store such additional information this module contains the AlignmentDerivativeAlgorithm. A usual implementation of this is classic backtracing, which can be stored in an AlignmentPath object. If an AlignmentAlgorithm returns several possible AlignmentPaths, they can be stored in the PathList or PathMap datastructure. To make an alignment distance differentiable, we usually employ the Softmin approximation of the strict minimum. A standard implementation is provided in the Softmin class. For faster (parallel) computation of many different alignments or derivatives we also provide the ParallelProcessingEngine, the ParallelDerivativeEngine and the ParallelWeightDerivativeEngine.

Group: de.cit-ec.tcs.alignment Artifact: algorithms
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algorithms from group de.cit-ec.tcs.alignment (version 2.1.0)

This module defines the interface for AlignmentAlgorithms as well as some helper classes. An AlignmentAlgorithm computes an alignment of two given input sequences, given an AlignmentSpecification. An AlignmentSpecification in turn is a vector of Comparators (refer to the respective module for more information), such that the distance between two elements of the input sequences can be computed. In that sense all an AlignmentAlgorithm has to do is to implement the computation of an Alignment, under the assumption that a distance between sequence elements is given as the weighted sum of comparator distances, as specified in the AlignmentSpecification. An AlignmentAlgorithm does not need to calculate just a real-valued distance between the input sequences but may also provide additional information about the alignment in order to calculate a derivative. To store such additional information this module contains the AlignmentDerivativeAlgorithm. A usual implementation of this is classic backtracing, which can be stored in an AlignmentPath object. If an AlignmentAlgorithm returns several possible AlignmentPaths, they can be stored in the PathList or PathMap datastructure. To make an alignment distance differentiable, we usually employ the Softmin approximation of the strict minimum. A standard implementation is provided in the Softmin class. For faster (parallel) computation of many different alignments or derivatives we also provide the ParallelProcessingEngine, the ParallelDerivativeEngine and the ParallelWeightDerivativeEngine.

Group: de.cit-ec.tcs.alignment Artifact: algorithms
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algorithms from group de.cit-ec.tcs.alignment (version 2.0.0)

This module defines the interface for AlignmentAlgorithms as well as some helper classes. An AlignmentAlgorithm computes an alignment of two given input sequences, given an AlignmentSpecification. An AlignmentSpecification in turn is a vector of Comparators (refer to the respective module for more information), such that the distance between two elements of the input sequences can be computed. In that sense all an AlignmentAlgorithm has to do is to implement the computation of an Alignment, under the assumption that a distance between sequence elements is given as the weighted sum of comparator distances, as specified in the AlignmentSpecification. An AlignmentAlgorithm does not need to calculate just a real-valued distance between the input sequences but may also provide additional information about the alignment in order to calculate a derivative. To store such additional information this module contains the AlignmentDerivativeAlgorithm. A usual implementation of this is classic backtracing, which can be stored in an AlignmentPath object. If an AlignmentAlgorithm returns several possible AlignmentPaths, they can be stored in the PathList or PathMap datastructure. To make an alignment distance differentiable, we usually employ the Softmin approximation of the strict minimum. A standard implementation is provided in the Softmin class. For faster (parallel) computation of many different alignments or derivatives we also provide the ParallelProcessingEngine, the ParallelDerivativeEngine and the ParallelWeightDerivativeEngine.

Group: de.cit-ec.tcs.alignment Artifact: algorithms
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