FLENS is short for Flexible Library for Efficient Numerical Solutions. This C++ can be used as a builing block for the implementation of other (higher-level) numerical libraries or numerical applications. It is a C++ library (requires a C++11 conform compiler). Easy install, as FLENS is headers only. It gives you Matrix/vector types for dense linear algebra; a generic (i.e. templated) implementation of BLAS; and a generic reimplementation of LAPACK. If high performance BLAS libraries like ATLAS, GotoBLAS, etc. are available, you simply can link against them and boost performance.
FFTW++ is a C++ header class for the FFTW Fast Fourier Transform library that automates memory allocation, alignment, planning, and wisdom. In 2D and 3D, implicit dealiasing of convolutions substantially reduces memory usage and computation time. Wrappers for C, Python, and Fortran are included.
Sally is a tool for mapping a set of strings to a set of vectors. This mapping is referred to as embedding and allows techniques of machine learning and data mining to be applied for the analysis of string data. It can be used with data such as text documents, DNA sequences, or log files. The vector space model or bag-of-words model is used. Strings are characterized by a set of features, where each feature is associated with one dimension of the vector space. Occurrences of the features in each string are counted. Alternatively, binary or TF-IDF values can be computed. Vectors can be output in plain text, LibSVM, or Matlab format.
Salad (short for Letter Salad) is an efficient and flexible implementation of the well-known anomaly detection method Anagram by Wang et al. (RAID 2006). Salad is based on n-gram models, that is, data is represented as all of its substrings of length n. During training these n-grams are stored in a Bloom filter. This enables the detector to represent a large number of n-grams in little memory and still being able to efficiently access the data. Salad extends Anagram by allowing various n-gram types, a 2-class version of the detector for classification, and various model analysis modes.
Harry is a small tool for comparing strings and measuring their similarity. It implements several common distance and kernel functions for strings, as well as some exotic similarity measures. For example, Harry supports the Levenshtein (edit) distance, the Jaro-Winkler distance, and the compression distance. Harry is implemented using OpenMP, so its runtime scales linearly with the number of available CPU cores. Efficient implementations and effective caching speed comparison of strings.