Standard Numerical Library (SNL)
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Modules of Standard Numerical Library

Topic Status Notes
Basic Data Types   ...
- Quaternions C Quaternion is a sort of higher-level complex number.
- Utility Classes B Exceptions, etc...
Linear Algebra   ...
- Vectors and Matrices B Generic one- and two-dimensional matrix classes with arbitrary row and column sizes. It can use as elements any data types with addition and multiplication operations defined, including matrix and vector classes themselves.
- Eigensystems X ...
Analytic Geometry   ...
- Vectors and Tensors A ...
- Coordinate Transformations A ...
- 3 Dimensional Specializations B Optimized data types for three dimensional Euclidean space. This collection of classes can be used for computer graphics and computer vision applications. It uses both homogeneous and non-homogeneous coordinate representations.
Arithmetic   ...
- Radix Conversion X ...
- Multiple Precision Arithmetic X ...
- Polynomial Arithmetic X ...
Root Finding   ...
- Quadrature X ...
- Linear Algebraic Equations X ...
- Nonlinear Equations X ...
Linear Filters   ...
- Spectral Analysis X ...
- Fast Fourier Transforms X ...
- Wavelet Transforms X ...
Random Numbers   ...
- Generating Uniform Random Numbers X ...
- Quasi-Random Sequences X ...
- Statistical Tests X ...
- Monte-Carlo Integration X ...
Probability Theory   ...
- Random Distributions X ...
- Stochastic Processes X ...
- Information Theory X ...
Statistical Analysis   ...
- Least-Squares Fitting X ...
- Statistical Hypothesis Testing X ...
- Maximum Likelihood Estimation X ...
- Bayesian Inference X ...
(A: Alpha, B: Beta, C: Complete, X: Not implemented yet.)

Additional Modules of SNL:
Numerical Function Evalution. Special Functions. Interpolation/Extrapolation. Optimization. - Function Minimization/Maximization. - Linear Programming. - Dynamic Programming. - Simulated Annealing. - Genetic Algorithm. Numerical Differentiation/Integration. Boundary Value Problems. - Ordinary Differential Equations. - Partial Differential Equations. Integral Equations and Inverse Theory. Time Series Analysis. Clustering.