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The primary difference between a computer algebra system and a traditional calculator is the ability to deal with equations symbolically rather than numerically. The precise uses and capabilities of these systems differ greatly from one system to another, yet their purpose remains the same: manipulation of symbolic equations .
Add a calculator widget to the page. Like a spreadsheet you can refer to other widgets in the same page. Template parameters [Edit template data] Parameter Description Type Status id id The id for this input. This is used to reference it in formula of other calculator templates String required type type What type of input box Suggested values plain number text radio checkbox passthru hidden ...
This is a documentation subpage for Template:Calculator ifenabled. It may contain usage information, categories and other content that is not part of the original template page. Allows you to detect if the calculator gadget is enabled and provide fallback content for cases where it is not such as when printing.
Core math functions include BLAS, LAPACK, ScaLAPACK, sparse solvers, fast Fourier transforms, and vector math. Intel IPP is a multi-threaded software library of functions for multimedia and data processing applications. OpenBLAS is an open source implementation of the BLAS API with many hand-crafted optimizations for specific processor types ...
MATLAB (an abbreviation of "MATrix LABoratory" [18]) is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks. MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.
C++ template library for linear algebra; includes various decompositions and factorisations; syntax is similar to MATLAB. GNU Scientific Library: GNU Project C 1996 2.7, 1 June 2021 Free GPL: General purpose numerical analysis library. Targets Linux, can be built on almost any *nix OS with Ansi C compiler. ILNumerics: H. Kutschbach C#, PowerShell
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When using interpolation, the size of the lookup table can be reduced by using nonuniform sampling, which means that where the function is close to straight, we use few sample points, while where it changes value quickly we use more sample points to keep the approximation close to the real curve.