Search Results for "scientific calculator code in python"
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Showing 6 open source projects for "scientific calculator code in python"
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads: http://arma.sourceforge.net... -
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calculatorpp
Calculator++
Written in C++ (using template). Calculator++ is a application/library for Window (POSIX). The core of code is adaptable for posix. This algorithm support: + built-in operator + built-in functions + run-time functions and variables definition + run-time units system, units with prefix + constants definition + Pretty mathematical expressions - Process ascii files (dev) - vector and matrix (dev) - graph 2D and 3D (dev) - vector graph (dev... -
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TA-Lib.git: Technical Analysis Library
Mirror of the TA-Lib project using a Git repository
This project is intended to provide Git access to the code of the original project, TA-Lib, which uses Subversion. It is intended for system integrators wishing to use TA-Lib in their Git-managed project through Git submodules or subtrees. No actual development is being done here; all development happens in the original project. -
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pycrc
CRC C source generator
pycrc is an easy to use CRC (cyclic redundancy check) calculator and C source code generator. The generated source code can be optimized for simplicity, speed or space. pycrc contains a long parameter list of common CRC models. The program is self contained and does not require installation. Apart from a python installation, it does not require other libraries to be installed. -
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Open Metaheuristic (oMetah) is a library aimed at the conception and the rigourous testing of metaheuristics (i.e. genetic algorithms, simulated annealing, ...). The code design is separated in components : algorithms, problems and a test report generator
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