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MATLAB (an abbreviation of "MATrix LABoratory" [22]) 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.
SymPy, a Python package that can solve ODEs symbolically Julia (programming language) , a high-level language primarily intended for numerical computations. SageMath , an open-source application that uses a Python-like syntax with a wide range of capabilities spanning several branches of mathematics.
matrix-free save memory: Yes No Yes matrix-free speed-up: Yes No Yes Used language: Native language: Primarily C++ and Java C++ C++ C++ Fortran (2008 standard) C++ C++ Matlab / Octave Bindings to language: Full API for Java and Matlab (the latter via add-on product) PyMFEM (Python) Python, Scilab or Matlab Python bindings to some functionality ...
Shogun, an open-source large-scale machine-learning toolbox that provides several SVM implementations (like libSVM, SVMlight) under a common framework and interfaces to Octave, MATLAB, Python, R; Waffles is a free-software collection of command-line tools designed for scripting machine-learning operations in automated experiments and processes.
Numerical methods for ordinary differential equations are methods used to find numerical approximations to the solutions of ordinary differential equations (ODEs). Their use is also known as "numerical integration", although this term can also refer to the computation of integrals. Many differential equations cannot be solved exactly.
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PyCharm – Cross-platform Python IDE with code inspections available for analyzing code on-the-fly in the editor and bulk analysis of the whole project. PyDev – Eclipse-based Python IDE with code analysis available on-the-fly in the editor or at save time. Pylint – Static code analyzer. Quite stringent; includes many stylistic warnings as ...
In practical terms, the distinction between DAEs and ODEs is often that the solution of a DAE system depends on the derivatives of the input signal and not just the signal itself as in the case of ODEs; [3] this issue is commonly encountered in nonlinear systems with hysteresis, [4] such as the Schmitt trigger. [5]