Cython vs. NumPy vs. Python vs. RT-LAB Comparison Chart

Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.

RT-LAB is OPAL-RT’s real-time simulation software combining performance and enhanced user experience. Fully integrated with MATLAB/Simulink®, RT-LAB offers the most complex model-based design for interaction with real-world environments. It provides the flexibility and scalability to achieve the most complex real-time simulation applications in the automotive, aerospace, power electronics, and power systems industries. Since its first application nearly 20 years ago on the Canadian Space Agency’s Canada Arm, RT-LAB has revolutionized the world of systems engineering, whether in space, on the ground or at sea. RT-LAB enables engineers and scientists to accelerate the development of new prototypes and to meet the most rigorous testing required by new and innovative technologies. RT-LAB handles everything, including code generation, with an easy-to-use interface. With just a few clicks of the mouse, a Simulink® model becomes an interactive real-time simulation application.