anvaka/streamlines

Algorithm

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Thank you for the great implementation.
I have read the paper several times, but couldn't implement it
I want to implement it in python using numpy.
Please can you provide detailed algorithm or pipeline, mainly the runge-kutta part

The Runge-Kutta part is a simple way of approximating a function f(x) when all you have is its first derivative f'(x). You can see the code strictly follow the method description from wikipedia.

The streamlines are computed over a function that is defined in every single point (x, y). Usually the result of this function is interpreted as a velocity vector. f(x, y) = (Vx, Vy) - velocity vector at point (x, y).

Velocity is indeed can be interpreted as first derivative of your position. Which means to figure out the next position of a streamline segment we can apply Runge-Kutta method - its output going to be a point (x1, y1) where the streamline should go.