Jupyter

Provides a different approach than ipywidgets.interact` for making sliders that affect a Matplotlib plot. When using ipywidgets.interact you are responsible for:

  1. Defining the function to plot f(x, ...) => y

  2. Handling the plotting logic (plt.plot, fig.cla, ax.set_ylim, etc.)

In contrast, with mpl-interactions, you only need to provide f(x, …) => y to have the plotting and updating boilerplate handled for you.

x = np.linspace(0,6,100)
beta = np.linspace(0,5*np.pi)
def f(x, beta):
   return np.sin(x*4+beta)
interactive_plot(f, x=x, beta=beta)