Hi, Easiest way to do this is with @manipulate and `withfig` as you have discovered.
I'm inclined to remove @lift from reactive since it's hard to implement correctly and has caused frustrating problems. (also it's not eval-free) I recommend you use the lift function instead. s = slider(1:10) display(s) lift(x -> greyim(eye(x)), s) Should do the trick for you. With PyPlot, this will be: f = figure() lift(s) do slider_val withfig(f) # This basically says "do the drawing on the same plot f." .... plot something with slider_val... end On Mon, Aug 3, 2015 at 12:06 AM, Júlio Hoffimann <julio.hoffim...@gmail.com> wrote: > Hi, > > Suppose I have: > > s = slider(1:10) > img = @lift eye(s) > > How can I create the interactive plot in Jupyter using @lift? > > @lift imshow(img) > > I know @manipulate has the withfig() option where we can pass the PyPlot > Figure object, what about @lift? > > -Júlio >
