Hi Shashi, thank you very much for your help. What is slider_val in your code snippet? I actually have multiple sliders and other widgets that I want to play with before plotting. Is there any version of @manipulate where I can pass all sorts of widgets at once?
@manipulate slider, checkbox, togglebuttons, ... withfig() do ... plot commands ... end -Júlio 2015-08-02 11:51 GMT-07:00 Shashi Gowda <shashigowd...@gmail.com>: > 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 >> > >
