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Visualization #474
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Hi @Daniele-Dondi, if I'm understanding your question right, you would like to plot some 2D optimization results? |
I'm sorry because I wasn't clear enough. I will try to explain better: In the readme.md file, you are showing an animated gif: I wish to know how you created the topleft graph (Gaussian Process Predicted Mean). Later, You showed a code able to plot the guess for a function target(x) by defining a procedure named plot_gp(optimizer, x, y) and you are showing the change step after step calling the code: optimizer.maximize(init_points=0, n_iter=1) My question is: |
Hi @Daniele-Dondi, the code used to create the animated gif is discussed in #18. If you want to generally plot 2D-optimization results (i.e. no animation), see the code I linked in the constraints notebook, specifically the bottom left cell ( |
Thank you, |
I inserted your function in the step to step optimizer.
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Hi @Daniele-Dondi, glad to see things worked out for you. I will close this issue. Feel free to make a new issue, if you run into other problems. |
I've seen your docs on visualization, and everything is explained with 1D function.
However,
in the program description you shown the visualization of a 2D function.
My question is:
How to implement visualization for 2D functions?
We just iterate the optimizer._gp.fit(x_obs, y_obs) two times?
Thank you
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