Generate plots

[suman1209]

Task Details

the task is to generate the performance plots after training the diffusion model

TODOs

• [ ] inside main.py , use irene.methods.MyAlgorithm and get the relevant final plots

• [x] update the code to use comapare against all three baselines of "RandomSearch", "Gaussian Process" and "Deep Gaussian Process"

[suman1209]

You can now generate plots by running main.py in the 'main' branch, Please adjust the timesteps in the inference and the epochs to play around and experiment with results. I noticed that it takes a very long time for sampling / recommendations when you use T = 1000

[santanamartinir]

I created a plotting.py to compare against all three baselines using the .json inside /results

[suman1209]

There are path related things that need to be checked when running in your local pc, but running main.py should give you some results like the one below