Merge #67

67: Clean up CalibrateEmulateSample r=bielim a=bielim

This PR is a major clean-up (goal: code hygiene and reduction of the insanely long precompile times, i.e., addressing #65) -- the following changes were made:

(1) Deleted the modules `EKS.jl`, `GPR.jl`, `Histograms.jl`, `problems.jl`, and `spaces.jl`. These modules are not functional and not being developed anymore.

(2) Deleted `test/EKS`, `test/Histograms`, `test/GPR`,  `test/L96m`, as well as `examples/GPR` and `examples/L96`, because they are based on non-functional modules or (in the case of `L96`) because they don't seem to demonstrate any CES functionality.

(3) Deleted `test/Cloudy`, moved and renamed its content (`test/Cloudy/runtests.jl`) to `examples/Cloudy/Cloudy_example.jl`. The Cloudy "test" never was a proper test but rather an example, so it fits much better in the `examples` folder. The Cloudy notebook (`examples/Cloudy/calibrate_emulate_sample_Cloudy_demo.ipynb`) was deleted as it's basically just a more "eye-friendly" version of `Cloudy_example.jl`.

(4) Moved `GModel.jl` to `examples/Cloudy`.  This module shows what a forward model G that maps the parameters u to G(u) could look like, but it does so using Cloudy as an example, and for that reason I never liked the fact that this module was there with all the general-purpose code in the first place. As a result of (3) and (4), there is no more Cloudy dependency in the tests or core CES code.

(5) Generated separate `Project.toml` and `Manifest.toml` files for each example. With this setup, running the core CES code does not require to precompile packages that are only used in the examples (e.g., `DifferentialEquations.jl`) anymore.

(6) Removed unused packages from the main `Project.toml` file

Finally, I also changed the way the `ScikitLearn.jl` imports are handled in `GPEmulator.jl`. At least on my machine, this solves the problems with the seg faults that I mentioned in the discussion to PR #63.

Co-authored-by: Melanie Bieli <melanie.bieli@bluewin.ch>
Co-authored-by: odunbar <odunbar@caltech.edu>

Project.toml

@@ -4,21 +4,13 @@ authors = ["Charles Kawczynski <kawczynski.charles@gmail.com>"]
 version = "0.1.0"
 
 [deps]
-Cloudy = "9e3b23bb-e7cc-4b94-886c-65de2234ba87"
 Conda = "8f4d0f93-b110-5947-807f-2305c1781a2d"
-DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
 GaussianProcesses = "891a1506-143c-57d2-908e-e1f8e92e6de9"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-Optim = "429524aa-4258-5aef-a3af-852621145aeb"
-Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
-Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
 PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 ScikitLearn = "3646fa90-6ef7-5e7e-9f22-8aca16db6324"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
-StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
-StatsPlots = "f3b207a7-027a-5e70-b257-86293d7955fd"
-Sundials = "c3572dad-4567-51f8-b174-8c6c989267f4"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"