Improve documentation

[kiudee]

To make the library more accessible, all the publicly facing methods should be properly documented. In addition example Jupyter notebooks could be beneficial to illustrate how the library is to be used. Differences to the parent library scikit-optimize need to be clear.

To do

• [x] Set up API reference in sphinx
• [x] Write the docstrings for
  • [x] Optimizer(...)
  • [x] Optimizer.tell(...)
  • [x] Optimizer.ask()
  • [x] Optimizer.run(...)
  • [x] BayesGPR.theta (property)
  • [x] BayesGPR.noise_set_to_zero (context manager)
  • [x] BayesGPR.sample(...)
  • [x] BayesGPR.fit(...)
  • [x] BayesGPR.sample_y(...)
  • [x] Acquisition functions:
    • [x] PVRS
    • [x] MaxValueSearch
    • [x] ExpectedImprovement
    • [x] TopTwoEI
    • [x] LCB
    • [x] Expectation
    • [x] ThompsonSampling
    • [x] VarianceReduction
• [ ] Write example notebooks for
  • [x] How to fit a BayesGPR to a simple noisy 1d function
  • [x] How to optimize a simple noisy 1d function
  • [ ] How to warm start an optimization
  • [ ] How to save/resume
  • [ ] How to save the hyperposterior and load it for the next optimization
• [ ] Write usage instructions in sphinx
• [x] Link notebooks to sphinx