If you are not familiar with the main concepts of Bayesian Optimization, a quick introduction is available :ref:`here <bayesian_optimization>`.
In this tutorial, we will explain how to create a new experiment in which a simple function ( :math:`-{(5 * x - 2.5)}^2 + 5`) is maximized.
Let's say we want to create an experiment called "myExp". The first thing to do is to create the folder ``exp/myExp`` under the limbo root. Then add two files:
...
...
@@ -22,6 +24,8 @@ Next, copy the following content to the ``wscript`` file:
.. code:: python
from waflib.Configure import conf
def options(opt):
pass
...
...
@@ -70,16 +74,26 @@ With this, we can declare the main function:
:linenos:
:lines: 114-123
The full ``main.cpp`` can be found `here <../../src/tutorials/basic_example.cpp>`_
Finally, from the root of limbo, run a build command, with the additional switch ``--exp myExp``: ::
./waf build --exp myExp
Then, an executable named ``myExp`` should be produced under the folder ``build/exp/myExp``.
When running this executable, you should see something similar to this:
These lines show the result of each sample evaluation of the :math:`40` iterations (after the random initialization). In particular, we can see that algorithm progressively converges toward the maximum of the function (:math:`5`) and that the maximum found is located at :math:`x = 0.500014`.
Running the executable also created a folder with a name composed of YOUCOMPUTERHOSTNAME-DATE-HOUR-PID. This folder should contain two files: ::
limbo
|-- YOUCOMPUTERHOSTNAME-DATE-HOUR-PID
+-- samples.dat
+-- aggregated_observations.dat
The file ``samples.dat`` contains the coordinates of the samples that have been evaluated during each iteration, while the file ``aggregated_observations.dat`` contains the corresponding observed values.
