Examples
M-LOOP includes a series of example configuration files for each of the controllers and interfaces. The examples can be found in examples folder. For some controllers there are two files, ones ending with _basic_config which includes the standard configuration options and _complete_config which include a comprehensive list of all the configuration options available.
The options available are also comprehensively documented in the :ref:`sec-api` as keywords for each of the classes. However, the quickest and easiest way to learn what options are available, if you are not familiar with python, is to just look at the provided examples.
Each of the example files is used when running tests of M-LOOP. So please copy and modify them elsewhere if you use them as a starting point for your configuration file.
Interfaces
There is currently one interface supported: 'file'. You can specify which interface you want with the option:
interface_type = [name]
The default will be 'file'. The specific options for each of the interfaces are described below.
File Interface
You can change the names of the files used for the file interface and their type. The file interface options are described in file_interface_config.txt.
Controllers
There are currently three controller types supported: 'gaussian_process', 'random' and 'nelder_mead'. The default is 'gaussian_process'. You can set which interface you want to use with the option:
controller_type = [name]
Each of the controllers and their specific options are described below. There is also a set of common options shared by all controllers which is described in controller_options.txt. The common options include the parameter settings and the halting conditions.
Gaussian Process
The Gaussian-process controller is the default controller and is the currently the most sophisticated machine learner algorithm. It uses a Link Gaussian process to develop a model for how the parameters relate to the measured cost, effectively creating a model for how the experiment operates. This model is then used when picking new points to test.
There are two example files for the Gaussian-process controller: gaussian_process_simple_config.txt which contains the basic options.
gaussian_process_complete_config.txt which contains a comprehensive list of options.
Nelder Mead
The Nelder Mead controller implements the Link Nelder-Mead method for optimization. You can control the starting point and size of the initial simplex of the method with the configuration file.
There are two example files for the Nelder-Mead controller: nelder_mead_simple_config.txt which contains the basic options.
nelder_mead_complete_config.txt which contains a comprehensive list of options.
Random
The random optimization algorithm picks parameters randomly from a uniform distribution from within the parameter bounds or trust region.
There are two example files for the random controller: random_simple_config.txt which contains the basic options.
random_complete_config.txt which contains a comprehensive list of options.
Logging
You can control the filename of the logs and also the level which is reported to the file and the console. For more information see Link logging levels. The logging options are described in logging_config.txt.
Extras
Extras refers to options related to post processing your data once the optimization is complete. Currently the only extra option is for visualizations. The extra options are described in extras_config.txt.