Python Module for BayesOptContinuous. More...
Inheritance diagram for bayesoptmodule.BayesOptContinuous:
Collaboration diagram for bayesoptmodule.BayesOptContinuous:
Public Member Functions | |
| def | __init__ (self, n_dim) |
| Let's define the parameters. More... | |
| def | parameters (self) |
| def | parameters (self, params) |
| def | lower_bound (self) |
| def | lower_bound (self, lb) |
| def | upper_bound (self) |
| def | upper_bound (self, ub) |
| def | evaluateSample (self, x_in) |
| Function for testing. More... | |
| def | optimize (self) |
| Main function. More... | |
Public Attributes | |
| params | |
| Library parameters. | |
| n_dim | |
| n dimensions | |
| lb | |
| Lower bounds. | |
| ub | |
| Upper bounds. | |
Detailed Description
Python Module for BayesOptContinuous.
Python module to get run BayesOpt library in a OO pattern. The objective module should inherit this one and override evaluateSample.
Definition at line 38 of file bayesoptmodule.py.
Constructor & Destructor Documentation
◆ __init__()
| def bayesoptmodule.BayesOptContinuous.__init__ | ( | self, | |
| n_dim | |||
| ) |
Let's define the parameters.
For different options: see parameters.h and parameters.cpp . If a parameter is not defined, it will be automatically set to a default value.
Definition at line 45 of file bayesoptmodule.py.
Member Function Documentation
◆ evaluateSample()
| def bayesoptmodule.BayesOptContinuous.evaluateSample | ( | self, | |
| x_in | |||
| ) |
Function for testing.
It should be overriden.
Definition at line 81 of file bayesoptmodule.py.
Referenced by bayesoptmodule.BayesOptContinuous.optimize(), bayesoptmodule.BayesOptDiscrete.optimize(), and bayesoptmodule.BayesOptCategorical.optimize().
◆ optimize()
| def bayesoptmodule.BayesOptContinuous.optimize | ( | self | ) |
Main function.
Starts the optimization process.
Definition at line 85 of file bayesoptmodule.py.
References SystemCallsBranin.evaluateSample(), ExampleQuadratic.evaluateSample(), ExampleDisc.evaluateSample(), bayesoptmodule.BayesOptContinuous.evaluateSample(), bayesopt::BayesOptBase.evaluateSample(), XMLCallsBranin.evaluateSample(), bayesoptmodule.BayesOptContinuous.lb, bayesoptmodule.BayesOptContinuous.n_dim, bayesoptmodule.BayesOptContinuous.params, bayesopt::AtomicKernel.params, and bayesoptmodule.BayesOptContinuous.ub.
The documentation for this class was generated from the following file:
