We have done a good job of making the badapted repo devoid of any DARC specific content so that it is entirely general.
But the badapted repo is missing the BayesianAdaptiveDesignGeneratorDARC class which is very general. We need to move this class (and associated helper functions into the badapted repo and out of this one.
By doing this, we create a new class (BayesianAdaptiveDesignGenerator) in the badapted repo which developers can then easily subclass for their own custom experiment toolboxes.
BayesianAdaptiveDesignGeneratorDARC class
[x] move BayesianAdaptiveDesignGeneratorDARC into the badapted repo.
[x] Rename it BayesianAdaptiveDesignGenerator to avoid the DARC related naming
[x] Inherit from DesignGeneratorABC rather than DARCDesignGenerator
[x] update the necessary imports
Then...
[x] We will then use DARCDesignGenerator as the DARC specific class
[x] so BayesianAdaptiveDesignGeneratorDARC will be the concrete class that people use.
[x] Then go through the code (PsychoPy demos, tests, etc) and set the actual concrete design generator as DARCDesignGenerator
We have done a good job of making the
badaptedrepo devoid of any DARC specific content so that it is entirely general.But the
badaptedrepo is missing theBayesianAdaptiveDesignGeneratorDARCclass which is very general. We need to move this class (and associated helper functions into thebadaptedrepo and out of this one.By doing this, we create a new class (
BayesianAdaptiveDesignGenerator) in thebadaptedrepo which developers can then easily subclass for their own custom experiment toolboxes.BayesianAdaptiveDesignGeneratorDARCclassBayesianAdaptiveDesignGeneratorDARCinto thebadaptedrepo.BayesianAdaptiveDesignGeneratorto avoid the DARC related namingDesignGeneratorABCrather thanDARCDesignGeneratorThen...
DARCDesignGeneratoras the DARC specific classBayesianAdaptiveDesignGeneratorDARCwill be the concrete class that people use.DARCDesignGeneratorbadaptedrepo