# get response from the generative model response = genAgent.getResponses(rod, frame, 1) # plot selected stimuli plotter.plotStimuli() # plot updated parameter values based on mean and MAP plotter.plotParameterValues() # the parameter distributions may be plotted at most once (so comment out at least one) # plot parameter distributions of current trial # plotter.plotParameterDistributions() # plot parameter distributions of each trial as surfaces plotter.plotParameterDistributions(projection='3d') # the negative log likelihood may be plotted at most once (so comment out at least one) # plot negative log likelihood of responses thus far as a contour plot # plotter.plotNegLogLikelihood() # plot negative log likelihood of responses thus far as a surface plotter.plotNegLogLikelihood(projection='3d') # actually plot all the figures plotter.plot() # add data to psi object psi.addData(response)
# get stimulus from psi object rod, frame = psi.stim # get response from the generative model response = genAgent.getResponses(rod, frame, 1) # plot selected stimuli plotter.plotStimuli() # plot updated parameter values based on mean and MAP plotter.plotParameterValues() # the parameter distributions may be plotted at most once (so comment out at least one) # plot parameter distributions of current trial plotter.plotParameterDistributions() # plot parameter distributions of each trial as surfaces # plotter.plotParameterDistributions(projection='3d') # the negative log likelihood may be plotted at most once (so comment out at least one) # plot negative log likelihood of responses thus far as a contour plot plotter.plotNegLogLikelihood() # plot negative log likelihood of responses thus far as a surface # plotter.plotNegLogLikelihood(projection='3d') # plot parameter value distribution standard deviations of each trial plotter.plotParameterStandardDeviations()