# 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()
