diff --git a/GPy/examples/dimensionality_reduction.py b/GPy/examples/dimensionality_reduction.py index ce1c89e8..f1df3cf9 100644 --- a/GPy/examples/dimensionality_reduction.py +++ b/GPy/examples/dimensionality_reduction.py @@ -340,7 +340,7 @@ def bgplvm_simulation(optimize=True, verbose=1, gtol=.05) if plot: m.X.plot("BGPLVM Latent Space 1D") - m.kern.plot_ARD('BGPLVM Simulation ARD Parameters') + m.kern.plot_ARD() return m def gplvm_simulation(optimize=True, verbose=1, @@ -364,7 +364,7 @@ def gplvm_simulation(optimize=True, verbose=1, gtol=.05) if plot: m.X.plot("BGPLVM Latent Space 1D") - m.kern.plot_ARD('BGPLVM Simulation ARD Parameters') + m.kern.plot_ARD() return m def ssgplvm_simulation(optimize=True, verbose=1, plot=True, plot_sim=False, @@ -388,7 +388,7 @@ def ssgplvm_simulation(optimize=True, verbose=1, gtol=.05) if plot: m.X.plot("SSGPLVM Latent Space 1D") - m.kern.plot_ARD('SSGPLVM Simulation ARD Parameters') + m.kern.plot_ARD() return m def bgplvm_simulation_missing_data(optimize=True, verbose=1, @@ -418,7 +418,7 @@ def bgplvm_simulation_missing_data(optimize=True, verbose=1, gtol=.05) if plot: m.X.plot("BGPLVM Latent Space 1D") - m.kern.plot_ARD('BGPLVM Simulation ARD Parameters') + m.kern.plot_ARD() return m def bgplvm_simulation_missing_data_stochastics(optimize=True, verbose=1, @@ -448,7 +448,7 @@ def bgplvm_simulation_missing_data_stochastics(optimize=True, verbose=1, gtol=.05) if plot: m.X.plot("BGPLVM Latent Space 1D") - m.kern.plot_ARD('BGPLVM Simulation ARD Parameters') + m.kern.plot_ARD() return m @@ -469,7 +469,7 @@ def mrd_simulation(optimize=True, verbose=True, plot=True, plot_sim=True, **kw): m.optimize(messages=verbose, max_iters=8e3) if plot: m.X.plot("MRD Latent Space 1D") - m.plot_scales("MRD Scales") + m.plot_scales() return m def mrd_simulation_missing_data(optimize=True, verbose=True, plot=True, plot_sim=True, **kw): @@ -496,7 +496,7 @@ def mrd_simulation_missing_data(optimize=True, verbose=True, plot=True, plot_sim m.optimize('bfgs', messages=verbose, max_iters=8e3, gtol=.1) if plot: m.X.plot("MRD Latent Space 1D") - m.plot_scales("MRD Scales") + m.plot_scales() return m def brendan_faces(optimize=True, verbose=True, plot=True):