faster params

demos/variational_inference_visualized.py

@@ -82,10 +82,10 @@ def main():
     n_samples = 100
     minimizer = ift.NewtonCG(
         ift.GradientNormController(iteration_limit=3, name='Mini'))
-    IC = ift.StochasticAbsDeltaEnergyController(0.1, iteration_limit=20,
+    IC = ift.StochasticAbsDeltaEnergyController(0.5, iteration_limit=20,
                                                 name='advi')
-    stochastic_minimizer_mf = ift.ADVIOptimizer(IC, eta = 0.5)
-    stochastic_minimizer_fc = ift.ADVIOptimizer(IC, eta = 0.5)
+    stochastic_minimizer_mf = ift.ADVIOptimizer(IC, eta = 0.3)
+    stochastic_minimizer_fc = ift.ADVIOptimizer(IC, eta = 0.3)
     posmg = posgeo = posmf = posfc = ift.from_random(ham.domain, 'normal')
     fc = ift.FullCovarianceVI(posfc, ham, 10, False, initial_sig=0.01)
     mf = ift.MeanFieldVI(posmf, ham, 10, False, initial_sig=0.01)
@@ -96,8 +96,9 @@ def main():
     def update_plot(runs):
         for axx, (nn, kl, pp, sam) in zip(axs,runs):
             axx.clear()
-            axx.imshow(z.T, origin='lower', norm=LogNorm(vmin=1e-3, vmax=np.max(z)),
-                       cmap='gist_earth_r', extent=x_limits_scaled + y_limits)
+            axx.imshow(z.T, origin='lower',  cmap='gist_earth_r',
+                       norm=LogNorm(vmin=1e-3, vmax=np.max(z)),
+                       extent=x_limits_scaled + y_limits)
             xs, ys = [], []
             if sam:
                 samples = (samp + pp for samp in kl.samples)
@@ -113,8 +114,9 @@ def main():
                 my += b
             mx /= n_samples
             my /= n_samples
-            axx.scatter(np.array(xs)*scale, np.array(ys), label=f'{nn} samples')
-            axx.scatter(mx*scale, my, label=f'{nn} mean')
+            axx.scatter(np.array(xs)*scale, np.array(ys),
+                        label = f'{nn} samples')
+            axx.scatter(mx*scale, my, label = f'{nn} mean')
             axx.scatter(mapx*scale, mapy, label = 'MAP')
             axx.scatter(meanx*scale, meany, label = 'Posterior mean')
             axx.set_title(nn)
@@ -131,13 +133,13 @@ def main():
         plt.tight_layout()
         plt.draw()
         plt.pause(2.0)
-    
+
     for ii in range(20):
         if ii % 2 == 0:
-            # Resample
+            # Resample GeoVI and MGVI
             mgkl = ift.MetricGaussianKL(posmg, ham, n_samples, False)
-            mini_samp = ift.NewtonCG(ift.AbsDeltaEnergyController(1E-8,
-                                                                  iteration_limit=5))
+            mini_samp = ift.NewtonCG(
+                    ift.AbsDeltaEnergyController(1E-8, iteration_limit=5))
             geokl = ift.GeoMetricKL(posgeo, ham, n_samples, mini_samp, False)
 
             runs = (("MGVI", mgkl, posmg, True),