Add new minimization heuristics to getting_started_3

.gitignore

@@ -2,6 +2,7 @@
 git_version.py
 
 # custom
+*.txt
 setup.cfg
 .idea
 .DS_Store

demos/getting_started_3.py

@@ -103,10 +103,15 @@ if __name__ == '__main__':
     data = signal_response(mock_position) + N.draw_sample()
 
     # Minimization parameters
-    ic_sampling = ift.GradientNormController(iteration_limit=100)
-    ic_newton = ift.GradInfNormController(
-        name='Newton', tol=1e-7, iteration_limit=35)
-    minimizer = ift.NewtonCG(ic_newton)
+    fo = 'energy0.txt'
+    fs = 'energy1.txt'
+    fi = 'energy2.txt'
+    ic_sampling = ift.AbsDeltaEnergyController(0.5, convergence_level=5,
+                                               iteration_limit=100,
+                                               file_name=fs)
+    ic_newton = ift.GradInfNormController(name='Newton', tol=1e-7,
+                                          iteration_limit=35, file_name=fo)
+    minimizer = ift.NewtonCG(ic_newton, file_name=fi)
 
     # Set up likelihood and information Hamiltonian
     likelihood = ift.GaussianEnergy(mean=data,
@@ -128,7 +133,7 @@ if __name__ == '__main__':
     # Draw new samples to approximate the KL five times
     for i in range(5):
         # Draw new samples and minimize KL
-        KL = ift.MetricGaussianKL(mean, H, N_samples)
+        KL = ift.MetricGaussianKL(mean, H, N_samples, napprox=20)
         KL, convergence = minimizer(KL)
         mean = KL.position
 
@@ -159,3 +164,5 @@ if __name__ == '__main__':
         linewidth=[1.]*len(powers) + [3., 3.])
     plot.output(ny=1, nx=3, xsize=24, ysize=6, name=filename_res)
     print("Saved results as '{}'.".format(filename_res))
+
+    ift.energy_history_analysis(fo, fi, fs, fname='energy_history.png')

nifty5/plot.py

@@ -555,7 +555,7 @@ def energy_history_analysis(fname_outer, fname_inner, fname_sampling,
     tsa, esa, _ = np.loadtxt(fname_sampling, delimiter=' ').T
     tou, eou, _ = np.loadtxt(fname_outer, delimiter=' ').T
     tin, ein, _ = np.loadtxt(fname_inner, delimiter=' ').T
-    t0 = np.min([tsa, tou, tin])
+    t0 = np.min([*tsa, *tou, *tin])
     tsa = (tsa-t0)/3600
     tou = (tou-t0)/3600
     tin = (tin-t0)/3600
@@ -569,11 +569,11 @@ def energy_history_analysis(fname_outer, fname_inner, fname_sampling,
     ax0.legend([p1, p2], [p1.get_label(), p2.get_label()])
     ax1.scatter(tou, eou, marker='>', c='g')
     ax1.set_ylabel('Newton energy')
-    ax1.set_yscale('log')
+    # ax1.set_yscale('log')
     ax1.set_xlabel("Time [h]")
     plt.tight_layout()
     if fname is None:
-        plt.savefig(fname)
-    else:
         plt.show()
+    else:
+        plt.savefig(fname)
     plt.close()