be more fussy about convergence

demos/log_normal_wiener_filter.py

@@ -47,7 +47,7 @@ if __name__ == "__main__":
 
     # Wiener filter
     m0 = ift.Field.zeros(harmonic_space)
-    ctrl = ift.GradientNormController(verbose=False, tol_abs_gradnorm=1)
+    ctrl = ift.GradientNormController(verbose=False, tol_abs_gradnorm=0.0001)
     ctrl2 = ift.GradientNormController(verbose=True, tol_abs_gradnorm=0.1,
                                        name="outer")
     inverter = ift.ConjugateGradient(controller=ctrl)

nifty/minimization/line_search_strong_wolfe.py

@@ -104,7 +104,10 @@ class LineSearchStrongWolfe(LineSearch):
         old_phi_0 = f_k_minus_1
         phi_0 = le_0.value
         phiprime_0 = le_0.directional_derivative
-        if phiprime_0 >= 0:
+        if phiprime_0 == 0:
+            dobj.mprint("Directional derivative is zero; assuming convergence")
+            return energy
+        if phiprime_0 > 0:
             dobj.mprint("Error: search direction is not a descent direction")
             raise ValueError("search direction must be a descent direction")