More tweaks to harmonic modelling

akvo/gui/akvoGUI.py

             self.Log()
         else:
             err_msg = "Harmonic modelling noise cancellation has already been applied!"
-            reply =QtWidgets.QMessageBox.critical(self, 'Error', 
+            reply = QtWidgets.QMessageBox.critical(self, 'Error', 
                 err_msg) 
             return 
 

akvo/gui/main.ui

                   <number>1</number>
                  </property>
                  <property name="maximum">
-                  <number>10</number>
+                  <number>100</number>
                  </property>
                  <property name="value">
                   <number>1</number>

akvo/tressel/harmonic.py

     # CG, BFGS, Newton-CG, L-BFGS-B, TNC, SLSQP, dogleg, trust-ncg, trust-krylov, trust-exact and trust-constr
     res = minimize(harmonicNorm, np.array((f0)), args=(sN, fs, t, k1, kN, ks), jac='2-point', method='BFGS') # hess=None, bounds=None )
     #print(res)
+    #print ( "guess", guessf0(  harmonicEuler(sN, fs, t, res.x[0], k1, kN, ks), fs  ) )
     return harmonicEuler(sN, fs, t, res.x[0], k1, kN, ks)#[0]
 
 def harmonicEuler2 ( sN, fs, t, f0, f0k1, f0kN, f0ks, f1, f1k1, f1kN, f1ks ): 
 def minHarmonic2(sN, fs, t, f0, f0k1, f0kN, f0ks, f1, f1k1, f1kN, f1ks):
     # CG, BFGS, Newton-CG, L-BFGS-B, TNC, SLSQP, dogleg, trust-ncg, trust-krylov, trust-exact and trust-constr
     res = minimize(harmonic2Norm, np.array((f0, f1)), args=(sN, fs, t, f0k1, f0kN, f0ks, f1k1,f1kN, f1ks), jac='2-point', method='BFGS') # hess=None, bounds=None )
-    print(res)
+    #print(res)
+    #print ( "guess", guessf0(harmonicEuler2(sN, fs, t, res.x[0], f0k1, f0kN, f0ks, res.x[1], f1k1, f1kN, f1ks), fs)  )
     return harmonicEuler2(sN, fs, t, res.x[0], f0k1, f0kN, f0ks, res.x[1], f1k1, f1kN, f1ks)#[0]
 
 def guessf0( sN, fs ):