More tweaks to the GUI for better use experience.

akvo/gui/akvoGUI.py

@@ -1024,6 +1024,7 @@ class ApplicationWindow(QtWidgets.QMainWindow):
         self.ui.BandPassBox.setEnabled(False)
         self.ui.downSampleGroupBox.setEnabled(False)
         self.ui.windowFilterGroupBox.setEnabled(False)
+        self.ui.harmonicBox.setEnabled(False)
 #        self.ui.despikeGroupBox.setEnabled(False)
         self.ui.adaptBox.setEnabled(False)
         self.ui.adaptFDBox.setEnabled(False)
@@ -1069,12 +1070,14 @@ class ApplicationWindow(QtWidgets.QMainWindow):
         # Harmonic
         self.ui.harmonicBox.setEnabled(True)
         self.ui.harmonicBox.setChecked(True)
+        self.LCDHarmonics()
+        self.LCDHarmonics2()
 
         # sum group box
         try:
             if len(self.dataChan) > 1:
                 self.ui.sumDataBox.setEnabled(True)
-                self.ui.sumDataBox.setChecked(True)
+                self.ui.sumDataBox.setChecked(False)
         except:
             pass
 
@@ -1157,11 +1160,11 @@ class ApplicationWindow(QtWidgets.QMainWindow):
                 self.YamlNode.Processing["Harmonic modelling"]["f1Ks"] = str( self.ui.f1KsSpin.value() )
                 self.YamlNode.Processing["Harmonic modelling"]["f1"] = str( self.ui.f1Spin.value() )
             self.Log()
-        else:
-            err_msg = "Harmonic modelling noise cancellation has already been applied!"
-            reply = QtWidgets.QMessageBox.critical(self, 'Error', 
-                err_msg) 
-            return 
+        #else:
+        #    err_msg = "Harmonic modelling noise cancellation has already been applied!"
+        #    reply = QtWidgets.QMessageBox.critical(self, 'Error', 
+        #        err_msg) 
+        #    return 
 
         self.lock("harmonic noise modelling")
 

akvo/gui/main.ui

@@ -1154,9 +1154,6 @@ background: dark grey;
                </item>
                <item row="4" column="2">
                 <widget class="QLCDNumber" name="lcdH1F">
-                 <property name="enabled">
-                  <bool>false</bool>
-                 </property>
                  <property name="styleSheet">
                   <string notr="true">#lcdH1F {
 color: green;

akvo/tressel/harmonic.py

@@ -40,7 +40,7 @@ def harmonicNorm (f0, sN, fs, t, k1, kN, ks):
 def minHarmonic(sN, fs, t, f0, k1, kN, ks):
     
     # 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 )
+    res = minimize(harmonicNorm, np.array((f0)), args=(sN, fs, t, k1, kN, ks), jac='2-point', method='BFGS') # hess=None, bounds=None )
     
     #############
     # Reduced N #
@@ -51,11 +51,12 @@ def minHarmonic(sN, fs, t, f0, k1, kN, ks):
     ########## 
     # Bounds #
     ##########
-    print("bounded search for f0", f0)
-    bnds = ( (f0-0.125, f0+0.125), )
+    #print("bounded search for f0 with 10", f0)
+    #bnds = ( (f0-0.125, f0+0.125), )
     #print("len f0", len( [f0,] ))
     #print("len bnds", len(bnds) )
-    res = minimize(harmonicNorm, (f0,), args=(sN, fs, t, k1, kN, ks), jac='2-point', method='L-BFGS-B', bounds=bnds ) # hess=None, bounds=None )
+    #res = minimize(harmonicNorm, (f0,), args=(sN, fs, t, k1, kN, ks), jac='2-point', method='L-BFGS-B', bounds=bnds ) # hess=None, bounds=None )
+    #res = minimize(harmonicNorm, (f0,), args=(sN, fs, t, k1, 10, ks), jac='2-point', method='L-BFGS-B', bounds=bnds ) # hess=None, bounds=None )
     
     #print(res)
     #print ( "guess", guessf0(  harmonicEuler(sN, fs, t, res.x[0], k1, kN, ks), fs  ) )

akvo/tressel/mrsurvey.py

@@ -2002,10 +2002,12 @@ class GMRDataProcessor(SNMRDataProcessor):
         self.samp /= dec
         self.dt   = 1./self.samp       
 
-        if truncate:
-            itrunc = (int)( 1e-3*truncate*self.samp )
         iFID = 0  
         for pulse in self.DATADICT["PULSES"]:
+            RSTIMES = self.DATADICT[pulse]["TIMES"][::dec]
+            if truncate:
+                itrunc = (int)( 1e-3*truncate*self.samp )
+                RSTIMES = RSTIMES[0:itrunc]
             for ipm in range(self.DATADICT["nPulseMoments"]):
                 for istack in self.DATADICT["stacks"]:
                     if plot:
@@ -2014,16 +2016,18 @@ class GMRDataProcessor(SNMRDataProcessor):
                         # trim off indices that don't divide evenly
                         ndi = np.shape(self.DATADICT[pulse][ichan][ipm][istack])[0]%dec
                         if ndi:
-                            [self.DATADICT[pulse][ichan][ipm][istack], RSTIMES] = signal.resample(self.DATADICT[pulse][ichan][ipm][istack][0:-ndi],\
-                                         len(self.DATADICT[pulse][ichan][ipm][istack][0:-ndi])//dec,\
-                                         self.DATADICT[pulse]["TIMES"][0:-ndi], window='hamm')
+                            #[self.DATADICT[pulse][ichan][ipm][istack], RSTIMES] = signal.resample(self.DATADICT[pulse][ichan][ipm][istack][0:-ndi],\
+                            #             len(self.DATADICT[pulse][ichan][ipm][istack][0:-ndi])//dec,\
+                            #             self.DATADICT[pulse]["TIMES"][0:-ndi], window='hamm')
+                            self.DATADICT[pulse][ichan][ipm][istack] = signal.decimate(self.DATADICT[pulse][ichan][ipm][istack], dec, n=None, ftype='iir', zero_phase=True)
                         else:
-                            [self.DATADICT[pulse][ichan][ipm][istack], RSTIMES] = signal.resample(self.DATADICT[pulse][ichan][ipm][istack],\
-                                         len(self.DATADICT[pulse][ichan][ipm][istack])//dec,\
-                                         self.DATADICT[pulse]["TIMES"], window='hamm')
+                            #[self.DATADICT[pulse][ichan][ipm][istack], RSTIMES] = signal.resample(self.DATADICT[pulse][ichan][ipm][istack],\
+                            #             len(self.DATADICT[pulse][ichan][ipm][istack])//dec,\
+                            #             self.DATADICT[pulse]["TIMES"], window='hamm')
+                            self.DATADICT[pulse][ichan][ipm][istack] = signal.decimate(self.DATADICT[pulse][ichan][ipm][istack], dec, n=None, ftype='iir', zero_phase=True)
                         if truncate:
                             self.DATADICT[pulse][ichan][ipm][istack] = self.DATADICT[pulse][ichan][ipm][istack][0:itrunc]
-                            RSTIMES = RSTIMES[0:itrunc]
+
                     if plot:
                         for ichan in self.DATADICT[pulse]["chan"]:
                             canvas.ax2.plot( RSTIMES, 1e9*self.DATADICT[pulse][ichan][ipm][istack], \