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time domain noise plot for harmonics

tags/1.6.1
Trevor Irons 5 years ago
parent
commit
596e5bd808
1 changed files with 44 additions and 28 deletions
  1. 44
    28
      akvo/tressel/mrsurvey.py

+ 44
- 28
akvo/tressel/mrsurvey.py View File

@@ -560,17 +560,25 @@ class GMRDataProcessor(SNMRDataProcessor):
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             plot = should Akvo plot the results 
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             canvas = mpl plotting axis      
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         """
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+        TDPlot = True
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+        
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         if plot:
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             canvas.reAx2(shy=False)
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-            canvas.ax1.set_ylabel(r"signal [nV]", fontsize=8)
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-            #canvas.ax2.set_xlabel(r"time [s]", fontsize=8)
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-            canvas.ax2.set_ylabel(r"signal [nV]", fontsize=8)
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-            canvas.ax2.set_xlabel(r"frequency [Hz]", fontsize=8)
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-            canvas.ax1.set_yscale('log')
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-            canvas.ax2.set_yscale('log')
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+            canvas.ax1.set_ylabel(r"signal (nV)", fontsize=8)
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+            canvas.ax2.set_ylabel(r"signal (nV)", fontsize=8)
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+            if TDPlot:
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+                canvas.ax2.set_xlabel(r"time (s)", fontsize=8)
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+            else:
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+                canvas.ax2.set_xlabel(r"frequency (Hz)", fontsize=8)
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+                canvas.ax1.set_yscale('log')
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+                canvas.ax2.set_yscale('log')
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+
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+
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+
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         # Data
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         iFID = 0
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+
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         # stores previous f0 as starting point in non-linear search 
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         f0p = {} 
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         f1p = {} 
@@ -592,19 +600,23 @@ class GMRDataProcessor(SNMRDataProcessor):
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                         mmaxd = 0
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                         if procRefs: 
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                             for ichan in self.DATADICT[pulse]["rchan"]:
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-                                #canvas.ax1.plot( self.DATADICT[pulse]["TIMES"], 1e9*self.DATADICT[pulse][ichan][ipm][istack], alpha=.5) 
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-                                #mmaxr = max( mmaxr, np.max(1e9*self.DATADICT[pulse][ichan][ipm][istack])) 
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-                                ww = np.fft.fftfreq(len(self.DATADICT[pulse][ichan][ipm][istack]), d=self.dt)
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-                                X = np.fft.rfft(self.DATADICT[pulse][ichan][ipm][istack])
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-                                canvas.ax1.plot(np.abs(ww[0:len(X)]), np.abs(X), alpha=.5)
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+                                if TDPlot:
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+                                    canvas.ax1.plot( self.DATADICT[pulse]["TIMES"], 1e9*self.DATADICT[pulse][ichan][ipm][istack], alpha=.5) 
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+                                    mmaxr = max( mmaxr, np.max(1e9*self.DATADICT[pulse][ichan][ipm][istack])) 
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+                                else:
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+                                    ww = np.fft.fftfreq(len(self.DATADICT[pulse][ichan][ipm][istack]), d=self.dt)
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+                                    X = np.fft.rfft(self.DATADICT[pulse][ichan][ipm][istack])
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+                                    canvas.ax1.plot(np.abs(ww[0:len(X)]), np.abs(X), alpha=.5)
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                             canvas.ax1.set_prop_cycle(None)
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                             #canvas.ax1.set_ylim(-mmaxr, mmaxr) 
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                         for ichan in self.DATADICT[pulse]["chan"]:
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-                            #canvas.ax2.plot( self.DATADICT[pulse]["TIMES"], 1e9*self.DATADICT[pulse][ichan][ipm][istack], alpha=.5) 
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-                            #mmaxd = max( mmaxd, np.max(1e9*self.DATADICT[pulse][ichan][ipm][istack])) 
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-                            ww = np.fft.fftfreq(len(self.DATADICT[pulse][ichan][ipm][istack]), d=self.dt)
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-                            X = np.fft.rfft(self.DATADICT[pulse][ichan][ipm][istack])
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-                            canvas.ax2.plot(np.abs(ww[0:len(X)]), np.abs(X), alpha=.5)
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+                            if TDPlot:
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+                                canvas.ax2.plot( self.DATADICT[pulse]["TIMES"], 1e9*self.DATADICT[pulse][ichan][ipm][istack], alpha=.5) 
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+                                mmaxd = max( mmaxd, np.max(1e9*self.DATADICT[pulse][ichan][ipm][istack])) 
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+                            else:
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+                                ww = np.fft.fftfreq(len(self.DATADICT[pulse][ichan][ipm][istack]), d=self.dt)
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+                                X = np.fft.rfft(self.DATADICT[pulse][ichan][ipm][istack])
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+                                canvas.ax2.plot(np.abs(ww[0:len(X)]), np.abs(X), alpha=.5)
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                         canvas.ax2.set_prop_cycle(None)
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                         #canvas.ax2.set_ylim(-mmaxd, mmaxd)
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                     if procRefs: 
@@ -637,12 +649,14 @@ class GMRDataProcessor(SNMRDataProcessor):
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                                         f1p[ichan], f1K1, f1KN, f1Ks, Bounds, Nsearch ) 
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                             # plot
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                             if plot:
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-                                #canvas.ax1.plot( self.DATADICT[pulse]["TIMES"], 1e9*self.DATADICT[pulse][ichan][ipm][istack], \
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-                                #    label = pulse + " ipm=" + str(ipm) + " istack=" + str(istack) + " rchan="  + str(ichan))
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-                                ww = np.fft.fftfreq(len(self.DATADICT[pulse][ichan][ipm][istack]), d=self.dt)
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-                                X = np.fft.rfft(self.DATADICT[pulse][ichan][ipm][istack])
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-                                canvas.ax1.plot(np.abs(ww[0:len(X)]), np.abs(X),\
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-                                label = pulse + " ipm=" + str(ipm) + " istack=" + str(istack) + " rchan="  + str(ichan))
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+                                if TDPlot:
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+                                    canvas.ax1.plot( self.DATADICT[pulse]["TIMES"], 1e9*self.DATADICT[pulse][ichan][ipm][istack], \
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+                                        label = pulse + " ipm=" + str(ipm) + " istack=" + str(istack) + " rchan="  + str(ichan))
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+                                else:
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+                                    ww = np.fft.fftfreq(len(self.DATADICT[pulse][ichan][ipm][istack]), d=self.dt)
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+                                    X = np.fft.rfft(self.DATADICT[pulse][ichan][ipm][istack])
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+                                    canvas.ax1.plot(np.abs(ww[0:len(X)]), np.abs(X),\
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+                                    label = pulse + " ipm=" + str(ipm) + " istack=" + str(istack) + " rchan="  + str(ichan))
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                     for ichan in self.DATADICT[pulse]["chan"]:
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                         if nF == 1:
@@ -675,12 +689,14 @@ class GMRDataProcessor(SNMRDataProcessor):
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                         # plot
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                         if plot:
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-                            #canvas.ax2.plot( self.DATADICT[pulse]["TIMES"], 1e9*self.DATADICT[pulse][ichan][ipm][istack], \
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-                            #    label = pulse + " ipm=" + str(ipm) + " istack=" + str(istack) + " chan="  + str(ichan))
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-                            ww = np.fft.fftfreq(len(self.DATADICT[pulse][ichan][ipm][istack]), d=self.dt)
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-                            X = np.fft.rfft(self.DATADICT[pulse][ichan][ipm][istack])
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-                            canvas.ax2.plot(np.abs(ww[0:len(X)]), np.abs(X), \
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-                                label = pulse + " ipm=" + str(ipm) + " istack=" + str(istack) + " chan="  + str(ichan))
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+                            if TDPlot:
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+                                canvas.ax2.plot( self.DATADICT[pulse]["TIMES"], 1e9*self.DATADICT[pulse][ichan][ipm][istack], \
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+                                    label = pulse + " ipm=" + str(ipm) + " istack=" + str(istack) + " chan="  + str(ichan))
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+                            else:
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+                                ww = np.fft.fftfreq(len(self.DATADICT[pulse][ichan][ipm][istack]), d=self.dt)
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+                                X = np.fft.rfft(self.DATADICT[pulse][ichan][ipm][istack])
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+                                canvas.ax2.plot(np.abs(ww[0:len(X)]), np.abs(X), \
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+                                    label = pulse + " ipm=" + str(ipm) + " istack=" + str(istack) + " chan="  + str(ichan))
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                     if plot:
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                         if procRefs: 

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