From f1a6137b399921d49bf115178054c49c1bdc4626 2019-10-15 14:52:38
From: avaldez <avaldez@igp.gob.pe>
Date: 2019-10-15 14:52:38
Subject: [PATCH] update y fix

---

diff --git a/schainpy/model/graphics/jroplot_spectra.py b/schainpy/model/graphics/jroplot_spectra.py
index 648ccd6..aeb3868 100644
--- a/schainpy/model/graphics/jroplot_spectra.py
+++ b/schainpy/model/graphics/jroplot_spectra.py
@@ -318,6 +318,7 @@ class ACFPlot(Figure):
 
         #z           =  numpy.where(numpy.isfinite(z), z, numpy.NAN)
         shape        =  dataOut.data_acf.shape
+	print "shape_plot",shape
         hei_index    =  numpy.arange(shape[2])
         hei_plot     =  numpy.arange(nSamples)*resFactor
 
@@ -330,7 +331,7 @@ class ACFPlot(Figure):
             hei_plot = numpy.array(nSampleList)*resFactor
 
         if hei_plot[-1] >= hei_index[-1]:
-            print ("La cantidad de puntos en altura es %d y la resolucion es %d Km"%(hei_plot.shape[0],deltaHeight*resFactor ))
+            print ("La cantidad de puntos en altura es %d y la resolucion es %f Km"%(hei_plot.shape[0],deltaHeight*resFactor ))
             raise ValueError, "resFactor %d multiplicado por el valor de %d nSamples  es mayor a %d cantidad total de puntos"%(resFactor,nSamples,hei_index[-1])
 
         #escalamiento  -1 a 1 a resolucion (factor de resolucion en altura)* deltaHeight
@@ -376,8 +377,8 @@ class ACFPlot(Figure):
             if ymin == None: ymin = numpy.nanmin(zdB)
             if ymax == None: ymax = numpy.nanmax(zdB)
 
-            print ("El parametro resFactor es %d y la resolucion en altura es %d"%(resFactor,deltaHeight ))
-            print ("La cantidad de puntos en altura es %d y la nueva resolucion es %d Km"%(hei_plot.shape[0],deltaHeight*resFactor ))
+            print ("El parametro resFactor es %d y la resolucion en altura es %f"%(resFactor,deltaHeight ))
+            print ("La cantidad de puntos en altura es %d y la nueva resolucion es %f Km"%(hei_plot.shape[0],deltaHeight*resFactor ))
             print ("La altura maxima es %d Km"%(hei_plot[-1]*deltaHeight ))
 
             self.isConfig = True
diff --git a/schainpy/model/proc/jroproc_spectra_acf.py b/schainpy/model/proc/jroproc_spectra_acf.py
index 355c4f3..41d39db 100644
--- a/schainpy/model/proc/jroproc_spectra_acf.py
+++ b/schainpy/model/proc/jroproc_spectra_acf.py
@@ -151,24 +151,28 @@ class SpectraAFCProc(ProcessingUnit):
             shape       =  acf.shape            #  nchannels, nprofiles, nsamples
 
             #import matplotlib.pyplot as plt
-            #acf_tmp=acf[0,:,85]
+	    #print "test",acf.shape
+            #acf_tmp=acf[0,:,]
     	    #plt.plot(acf_tmp)
             #plt.show()
-
-    	    for i in range(shape[1]):
-                tmp = numpy.argmax(acf[0,:,i])
-                if i>30:
-                    value  = (acf[0,:,i][tmp+3]+acf[0,:,i][tmp+4])/2.0
-                    acf[0,:,i][tmp] = value
-                    acf[0,:,i][tmp-1] = value
-                    acf[0,:,i][tmp+1] = value
-                    acf[0,:,i][tmp-2] = value
-                    acf[0,:,i][tmp+2] = value
-
-                    import scipy as sp
-                    from scipy import signal
-                    acf[0,:,i] =  sp.signal.medfilt(acf[0,:,i],21)
-
+	    #import time
+    	    #time.sleep(10)
+  	    
+	    for j in range(shape[0]):
+	    	    for i in range(shape[1]):
+		        tmp = numpy.argmax(acf[j,:,i])
+		        if i>30:
+		            value  = (acf[j,:,i][tmp+3]+acf[j,:,i][tmp+4])/2.0
+		            acf[j,:,i][tmp] = value
+		            acf[j,:,i][tmp-1] = value
+		            acf[j,:,i][tmp+1] = value
+		            acf[j,:,i][tmp-2] = value
+		            acf[j,:,i][tmp+2] = value
+
+		            import scipy as sp
+		            from scipy import signal
+		            #acf[3,:,i] =  sp.signal.medfilt(acf[3,:,i],21)
+		    
 
 
     	    #print numpy.argmax(acf[0,:,85])
diff --git a/schainpy/model/proc/jroproc_voltage.py b/schainpy/model/proc/jroproc_voltage.py
index a4c63f7..4f74164 100644
--- a/schainpy/model/proc/jroproc_voltage.py
+++ b/schainpy/model/proc/jroproc_voltage.py
@@ -1276,6 +1276,11 @@ class SSheightProfiles(Operation):
         self.__nProfiles  = dataOut.nProfiles
         self.__nHeis      = dataOut.nHeights
         shape             = dataOut.data.shape #nchannels, nprofiles, nsamples
+	print "input nChannels",self.__nChannels
+	print "input nProfiles",self.__nProfiles
+	print "input nHeis",self.__nHeis
+	print "input Shape",shape
+
 
 
         residue     =  (shape[1] - self.nsamples) % self.step
@@ -1286,7 +1291,10 @@ class SSheightProfiles(Operation):
         numberProfile    =  self.nsamples
         numberSamples    =  (shape[1] - self.nsamples)/self.step
 
-        print "New number of profile: %d, number of height: %d, Resolution %d Km"%(numberProfile,numberSamples,deltaHeight*self.step)
+	print "new numberProfile",numberProfile
+	print "new numberSamples",numberSamples
+
+        print "New number of profile: %d, number of height: %d, Resolution %f Km"%(numberProfile,numberSamples,deltaHeight*self.step)
 
         self.bufferShape  = shape[0], numberSamples, numberProfile  # nchannels, nsamples , nprofiles
         self.profileShape = shape[0], numberProfile, numberSamples  # nchannels, nprofiles, nsamples
@@ -1306,7 +1314,9 @@ class SSheightProfiles(Operation):
             self.isConfig = True
 
         for i in range(self.buffer.shape[1]):
-            self.buffer[:,i]    = numpy.flip(dataOut.data[:,i*self.step:i*self.step + self.nsamples])
+            #self.buffer[:,i]    = numpy.flip(dataOut.data[:,i*self.step:i*self.step + self.nsamples])
+            self.buffer[:,i]    = dataOut.data[:,i*self.step:i*self.step + self.nsamples]
+
             #self.buffer[:,j,self.__nHeis-j*self.step - self.nheights:self.__nHeis-j*self.step] = numpy.flip(dataOut.data[:,j*self.step:j*self.step + self.nheights])
 
         for j in range(self.buffer.shape[0]):