diff --git a/schainpy/model/data/jrodata.py b/schainpy/model/data/jrodata.py
index f962b34..d14b827 100644
--- a/schainpy/model/data/jrodata.py
+++ b/schainpy/model/data/jrodata.py
@@ -297,7 +297,6 @@ class JROData(GenericData):
 
     def getFmax(self):
         PRF = 1. / (self.ippSeconds * self.nCohInt)
-
         fmax = PRF
         return fmax
 
@@ -605,11 +604,9 @@ class Spectra(JROData):
         noise = numpy.zeros(self.nChannels)
 
         for channel in range(self.nChannels):
-            #print "confuse",self.data_spc.dtype
             daux = self.data_spc[channel,
                                  xmin_index:xmax_index, ymin_index:ymax_index]
 
-            #print "HI3.0",(daux.dtype),daux.shape
             noise[channel] = hildebrand_sekhon(daux, self.nIncohInt)
 
         return noise
@@ -634,9 +631,7 @@ class Spectra(JROData):
         return freqrange
 
     def getAcfRange(self, extrapoints=0):
-        #print "miay",self.ippFactor
-        deltafreq = 10. / (self.getFmax() / (self.nFFTPoints * self.ippFactor))
-        #print deltafreq
+        deltafreq = 10. / (  self.getFmax() / (self.nFFTPoints * self.ippFactor)   )
         freqrange = deltafreq * \
             (numpy.arange(self.nFFTPoints + extrapoints) -
              self.nFFTPoints / 2.) - deltafreq / 2
@@ -646,10 +641,11 @@ class Spectra(JROData):
     def getFreqRange(self, extrapoints=0):
 
         deltafreq = self.getFmax() / (self.nFFTPoints * self.ippFactor)
+        #print "deltafreq", deltafreq
         freqrange = deltafreq * \
             (numpy.arange(self.nFFTPoints + extrapoints) -
              self.nFFTPoints / 2.) - deltafreq / 2
-
+        #print "freqrange",freqrange
         return freqrange
 
     def getVelRange(self, extrapoints=0):
diff --git a/schainpy/model/graphics/jroplot_spectra.py b/schainpy/model/graphics/jroplot_spectra.py
index 83ac624..7a43c20 100644
--- a/schainpy/model/graphics/jroplot_spectra.py
+++ b/schainpy/model/graphics/jroplot_spectra.py
@@ -274,7 +274,6 @@ class ACFPlot(Figure):
             folder=None, username=None, password=None,
             xaxis="frequency"):
 
-
         channel0      =  channel
         nSamples      =  nSamples
         resFactor     =  resolutionFactor
@@ -313,12 +312,6 @@ class ACFPlot(Figure):
         shape        =  dataOut.data_acf.shape
         hei_index    =  numpy.arange(shape[2])
         hei_plot     =  numpy.arange(nSamples)*resFactor
-        #print hei_plot
-        #import matplotlib.pyplot as plt
-        #c=z[0,:,0]*15+15
-        #plt.plot(c)
-        #plt.show()
-        #print "HOLA#
 
         if nSampleList    is not  None:
             for nsample in nSampleList:
@@ -335,18 +328,9 @@ class ACFPlot(Figure):
         #escalamiento  -1 a 1 a resolucion (factor de resolucion en altura)* deltaHeight
         min = numpy.min(z[0,:,0])
         max =numpy.max(z[0,:,0])
-
         for i in range(shape[0]):
             for j in range(shape[2]):
                 z[i,:,j]= (((z[i,:,j]-min)/(max-min))*deltaHeight*resFactor + j*deltaHeight)
-                #z[i,:,j]= (z[i,:,j]+1.0)*deltaHeight*dataOut.step/2.0 + j*deltaHeight*dataOut.step
-
-        #print deltaHeight
-        #print resFactor
-        #print numpy.max(z[0,:,0])
-        #import matplotlib.pyplot as plt
-        #plt.plot((z[0,:,0])*deltaHeight)
-        #plt.show()
 
         if xaxis == "frequency":
             x = dataOut.getFreqRange()/1000.
@@ -355,7 +339,8 @@ class ACFPlot(Figure):
             ylabel = "Power (dB)"
 
         elif xaxis == "time":
-            x = dataOut.getAcfRange()
+            delta= dataOut.getAcfRange()[1]-dataOut.getAcfRange()[0]
+            x = dataOut.getAcfRange()+delta/2.0
             zdB = z[channel0,:,hei_plot]
             xlabel = "Time (ms)"
             ylabel = "ACF"
diff --git a/schainpy/model/proc/jroproc_spectra.py b/schainpy/model/proc/jroproc_spectra.py
index 1b54d09..2afb375 100644
--- a/schainpy/model/proc/jroproc_spectra.py
+++ b/schainpy/model/proc/jroproc_spectra.py
@@ -22,20 +22,19 @@ class SpectraProc(ProcessingUnit):
 
     def __updateSpecFromVoltage(self):
 
-        self.dataOut.timeZone = self.dataIn.timeZone
-        self.dataOut.dstFlag = self.dataIn.dstFlag
-        self.dataOut.errorCount = self.dataIn.errorCount
-        self.dataOut.useLocalTime = self.dataIn.useLocalTime
+        self.dataOut.timeZone    = self.dataIn.timeZone
+        self.dataOut.dstFlag     = self.dataIn.dstFlag
+        self.dataOut.errorCount  = self.dataIn.errorCount
+        self.dataOut.useLocalTime= self.dataIn.useLocalTime
         try:
             self.dataOut.processingHeaderObj = self.dataIn.processingHeaderObj.copy()
         except:
             pass
         self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy()
-        self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy()
-        self.dataOut.channelList = self.dataIn.channelList
-        self.dataOut.heightList = self.dataIn.heightList
-        #print self.dataOut.heightList.shape,"spec4"
-        self.dataOut.dtype = numpy.dtype([('real', '<f4'), ('imag', '<f4')])
+        self.dataOut.systemHeaderObj          = self.dataIn.systemHeaderObj.copy()
+        self.dataOut.channelList              = self.dataIn.channelList
+        self.dataOut.heightList               = self.dataIn.heightList
+        self.dataOut.dtype                    = numpy.dtype([('real', '<f4'), ('imag', '<f4')])
 
         self.dataOut.nBaud = self.dataIn.nBaud
         self.dataOut.nCode = self.dataIn.nCode
@@ -65,8 +64,6 @@ class SpectraProc(ProcessingUnit):
         self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList
         self.dataOut.beam.zenithList = self.dataIn.beam.zenithList
 
-        self.dataOut.step = self.dataIn.step #
-
     def __getFft(self):
         """
         Convierte valores de Voltaje a Spectra
@@ -125,7 +122,7 @@ class SpectraProc(ProcessingUnit):
 
         if self.dataIn.type == "Spectra":
             self.dataOut.copy(self.dataIn)
-            print "hi",self.dataOut.ippSeconds
+
             if shift_fft:
                 #desplaza a la derecha en el eje 2 determinadas posiciones
                 shift = int(self.dataOut.nFFTPoints/2)
@@ -156,7 +153,7 @@ class SpectraProc(ProcessingUnit):
             if self.buffer is None:
                 self.buffer = numpy.zeros((self.dataIn.nChannels,
                                            nProfiles,
-                                           self.dataIn.heightList.shape[0]),
+                                           self.dataIn.heightList.shape[0]),#update heightlist
                                           dtype='complex')
 
 
diff --git a/schainpy/model/proc/jroproc_spectra_acf.py b/schainpy/model/proc/jroproc_spectra_acf.py
index 5088a5c..f789021 100644
--- a/schainpy/model/proc/jroproc_spectra_acf.py
+++ b/schainpy/model/proc/jroproc_spectra_acf.py
@@ -134,34 +134,27 @@ class SpectraAFCProc(ProcessingUnit):
         self.dataOut.blockSize = blocksize
         self.dataOut.flagShiftFFT = True
 
-    def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], code=None, nCode=1, nBaud=1):
+    def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], code=None, nCode=1, nBaud=1,real= None, imag=None):
 
         self.dataOut.flagNoData = True
 
         if self.dataIn.type == "Spectra":
             self.dataOut.copy(self.dataIn)
-            #print "hi",self.dataOut.ippSeconds
-
-            spc         = self.dataOut.data_spc
-            data        = numpy.fft.ifft(spc, axis=1)
-            data        = numpy.fft.fftshift(data, axes=(1,))
-            acf         = numpy.abs(data) # Autocorrelacion LLAMAR A ESTE VALOR ACF
-            #acf         = data.imag
-            shape       = acf.shape #nchannels, nprofiles, nsamples
-
-            #import matplotlib.pyplot as plt
-            #plt.plot(acf[0,:,0] / numpy.max(numpy.abs(acf[0,:,0])))
-            #plt.show()
+            spc         =  self.dataOut.data_spc
+            data        =  numpy.fft.ifft(spc, axis=1)
+            data        =  numpy.fft.fftshift(data, axes=(1,))
+            acf         =  numpy.abs(data)     #  Autocorrelacion LLAMAR A ESTE VALOR ACF
+            if real:
+                acf     = data.real
+            if imag:
+                acf     = data.imag
+            shape       =  acf.shape            #  nchannels, nprofiles, nsamples
 
             # Normalizando
             for i in range(shape[0]):
                 for j in range(shape[2]):
                     acf[i,:,j]= acf[i,:,j] / numpy.max(numpy.abs(acf[i,:,j]))
 
-            #import matplotlib.pyplot as plt
-            #plt.plot(acf[0,:,0])
-            #plt.show()
-
             self.dataOut.data_acf = acf
             return True
 
diff --git a/schainpy/model/proc/jroproc_voltage.py b/schainpy/model/proc/jroproc_voltage.py
index 146bd5c..c749abb 100644
--- a/schainpy/model/proc/jroproc_voltage.py
+++ b/schainpy/model/proc/jroproc_voltage.py
@@ -1186,12 +1186,12 @@ class CombineProfiles(Operation):
 
 class SSheightProfiles(Operation):
 
-    step        = None
-    nsamples    = None
-    bufferShape = None
-    profileShape= None
-    sshProfiles = None
-    profileIndex= None
+    step          = None
+    nsamples      = None
+    bufferShape   = None
+    profileShape  = None
+    sshProfiles   = None
+    profileIndex  = None
 
     def __init__(self, **kwargs):
 
@@ -1203,35 +1203,35 @@ class SSheightProfiles(Operation):
         if step == None and nsamples == None:
             raise ValueError, "step or nheights should be specified ..."
 
-        self.step        = step
-        self.nsamples    = nsamples
-        self.__nChannels = dataOut.nChannels
-        self.__nProfiles = dataOut.nProfiles
-        self.__nHeis     = dataOut.nHeights
-        shape            = dataOut.data.shape #nchannels, nprofiles, nsamples
-        #print  "shape",shape
-        #last test
-        residue =  (shape[1] - self.nsamples) % self.step
+        self.step         = step
+        self.nsamples     = nsamples
+        self.__nChannels  = dataOut.nChannels
+        self.__nProfiles  = dataOut.nProfiles
+        self.__nHeis      = dataOut.nHeights
+        shape             = dataOut.data.shape #nchannels, nprofiles, nsamples
+
+
+        residue     =  (shape[1] - self.nsamples) % self.step
         if residue != 0:
             print "The residue is %d, step=%d should be multiple of %d to avoid loss of %d samples"%(residue,step,shape[1] - self.nsamples,residue)
 
-        deltaHeight     = dataOut.heightList[1] - dataOut.heightList[0]
-        numberProfile   = self.nsamples
-        numberSamples   = (shape[1] - self.nsamples)/self.step
+        deltaHeight      =  dataOut.heightList[1] - dataOut.heightList[0]
+        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)
 
         self.bufferShape  = shape[0], numberSamples, numberProfile  # nchannels, nsamples , nprofiles
         self.profileShape = shape[0], numberProfile, numberSamples  # nchannels, nprofiles, nsamples
 
-        self.buffer      = numpy.zeros(self.bufferShape , dtype=numpy.complex)
-        self.sshProfiles = numpy.zeros(self.profileShape, dtype=numpy.complex)
+        self.buffer       = numpy.zeros(self.bufferShape , dtype=numpy.complex)
+        self.sshProfiles  = numpy.zeros(self.profileShape, dtype=numpy.complex)
 
     def run(self, dataOut, step, nsamples):
 
-        dataOut.flagNoData = True
-        dataOut.flagDataAsBlock =False
-        profileIndex = None
+        dataOut.flagNoData      = True
+        dataOut.flagDataAsBlock = False
+        profileIndex            = None
 
         if not self.isConfig:
             self.setup(dataOut, step=step , nsamples=nsamples)
@@ -1244,12 +1244,10 @@ class SSheightProfiles(Operation):
         for j in range(self.buffer.shape[0]):
             self.sshProfiles[j] = numpy.transpose(self.buffer[j])
 
-        profileIndex =  self.nsamples
-        deltaHeight  =  dataOut.heightList[1] - dataOut.heightList[0]
-        ippSeconds   =  (deltaHeight*1.0e-6)/(0.15)
+        profileIndex  =  self.nsamples
+        deltaHeight   =  dataOut.heightList[1] - dataOut.heightList[0]
+        ippSeconds    =  (deltaHeight*1.0e-6)/(0.15)
 
-        #print "hi",dataOut.ippSeconds
-        #print ippSeconds
         dataOut.data            = self.sshProfiles
         dataOut.flagNoData      = False
         dataOut.heightList      = numpy.arange(self.buffer.shape[1]) *self.step*deltaHeight + dataOut.heightList[0]
@@ -1258,7 +1256,6 @@ class SSheightProfiles(Operation):
         dataOut.flagDataAsBlock = True
         dataOut.ippSeconds      = ippSeconds
         dataOut.step            = self.step
-        #print dataOut.ippSeconds
 
 
 # import collections