diff --git a/schainpy/scripts/optimun_offset.py b/schainpy/scripts/optimun_offset.py
new file mode 100644
index 0000000..8ebcba0
--- /dev/null
+++ b/schainpy/scripts/optimun_offset.py
@@ -0,0 +1,113 @@
+import h5py
+import numpy
+import matplotlib.pyplot as plt
+import glob
+import os
+ 
+#----------------------    Functions     ---------------------
+ 
+def findFiles(path):
+    
+    dirList = []
+    fileList = []
+    
+    for thisPath in os.listdir(path):
+        dirList.append(os.path.join(path,thisPath))
+        dirList.sort()
+    
+    for thisDirectory in dirList:
+		files = glob.glob1(thisDirectory, "*.hdf5")
+		files.sort()
+		for thisFile in files:
+			fileList.append(os.path.join(thisDirectory,thisFile))   
+    
+    return fileList
+ 
+def readFiles(fileList):
+    
+    meteors_array = numpy.zeros((1,4))
+    
+    for thisFile in fileList:
+        
+        #Leer
+		f1 = h5py.File(thisFile,'r')
+		grp1 = f1['Data']
+		grp2 = grp1['data_output']     
+		meteors1 = grp2['table0'][:]
+		meteors_array = numpy.vstack((meteors_array,meteors1))
+        #cerrar
+		f1.close()
+
+    meteors_array = numpy.delete(meteors_array, 0, axis=0)
+    meteors_list = [meteors_array[:,0],meteors_array[:,1],meteors_array[:,2],meteors_array[:,3]]
+    return meteors_list
+        
+def estimateMean(offset_list):
+    
+    mean_off = []
+    axisY_off = []
+    axisX_off = []
+    
+    for thisOffset in offset_list:
+		mean_aux = numpy.mean(thisOffset, axis = 0)
+		mean_off.append(mean_aux)
+		axisX_off.append(numpy.array([0,numpy.size(thisOffset)]))
+		axisY_off.append(numpy.array([mean_aux,mean_aux]))
+        
+    return mean_off, axisY_off, axisX_off
+ 
+def plotPhases(offset0, axisY0, axisX0, title):
+    f, axarr = plt.subplots(4, sharey=True)
+    color = ['b','g','r','c']
+# plt.grid()
+    for i in range(len(offset0)):
+		thisMeteor = offset0[i]
+		thisY = axisY0[i]
+		thisX = axisX0[i]
+		thisColor = color[i]
+	
+		opt = thisColor + 'o'
+		axarr[i].plot(thisMeteor,opt)
+		axarr[i].plot(thisX, thisY, thisColor)
+		axarr[i].set_ylabel('Offset ' + str(i))
+   
+    plt.ylim((-180,180))
+    axarr[0].set_title(title + ' Offsets')
+    axarr[3].set_xlabel('Number of estimations')
+    
+    return
+ 
+def filterOffsets(offsets0, stdvLimit):
+    offsets1 = []
+    
+    for thisOffset in offsets0:
+        pstd = numpy.std(thisOffset)*stdvLimit
+        pmean = numpy.mean(thisOffset)
+        outlier1 = thisOffset > pmean - pstd
+        outlier2 = thisOffset < pmean + pstd       
+        not_outlier = numpy.logical_and(outlier1,outlier2)
+        thisOffset1 = thisOffset[not_outlier]
+        offsets1.append(thisOffset1)
+    
+    return offsets1
+ 
+#----------------------     Setup    ---------------------------
+ 
+path = '/home/jespinoza/Pictures/JASMET30/201608/phase'
+stdvLimit = 0.5
+ 
+#----------------------   Script     ---------------------------
+ 
+fileList = findFiles(path)
+offsets0 = readFiles(fileList)
+mean0, axisY0, axisX0 = estimateMean(offsets0)
+plotPhases(offsets0, axisY0, axisX0, 'Original')
+ 
+offsets1 = filterOffsets(offsets0, stdvLimit)
+mean1, axisY1, axisX1 = estimateMean(offsets1)
+plotPhases(offsets1, axisY1, axisX1, 'Filtered')
+ 
+print "Original Offsets: %.2f, %.2f, %.2f, %.2f" % (mean0[0],mean0[1],mean0[2],mean0[3])
+print "Filtered Offsets: %.2f, %.2f, %.2f, %.2f" % (mean1[0],mean1[1],mean1[2],mean1[3])
+ 
+plt.show()