diff --git a/TaipeiRawData/surfdata.dat b/TaipeiRawData/surfdata.dat
index e4bf857..e69de29 100644
--- a/TaipeiRawData/surfdata.dat
+++ b/TaipeiRawData/surfdata.dat
@@ -1,2510 +0,0 @@
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-#  25.090361 121.462250 8 2 0
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-#  25.133539 121.499190 8 2 0
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-#  25.128920 121.417420 9 2 0
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-#  25.102119 121.515930 10 2 0
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-#  25.106000 121.564030 10 2 0
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-#  25.065750 121.477750 10 2 0
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-#  25.064800 121.556200 10 2 0
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-#  25.034278 121.493670 10 2 0
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-#  25.158529 121.476890 11 2 0
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-#  25.128920 121.417420 11 2 0
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-#  25.119850 121.473190 11 2 0
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-#  25.090361 121.462250 11 2 0
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-#  25.083694 121.435220 11 2 0
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-#  25.133539 121.499190 11 2 0
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-#  25.102119 121.515930 11 2 0
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-#  25.106000 121.564030 11 2 0
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-#  25.065750 121.477750 11 2 0
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-#  25.064800 121.556200 11 2 0
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-#  25.053694 121.515720 11 2 0
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-#  25.061472 121.431140 11 2 0
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-#  25.034278 121.493670 11 2 0
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-#  25.034611 121.442190 11 2 0
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-#  25.019000 121.474190 11 2 0
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-#  25.158529 121.476890 12 2 0
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-#  25.128920 121.417420 12 2 0
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-#  25.119850 121.473190 12 2 0
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-#  25.090361 121.462250 12 2 0
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-#  25.083694 121.435220 12 2 0
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-#  25.133539 121.499190 12 2 0
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-#  25.102119 121.515930 12 2 0
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-#  25.106000 121.564030 12 2 0
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-#  25.128920 121.417420 13 2 0
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-#  25.090361 121.462250 13 2 0
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-#  25.083694 121.435220 13 2 0
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-#  25.133539 121.499190 13 2 0
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-#  25.102119 121.515930 13 2 0
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-#  25.106000 121.564030 13 2 0
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-#  25.065750 121.477750 13 2 0
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-#  25.128920 121.417420 14 2 0
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-#  25.061472 121.431140 14 2 0
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-#  25.128920 121.417420 15 2 0
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-#  25.090361 121.462250 15 2 0
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- 25.010056 121.387470 1.7850
-#  25.106000 121.564030 26 2 0
- 25.010056 121.387470 1.8950
-#  25.064800 121.556200 26 2 0
- 25.010056 121.387470 1.6950
-#  25.034278 121.493670 26 2 0
- 25.010056 121.387470 1.1140
-#  24.999536 121.568640 26 2 0
- 25.010056 121.387470 1.8650
diff --git a/scripts/GenerateDSurfTomoInputFile.py b/scripts/GenerateDSurfTomoInputFile.py
new file mode 100644
index 0000000..d15e0be
--- /dev/null
+++ b/scripts/GenerateDSurfTomoInputFile.py
@@ -0,0 +1,146 @@
+#/* -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.
+#
+# File Name : GenerateDSurfTomoInputFile.py
+#
+# Purpose : Generate the Input File for DSurfTomo using the data themselves
+#
+# Creation Date : 05-07-2023
+#
+# Last Modified : Tue 18 Jul 2023 08:10:22 PM CST
+#
+# Created By : Hongjian Fang: fanghj1990@gmail.com
+#
+#_._._._._._._._._._._._._._._._._._._._._.*/
+
+import os
+import numpy as np
+import glob
+import pandas as pd
+
+#These are for generating the right format
+DataPath = 'TaipeiRawData'
+DataNames = 'CDisp*.dat'
+wavetype = 2
+phasetype = 0
+
+# These following can be changed in DSurfTomo.in
+nz = 9
+sublayers = 3
+minvel = 0.5
+maxvel = 2.8
+noiselevel = 0.02
+datathreshold = 1.5
+DataFiles = glob.glob(DataPath+'/'+DataNames)
+
+sta1latall = []
+sta1lonall = []
+sta2latall = []
+sta2lonall = []
+periodsall = []
+dispersionall = []
+stationpairID = []
+
+for ifile in DataFiles:
+    dispersion = np.loadtxt(ifile)
+    pairID = ifile.split('/')[-1]
+    sta1lon = dispersion[0,0]
+    sta1lat = dispersion[0,1]
+    sta2lon = dispersion[1,0]
+    sta2lat = dispersion[1,1]
+    nperiods,_ = dispersion.shape
+    nperiods = nperiods - 2
+    periods = np.zeros(nperiods,)
+    disper = np.zeros(nperiods,)
+    for ii in range(nperiods):
+        periods[ii] = dispersion[ii+2,0]
+        disper[ii] = dispersion[ii+2,1]
+   
+    dispersionall = np.hstack([dispersionall,disper])
+    periodsall = np.hstack([periodsall,periods])
+    sta1latall = np.hstack([sta1latall,np.ones(nperiods,)*sta1lat])
+    sta1lonall = np.hstack([sta1lonall,np.ones(nperiods,)*sta1lon])
+    sta2latall = np.hstack([sta2latall,np.ones(nperiods,)*sta2lat])
+    sta2lonall = np.hstack([sta2lonall,np.ones(nperiods,)*sta2lon])
+    stationpairID = stationpairID + [pairID] * nperiods
+
+dataall = pd.DataFrame({'sta1lat':sta1latall, 'sta1lon':sta1lonall, \
+                        'sta2lat':sta2latall, 'sta2lon':sta2lonall, \
+                        'periods':periodsall, 'dispersion': dispersionall, \
+                        'pairid':stationpairID})
+
+dataall = dataall.sort_values(by = ['periods', 'pairid'])
+dataall = dataall.set_index('periods')
+with open('surfdata.dat','w') as fout:
+    UniqPeriods = dataall.index.unique()
+    for iperiod,period in enumerate(UniqPeriods):
+        datasubperiod = dataall.loc[period]
+        if isinstance(datasubperiod,pd.Series):
+            continue
+        datasubperiod = datasubperiod.reset_index().set_index('sta1lat')
+        sta1lat = datasubperiod.index.unique()
+        for ista1 in sta1lat:
+            datasubstation = datasubperiod.loc[ista1]
+            if isinstance(datasubstation,pd.DataFrame):
+                fout.write(f'# {datasubstation.index[0]} {datasubstation["sta1lon"].iloc[0]} {iperiod+1} {wavetype} {phasetype}\n')
+                for ista2 in range(len(datasubstation)):
+                    fout.write(f'{datasubstation["sta2lat"].iloc[ista2]} {datasubstation["sta2lon"].iloc[ista2]} {datasubstation["dispersion"].iloc[ista2]}\n')
+            else:
+                fout.write(f'# {datasubstation.name} {datasubstation["sta1lon"]} {iperiod+1} {wavetype} {phasetype}\n')
+                fout.write(f'{datasubstation["sta2lat"]} {datasubstation["sta2lon"]} {datasubstation["dispersion"]}\n')
+
+
+print('Finish reformatting disperison data')
+
+# Determin the grid interval, 1/3 of the smallest station distance
+
+# Weight and Damp, you will have to run the code a couple of time to decide
+# The default values is 5.0 and 1.0, respectively
+weight = 1.0
+damp = 1.0
+
+# Sparsity fraction, this parameter represent the sparsity of the sensitivity matrix and is set to be 0.2 for safe keeping, but could be as low as 0.02.it is not important as long as your code does not throw you memory erros
+sparsityfraction = 0.1
+
+# Iteration number, the default is 10 time, most often you get stable results after 4-5 iterations.
+maxiteration = 10
+
+
+distall = np.sqrt((dataall['sta2lat']-dataall['sta1lat'])**2+(dataall['sta2lon']-dataall['sta1lon'])**2)
+mindist = distall.min()
+gridintval = int(np.ceil(mindist/3*1000))/1000
+# Determine the origin, 1 grids
+originLat = np.max([np.max(dataall.sta1lat.max()),np.max(dataall.sta2lat.max())]) + 1*gridintval
+originLon = np.min([np.min(dataall.sta1lon.min()),np.min(dataall.sta2lon.min())]) - 1*gridintval
+largestLat = np.max([dataall['sta1lat'].max()-dataall['sta1lat'].min(),dataall['sta2lat'].max()-dataall['sta2lat'].min()])
+largestLon = np.max([dataall['sta1lon'].max()-dataall['sta1lon'].min(),dataall['sta2lon'].max()-dataall['sta2lon'].min()])
+inputfile = open('DSurfTomo.in','w')
+dummy = 'cccc'
+inputfile.write(f'{dummy*10}\n')
+inputfile.write(f'{dummy*10}\n')
+inputfile.write(f'{dummy*10}\n')
+inputfile.write('surfdata.dat\n')
+nx = int(np.ceil(largestLat/gridintval))+5
+ny = int(np.ceil(largestLon/gridintval))+5
+nreceivers = len(dataall.sta1lat.unique())+1
+inputfile.write(f'{nx} {ny} {nz}\n')
+inputfile.write(f'{originLat:<7.3f} {originLon:7.3f}\n')
+inputfile.write(f'{gridintval:<7.3f} {gridintval:7.3f}\n')
+inputfile.write(f'{nreceivers}\n')
+inputfile.write(f'{weight} {damp}\n')
+inputfile.write(f'{sublayers}\n')
+inputfile.write(f'{minvel} {maxvel}\n')
+inputfile.write(f'{maxiteration}\n')
+inputfile.write(f'{sparsityfraction}\n')
+nperiods = len(UniqPeriods)
+inputfile.write(f'{nperiods}\n')
+#inputfile.write(f'{*UniqPeriods}\n')
+inputfile.write(' '.join([str(iperiod) for iperiod in UniqPeriods])+'\n')
+inputfile.write(f'0\n')
+inputfile.write(f'0\n')
+inputfile.write(f'0\n')
+inputfile.write(f'0\n')
+inputfile.write(f'{noiselevel}\n')
+inputfile.write(f'{datathreshold}\n')
+inputfile.close()
+
+print('Finishing generating input file\n')