diff --git a/witgit-proc b/witgit-proc
index 3a01f2e..9adb924 100755
--- a/witgit-proc
+++ b/witgit-proc
@@ -10,3 +10,102 @@ https://github.com/ozel/DIY_particle_detector
 @date: January 2022
 """
 
+import pandas as pd
+import numpy as np
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+from scipy.optimize import curve_fit
+import matplotlib.gridspec as gridspec
+import decimal as D
+import msgpack
+import argparse
+
+mpl.rcParams['font.size']=12
+
+parser = argparse.ArgumentParser()
+parser.add_argument("file_name", help="filename to import, e.g. pulses.pkl")
+args = parser.parse_args()
+
+def poly1(x, a, b):
+    return a*x + b
+
+df = pd.read_pickle(args.file_name)
+
+THL = -300
+
+lp = []
+for i,p in df.iterrows():
+    if p.pulse.min() < (THL):
+        lp.append(p.pulse)
+
+lp = np.asarray(lp[:])
+
+count=0
+loopcnt =0
+areas = []
+peaks = []
+min_alpha_peak = 1243
+
+min_g = -20
+max_g = -3300
+min_length = 44
+max_length = 120
+min_skip = min_length
+
+xpulses = []
+ypulses = []
+
+gmax=0
+for i,y in enumerate(lp[:]):
+    dydx=np.gradient(y)
+    gy= dydx.min()
+    gx= dydx.argmin()
+
+    while True:
+        if y[0] > THL and y[0] < np.abs(THL) and y.min() < THL and y[gx] <= np.abs(THL) and gy < min_g and gy > max_g:
+            trigx=np.where(dydx < min_g)[0]
+            trigy=dydx[dydx < min_g]
+            peakx1=trigx[0]
+            crossing_x1 = (y[peakx1+min_length:] > y[peakx1]).argmax() if (y[peakx1+min_length:] > y[peakx1]).any() else -1
+            if crossing_x1 > 0:
+                peakx2=peakx1+crossing_x1+min_length
+                diff = np.abs(peakx2 - peakx1)
+                peak = y[peakx1:peakx2].min()
+                if diff >= min_length and diff <= max_length and peak <= THL :
+                     area = np.absolute(y[peakx1:peakx2]).sum()
+                     areas.append(area)
+                     peak = np.absolute(peak) + y[peakx1]
+                     peaks.append(peak)
+                     ypulse = np.roll(y[peakx1-100:peakx2+100],50-y[peakx1:peakx2].argmin())[130:]
+                     if ypulse.size > min_length:
+                         xpulses.append(list(range(len(ypulse))))
+                         ypulses.append(ypulse)
+                     if gy < gmax:
+                         gmax=gy
+                     count+=1
+                else:
+                    peakx2=peakx1+min_skip
+            else:
+                peakx2 = peakx1 + min_skip
+        else:
+            peakx1=0
+            remaining = len(y)
+            if remaining <  min_length:
+                break
+            else:
+                peakx2=min_skip
+        y = np.delete(y, slice(0,peakx2))
+        if len(y) < min_length:
+            break
+        else:
+            dydx=np.delete(dydx, slice(0,peakx2))
+            gy= dydx.min()
+            gx= dydx.argmin()
+        loopcnt+=1
+
+time_diff = df.iloc[-1,0] - df.iloc[0,0]
+time_diff = time_diff.total_seconds() / 60.0
+cpm = count/time_diff
+print("detected pulses:",count, "in", round(time_diff), "minutes ->", round(cpm,3), "CPM")
+peaks=np.asarray(peaks)
+