diff --git a/RingDown.py b/RingDown.py
deleted file mode 100644
index 1536196..0000000
--- a/RingDown.py
+++ /dev/null
@@ -1,45 +0,0 @@
-import matplotlib.pyplot as plt
-import numpy as np
-import csv, glob, sys
-from scipy.optimize import curve_fit
-
-list_files = (glob.glob(sys.argv[1]))
-
-data = []
-
-for f in list_files:
-    data_iter = csv.reader(open(f, 'r'), delimiter = ',', quotechar = '"')
-    for i in range(2):
-        data_iter.next()
-    #temp_data = [value for value in data_iter]      #if ends with a number
-    temp_data = [value[:-1] for value in data_iter]#if ends with a comma
-    data.extend(temp_data)
-
-data = np.asarray(data, dtype = float)
-
-del(temp_data, list_files, value, f)
-
-plt.subplot(111)
-plt.clf()
-
-plt.plot(data[data[:,0]>=0,0], data[data[:,0]>=0,1], label ='mes')
-
-def func(t, tau, A, w , a, b):
-    return A * np.exp(-t/tau) * np.sin((w+a*t)*t) + b
-
-popt, pcov = curve_fit(func, data[data[:,0]>=0,0], data[data[:,0]>=0,1], p0 = [1e-5, 1e-2, 1e5, 1e10, 1e-4], maxfev=10000)
-yfit = func(data[data[:,0]>=0,0], *popt)
-
-tau = float(popt[0])
-Q = np.pi*299792458*tau/(2.*140e-3)
-
-#print(np.sqrt(np.diag(pcov)))
-print(tau, Q)
-
-plt.plot(data[data[:,0]>=0,0], yfit, label ='fit')
-
-plt.xlabel('t')
-plt.ylabel('Intensity')
-plt.grid(which='both')
-plt.legend()
-plt.show()