diff --git a/ringdown.py b/ringdown.py
new file mode 100644
index 0000000..1536196
--- /dev/null
+++ b/ringdown.py
@@ -0,0 +1,45 @@
+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()