diff --git a/dat_ident.py b/dat_ident.py
new file mode 100644
index 0000000..8cfd02c
--- /dev/null
+++ b/dat_ident.py
@@ -0,0 +1,70 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Wed Mar 16 10:22:54 2016
+
+@author: Baptiste Marechal
+"""
+
+import csv, time, glob, datetime, os
+import matplotlib.pyplot as plt
+import matplotlib.dates as md
+
+#from scipy import signal
+#from scipy.optimize import curve_fit
+
+tic = time.time()
+
+os.chdir('/home/user/sicav_data/Manip/2016/2016-03/')
+
+def getColumn(filename, column):
+    results = []
+    for dat_file in sorted(glob.glob(filename)):
+        file_result = csv.reader(open(dat_file), delimiter='\t')
+        results = results + map(float,[result[column] for result in file_result])
+    return results
+
+t = getColumn('*-lakeshore.dat', 0)
+T1 = getColumn('*-lakeshore.dat', 2)
+T2 = getColumn('*-lakeshore.dat', 3)
+T3 = getColumn('*-lakeshore.dat', 4)
+T4 = getColumn('*-lakeshore.dat', 5)
+
+"""
+n = 400
+t = [t[n*i] for i in range(len(t)/n)]
+T1 = [T1[n*i] for i in range(len(T1)/n)]
+T2 = [T2[n*i] for i in range(len(T2)/n)]
+T3 = [T3[n*i] for i in range(len(T3)/n)]
+T4 = [T4[n*i] for i in range(len(T4)/n)]
+
+def func(U, a0, b1, b2, y0):
+    sys = signal.lti([a0],[b2, b1, 1])
+    y = sys.output(U, t, y0)
+    return y[1]
+
+print('Fitting...')
+popt, cov = curve_fit(func, T1, T4)
+print(popt)
+Yfit = func(T1, *popt)
+"""
+timetamps = [datetime.datetime.fromtimestamp(ti) for ti in t]
+datenums=md.date2num(timetamps)
+
+plt.subplots_adjust(bottom=0.35)
+plt.xticks(rotation=90)
+ax=plt.gca()
+xfmt = md.DateFormatter('%Y-%m-%d %H:%M:%S')
+ax.xaxis.set_major_formatter(xfmt)
+
+plt.plot(datenums, T1, label = 'Table')
+plt.plot(datenums, T2, label = 'Link st.')
+plt.plot(datenums, T3, label = 'PT2')
+plt.plot(datenums, T4, label = 'Reg. st.')
+#plt.plot(datenums, Yfit, label = 'Fit')
+
+plt.legend()
+plt.grid()
+plt.show()
+
+toc = time.time() - tic
+print(toc)
diff --git a/first_order_ident.py b/first_order_ident.py
new file mode 100644
index 0000000..aeb6c42
--- /dev/null
+++ b/first_order_ident.py
@@ -0,0 +1,49 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Fri Mar 11 11:04:35 2016
+
+@author: Baptiste Marechal
+"""
+
+from scipy import signal, linspace, pi, randn, ones
+from scipy.optimize import curve_fit
+import matplotlib.pyplot as plt
+import time
+
+tic = time.time()
+
+'''function to optimize'''
+def func(u, K, tau, y0):
+    sys = signal.lti(K, [tau, 1])
+    y = sys.output(u, t, y0)
+    return y[1]
+
+'''input square signal'''
+global t
+t = linspace(0, 20, 1000)
+Umes = -0.5*(signal.square(2*pi*0.1*t)+ones(len(t)))+ones(len(t))+randn(len(t))/50
+
+'''noisy output signal'''
+p = [1, 1, 0]
+Ymes = func(Umes, *p)+randn(len(Umes))/50
+
+'''input and output signals plot'''
+plt.plot(t, Umes, label = 'Umes')
+plt.plot(t, Ymes, label = 'Ymes')
+
+
+'''optimization with non-linear least squares method'''
+popt, cov = curve_fit(func, Umes, Ymes)
+print(p)
+print(popt)
+
+'''estimated response plot'''
+Yfit = func(Umes, *popt)
+plt.plot(t, Yfit, label ='Yfit')
+
+plt.legend()
+plt.grid()
+plt.show()
+
+toc = time.time() - tic
+print(toc)
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