diff --git a/Plotting/PSD_Analysis_Michael.py b/Plotting/PSD_Analysis_Michael.py
new file mode 100644
index 0000000..e4b5df4
--- /dev/null
+++ b/Plotting/PSD_Analysis_Michael.py
@@ -0,0 +1,51 @@
+import numpy as np
+import scipy
+import scipy.signal as sig
+import Functions as uf
+import pyqtgraph as pg
+import os
+import matplotlib.pyplot as plt
+import matplotlib
+from tkinter import Tk
+from tkinter.filedialog import askopenfilenames
+root = Tk()
+root.withdraw()
+from matplotlib.font_manager import FontProperties
+import platform
+import csv
+fontP = FontProperties()
+fontP.set_size('small')
+props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)
+matplotlib.rcParams['pdf.fonttype'] = 42
+matplotlib.rcParams['ps.fonttype'] = 42
+from matplotlib.ticker import EngFormatter
+
+fig = plt.figure(1, figsize=(10, 8))
+ax = fig.add_subplot(111)
+
+#file = '/Volumes/lben/lben-commun/2018 User Data/Michael/Axopatch/20181003/NIPm10_5nm_1MKCl_pH75_Noise_100kHz_0mV_1.dat'
+filenames = askopenfilenames() # show an "Open" dialog box and return the path to the selected file
+#colors=['k','r','b']
+root.update()
+for i,file in enumerate(filenames):
+    dat = uf.OpenFile(file)
+    filename = str(os.path.split(file)[1][:-4])
+    os.chdir(os.path.dirname(file))
+    directory = (str(os.path.split(file)[0]) + os.sep + 'PSD' + '_SavedImages')
+    if not os.path.exists(directory):
+        os.makedirs(directory)
+    f, Pxx = sig.welch(dat['i1'], dat['samplerate'], nperseg=2**18)
+    ax.plot(f, Pxx*1e24, label = filename)#, color = colors[i])
+
+ax.set_xlabel('Frequency (Hz)')
+ax.set_ylabel(r'PSD ($\frac{pA^2}{Hz}$)')
+ax.set_yscale('log')
+ax.set_xscale('log')
+ax.legend()
+
+fig.savefig(directory + os.sep + filename + '_PSD.pdf', transparent=True)
+fig.savefig(directory + os.sep + filename + '_PSD.png', dpi=300)
+
+#plt.show()
+
+