PSD_Analysis.py
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	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
	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']
	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()