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Nanopore-tools/ObsoleteFunctions/MakePSDs.py
e1fb93801dfbDevelopment-of-Analysis…

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MakePSDs.py
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#Input Stuff
import AnalysisParameters as pm
import numpy as np
import scipy
import scipy.signal as sig
import Functions as f
import os
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
from tkinter import Tk
from tkinter.filedialog import askopenfilenames
from matplotlib.ticker import EngFormatter
from matplotlib.font_manager import FontProperties
fontP = FontProperties()
props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)
import pyqtgraph as pg
fontP.set_size('small')
pm.init()
root = Tk()
root.withdraw()
os.system('''/usr/bin/osascript -e 'tell app "Finder" to set frontmost of process "python" to true' ''')
SaveAsPDF=0
foldername='PSD'
# Load File, empty string prompts a pop.up window for file selection. Else a file-path can be given
root.update()
#filenames = ['/Users/migraf/Desktop/Temp/BigBerta_Noise_2.dat']
filenames = askopenfilenames()
root.destroy()
# Make Dir to save images
directory = (str(os.path.split(filenames[0])[0]) + os.sep + foldername)
if not os.path.exists(directory):
os.makedirs(directory)
if SaveAsPDF:
pp = PdfPages(directory + os.sep + '_ALLPSD.pdf')
for filename in filenames:
print(filename)
#filename = '/Users/migraf/Desktop/TestTrace/07B_10mMKClBoth_1kBDN_BothChannels12.dat'
inp = f.OpenFile(filename)
folder = str(os.path.split(filename)[0]) + os.sep +'PSD'
file = os.sep + str(os.path.split(filename)[1][:-4])
if not os.path.exists(folder):
os.makedirs(folder)
fig1 = plt.figure()
ax = fig1.add_subplot(211)
ax2 = fig1.add_subplot(212, sharex = ax)
fr, Pxx_den = scipy.signal.periodogram(inp['i1'], inp['samplerate'])
#f, Pxx_den = scipy.signal.welch(input, samplerate, nperseg=10*256, scaling='spectrum')
ax.set_ylabel(r'PSD of Ionic [$\frac{pA^2}{Hz}$]')
ax.set_xlabel('Frequency')
ax.set_yscale('log')
ax.set_xscale('log')
#ax.set_ylim(1e4, 1e17)
#ax.set_xlim(100e-3, 100e3)
ax.xaxis.set_major_formatter(EngFormatter(unit='Hz'))
ax.plot(fr, Pxx_den*1e24, 'b')
ax.grid(1)
ax.autoscale()
if inp['graphene']:
print(np.mean(inp['v2']))
fr, Pxx_den = scipy.signal.periodogram(inp['i2'], inp['samplerate'])
ax2.plot(fr, Pxx_den * 1e24, 'r')
ax2.set_ylabel(r'PSD of Transverse [$\frac{pA^2}{Hz}$]')
ax2.set_xlabel('Frequency')
ax2.set_yscale('log')
ax2.set_xscale('log')
ax2.xaxis.set_major_formatter(EngFormatter(unit='Hz'))
ax2.plot(fr, Pxx_den * 1e24, 'r')
ax2.grid(1)
ax2.autoscale()
#ax.legend(['Ion', 'Transverse'])
textstr = 'STD ionic: {}\nSTD trans: {}'.format(pg.siFormat(np.std(inp['i1'])), pg.siFormat(np.std(inp['i2'])))
ax2.set_title('STD trans: {}'.format(pg.siFormat(np.std(inp['i2']))))
ax.set_title('STD ionic: {}'.format(pg.siFormat(np.std(inp['i1']))))
else:
textstr = 'STD ionic: {}'.format(pg.siFormat(np.std(inp['i1'])))
ax.set_title(textstr)
#ax2.text(0.75, 0.1, textstr, transform=ax.transAxes, fontsize=8,
# verticalalignment='bottom', bbox=props)
fig1.tight_layout()
if SaveAsPDF:
pp.savefig(fig1)
else:
fig1.savefig(directory + os.sep + str(os.path.split(filename)[1][:-4]) + '_PSD.png', dpi=300)
fig1.clear()
ax.clear()
plt.close(fig1)
if SaveAsPDF:
pp.close()
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