diff --git a/Plotting/NanoporePlots.py b/Plotting/NanoporePlots.py
index 90f0aa8..bc6c1df 100644
--- a/Plotting/NanoporePlots.py
+++ b/Plotting/NanoporePlots.py
@@ -1,75 +1,79 @@
 import numpy as np
 import matplotlib.pyplot as plt
+from matplotlib.ticker import EngFormatter
 
-
+Amp = EngFormatter(unit='A', places=2)
+Time = EngFormatter(unit='s', places=2)
+Volt = EngFormatter(unit='V', places=2)
 
 
 
 def PlotI_tau(current,tau):
     # definitions for the axes
     left, width = 0.1, 0.6
     bottom, height = 0.1, 0.6
     bottom_h = left_h = left + width + 0.05
 
     rect_scatter = [left, bottom, width, height]
     rect_histx = [left, bottom_h, width, 0.2]
     rect_histy = [left_h, bottom, 0.2, height]
 
 
     # start with a rectangular Figure
     plt.figure(1, figsize=(8, 8))
 
     axScatter = plt.axes(rect_scatter)
     axHistx = plt.axes(rect_histx)
     axHisty = plt.axes(rect_histy)
 
     # the scatter plot:
     axScatter.scatter(tau, current)
 
     # now determine nice limits by hand:
     extra = 0.1 #0.1 = 10%
     tauRange=np.max(tau)-np.min(tau)
     currentRange=np.max(current)-np.min(current)
     #
     # tauLim = (int(tauMax/binwidth) + 1) * binwidth
     # currentLim = (int(currentMax/binwidth) + 1) * binwidth
 
 
     axScatter.set_xlim((np.min(tau)-extra*tauRange, np.max(tau)+extra*tauRange))
     axScatter.set_ylim((np.min(current)-extra*currentRange, np.max(current)+extra*currentRange))
 
     #tauBins = np.arange(-tauLim, tauLim + binwidth, binwidth)
     #currentBins = np.arange(-currentLim, currentLim + binwidth, binwidth)
     axHistx.hist(tau, bins=10)
     axHisty.hist(current, bins=10, orientation='horizontal')
 
     axHistx.set_xlim(axScatter.get_xlim())
     axHisty.set_ylim(axScatter.get_ylim())
 
     axScatter.set_xlabel('Event length (s)')
-    axScatter.set_ylabel('current drop (A)')
+    axScatter.set_ylabel('current drop (A
+    axScatter.xaxis.set_major_formatter(Time)
+    axScatter.yaxis.set_major_formatter(Amp)
     plt.show()
 
 def PlotCurrentTrace(currentTrace,samplerate):
     timeVals=np.linspace(0, len(currentTrace)/samplerate, num=len(currentTrace))
     plt.figure(figsize=(10, 6))
 
     plt.plot(timeVals,currentTrace)
     plt.xlabel('time (s)')
     plt.ylabel('current (A)')
     plt.show()
 
 def PlotCurrentTraceBaseline(before,currentTrace,after,samplerate):
     timeVals1=np.linspace(0, len(before)/samplerate, num=len(before))
     timeVals2=np.linspace(0+max(timeVals1), len(currentTrace)/samplerate+max(timeVals1), num=len(currentTrace))
     timeVals3=np.linspace(0+max(timeVals2), len(after)/samplerate+max(timeVals2), num=len(after))
 
     plt.figure(figsize=(10, 6))
 
     plt.plot(timeVals1,before,color='red')
     plt.plot(timeVals2,currentTrace)
     plt.plot(timeVals3,after,color='red')
     plt.xlabel('time (s)')
     plt.ylabel('current (A)')
     plt.show()
-