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Nanopore-tools/Plotting/NanoporePlots.py
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NanoporePlots.py
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import numpy as np
import matplotlib.pyplot as plt
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)')
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()
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