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Nanopore-tools/NanoporeClasses.py
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NanoporeClasses.py
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import numpy as np
from pprint import pprint
import shelve
import os
import math
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)
Cond = EngFormatter(unit='S', places=2)
class TranslocationEvent:
"""
Class used to represent an event.
Attributes
----------
filename : str
directory of the source file from which the event was extracted
type: str
classification of the event 'CUSUM' (CUSUM-fitted), 'Rough' (non-CUSUM fitted), 'Impulse' (short events)
evenTrace: lst(int)
list of data points within the event
baseline:float
mean current value in the basline around the event
samplerate:float
sampling frequency
beginEvent: int
start coordinate of the event in the signal
endEvent: int
end coordinate of the event in the signal
meanTrace: float
mean current in the event
minTrace: float
minimum current in the event
eventLength: float
lenght of the event in seconds
currentDrop: float
current drop defined as the difference of the baseline and meanTrace or minTrace dependeng on the event type
before: lst(float)
list of data points before the event, used for plotting
after: lst(float)
list of data points after the event, used for plotting
changeTimes: lst(int)
list of coordinates where the current level changes in the event, only for multilevel events
kd: ****
segmentedSignal: lst(float)
CUSUM fit
beginEventCUSUM:
more precise start coordinate of the event detected with the CUSUM algorithm
currentDropCUSUM:
more precise start coordinate of the event detected with the CUSUM algorithm
coefficients:
coefficients used in the CUSUM algorithm
voltage:
voltage applied across the nanopore during the data recording
"""
def __init__(self, filename, type='roughEvent'):
self.filename = filename
self.type = type
def SetEvent(self, eventTrace, beginEvent, baseline, samplerate, currentDrop=None):
self.eventTrace = eventTrace
self.baseline = baseline
self.samplerate = samplerate
self.beginEvent = beginEvent
self.endEvent = beginEvent+len(eventTrace)
self.meanTrace = np.mean(eventTrace)
self.minTrace = np.min(eventTrace)
self.eventLength = len(eventTrace)/samplerate
if currentDrop is None:
self.currentDrop = baseline - self.meanTrace
else:
self.currentDrop = currentDrop
def SetCoefficients(self,coefficients,voltage):
self.coefficients = coefficients
self.voltage = voltage
def SetBaselineTrace(self, before,after):
self.before = before
self.after = after
self.baseline=np.mean(np.append(before,after))
def SetCUSUMVariables(self, segmentedSignal, kd, changeTimes):
self.changeTimes = changeTimes
self.kd = kd
self.segmentedSignal = segmentedSignal
self.changeTimes = changeTimes
if len(changeTimes) >= 1:
self.beginEventCUSUM = changeTimes[0]
self.currentDropCUSUM = max(segmentedSignal)-min(segmentedSignal)
if len(changeTimes) >= 2:
self.endEventCUSUM = changeTimes[-1]
self.eventLengthCUSUM = (changeTimes[-1]-changeTimes[0])/self.samplerate
if hasattr(self,'before') and hasattr(self,'after') and hasattr(self,'eventTrace'):
self.mcbefore=np.mean(self.before)*np.ones(len(self.before))
self.mcafter = np.mean(self.after) * np.ones(len(self.after))
self.mctrace=np.array([])
for ii in range(1,len(changeTimes)):
self.mctrace=np.append(self.mctrace,np.mean(self.eventTrace[changeTimes[ii-1]-changeTimes[0]:changeTimes[ii]-changeTimes[0]])*np.ones(changeTimes[ii]-changeTimes[ii-1]))
class AllEvents:
""""
Class used to represent all the events in a nanopore experiment output as a list of events.
Attributes
----------
events : lst(events)
list of events containing all the events detected by the eventdetection function
"""
def __init__(self):
self.events=[]
def AddEvent(self, translocationEvent):
if isinstance(translocationEvent,AllEvents):
if len(self.events) == 0:
self.events = translocationEvent.events
else:
self.events.extend(translocationEvent.events)
elif isinstance(translocationEvent,list):
self.events.extend(translocationEvent)
else:
self.events.append(translocationEvent)
def GetAllLengths(self):
Lengths=[event.lengthEvents for event in self.events]
return Lengths
def GetAllIdrops(self):
currentDrops=[event.currentDrop for event in self.events]
return currentDrops
def GetAllIdropsNorm(self):
currentDrops = [event.currentDrop/ event.baseline for event in self.events]
return currentDrops
def GetEventTypes(self,eventType):
events = []
events = [event for event in self.events if event.type == eventType]
return events
def GetEventsforVoltages(self,voltage):
events = [event for event in self.events if event.voltage == voltage]
return events
def GetAllVoltages(self):
voltages = [event.voltage for event in self.events]
voltages = set(voltages)
return voltages
def SetFolder(self,loadname):
self.savefile=loadname
def GetEventsMinCondition(self,minCurrent=-math.inf,maxCurrent=math.inf,minLength=0,maxLength=math.inf):
minCurrent = -math.inf if not minCurrent else minCurrent
maxCurrent = math.inf if not maxCurrent else maxCurrent
minLength = 0 if not minLength else minLength
maxLength = math.inf if not maxLength else maxLength
newEvents=AllEvents()
for event in self.events:
if minCurrent<event.currentDrop<maxCurrent and minLength<event.lengthEvents<maxLength:
newEvents.AddEvent(event)
newEvents.SetFolder(self.savefile)
print('selected {} events from {}'.format(len(newEvents.events), len(self.events)))
return newEvents
def PlotAllEvents(self):
for event in self.events:
event.PlotEvent()
def PlotIEvent(self,i):
event = self.events[i]
event.Plotevent()
def PlotHistogram(self):
appendTrace=[]
for event in self.events:
appendTrace.extend(event.eventTrace)
fig, ax = plt.subplots(figsize=(6, 10))
weights = np.ones_like(appendTrace) / float(len(appendTrace))
ax.hist(appendTrace,weights=weights,bins=40,orientation='horizontal')
ax.yaxis.set_major_formatter(Amp)
savefile=self.savefile
# Check if directory exists
directory = os.path.dirname(savefile)
fig.savefig(directory + os.sep + 'Histogram.pdf', transparent=True)
plt.show()
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