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baseline.py
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baseline.py
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#FINDS BOTH BASELINE AND MEAN LINE
import numpy
from numpy import NaN, Inf, arange, isscalar, asarray, array, mean
import peakutils
from peakutils.plot import plot as pplot
from matplotlib import pyplot
from peakfind import findArea, findBaseline
def peakdet(v, delta, x = None):
maxtab = []
mintab = []
if x is None:
x = arange(len(v))
v = asarray(v)
if len(v) != len(x):
sys.exit('Input vectors v and x must have same length')
if not isscalar(delta):
sys.exit('Input argument delta must be a scalar')
if delta <= 0:
sys.exit('Input argument delta must be positive')
mn, mx = Inf, -Inf
mnpos, mxpos = NaN, NaN
lookformax = True
for i in arange(len(v)):
this = v[i]
if this > mx:
mx = this
mxpos = x[i]
if this < mn:
mn = this
mnpos = x[i]
if lookformax:
if this < mx-delta:
maxtab.append((mxpos, mx))
mn = this
mnpos = x[i]
lookformax = False
else:
if this > mn+delta:
mintab.append((mnpos, mn))
mx = this
mxpos = x[i]
lookformax = True
return array(maxtab), array(mintab)
def findMean(ys):
basel = mean(ys)
return basel
def cutdata(x_axis, y_axis, threshold):
cut = []
cutx = []
cuty=[]
two = numpy.column_stack((x_axis,y_axis))
variance = numpy.var(asarray(two))
basel = findMean(y_axis)
highcut = basel + ((variance-basel)/(threshold))
lowcut = basel - ((variance-basel)/(threshold))
for a in range (0,len(two)):
if two[a][1] > lowcut and two[a][1] < highcut:
cut.append(two[a])
for m in range (0, len(cut)):
cutx.append(cut[m][0])
cuty.append(cut[m][1])
return cutx, cuty
def meanarray(y_axis):
mean = []
meanval = findMean(y_axis)
for y in y_axis:
mean.append(float(meanval))
return mean
def removePeaks(final_peaks, x_axis, y_axis):
basel = findMean(y_axis)
two = numpy.column_stack((x_axis,y_axis))
withoutpeaks = []
withoutpeaksx = []
withoutpeaksy = []
delete = {}
for peak in final_peaks:
low, up, area = findArea(peak, x_axis, y_axis, basel)
#print "low : ",low
#print "up : ",up
for a in range (0,len(two)):
if two[a][0] > low and two[a][0] < up:
try:
foo = delete[str(a)]
except:
delete[str(a)] = True
# withoutpeaks = numpy.delete(two, delete)
withoutpeaks = []
for _index in range(len(two)):
try:
foo = delete[str(_index)]
# pass as its meant to be deleted
except:
withoutpeaks.append(two[_index])
for m in range (0, len(withoutpeaks)):
#print m,",",withoutpeaks[m]
withoutpeaksx.append(withoutpeaks[m][0])
withoutpeaksy.append(withoutpeaks[m][1])
return withoutpeaksx, withoutpeaksy
if __name__=="__main__":
#f= open('input.txt', 'r')
#f = open('export_elpho_drug_ISZ.txt','r')
f = open('export_elpho_drug_ISZ+RIF.txt','r')
pairs = f.readlines()
x_axis = []
y_axis = []
final_peaks = []
for pair in pairs:
values = pair.split()
x_axis.append(float(values[0]))
y_axis.append(float(values[1]))
series = y_axis
maxtab, mintab = peakdet(series,10.)
for pair in maxtab:
final_peaks.append((float(x_axis[int(pair[0])]), float(pair[1])))
if len(final_peaks) > 4:
final_peaks.pop(0)
#print(final_peaks)
withoutpeaksx, withoutpeaksy = removePeaks(final_peaks, x_axis, y_axis)
# basel1, basel2 = findBaseline(series, final_peaks, x_axis)
# peaknum = 0
# for peak in final_peaks:
# if peaknum in [0,1]:
# basel = basel1
# else:
# basel = basel2
# low, up, area = findArea(peak,x_axis,y_axis,basel)
# peaknum = peaknum + 1
cutx, cuty = cutdata(x_axis, y_axis,15)
mean = meanarray(y_axis)
x_axis = asarray(x_axis)
y_axis = asarray(y_axis)
cutx = asarray(cutx)
cuty = asarray(cuty)
mean = asarray(mean)
withoutpeaksx = asarray(withoutpeaksx)
withoutpeaksy = asarray(withoutpeaksy)
base = peakutils.baseline(y_axis, 2)
cutbase = peakutils.baseline(cuty, 2)
pyplot.figure(figsize=(10,6))
pyplot.plot(x_axis, y_axis, label="data")
pyplot.plot(x_axis, base, label = "baseline")
pyplot.plot(x_axis, mean, label= "mean")
pyplot.plot(cutx, cuty, label= "cut")
pyplot.plot(cutx, asarray(cutbase), label = "cut baseline")
pyplot.plot(withoutpeaksx, withoutpeaksy, label = "without peaks")
pyplot.plot()
pyplot.legend()
pyplot.show()