def dataGrapherSingle(dataStructure, figureLabel):
resolution = 1000
for epocLabel in dataStructure:
epoc = epocLabel.split('_')[0]
localTime = numpy.array(dataStructure[epocLabel][0])
shiftedTime = localTime - min(localTime)
localCells = dataStructure[epocLabel][1]
highResolutionTime = numpy.linspace(min(shiftedTime), max(shiftedTime),
resolution)
if len(localCells) > 2: # dealing with sets of at least 2 data points
print figureLabel + '_' + epocLabel, '\t',
fittedTrajectory = library.dataFitter(shiftedTime, localCells)
b = library.peval(highResolutionTime, fittedTrajectory[0])
checkFit(highResolutionTime, b, shiftedTime, localCells,
figureLabel + '_' + epocLabel)
return None
def dataGrapherEpocs(dataStructure,figureLabel):
resolution=1000
figureFile='../results/figure_%s.pdf'%figureLabel
legendWritten=False
if figureLabel == '300':
localColor='blue'
elif figureLabel == '1000':
localColor='red'
else:
print 'error a'
sys.exit()
for epocLabel in dataStructure:
epoc=epocLabel.split('_')[0]
localTime=numpy.array(dataStructure[epocLabel][0])
shiftedTime=localTime-min(localTime)
localCells=dataStructure[epocLabel][1]
highResolutionTime=numpy.linspace(min(shiftedTime),max(shiftedTime),resolution)
# plotting the data
if legendWritten == False:
matplotlib.pyplot.plot(localTime,localCells,'o',color=localColor,markeredgecolor='None',label='%s ppm'%figureLabel)
legendWritten=True
else:
matplotlib.pyplot.plot(localTime,localCells,'o',color=localColor,markeredgecolor='None')
# plotting the model if there is growth, otherwise plot a best model straight line
if len(localCells) == 2:
matplotlib.pyplot.plot([localTime[0],localTime[-1]],[localCells[0],localCells[-1]],'-',color=localColor)
elif localCells[0] > localCells[-1]:
slope, intercept, temp0, temp1, temp2 = scipy.stats.linregress(shiftedTime,localCells)
matplotlib.pyplot.plot([localTime[0],localTime[-1]],[intercept,slope*shiftedTime[-1]+intercept],'-',color=localColor)
else:
fittedTrajectory=library.dataFitter(shiftedTime,localCells)
b=library.peval(highResolutionTime,fittedTrajectory[0])
matplotlib.pyplot.plot(highResolutionTime+min(localTime),b,'-',color=localColor)
matplotlib.pyplot.xlim([-0.5,19])
matplotlib.pyplot.ylim([-0.5e5,10e5])
matplotlib.pyplot.xlabel('time (days)')
matplotlib.pyplot.ylabel('number of cells (x 1e5)')
matplotlib.pyplot.yticks((0,1e5,2e5,3e5,4e5,5e5,6e5,7e5,8e5,9e5,10e5),('0','1','2','3','4','5','6','7','8','9','10'))
matplotlib.pyplot.legend(numpoints=1,loc=1,frameon=False)
matplotlib.pyplot.savefig(figureFile)
matplotlib.pyplot.clf()
return None
def dataGrapherEpochs(dataStructure,figureLabel):
resolution=1000
figureFile='results/figure_%s.pdf'%figureLabel
for epochLabel in dataStructure:
epoch=epochLabel.split('_')[0]
localTime=numpy.array(dataStructure[epochLabel][0])
shiftedTime=localTime-min(localTime)
localCells=dataStructure[epochLabel][1]
highResolutionTime=numpy.linspace(min(shiftedTime),max(shiftedTime),resolution)
epochColor=colorDefiner(epoch)
# plotting the data
if len(localCells) > 1:
matplotlib.pyplot.plot(localTime,localCells,'o',color=epochColor,markeredgecolor='None',ms=4)
# plotting the model if there is growth, otherwise plot a best model straight line
if len(localCells) <= 2:
matplotlib.pyplot.plot([localTime[0],localTime[-1]],[localCells[0],localCells[-1]],'-',color=epochColor)
elif localCells[0] > localCells[-1]:
slope, intercept, temp0, temp1, temp2 = scipy.stats.linregress(shiftedTime,localCells)
matplotlib.pyplot.plot([localTime[0],localTime[-1]],[intercept,slope*shiftedTime[-1]+intercept],'-',color=epochColor)
else:
fittedTrajectory=library.dataFitter(shiftedTime,localCells)
b=library.peval(highResolutionTime,fittedTrajectory[0])
matplotlib.pyplot.plot(highResolutionTime+min(localTime),b,'-',color=epochColor)
matplotlib.pyplot.xlim([-0.5,20])
matplotlib.pyplot.ylim([-0.5e5,18e5])
matplotlib.pyplot.xlabel('time (days)')
matplotlib.pyplot.ylabel('number of cells (x 1e5)')
matplotlib.pyplot.title('%s ppm'%figureLabel)
matplotlib.pyplot.yticks((0,2e5,4e5,6e5,8e5,10e5,12e5,14e5,16e5,18e5),('0','2','4','6','8','10','12','14','16','18'))
matplotlib.pyplot.savefig(figureFile)
matplotlib.pyplot.clf()
return None
def dataGrapherSingle(dataStructure,figureLabel):
resolution=1000
for epocLabel in dataStructure:
epoc=epocLabel.split('_')[0]
localTime=numpy.array(dataStructure[epocLabel][0])
shiftedTime=localTime-min(localTime)
localCells=dataStructure[epocLabel][1]
highResolutionTime=numpy.linspace(min(shiftedTime),max(shiftedTime),resolution)
if len(localCells) > 2: # dealing with sets of at least 2 data points
print figureLabel+'_'+epocLabel,'\t',
fittedTrajectory=library.dataFitter(shiftedTime,localCells)
b=library.peval(highResolutionTime,fittedTrajectory[0])
checkFit(highResolutionTime,b,shiftedTime,localCells,figureLabel+'_'+epocLabel)
return None
def dataGrapherEpocs(dataStructure, figureLabel):
resolution = 1000
figureFile = '../results/figure_%s.pdf' % figureLabel
legendWritten = False
if figureLabel == '300':
localColor = 'blue'
elif figureLabel == '1000':
localColor = 'red'
else:
print 'error a'
sys.exit()
for epocLabel in dataStructure:
epoc = epocLabel.split('_')[0]
localTime = numpy.array(dataStructure[epocLabel][0])
shiftedTime = localTime - min(localTime)
localCells = dataStructure[epocLabel][1]
highResolutionTime = numpy.linspace(min(shiftedTime), max(shiftedTime),
resolution)
# plotting the data
if legendWritten == False:
matplotlib.pyplot.plot(localTime,
localCells,
'o',
color=localColor,
markeredgecolor='None',
label='%s ppm' % figureLabel)
legendWritten = True
else:
matplotlib.pyplot.plot(localTime,
localCells,
'o',
color=localColor,
markeredgecolor='None')
# plotting the model if there is growth, otherwise plot a best model straight line
if len(localCells) == 2:
matplotlib.pyplot.plot([localTime[0], localTime[-1]],
[localCells[0], localCells[-1]],
'-',
color=localColor)
elif localCells[0] > localCells[-1]:
slope, intercept, temp0, temp1, temp2 = scipy.stats.linregress(
shiftedTime, localCells)
matplotlib.pyplot.plot(
[localTime[0], localTime[-1]],
[intercept, slope * shiftedTime[-1] + intercept],
'-',
color=localColor)
else:
fittedTrajectory = library.dataFitter(shiftedTime, localCells)
b = library.peval(highResolutionTime, fittedTrajectory[0])
matplotlib.pyplot.plot(highResolutionTime + min(localTime),
b,
'-',
color=localColor)
matplotlib.pyplot.xlim([-0.5, 19])
matplotlib.pyplot.ylim([-0.5e5, 10e5])
matplotlib.pyplot.xlabel('time (days)')
matplotlib.pyplot.ylabel('number of cells (x 1e5)')
matplotlib.pyplot.yticks(
(0, 1e5, 2e5, 3e5, 4e5, 5e5, 6e5, 7e5, 8e5, 9e5, 10e5),
('0', '1', '2', '3', '4', '5', '6', '7', '8', '9', '10'))
matplotlib.pyplot.legend(numpoints=1, loc=1, frameon=False)
matplotlib.pyplot.savefig(figureFile)
matplotlib.pyplot.clf()
return None
def dataGrapherEpochs(dataStructure, figureLabel):
resolution = 1000
figureFile = 'results/figure_%s.pdf' % figureLabel
for epochLabel in dataStructure:
epoch = epochLabel.split('_')[0]
localTime = numpy.array(dataStructure[epochLabel][0])
shiftedTime = localTime - min(localTime)
localCells = dataStructure[epochLabel][1]
highResolutionTime = numpy.linspace(min(shiftedTime), max(shiftedTime),
resolution)
epochColor = colorDefiner(epoch)
# plotting the data
if len(localCells) > 1:
matplotlib.pyplot.plot(localTime,
localCells,
'o',
color=epochColor,
markeredgecolor='None',
ms=4)
# plotting the model if there is growth, otherwise plot a best model straight line
if len(localCells) <= 2:
matplotlib.pyplot.plot([localTime[0], localTime[-1]],
[localCells[0], localCells[-1]],
'-',
color=epochColor)
elif localCells[0] > localCells[-1]:
slope, intercept, temp0, temp1, temp2 = scipy.stats.linregress(
shiftedTime, localCells)
matplotlib.pyplot.plot(
[localTime[0], localTime[-1]],
[intercept, slope * shiftedTime[-1] + intercept],
'-',
color=epochColor)
else:
fittedTrajectory = library.dataFitter(shiftedTime, localCells)
b = library.peval(highResolutionTime, fittedTrajectory[0])
matplotlib.pyplot.plot(highResolutionTime + min(localTime),
b,
'-',
color=epochColor)
matplotlib.pyplot.xlim([-0.5, 20])
matplotlib.pyplot.ylim([-0.5e5, 18e5])
matplotlib.pyplot.xlabel('time (days)')
matplotlib.pyplot.ylabel('number of cells (x 1e5)')
matplotlib.pyplot.title('%s ppm' % figureLabel)
matplotlib.pyplot.yticks(
(0, 2e5, 4e5, 6e5, 8e5, 10e5, 12e5, 14e5, 16e5, 18e5),
('0', '2', '4', '6', '8', '10', '12', '14', '16', '18'))
matplotlib.pyplot.savefig(figureFile)
matplotlib.pyplot.clf()
return None
