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