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scriptItalyISS.py
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scriptItalyISS.py
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# -*- coding: utf-8 -*-
#import csv
#import copy
from tools import colors, fillDataRegioni, fillDataISTATpickle, newCases, getRatio, makeHistos, fitErf, fitGauss, fitGaussAsymmetric, fitExp, extendDates, saveCSV, savePlotNew, getPrediction, getPredictionErf, getColumn, selectComuniDatesAgeGender, makeCompatible, fitLinear, fitTwoExp, fitGaussExp, applyScaleFactors, useLog, positiveHisto, fitTwoGaussDiff, fitGaussExp, getScaled, fillDataISS
useDatiISTAT = False
useScaleFactor = True
daysSmearing = 1
places = ["Italia"]
import ROOT
ROOT.gStyle.SetOptStat(0)
ROOT.gROOT.SetBatch(1)
#ROOT.gROOT.SetBatch(0)
resX, resY = 1920, 1080
dataCasi, dates = fillDataISS('calcoloRt/casi_inizio_sintomi.csv')
casi = getColumn(dataCasi, "CASI")
dataCasiSintomatici, dateCasiSintomatici = fillDataISS('calcoloRt/casi_inizio_sintomi_sint.csv')
casiSintomatici = getColumn(dataCasiSintomatici, "CASI_SINT")
dataPrelievi, datesPrelievi = fillDataISS('calcoloRt/casi_prelievo_diagnosi.csv')
prelievi = getColumn(dataPrelievi, "CASI")
dataDecessi, datesDecessi = fillDataISS('calcoloRt/decessi.csv')
decessi = getColumn(dataDecessi, "DECESSI")
lastDateData = len(dates)-1
dates = extendDates(dates, 1000)
print(dates)
print(dataCasi["Italia"])
print(dataCasiSintomatici["Italia"])
print(dataPrelievi["Italia"])
print(dataDecessi["Italia"])
################
#firstDate = 0
#firstDate = dates.index("6/1/20")
#firstDate = dates.index("5/15/20")
#firstDate = dates.index("5/15/20")
#firstDate = dates.index("9/1/20")
#firstDate = dates.index("12/1/20")
#firstDate = dates.index("12/30/20")
#firstDate = dates.index("10/1/20")
#firstDate = dates.index("1/1/21")
firstDate = dates.index("6/10/22")
#firstDate = dates.index("10/1/20")
#firstDate = dates.index("1/1/21")
#firstDate = dates.index("12/20/20")
#firstDate = dates.index("4/1/20")
#firstDate = 16
lastDate = lastDateData - 2
#lastDate = dates.index("2/29/20")
#lastDate = dates.index("3/1/20")
#lastDate = 30
#predictionsDate = dates.index("12/31/20")
predictionsDate = dates.index("8/1/22")
#predictionsDate = 95
#firstDate = dates.index("3/1/20")
#lastDate = dates.index("5/1/20")
#predictionsDate = dates.index("6/30/20")
#firstDate = 10
#lastDate = 35
#predictionsDate = 35
#firstDate = dates.index("10/1/20")
#lastDate = dates.index("10/15/20")
#predictionsDate = lastDate+1
################
#casi = decessi
newcasi = casi
newdecessi = decessi
newprelievi = prelievi
newcasiSintomatici = casiSintomatici
#newcasi = newCases(casi, dates)
#newdecessi = newCases(decessi, dates)
#newprelievi = newCases(prelievi, dates)
#newcasiSintomatici = newCases(casiSintomatici, dates)
#newIntensivas = newCases(intensivas, dates) # newIntensivas taken from ingressi_terapia_intensiva
intensivas = []
ricoveratis = []
positives = []
newRicoveratis = []
newPositives = []
newIntensivas = []
###########################
## scale used ##
casi_scale=1
decessi_scale=40
decessiIstatExcess_scale=20
intensivas_scale=90
ricoveratis_scale=20
casiSintomatici_scale=0.10
prelievi_scale=casi_scale
positives_scale=casi_scale
predictioncasi_scale=casi_scale
predictionprelievi_scale=casi_scale
predictionPositives_scale=casi_scale
predictionIntensivas_scale=intensivas_scale
predictionRicoveratis_scale=ricoveratis_scale
predictiondecessi_scale=decessi_scale
newcasi_scale=casi_scale
newprelievi_scale=casi_scale
newdecessi_scale=decessi_scale
newdecessiIstatExcess_scale=decessi_scale
newIntensivas_scale=intensivas_scale
newRicoveratis_scale=ricoveratis_scale
newcasiSintomatici_scale=casi_scale
newPositives_scale=casi_scale
################
fits = {}
fits2 = {}
fitdiffs = {}
d1 = ROOT.TCanvas("d1","",resX,resY)
print(places)
casi_h = makeHistos("histo_casi", casi, dates, places, firstDate, lastDate, predictionsDate, 0, cutTails=False, errorType='cumulative', lineWidth=2, daysSmearing=1)
prelievi_h = makeHistos("histo_prelievi", prelievi, dates, places, firstDate, lastDate, predictionsDate, 0, cutTails=False, errorType='cumulative', lineWidth=2, daysSmearing=1)
decessi_h = makeHistos("histo_decessi", decessi, dates, places, firstDate, lastDate, predictionsDate, 0, cutTails=False, errorType='cumulative', lineWidth=2, daysSmearing=1)
casiSintomatici_h = makeHistos("histo_casiSintomatici", casiSintomatici, dates, places, firstDate, lastDate, predictionsDate, 0, cutTails=False, errorType='cumulative', lineWidth=2, daysSmearing=1)
#casiSintomatici_h["Italia"].Draw()
#casiSintomatici_h["Italia"].Integral()
#print(casiSintomatici["Italia"]["4/11/21"])
#1/0
#print("CHECK",positives_h[place].GetBinContent(1))
#histos = makeHistos(casi, places, firstDate, lastDate, predictionsDate, cumulativeError=True)
#eType = "default"
eType = "3sqrtN"
newcasi_h = makeHistos("histo_newcasi", newcasi, dates, places, firstDate, lastDate, predictionsDate, 1, cutTails=True, lineWidth=2, daysSmearing=daysSmearing, errorType=eType)
newprelievi_h = makeHistos("histo_newprelievi", newprelievi, dates, places, firstDate, lastDate, predictionsDate, 1, cutTails=False, lineWidth=2, daysSmearing=daysSmearing, errorType=eType)
newdecessi_h = makeHistos("histo_newdecessi", newdecessi, dates, places, firstDate, lastDate, predictionsDate, 1, cutTails=False, lineWidth=2, daysSmearing=daysSmearing, errorType=eType)
newcasiSintomatici_h = makeHistos("histo_newcasiSintomatici", newcasiSintomatici, dates, places, firstDate, lastDate, predictionsDate, 1, cutTails=False, lineWidth=2, daysSmearing=daysSmearing, errorType=eType)
place = places[0]
for place in places:
# positiveHisto(casiSintomatici_h[place])
# positiveHisto(newcasiSintomatici_h[place])
# positiveHisto(casi_h[place])
# positiveHisto(newcasi_h[place])
# positiveHisto(decessi_h[place])
# positiveHisto(newdecessi_h[place])
if useScaleFactor:
for histos in [newcasi_h,newprelievi_h,newdecessi_h,newcasiSintomatici_h]: #newRicoveratis_h,
applyScaleFactors(histos[place], errorType=eType, lastDate=lastDate)
pass
if useLog:
for histo in [newcasi_h,newprelievi_h,newdecessi_h,newcasiSintomatici_h,casi_h,prelievi_h,decessi_h,casiSintomatici_h]:
# positiveHisto(histo[place])
pass
print(newcasiSintomatici_h[place])
#fits, fits_res, fits_error = fitErf(casi_h, places, firstDate, lastDate, predictionsDate)
##fitdiffs, fitdiffs_res, fitdiffs_error = fitGaussAsymmetric(newcasi_h, places, firstDate, lastDate, predictionsDate)
#fitdiffs, fitdiffs_res, fitdiffs_error = fitTwoExp(newcasi_h, places, firstDate, lastDate, predictionsDate)
#fitexps, fitexps_res, fitexps_error = fitExp(newcasi_h, places, lastDate-14, lastDate, predictionsDate)
#fitexptotals, fitexptotals_res, fitexptotals_error = fitExp(casi_h, places, lastDate-14-1, lastDate-1, predictionsDate)
##fitexptotals, fitexptotals_res, fitexptotals_error = fitExp(casi_h, places, lastDate-8, lastDate, predictionsDate)
#fitdiffIntensivas, fitdiffIntensivas_res, fitdiffIntensivas_error = fitTwoGaussDiff(newIntensivas_h, places, firstDate, lastDate, predictionsDate)
#fitdiffPositives, fitdiffPositives_res, fitdiffPositives_error = fitTwoGaussDiff(newPositives_h, places, firstDate, lastDate, predictionsDate)
#fitdiffRicoveratis, fitdiffRicoveratis_res, fitdiffRicoveratis_error = fitTwoGaussDiff(newRicoveratis_h, places, firstDate, lastDate, predictionsDate)
#fitdiffdecessi, fitdiffdecessi_res, fitdiffdecessi_error = fitTwoExp(newdecessi_h, places, firstDate, lastDate, predictionsDate)
#fitdiffprelievi, fitdiffprelievi_res, fitdiffprelievi_error = fitTwoExp(newprelievi_h, places, firstDate, lastDate, predictionsDate)
newdecessiIstatExcess_h = {}
if useDatiISTAT:
newdecessiIstats_h = makeHistos("histo_ISTAT", newdecessiIstats, dates, places, firstDate, lastDate, predictionsDate, 1, cutTails=False, lineWidth=2, errorType='sqrtN')
newdecessiIstats_old_h = makeHistos("histo_ISTAT_old", newdecessiIstats_old, dates, places, firstDate, lastDate, predictionsDate, 1, cutTails=False, lineWidth=2, errorType='sqrtN')
for place in newdecessiIstats_old_h:
if newdecessiIstats_old_h[place].Integral(0, dates.index("2/28/20"))>0: newdecessiIstats_old_h[place].Scale(newdecessiIstats_h[place].Integral(0, dates.index("2/28/20"))/newdecessiIstats_old_h[place].Integral(0, dates.index("2/28/20")))
feb29_bin = dates.index("3/1/20")
newdecessiIstats_old_h[place].SetBinContent(feb29_bin, newdecessiIstats_old_h[place].GetBinContent(feb29_bin-1))
newdecessiIstats_old_h[place].SetBinError( feb29_bin, newdecessiIstats_old_h[place].GetBinContent(feb29_bin-1))
fitLinears, fitLinears_res, fitLinears_error = fitLinear(newdecessiIstats_old_h, newdecessiIstats_old_h.keys(), firstDate+1, dates.index("4/30/20"), predictionsDate, maxConstExp=10000, tail=True, fitOption="SEQ0L")
for place in newdecessiIstats_old_h:
newdecessiIstatExcess_h[place] = newdecessiIstats_h[place].Clone(newdecessiIstats_h[place].GetName()+"Excess")
newdecessiIstatExcess_h[place].Add(fitLinears[place],-1)
#1/0
#for place in places:
# fits2[place] = copy.copy(ROOT.TF1("function"+place,"[0]*(1+TMath::Erf((x-[1])/[2])) + [3]",0,predictionsDate))
# mea = fitdiffs[place].GetParameter(1)
# sig = abs(fitdiffs[place].GetParameter(2))
# print "mean, sigma 0 = ", mea, sig
# fits2[place].SetParameters(casi[place][dates[lastDate]], mea, sig)
# histos[place].Fit(fits2[place],"0","",mea - 2*sig,lastDate)
# for i in range(10):
# mea = fits2[place].GetParameter(1)
# sig = abs(fits2[place].GetParameter(2))
# print "mean, sigma %i = ", mea, sig
# histos[place].Fit(fits2[place],"0","",mea - 2*sig ,lastDate)
# histos[place].Fit(fits2[place],"0","",mea - 2*sig,lastDate)
# color = colors[casi.keys().index(place)]
# fits2[place].SetLineColor(color)
#histos["Italy"].Draw()
#for place in casi.keys():
leg = ROOT.TLegend(0.9,0.1,1.0,0.9)
for place in places:
casi_h[place].GetYaxis().SetTitle("Number of cases")
if useLog: casi_h[place].SetMinimum(1)
# casi_h[place].SetBinError(casi_h[place].FindBin(lastDate-0.5),1E-9)
leg.AddEntry(casi_h[place], place, "lep")
casi_h[place].Draw("ERR,same")
prelievi_h[place].SetLineStyle(2)
# prelievi_h[place].Draw("ERR,same")
decessi_h[place].SetLineStyle(3)
# decessi_h[place].Draw("ERR,same")
# fits[place].Draw("same")
leg.Draw()
d1.SetGridx()
d1.SetGridy()
d1.SetLogy(useLog)
d1.Update()
d1.SaveAs("d1.png")
leg = ROOT.TLegend(0.9,0.1,1.0,0.9)
d2 = ROOT.TCanvas("d2","",resX,resY)
#diffs["Italy"].Draw()
#for place in ['Japan','Italy','Spain','France','South Korea']:
for place in places:
newcasi_h[place].GetYaxis().SetTitle("Number of cases / day")
if useLog: newcasi_h[place].SetMinimum(1)
newcasi_h[place].Draw("same")
# fitdiffs[place].Draw("same")
leg.Draw()
d2.SetGridx()
d2.SetGridy()
d2.SetLogy(useLog)
d2.Update()
d2.SaveAs("d2.png")
##########################################
d3 = ROOT.TCanvas("d1","",resX,resY)
leg = ROOT.TLegend(0.9,0.1,1.0,0.9)
histo_sigma1 = ROOT.TH1F("histo_sigma1","",100,0,30)
histo_sigma2 = ROOT.TH1F("histo_sigma2","",100,0,30)
#for place in places:
# histo_sigma1.Fill(abs(fitdiffs[place].GetParameter(2)))
# histo_sigma2.Fill(abs(fits[place].GetParameter(2)))
histo_sigma1.Draw()
histo_sigma2.Draw("same")
histo_sigma1.Fit("gaus")
print("Mean=",histo_sigma1.GetMean())
print("RMS=",histo_sigma1.GetRMS())
leg.Draw()
d3.SetGridx()
d3.SetGridy()
d3.SetLogy(useLog)
d3.Update()
d3.SaveAs("d3.png")
#input()
########################################
##########################################
'''
d4 = ROOT.TCanvas("d1","",resX,resY)
#ratios = getRatio(newdecessi_h, newprelievi_h)
ratios = getRatio(decessi_h, prelievi_h)
#ratios = getRatio(decessi_h, casi_h)
#ratios = getRatio(prelievi_h, casi_h)
for place in ratios:
ratios[place].SetMaximum(1)
ratios[place].SetMinimum(0)
ratios[place].Draw("HIST,C,same")
leg.Draw()
d4.SetGridx()
d4.SetGridy()
d4.SetLogy(0)
d4.Update()
'''
########################################
#print casi
#print casi["Italy"]["2/2/20"]
#file_.Write()
#file_.Close()
'''
print "############"
print "PREDICTION From %s to %s"%(dates[lastDate], dates[predictionsDate])
print "############"
for place in places:
print "#### ",place," ####"
print "sintomed (%s): %d"%(dates[lastDate], casi_h[place].GetBinContent(casi_h[place].FindBin(lastDate)))
val = casi_h[place].GetBinContent(casi_h[place].FindBin(lastDate))
print "Expected fit total (%s): %f"%(dates[predictionsDate], val + (fits[place].Eval(predictionsDate)-fits[place].Eval(lastDate)))
integr = fitdiffs[place].Integral(lastDate + 0.5, predictionsDate + 0.5)
interr = fitdiffs[place].IntegralError(lastDate + 0.5, predictionsDate + 0.5, fitdiffs_res[place].GetParams(), fitdiffs_res[place].GetCovarianceMatrix().GetMatrixArray())
print "Expected fit new cases (%s): %f +/- %f"%(dates[predictionsDate], val + integr, interr)
# for d in range(lastDate,predictionsDate):
# val = val + fitdiffs[place].Eval(d+1)
# print "Expected fit new cases (%s): %f"%(dates[predictionsDate], val)
try:
print "Real sintomed (%s): %d"%(dates[predictionsDate], casi[place][dates[predictionsDate]])
print "Error (sigma) : %f"%( (casi[place][dates[predictionsDate]] - (val + integr)) / interr)
except:
pass
'''
endDate = predictionsDate
startDate = lastDate + 1
#predictioncasi = getPrediction(places, dates, startDate, endDate, casi_h, fitdiffs, fitdiffs_res, casi)
##predictions = getPredictionErf(places, dates, startDate, endDate, casi_h, fits, fits_res, casi)
##predictionHistos = makeHistos(predictions, dates, startDate, endDate, predictionsDate, 0, errorType='dictionary')
#predictioncasi_h = makeHistos("histo_predictioncasi", predictioncasi, dates, places, startDate, None, endDate, threshold=0, cutTails=False, errorType='dictionary', lineWidth=3)
#predictiondecessi = getPrediction(places, dates, startDate, endDate, decessi_h, fitdiffdecessi, fitdiffdecessi_res, decessi)
#predictiondecessi_h = makeHistos("histo_predictiondecessi", predictiondecessi, dates, places, startDate, None, endDate, threshold=0, cutTails=False, errorType='dictionary', lineWidth=3)
#predictionprelievi = getPrediction(places, dates, startDate, endDate, prelievi_h, fitdiffprelievi, fitdiffprelievi_res, prelievi)
#predictionprelievi_h = makeHistos("histo_predictionprelievi", predictionprelievi, dates, places, startDate, None, endDate, threshold=0, cutTails=False, errorType='dictionary', lineWidth=3)
#predictionRicoveratis = getPrediction(places, dates, startDate, endDate, ricoveratis_h, fitdiffRicoveratis, fitdiffRicoveratis_res, ricoveratis)
#predictionRicoveratis_h = makeHistos("histo_predictionRicoveratis", predictionRicoveratis, dates, places, startDate, None, endDate, threshold=0, cutTails=False, errorType='dictionary', lineWidth=3)
#predictionIntensivas = getPrediction(places, dates, startDate, endDate, intensivas_h, fitdiffIntensivas, fitdiffIntensivas_res, intensivas)
#predictionIntensivas_h = makeHistos("histo_predictionIntensivas", predictionIntensivas, dates, places, startDate, None, endDate, threshold=0, cutTails=False, errorType='dictionary', lineWidth=3)
#predictionPositives = getPrediction(places, dates, startDate, endDate, positives_h, fitdiffPositives, fitdiffPositives_res, positives)
#predictionPositives_h = makeHistos("histo_predictionPositives", predictionPositives, dates, places, startDate, None, endDate, threshold=0, cutTails=False, errorType='dictionary', lineWidth=3)
#saveCSV(predictioncasi, places, dates, "predictionRegioni.csv", "predictionRegioni_error.csv")
#saveCSV(predictiondecessi, places, dates, "predictionRegioniMorti.csv", "predictionRegioniMorti_error.csv")
#saveCSV(predictionprelievi, places, dates, "predictionRegioniGuariti.csv", "predictionRegioniGuariti_error.csv")
#saveCSV(predictionIntensivas, places, dates, "predictionRegioniTerapiaIntensiva.csv", "predictionRegioniTerapiaIntensiva_error.csv")
#saveCSV(predictionPositives, places, dates, "predictionRegioniTerapiaPositive.csv", "predictionRegioniPositive_error.csv")
#saveCSV(predictionRicoveratis, places, dates, "predictionRegioniRicoverati.csv", "predictionRegioniRicoverati_error.csv")
d5 = ROOT.TCanvas("d5","",resX,resY)
#ratios = getRatio(newdecessi_h, newprelievi_h)
ratios = getRatio(decessi_h, prelievi_h)
#ratios = getRatio(decessi_h, casi_h)
#ratios = getRatio(prelievi_h, casi_h)
for place in ratios:
ratios[place].SetMaximum(1)
ratios[place].SetMinimum(0)
ratios[place].Draw("HIST,C,same")
leg.Draw()
d5.SetGridx()
d5.SetGridy()
d5.SetLogy(useLog)
d5.Update()
for place in places:
# savePlot(casi_h[place], prelievi_h[place], decessi_h[place], predictions_h[place], fits[place], fits_res[place], fits_error[place], fitexptotals[place], "plots/%s.png"%place, lastDate, d5)
# fitexptotals[place].error = fitexptotals_error[place]
# fitexptotals[place].fitResult = fitexptotals_res[place]
# fitdiffs[place].error = fitdiffs_error[place]
# fitdiffs[place].fitResult = fitdiffs_res[place]
# fitdiffdecessi[place].error = fitdiffdecessi_error[place]
# fitdiffdecessi[place].fitResult = fitdiffdecessi_res[place]
# fitdiffprelievi[place].error = fitdiffprelievi_error[place]
# fitdiffprelievi[place].fitResult = fitdiffprelievi_res[place]
# fitdiffIntensivas[place].error = fitdiffIntensivas_error[place]
# fitdiffIntensivas[place].fitResult = fitdiffIntensivas_res[place]
# fitdiffPositives[place].error = fitdiffPositives_error[place]
# fitdiffPositives[place].fitResult = fitdiffPositives_res[place]
# fitdiffRicoveratis[place].error = fitdiffRicoveratis_error[place]
# fitdiffRicoveratis[place].fitResult = fitdiffRicoveratis_res[place]
# fitexps[place].error = fitexps_error[place]
# fitexps[place].fitResult = fitexps_res[place]
if useDatiISTAT:
if not place in fitLinears: fitLinears[place] = None
else:
fitLinears[place].error = fitLinears_error[place]
fitLinears[place].res = fitLinears_res[place]
if not place in newdecessiIstatExcess_h: newdecessiIstatExcess_h[place] = None
savePlotNew([casi_h[place], prelievi_h[place], decessi_h[place], casiSintomatici_h[place] if useLog else 0], [], "plotsISS/%s.png"%place, startDate, dates, d3)
savePlotNew([newcasi_h[place], newprelievi_h[place], newdecessi_h[place], newcasiSintomatici_h[place] if useLog else 0], [], "plotsISS/%s_newCases.png"%place, startDate, dates, d3)
savePlotNew([getScaled(newcasi_h[place],newcasi_scale), getScaled(newprelievi_h[place],newprelievi_scale), getScaled(newdecessi_h[place],newdecessi_scale), getScaled(newcasiSintomatici_h[place],newcasiSintomatici_scale)], [], "plotsISS/%s_newCases_scaled.png"%place, startDate, dates, d3, log=False)
fromZero=False
savePlotNew([getScaled(casi_h[place], casi_scale, fromZero), getScaled(prelievi_h[place], prelievi_scale, fromZero), getScaled(decessi_h[place], decessi_scale, fromZero), getScaled(casiSintomatici_h[place], casiSintomatici_scale, fromZero)], [], "plotsISS/%s_scaled.png"%place, startDate, dates, d3, log=False)
positiveTocasiSintomaticiRatio = newcasi_h[place].Clone("positiveTocasiSintomaticiRatio_"+place)
positiveTocasiSintomaticiRatio.Reset()
positiveTocasiSintomaticiRatio.Divide(newcasiSintomatici_h[place], newcasi_h[place])
# positiveHisto(positiveTocasiSintomaticiRatio)
# for i in range(positiveTocasiSintomaticiRatio.GetNbins()+2):
# if positiveTocasiSintomaticiRatio.GetBinContent(i)<0: positiveTocasiSintomaticiRatio.SetBinContent(i,0)
decessiToRecoverRatio = decessi_h[place].Clone("decessiToRecoverRatio_"+place)
decessiToRecoverRatio.Reset()
decessiToRecoverRatio.Divide(prelievi_h[place], decessi_h[place])
decessiDailyToRecoverRatio = newdecessi_h[place].Clone("decessiDailyToRecoverRatio_"+place)
decessiDailyToRecoverRatio.Reset()
decessiDailyToRecoverRatio.Divide(newprelievi_h[place], newdecessi_h[place])
savePlotNew([getScaled(positiveTocasiSintomaticiRatio,0.2), decessiToRecoverRatio,decessiDailyToRecoverRatio], [], "plotsISS/%s_rapporto.png"%place, startDate, dates, d3, log=False)
ROOT.gROOT.SetBatch(0)
canv=ROOT.TCanvas("canv")
p = "Italia"
#p = placescasiSintomatici[0]
#intensivas_h[p].Draw()
#newdecessi_h[p].Draw()
#fitdiffdecessi[p].Draw("same")
#print(fitdiffdecessi[p])
#fitdiffdecessi[p].Print()
#newdecessi_h[p].Fit(fitdiffdecessi[p])
#newcasi_h[p].Draw()
#fitdiffs[p].Draw("same")
#print(fitdiffs[p])
#fitdiffs[p].Print()
#newcasi_h[p].Fit(fitdiffs[p])
#newcasi_h[p].Draw()
#fitdiffs[p].Draw("same")
#newcasi_h['Liguria'].Draw()
#fitdiffs['Liguria'].Draw("same")
#newdecessi_h[p].Draw()
#fitdiffdecessi[p].Draw("same")
#intensivas_h[p].Draw()
#predictionIntensivas_h[p].Draw("same")
newcasi_h[p].Draw()
#fitdiffs[p].Draw("same")
#fitdiffs[p].error.Draw("same")
#newRicoveratis_h[p].Draw()
#fitdiffRicoveratis[p].Draw("same")
#newprelievi_h[p].Draw()
#fitdiffprelievi[p].Draw("same")
#hist = newcasi_h[p]
#fixSigma=10
#fitdiffs[place].SetParameters(hist.GetMaximum(), hist.GetXaxis().GetXmax(), fixSigma, hist.GetXaxis().GetXmax(), hist.GetXaxis().GetXmax()/log(hist.GetMaximum()))
#hist.Draw()
#fitdiffs[place].Draw("same")
'''
TFitResultPtr r = graph->Fit(myFunction,"S");
double x[1] = { x0 };
double err[1]; // error on the function at point x0
r->GetConfidenceIntervals(1, 1, 1, x, err, 0.683, false);
cout << " function value at " << x[0] << " = " << myFunction->Eval(x[0]) << " +/- " << err[0] << endl;
'''