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scriptItaly_scaled.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, fitExpGauss, applyScaleFactors, useLog, positiveHisto, fitTwoGaussDiff, fitGaussExp, getScaled
placesTest = []
#placesTest = ["Italia","LaSpezia"]
placesTest = ["Italia"]
#placesTest = ["Veneto"]
startFromZero = False
#startFromZero = True
daysSmearing = 1
#doProvince = False
doProvince = True
useScaleFactor = True
#useScaleFactor = False
useDatiISTAT = False
#useDatiISTAT = True
if len(placesTest)>0:
doProvince = False
import ROOT
ROOT.gStyle.SetOptStat(0)
ROOT.gROOT.SetBatch(1)
#ROOT.gROOT.SetBatch(0)
resX, resY = 1920, 1080
#file_ = ROOT.TFile("data.root", "RECREATE")
if useDatiISTAT:
# dataISTAT, datesISTAT = fillDataISTATpickle('DatiISTAT/dati-giornalieri-comune/comune_giorno.csv', zerosuppression=100, pickleFileName = "temp_italia.pkl", writePickle = False)
# dataISTAT, datesISTAT = fillDataISTATpickle('dataISTAT/comuni_giornaliero_30giugno.csv', zerosuppression=100, pickleFileName = "temp_italia_31maggio.pkl", writePickle = False)
dataISTAT, datesISTAT = fillDataISTATpickle('dataISTAT/comuni_giornaliero_30settembre.csv', zerosuppression=100, pickleFileName = "temp_italia_30settembre.pkl", writePickle = False)
dataISTAT = makeCompatible(dataISTAT, firstDateDay=23, firstDateMonth=2)
dataRegioni, dates = fillDataRegioni('dataItaly/dati-regioni/dpc-covid19-ita-regioni.csv')
if (doProvince): dataProvince, dates = fillDataRegioni('dataItaly/dati-province/dpc-covid19-ita-province.csv', "denominazione_provincia")
#data,stato,codice_regione,denominazione_regione,lat,long,ricoverati_con_sintomi,terapia_intensiva,totale_ospedalizzati,isolamento_domiciliare,totale_attualmente_Positive,nuovi_attualmente_Positive,dimessi_guariti,deceduti,totale_casi,tamponi
SF_test=0.1
SF_ricoverati=20
SF_intensiva=200
SF_decessi=30
tests = getColumn(dataRegioni, "tamponi", scaleFactor=SF_test)
intensivas = getColumn(dataRegioni, "terapia_intensiva", scaleFactor=SF_intensiva)
ricoveratis = getColumn(dataRegioni, "ricoverati_con_sintomi", scaleFactor=SF_ricoverati)
confirmes = getColumn(dataRegioni, "totale_casi", scaleFactor=1.)
deaths = getColumn(dataRegioni, "deceduti", scaleFactor=SF_decessi)
recoveres = getColumn(dataRegioni, "dimessi_guariti", scaleFactor=1.)
if (doProvince): confirmesProv = getColumn(dataProvince, "totale_casi")
if useDatiISTAT:
# datesISTAT = dataISTAT.values()[0].keys()
newDeathIstats = selectComuniDatesAgeGender(dataISTAT, dates, places=None, ages=range(0,30), genders=[0,1])
newDeathIstats_old = selectComuniDatesAgeGender(dataISTAT, dates, places=None, ages=range(0,30), genders=[2,3])
lastDateData = len(dates)-1
dates = extendDates(dates, 650)
################
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("12/31/20")
firstDate = dates.index("1/3/21")
#firstDate = dates.index("4/1/20")
#firstDate = 16
lastDate = lastDateData - 1
#lastDate = dates.index("2/29/20")
#lastDate = dates.index("3/1/20")
#lastDate = 30
#predictionsDate = dates.index("12/31/20")
predictionsDate = dates.index("5/3/21")
#predictionsDate = 95
#firstDate = dates.index("3/1/20")
#predictionsDate = dates.index("2/1/21")
#firstDate = dates.index("3/1/20")
#lastDate = dates.index("5/1/20")
#predictionsDate = dates.index("6/30/20")
#firstDate = 10
#lastDate = 35
#predictionsDate = 35
################
#confirmes = deaths
positives = {}
for place in confirmes:
positives[place] = {}
for i in range(0, len(confirmes[place])):
positives[place][dates[i]] = confirmes[place][dates[i]] - deaths[place][dates[i]]/SF_decessi - recoveres[place][dates[i]]
newConfirmes = newCases(confirmes, dates)
newDeaths = newCases(deaths, dates)
newRecoveres = newCases(recoveres, dates)
newTests = newCases(tests, dates)
newIntensivas = newCases(intensivas, dates)
newRicoveratis = newCases(ricoveratis, dates)
newPositives = newCases(positives, dates)
if (doProvince): newConfirmesProv = newCases(confirmesProv, dates)
###########################
places = []
for place in confirmes.keys():
if place == "Others": continue
if confirmes[place][dates[lastDate]]>50:
places.append(place)
if (doProvince):
province = []
for place in confirmesProv.keys():
if place == "Others": continue
if confirmesProv[place][dates[lastDate]]>50:
province.append(place)
places = [p[1] for p in sorted([(confirmes[p][dates[lastDate]], p) for p in places], reverse=True)]
if (doProvince): province = [p[1] for p in sorted([(confirmesProv[p][dates[lastDate]], p) for p in province], reverse=True)]
places.remove("Trento")
places.remove("Basilicata")
#province.remove("FuoriRegione/ProvinciaAutonoma")
#province.remove("Infasedidefinizione/aggiornamento")
#places = ["Italia","Lombardia"]
#places = ["Italia","Lombardia"]
#places = ["Nord", "Lombardia", "Piemonte"]
#province = ["La Spezia", "Pisa", "Genova", "Milano", "Brescia", "Bergamo"]
#province = ["Pisa"]
#places = ["Lombardia"]
#places = ["Italia"]
#places = ["Liguria"]
if len(placesTest)>0: places = placesTest
#print "places:",places
################
fits = {}
fits2 = {}
fitdiffs = {}
d1 = ROOT.TCanvas("d1","",resX,resY)
positives_h = makeHistos("histo_positives", positives, dates, places, firstDate, lastDate, predictionsDate, 0, cutTails=False, errorType='cumulative', lineWidth=2, daysSmearing=1)
confirmes_h = makeHistos("histo_confirmes", confirmes, dates, places, firstDate, lastDate, predictionsDate, 0, cutTails=False, errorType='cumulative', lineWidth=2, daysSmearing=1)
recoveres_h = makeHistos("histo_recoveres", recoveres, dates, places, firstDate, lastDate, predictionsDate, 0, cutTails=False, errorType='cumulative', lineWidth=2, daysSmearing=1)
deaths_h = makeHistos("histo_deaths", deaths, dates, places, firstDate, lastDate, predictionsDate, 0, cutTails=False, errorType='cumulative', lineWidth=2, daysSmearing=1)
tests_h = makeHistos("histo_tests", tests, dates, places, firstDate, lastDate, predictionsDate, 0, cutTails=False, errorType='cumulative', lineWidth=2, daysSmearing=1)
ricoveratis_h = makeHistos("histo_ricoveratis", ricoveratis, dates, places, firstDate, lastDate, predictionsDate, 0, cutTails=False, errorType='cumulative', lineWidth=2, daysSmearing=1)
intensivas_h = makeHistos("histo_intensivas", intensivas, dates, places, firstDate, lastDate, predictionsDate, 0, cutTails=False, errorType='cumulative', lineWidth=2, daysSmearing=1)
if startFromZero:
for place in places:
for histo in [positives_h,confirmes_h,recoveres_h,deaths_h,tests_h,ricoveratis_h,intensivas_h]:
minVal_ = histo[place].GetBinContent(1)
for ibin in range(1,lastDate-firstDate):
val = histo[place].GetBinContent(ibin)
if val < minVal_:
minVal_ = val
# val = float(minVal_-1)
val = histo[place].GetBinContent(1)
for i in range(histo[place].GetNbinsX()+2):
histo[place].SetBinContent(i, histo[place].GetBinContent(i) - val)
# removeOffset(histo[place], firstDate)
#print("CHECK",positives_h[place].GetBinContent(1))
#histos = makeHistos(confirmes, places, firstDate, lastDate, predictionsDate, cumulativeError=True)
#eType = "default"
eType = "3sqrtN"
newConfirmes_h = makeHistos("histo_newConfirmes", newConfirmes, dates, places, firstDate, lastDate, predictionsDate, 1, cutTails=True, lineWidth=2, daysSmearing=daysSmearing, errorType=eType)
newRecoveres_h = makeHistos("histo_newRecoveres", newRecoveres, dates, places, firstDate, lastDate, predictionsDate, 1, cutTails=False, lineWidth=2, daysSmearing=daysSmearing, errorType=eType)
newDeaths_h = makeHistos("histo_newDeaths", newDeaths, dates, places, firstDate, lastDate, predictionsDate, 1, cutTails=False, lineWidth=2, daysSmearing=daysSmearing, errorType=eType)
newTests_h = makeHistos("histo_newTests", newTests, dates, places, firstDate, lastDate, predictionsDate, 1, cutTails=False, lineWidth=2, daysSmearing=daysSmearing, errorType=eType)
newRicoveratis_h = makeHistos("histo_newRicoveratis", newRicoveratis, dates, places, firstDate, lastDate, predictionsDate, 1, cutTails=False, lineWidth=2, daysSmearing=daysSmearing, errorType=eType)
newIntensivas_h = makeHistos("histo_newIntensivas", newIntensivas, dates, places, firstDate, lastDate, predictionsDate, 1, cutTails=False, lineWidth=2, daysSmearing=daysSmearing, errorType=eType)
newPositives_h = makeHistos("histo_newpositives", newPositives, dates, places, firstDate, lastDate, predictionsDate, 1, cutTails=False, lineWidth=2, daysSmearing=daysSmearing, errorType=eType)
for place in places:
if useScaleFactor:
for histo in [newPositives_h,newConfirmes_h,newRecoveres_h,newDeaths_h,newTests_h,newRicoveratis_h,newIntensivas_h]:
applyScaleFactors(histo[place], errorType=eType)
if useLog:
for histo in [newPositives_h,newConfirmes_h,newRecoveres_h,newDeaths_h,newTests_h,newRicoveratis_h,newIntensivas_h,positives_h,confirmes_h,recoveres_h,deaths_h,tests_h,ricoveratis_h,intensivas_h]:
positiveHisto(histo[place])
fits, fits_res, fits_error = fitErf(confirmes_h, places, firstDate, lastDate, predictionsDate)
#fitdiffs, fitdiffs_res, fitdiffs_error = fitGaussAsymmetric(newConfirmes_h, places, firstDate, lastDate, predictionsDate)
fitdiffs, fitdiffs_res, fitdiffs_error = fitGaussExp(newConfirmes_h, places, firstDate, lastDate, predictionsDate)
fitexps, fitexps_res, fitexps_error = fitExp(newConfirmes_h, places, lastDate-14, lastDate, predictionsDate)
fitexptotals, fitexptotals_res, fitexptotals_error = fitExp(confirmes_h, places, lastDate-14-1, lastDate-1, predictionsDate)
#fitexptotals, fitexptotals_res, fitexptotals_error = fitExp(confirmes_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)
fitdiffDeaths, fitdiffDeaths_res, fitdiffDeaths_error = fitGaussExp(newDeaths_h, places, firstDate, lastDate, predictionsDate)
fitdiffRecoveres, fitdiffRecoveres_res, fitdiffRecoveres_error = fitGaussExp(newRecoveres_h, places, firstDate, lastDate, predictionsDate)
newDeathIstatExcess_h = {}
if useDatiISTAT:
newDeathIstats_h = makeHistos("histo_ISTAT", newDeathIstats, dates, places, firstDate, lastDate, predictionsDate, 1, cutTails=False, lineWidth=2, errorType='sqrtN')
newDeathIstats_old_h = makeHistos("histo_ISTAT_old", newDeathIstats_old, dates, places, firstDate, lastDate, predictionsDate, 1, cutTails=False, lineWidth=2, errorType='sqrtN')
for place in newDeathIstats_old_h:
if newDeathIstats_old_h[place].Integral(0, dates.index("2/28/20"))>0: newDeathIstats_old_h[place].Scale(newDeathIstats_h[place].Integral(0, dates.index("2/28/20"))/newDeathIstats_old_h[place].Integral(0, dates.index("2/28/20")))
feb29_bin = dates.index("3/1/20")
newDeathIstats_old_h[place].SetBinContent(feb29_bin, newDeathIstats_old_h[place].GetBinContent(feb29_bin-1))
newDeathIstats_old_h[place].SetBinError( feb29_bin, newDeathIstats_old_h[place].GetBinContent(feb29_bin-1))
fitLinears, fitLinears_res, fitLinears_error = fitLinear(newDeathIstats_old_h, newDeathIstats_old_h.keys(), firstDate+1, dates.index("4/30/20"), predictionsDate, maxConstExp=10000, tail=True, fitOption="SEQ0L")
for place in newDeathIstats_old_h:
newDeathIstatExcess_h[place] = newDeathIstats_h[place].Clone(newDeathIstats_h[place].GetName()+"Excess")
newDeathIstatExcess_h[place].Add(fitLinears[place],-1)
#1/0
if (doProvince):
confirmesProv_h = makeHistos("histo_confirmes", confirmesProv, dates, province, firstDate, lastDate, predictionsDate, 0, cutTails=False, errorType='cumulative', lineWidth=2, daysSmearing=1)
newConfirmesProv_h = makeHistos("histo_newConfirmes", newConfirmesProv, dates, province, firstDate, lastDate, predictionsDate, 1, cutTails=True, lineWidth=2, daysSmearing=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(confirmes[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[confirmes.keys().index(place)]
# fits2[place].SetLineColor(color)
#histos["Italy"].Draw()
#for place in confirmes.keys():
leg = ROOT.TLegend(0.9,0.1,1.0,0.9)
for place in places:
confirmes_h[place].GetYaxis().SetTitle("Number of cases")
if useLog: confirmes_h[place].SetMinimum(1)
# confirmes_h[place].SetBinError(confirmes_h[place].FindBin(lastDate-0.5),1E-9)
leg.AddEntry(confirmes_h[place], place, "lep")
confirmes_h[place].Draw("ERR,same")
recoveres_h[place].SetLineStyle(2)
# recoveres_h[place].Draw("ERR,same")
deaths_h[place].SetLineStyle(3)
# deaths_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)
if (doProvince):
confirmesProv_h.values()[0].Draw("ERR")
for place in province:
confirmesProv_h[place].GetYaxis().SetTitle("Number of cases")
if useLog: confirmesProv_h[place].SetMinimum(1)
# confirmes_h[place].SetBinError(confirmes_h[place].FindBin(lastDate-0.5),1E-9)
leg.AddEntry(confirmesProv_h[place], place, "lep")
confirmesProv_h[place].Draw("ERR,same")
# recoveresProv_h[place].SetLineStyle(2)
# recoveresProv_h[place].Draw("ERR,same")
# deathsProv_h[place].SetLineStyle(3)
# deathsProv_h[place].Draw("ERR,same")
# fits[place].Draw("same")
d1.SaveAs("d1_prov.png")
d2 = ROOT.TCanvas("d2","",resX,resY)
#diffs["Italy"].Draw()
positives = {}
for place in confirmes:
positives[place] = {}
for i in range(0, len(confirmes[place])):
positives[place][dates[i]] = confirmes[place][dates[i]] - deaths[place][dates[i]] - recoveres[place][dates[i]]
#for place in ['Japan','Italy','Spain','France','South Korea']:
for place in places:
newConfirmes_h[place].GetYaxis().SetTitle("Number of cases / day")
if useLog: newConfirmes_h[place].SetMinimum(1)
newConfirmes_h[place].Draw("same")
fitdiffs[place].Draw("same")
leg.Draw()
d2.SetGridx()
d2.SetGridy()
d2.SetLogy(useLog)
d2.Update()
d2.SaveAs("d2.png")
if (doProvince):
d2 = ROOT.TCanvas("d2_prov","",resX,resY)
leg = ROOT.TLegend(0.9,0.1,1.0,0.9)
newConfirmesProv_h.values()[0].Draw("ERR")
#for place in ['Japan','Italy','Spain','France','South Korea']:
for place in province:
newConfirmesProv_h[place].GetYaxis().SetTitle("Number of cases / day")
if useLog: newConfirmesProv_h[place].SetMinimum(1)
newConfirmesProv_h[place].Draw("same")
leg.Draw()
d2.SetGridx()
d2.SetGridy()
d2.SetLogy(useLog)
d2.Update()
d2.SaveAs("d2_prov.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(newDeaths_h, newRecoveres_h)
ratios = getRatio(deaths_h, recoveres_h)
#ratios = getRatio(deaths_h, confirmes_h)
#ratios = getRatio(recoveres_h, confirmes_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 confirmes
#print confirmes["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 "Confirmed (%s): %d"%(dates[lastDate], confirmes_h[place].GetBinContent(confirmes_h[place].FindBin(lastDate)))
val = confirmes_h[place].GetBinContent(confirmes_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 Confirmed (%s): %d"%(dates[predictionsDate], confirmes[place][dates[predictionsDate]])
print "Error (sigma) : %f"%( (confirmes[place][dates[predictionsDate]] - (val + integr)) / interr)
except:
pass
'''
endDate = predictionsDate
startDate = lastDate + 1
predictionConfirmes = getPrediction(places, dates, startDate, endDate, confirmes_h, fitdiffs, fitdiffs_res, confirmes)
#predictions = getPredictionErf(places, dates, startDate, endDate, confirmes_h, fits, fits_res, confirmes)
#predictionHistos = makeHistos(predictions, dates, startDate, endDate, predictionsDate, 0, errorType='dictionary')
predictionConfirmes_h = makeHistos("histo_predictionConfirmes", predictionConfirmes, dates, places, startDate, None, endDate, threshold=0, cutTails=False, errorType='dictionary', lineWidth=3)
predictionDeaths = getPrediction(places, dates, startDate, endDate, deaths_h, fitdiffDeaths, fitdiffDeaths_res, deaths)
predictionDeaths_h = makeHistos("histo_predictionDeaths", predictionDeaths, dates, places, startDate, None, endDate, threshold=0, cutTails=False, errorType='dictionary', lineWidth=3)
predictionRecoveres = getPrediction(places, dates, startDate, endDate, recoveres_h, fitdiffRecoveres, fitdiffRecoveres_res, recoveres)
predictionRecoveres_h = makeHistos("histo_predictionRecoveres", predictionRecoveres, 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(predictionConfirmes, places, dates, "predictionRegioni.csv", "predictionRegioni_error.csv")
saveCSV(predictionDeaths, places, dates, "predictionRegioniMorti.csv", "predictionRegioniMorti_error.csv")
saveCSV(predictionRecoveres, 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(newDeaths_h, newRecoveres_h)
ratios = getRatio(deaths_h, recoveres_h)
#ratios = getRatio(deaths_h, confirmes_h)
#ratios = getRatio(recoveres_h, confirmes_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(confirmes_h[place], recoveres_h[place], deaths_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]
fitdiffDeaths[place].error = fitdiffDeaths_error[place]
fitdiffDeaths[place].fitResult = fitdiffDeaths_res[place]
fitdiffRecoveres[place].error = fitdiffRecoveres_error[place]
fitdiffRecoveres[place].fitResult = fitdiffRecoveres_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 newDeathIstatExcess_h: newDeathIstatExcess_h[place] = None
savePlotNew([confirmes_h[place], recoveres_h[place], deaths_h[place], predictionConfirmes_h[place], predictionDeaths_h[place], predictionRecoveres_h[place], predictionIntensivas_h[place], predictionPositives_h[place], predictionRicoveratis_h[place], intensivas_h[place], ricoveratis_h[place], tests_h[place] , positives_h[place]], [fitexptotals[place]], "plotsRegioni/%s.png"%place, startDate, dates, d3)
savePlotNew([newConfirmes_h[place], newRecoveres_h[place], newDeaths_h[place], newDeathIstatExcess_h[place], newIntensivas_h[place], newRicoveratis_h[place], newTests_h[place] , newPositives_h[place]], [fitexps[place], fitdiffs[place], fitdiffRecoveres[place], fitdiffDeaths[place], fitdiffIntensivas[place], fitdiffPositives[place], fitdiffRicoveratis[place]], "plotsRegioni/%s_newCases.png"%place, startDate, dates, d3)
# savePlotNew([newDeathIstats_old_h[place]], [fitLinears[place]], "plotsRegioni/%s_newCases.png"%place, startDate, d3)
if (doProvince):
for place in province:
# savePlot(confirmesProv_h[place], confirmesProv_h[place], confirmesProv_h[place], None, None, None, None, None, None, None, None, "plotsProvince/%s.png"%place, lastDate, d3)
# savePlot(newConfirmesProv_h[place], newConfirmesProv_h[place], newConfirmesProv_h[place], None, None, None, None, None, None, None, None, "plotsProvince/%s_newCases.png"%place, lastDate, d3)
savePlotNew([confirmesProv_h[place]], [], "plotsProvince/%s.png"%place, startDate, dates, d3)
savePlotNew([newConfirmesProv_h[place]], [], "plotsProvince/%s_newCases.png"%place, startDate, dates, d3)
ROOT.gROOT.SetBatch(0)
canv=ROOT.TCanvas("canv")
p = "Italia"
p = placesTest[0]
#intensivas_h[p].Draw()
#newDeaths_h[p].Draw()
#fitdiffDeaths[p].Draw("same")
#print(fitdiffDeaths[p])
#fitdiffDeaths[p].Print()
#newDeaths_h[p].Fit(fitdiffDeaths[p])
#newConfirmes_h[p].Draw()
#fitdiffs[p].Draw("same")
#print(fitdiffs[p])
#fitdiffs[p].Print()
#newConfirmes_h[p].Fit(fitdiffs[p])
newIntensivas_h[p].Draw()
fitdiffIntensivas[p].Draw("same")
#newConfirmes_h[p].Draw()
#fitdiffs[p].Draw("same")
#newConfirmes_h['Liguria'].Draw()
#fitdiffs['Liguria'].Draw("same")
#newDeaths_h[p].Draw()
#fitdiffDeaths[p].Draw("same")
#intensivas_h[p].Draw()
#predictionIntensivas_h[p].Draw("same")
#newConfirmes_h[p].Draw()
#fitdiffs[p].Draw("same")
#fitdiffs[p].error.Draw("same")
#newRicoveratis_h[p].Draw()
#fitdiffRicoveratis[p].Draw("same")
#newRecoveres_h[p].Draw()
#fitdiffRecoveres[p].Draw("same")
#hist = newConfirmes_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;
'''