def increment_incidenceEvolutionByAge(self):
report_date_list = self.getReportDate()
age_list = self.getAge()
nb_cases_list = self.getNbCases()
## Reverse
age_key_list = ['total'] + self.age_key_list[::-1]
## Initialize stock
stock = ccm.initializeStock_dailyCounts(age_key_list)
## Loop over series
for report_date, age, nb_cases in zip(report_date_list, age_list,
nb_cases_list):
ind = ccm.indexForOverall(report_date)
try:
stock['total'][ind] += nb_cases
except IndexError:
pass
else:
try:
stock[age][ind] += nb_cases
except KeyError:
pass
return stock
def increment_localCasePerCounty(self):
report_date_list = self.getReportDate()
county_list = self.getCounty()
nb_cases_list = self.getNbCases()
## Initialize stock
county_key_list = ['total'] + self.county_key_list
stock = ccm.initializeStock_dailyCounts(county_key_list)
ind_max = 0
## Loop over series
for report_date, county, nb_cases in zip(report_date_list, county_list,
nb_cases_list):
if 'unknown' == county:
continue
ind = ccm.indexForOverall(report_date)
ind_max = max(ind_max, ind + 1)
try:
stock['total'][ind] += nb_cases
stock[county][ind] += nb_cases
except IndexError: ## If NaN
pass
ind_today = ccm.getTodayOrdinal() - ccm.ISODateToOrd(ccm.ISO_DATE_REF)
ind = max(ind_max, ind_today - 1) ## Take the max of data date & today
stock = {k: v[:ind] for k, v in stock.items()}
## Moving average
for key in county_key_list:
stock[key + '_avg'] = ccm.makeMovingAverage(stock[key])
return stock
def increment_caseByTransmission(self):
report_date_list = self.getReportDate()
onset_date_list = self.getOnsetDate()
trans_list = self.getTransmission()
link_list = self.getLink()
## Initialize stocks
trans_key_list = ['imported', 'linked', 'unlinked', 'fleet', 'plane', 'unknown']
stock_r = ccm.initializeStock_dailyCounts(trans_key_list)
stock_o = ccm.initializeStock_dailyCounts(trans_key_list)
## Loop over cases
for report_date, onset_date, trans, link in zip(report_date_list, onset_date_list, trans_list, link_list):
if trans != trans:
continue
## Determine column tag
if trans == 'local':
if link == 'unlinked':
key = link
else:
key = 'linked'
else:
key = trans
try:
ind = ccm.indexForOverall(report_date)
stock_r[key][ind] += 1
except IndexError: ## If NaN
pass
## Check if NaN
if onset_date != onset_date:
continue
try:
ind = ccm.indexForOverall(onset_date)
stock_o[key][ind] += 1
except IndexError: ## If NaN
pass
return stock_r, stock_o
def increment_caseByDetection(self):
report_date_list = self.getReportDate()
onset_date_list = self.getOnsetDate()
trans_list = self.getTransmission()
channel_list = self.getChannel()
## Initialize data dict
det_key_list = ['airport', 'quarantine', 'isolation', 'monitoring', 'hospital', 'overseas', 'no_data']
stock_r = ccm.initializeStock_dailyCounts(det_key_list)
stock_o = ccm.initializeStock_dailyCounts(det_key_list)
## Loop over cases
for report_date, onset_date, trans, channel in zip(report_date_list, onset_date_list, trans_list, channel_list):
if trans != trans:
continue
## Determine column tag
if channel != channel:
key = 'no_data'
else:
key = channel
try:
ind = ccm.indexForOverall(report_date)
stock_r[key][ind] += 1
except IndexError: ## If NaN
pass
## Check if NaN
if onset_date != onset_date:
continue
try:
ind = ccm.indexForOverall(onset_date)
stock_o[key][ind] += 1
except IndexError: ## If NaN
pass
return stock_r, stock_o
def increment_deathCounts(self):
report_date_list = self.getReportDate()
## Initialize stocks
col_tag_list = ['death']
stock = ccm.initializeStock_dailyCounts(col_tag_list)
## Loop over cases
for report_date in report_date_list:
try:
ind = ccm.indexForOverall(report_date)
stock['death'][ind] += 1
except IndexError: ## If NaN
pass
## Make avg
for key in col_tag_list:
stock[key + '_avg'] = ccm.makeMovingAverage(stock[key])
return stock
def increment_incidenceEvolutionByCounty(self):
report_date_list = self.getReportDate()
county_list = self.getCounty()
nb_cases_list = self.getNbCases()
## Initialize stock
county_key_list = ['total'] + self.county_key_list
stock = ccm.initializeStock_dailyCounts(county_key_list)
## Loop over series
for report_date, county, nb_cases in zip(report_date_list, county_list,
nb_cases_list):
if 'unknown' == county:
continue
ind = ccm.indexForOverall(report_date)
try:
stock[county][ind] += nb_cases
stock['total'][ind] += nb_cases
except IndexError:
pass
return stock