def get_most_recent_issue(self):
"""Return the most recent epiweek for which FluView data is available."""
ew2 = EpiDate.today().get_ew()
ew1 = add_epiweeks(ew2, -9)
response = self.epidata.fluview('nat', self.epidata.range(ew1, ew2))
issues = [row['issue'] for row in self.epidata.check(response)]
return max(issues)
def get_kcdc_data():
issue = EpiDate.today().get_ew()
last_season = issue // 100 + (1 if issue % 100 > 35 else 0)
url = 'http://www.cdc.go.kr/npt/biz/npp/iss/influenzaListAjax.do'
params = {
'icdNm': 'influenza',
'startYear': '2004', # Started in 2004
'endYear': str(last_season)
}
response = requests.post(url, params)
datas = response.json()
data = datas['data']
ews = []
ilis = []
ew1 = 200436
for year in range(2004, last_season):
year_data = data[year - 2004]
if year > 2004:
ew1 = ews[-1] + 1
ili_yr = year_data["VALUE"].split('`')
ili_yr = [float(f) for f in ili_yr if f != '']
ew2 = add_epiweeks(ew1, len(ili_yr))
new_ews = list(range_epiweeks(ew1, ew2))
for i in range(len(new_ews)):
j = float(ili_yr[i])
ilis.append(j)
ews.append(new_ews[i])
return ews, ilis
def main():
# args and usage
parser = argparse.ArgumentParser()
parser.add_argument(
'--test',
action='store_true',
help='do dry run only, do not update the database'
)
parser.add_argument(
'--file',
type=str,
help='load an existing zip file (otherwise fetch current data)'
)
parser.add_argument(
'--issue',
type=int,
help='issue of the file (e.g. 201740); used iff --file is given'
)
args = parser.parse_args()
if (args.file is None) != (args.issue is None):
raise Exception('--file and --issue must both be present or absent')
date = datetime.datetime.now().strftime('%Y-%m-%d')
print('assuming release date is today, %s' % date)
ensure_tables_exist()
if args.file:
update_from_file(args.issue, date, args.file, test_mode=args.test)
else:
# Code doesn't always download all files, unreproducible errors
# Try a few times and hopefully one will work
flag = 0
max_tries = 5
while flag < max_tries:
flag = flag + 1
tmp_dir = ''.join(random.choice('0123456789abcdefghijklmnopqrstuvwxyz') for i in range(8))
tmp_dir = 'downloads_' + tmp_dir
subprocess.call(["mkdir",tmp_dir])
# Use temporary directory to avoid data from different time
# downloaded to same folder
download_ecdc_data(download_dir=tmp_dir)
issue = EpiDate.today().get_ew()
files = glob.glob('%s/*.csv' % tmp_dir)
for filename in files:
with open(filename,'r') as f:
_ = f.readline()
db_error = False
for filename in files:
try:
update_from_file(issue, date, filename, test_mode=args.test)
subprocess.call(["rm",filename])
except Exception:
db_error = True
subprocess.call(["rm","-r",tmp_dir])
if not db_error:
break # Exit loop with success
if flag >= max_tries:
print('WARNING: Database `ecdc_ili` did not update successfully')
def get_weeks(self):
"""Return a list of weeks on which truth and sensors are both available."""
latest_week = EpiDate.today().get_ew()
latest_week = add_epiweeks(latest_week, -1)
week_range = range_epiweeks(self.FIRST_DATA_EPIWEEK,
latest_week,
inclusive=True)
return list(week_range)
def get_most_recent_issue(self, location):
"""Return the most recent epiweek for which paho_dengue data is available in given location."""
ew2 = EpiDate.today().get_ew()
ew1 = add_epiweeks(ew2, -52)
response = self.epidata.paho_dengue(location,
self.epidata.range(ew1, ew2))
ews = [row['epiweek'] for row in self.epidata.check(response)]
return max(ews)
def main():
# args and usage
parser = argparse.ArgumentParser()
parser.add_argument('--test',
action='store_true',
help='do dry run only, do not update the database')
args = parser.parse_args()
date = datetime.datetime.now().strftime('%Y-%m-%d')
print('assuming release date is today, %s' % date)
issue = EpiDate.today().get_ew()
ensure_tables_exist()
ews, ilis = get_kcdc_data()
update_from_data(ews, ilis, date, issue, test_mode=args.test)
#print('Updated Epicast df for %d users.' % future._num_users)
forecaster._callback = update_epicast_df
print('Generating epicast for', epiweek)
forecaster.open()
forecast = forecaster.forecast(
epiweek) # is this the forecast function in fc_abstract.py?
filename = ForecastIO.save_csv(forecast)
forecaster.close()
print(filename)
return filename
if __name__ == '__main__':
epiweek = EpiDate.today().add_weeks(-1).get_ew()
print("epiweek: ", epiweek)
print('WARNING: For testing only!')
print(' - Using very small number of samples')
print(' - Not uploading submissions to database')
print(' - Not emailing submissions to CDC')
print(' - Assuming last published wILI on %d' % epiweek)
print(' - Limited locations')
ec_age_groups = [
'rate_overall', 'rate_age_0', 'rate_age_1', 'rate_age_2', 'rate_age_3',
'rate_age_4'
]
sub = Submissions_Hosp(ec_age_groups, 1000)
ec = None
ec = sub.run_epicast(epiweek, 0.001, 0.001)
def update(issue, location_name, test_mode=False):
"""Fetch and store the currently avialble weekly FluSurv dataset."""
# fetch data
location_code = flusurv.location_codes[location_name]
print('fetching data for', location_name, location_code)
data = flusurv.get_data(location_code)
# metadata
epiweeks = sorted(data.keys())
location = location_name
release_date = str(EpiDate.today())
# connect to the database
u, p = secrets.db.epi
cnx = mysql.connector.connect(user=u, password=p, database='epidata')
cur = cnx.cursor()
rows1 = get_rows(cur)
print('rows before: %d' % rows1)
# SQL for insert/update
sql = '''
INSERT INTO `flusurv` (
`release_date`, `issue`, `epiweek`, `location`, `lag`, `rate_age_0`,
`rate_age_1`, `rate_age_2`, `rate_age_3`, `rate_age_4`, `rate_overall`,
`rate_age_5`, `rate_age_6`, `rate_age_7`
)
VALUES (
%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s
)
ON DUPLICATE KEY UPDATE
`release_date` = least(`release_date`, %s),
`rate_age_0` = coalesce(%s, `rate_age_0`),
`rate_age_1` = coalesce(%s, `rate_age_1`),
`rate_age_2` = coalesce(%s, `rate_age_2`),
`rate_age_3` = coalesce(%s, `rate_age_3`),
`rate_age_4` = coalesce(%s, `rate_age_4`),
`rate_overall` = coalesce(%s, `rate_overall`),
`rate_age_5` = coalesce(%s, `rate_age_5`),
`rate_age_6` = coalesce(%s, `rate_age_6`),
`rate_age_7` = coalesce(%s, `rate_age_7`)
'''
# insert/update each row of data (one per epiweek)
for epiweek in epiweeks:
lag = delta_epiweeks(epiweek, issue)
if lag > 52:
# Ignore values older than one year, as (1) they are assumed not to
# change, and (2) it would adversely affect database performance if all
# values (including duplicates) were stored on each run.
continue
args_meta = [release_date, issue, epiweek, location, lag]
args_insert = data[epiweek]
args_update = [release_date] + data[epiweek]
cur.execute(sql, tuple(args_meta + args_insert + args_update))
# commit and disconnect
rows2 = get_rows(cur)
print('rows after: %d (+%d)' % (rows2, rows2 - rows1))
cur.close()
if test_mode:
print('test mode: not committing database changes')
else:
cnx.commit()
cnx.close()
def get_most_recent_issue():
# search for FluView issues within the last 10 weeks
ew2 = EpiDate.today().get_ew()
ew1 = flu.add_epiweeks(ew2, -9)
rows = Epidata.check(Epidata.fluview('nat', Epidata.range(ew1, ew2)))
return max([row['issue'] for row in rows])
