def computeLogScores(forecastsAndILI, forecastWeek, iliEW):
if forecastsAndILI.shape[0] == 0:
return pd.DataFrame()
from datetime import datetime
calendarEW = Week.thisweek()
dayOfWeek = datetime.today().weekday
if dayOfWeek in {5, 6}: # Saturday or Sunday
calendarWeek = "{:d}{:d}".format(
calendarEW.year,
calendarEW.week + 1) # should be referenced from the next week
else:
calendarWeek = "{:d}{:d}".format(calendarEW.year, calendarEW.week)
subsetToProbabilities = forecastsAndILI.loc[
(forecastsAndILI.bin_start_incl <= forecastsAndILI.wili)
& (forecastsAndILI.bin_end_notincl > forecastsAndILI.wili), :]
subsetToProbabilities['logScore'] = np.log(
[float(x) for x in subsetToProbabilities.value])
logScores = subsetToProbabilities.loc[:, [
'model', 'location', 'target', 'region', 'lag', 'releaseEW',
'releaseDate', 'wili', 'logScore'
]]
logScores[
'surveillanceWeek'] = forecastWeek # this is the most recent week of data available
logScores[
'calendarWeek'] = calendarWeek # this is the present week in real-time
logScores['targetWeek'] = iliEW # this is the target week of forecasting
return logScores
def grabForecastWeeks():
from epiweeks import Week, Year
thisWeek = Week.thisweek()
weeks = [Week(2019, 40)]
while weeks[-1] < thisWeek:
weeks.append(weeks[-1] + 1)
formattedWeeks = [
int("{:04d}{:02d}".format(x.year, x.week)) for x in weeks
]
return formattedWeeks
def generate_week_periods(open_future_periods, page_limit, begin_period, direction, direction_change):
weeks_to_display = {}
# When the user first visits the period screen the begin_period variable is empty.
# Therefore, use the current week as default.
week = Week.thisweek("iso") + open_future_periods
# If begin_period variable has a date, use it to calculate the weeks to display.
if begin_period != '':
week = Week.fromdate(datetime.datetime.strptime(begin_period, '%Y-%m-%d'), 'iso')
# This logic is to fix week discrepancy when a user clicks + and changes the direction and press - or vice versa
if direction_change:
if direction == '+':
week += page_limit - 1
if direction == '-':
week -= page_limit - 1
# We should not open future dates for data entry. The -1 is to prevent from opening this week.
if direction == '+' and week + page_limit > Week.thisweek("iso") + open_future_periods:
week = Week.thisweek("iso") + open_future_periods - page_limit - 1
rng = range(page_limit, 0, -1) if direction == '+' else range(page_limit)
for key, i in enumerate(rng):
w = week + i if direction == '+' else week - (i + 1)
weeks_to_display[str(key + 1)] = {
"period": w.isoformat(),
"display": "W{} - {} - {}".format(w.weektuple()[1], w.startdate(), w.enddate())
}
# Take the first week to calculate the beginning period in the next screen.
if direction == '+' and i == page_limit:
begin_period = str(w.enddate())
# Take the final week to calculate the beginning week in the next screen.
if direction == '-' and i == page_limit - 1:
begin_period = str(w.startdate())
return begin_period, weeks_to_display
def addTodaysEpiWeek(self):
thisweek = Week.thisweek()
yr,wek = thisweek.year,thisweek.week
self.todaysEW = int("{:04d}{:02d}".format(yr,wek))
def fromToday2EpiWeek():
thisweek = Week.thisweek()
yr,wek = thisweek.year,thisweek.week
return int("{:04d}{:02d}".format(yr,wek))
def handle_coverage():
"""
similar to /signal_dashboard_coverage for a specific signal returns the coverage (number of locations for a given geo_type)
"""
source_signal_pairs = parse_source_signal_pairs()
daily_signals, weekly_signals = count_signal_time_types(source_signal_pairs)
source_signal_pairs, alias_mapper = create_source_signal_alias_mapper(source_signal_pairs)
geo_type = request.args.get("geo_type", "county")
if "window" in request.values:
time_window, is_day = parse_day_or_week_range_arg("window")
else:
now_time = extract_date("latest")
last = extract_integer("days")
last_weeks = extract_integer("weeks")
# week if latest is week like or weeks are given otherwise we don't know and guess days
if (now_time is not None and not guess_time_value_is_day(now_time)) or last_weeks is not None or weekly_signals > 0:
# week
if last_weeks is None:
last_weeks = last or 30
is_day = False
now_week = Week.thisweek() if now_time is None else week_value_to_week(now_time)
time_window = (week_to_time_value(now_week - last_weeks), week_to_time_value(now_week))
else:
is_day = True
if last is None:
last = 30
now = date.today() if now_time is None else time_value_to_date(now_time)
time_window = (date_to_time_value(now - timedelta(days=last)), date_to_time_value(now))
_verify_argument_time_type_matches(is_day, daily_signals, weekly_signals)
q = QueryBuilder("covidcast", "c")
fields_string = ["source", "signal"]
fields_int = ["time_value"]
q.set_fields(fields_string, fields_int)
# manually append the count column because of grouping
fields_int.append("count")
q.fields.append(f"count({q.alias}.geo_value) as count")
if geo_type == "only-county":
q.where(geo_type="county")
q.conditions.append('geo_value not like "%000"')
else:
q.where(geo_type=geo_type)
q.where_source_signal_pairs("source", "signal", source_signal_pairs)
q.where_time_pairs("time_type", "time_value", [TimePair("day" if is_day else "week", [time_window])])
q.group_by = "c.source, c.signal, c.time_value"
q.set_order("source", "signal", "time_value")
_handle_lag_issues_as_of(q, None, None, None)
def transform_row(row, proxy):
if not alias_mapper or "source" not in row:
return row
row["source"] = alias_mapper(row["source"], proxy["signal"])
return row
return execute_query(q.query, q.params, fields_string, fields_int, [], transform=transform_row)