def _narrow_selection(index: Index, data: Data, region_name: str,
season: int) -> Tuple[Index, Data]:
"""
Return a narrowed index and data using the region and season information on the index.
Require index to have epiweek and region
"""
assert index.shape[0] == data.shape[
0], "Shape of index and data not matching in first dimension"
# All true selection
selection = index["epiweek"] > 0
narrowing = False
if region_name is not None:
selection = selection & (index["region"] == region_name)
narrowing = True
if season is not None:
first_ew = (season * 100) + 40
if pymmwr.mmwr_weeks_in_year(season) == 53:
# We skip the 20yy20 data and only provide upto 20yy19
# This makes it easy for the visualizations
last_ew = ((season + 1) * 100) + 19
else:
last_ew = ((season + 1) * 100) + 20
selection = selection & (index["epiweek"] >=
first_ew) & (index["epiweek"] <= last_ew)
narrowing = True
if narrowing:
return index[selection].reset_index(drop=True), data[selection]
else:
return index, data
def _process_csv_point_row(season_start_year, target_name, value):
# returns: point value for the args
if target_name == 'Season onset': # nominal target. value: None or an EW Monday date
if value is None:
return 'none' # convert back from None to original 'none' input
else: # value is an EW week number (float)
# note that value may be a fraction (e.g., 50.0012056690978, 4.96302456525203), so we round
# the EW number to get an int, but this could cause boundary issues where the value is
# invalid, either:
# 1) < 1 (so use last EW in season_start_year), or:
# 2) > the last EW in season_start_year (so use EW01 of season_start_year + 1)
ew_week = round(value)
if ew_week < 1:
ew_week = pymmwr.mmwr_weeks_in_year(
season_start_year) # wrap back to previous EW
elif ew_week > pymmwr.mmwr_weeks_in_year(
season_start_year): # wrap forward to next EW
ew_week = 1
monday_date = _monday_date_from_ew_and_season_start_year(
ew_week, season_start_year)
return monday_date.strftime(YYYY_MM_DD_DATE_FORMAT)
elif target_name in [
'1_biweek_ahead', '2_biweek_ahead', '3_biweek_ahead',
'4_biweek_ahead', '5_biweek_ahead'
]: # thai
return round(value) # some point predictions are floats
elif value is None:
raise RuntimeError(
f"None point values are only valid for 'Season onset' targets. "
f"target_name={target_name}")
elif target_name == 'Season peak week': # date target. value: an EW Monday date
# same 'wrapping' logic as above to handle rounding boundaries
ew_week = round(value)
if ew_week < 1:
ew_week = pymmwr.mmwr_weeks_in_year(
season_start_year) # wrap back to previous EW
elif ew_week > pymmwr.mmwr_weeks_in_year(
season_start_year): # wrap forward to next EW
ew_week = 1
monday_date = _monday_date_from_ew_and_season_start_year(
ew_week, season_start_year)
return monday_date.strftime(YYYY_MM_DD_DATE_FORMAT)
else: # 'Season peak percentage', '1 wk ahead', '2 wk ahead', '3 wk ahead', '4 wk ahead', '1_biweek_ahead', '2_biweek_ahead', '3_biweek_ahead', '4_biweek_ahead', # thai '5_biweek_ahead'
return value
def get_epiweek(season: str, season_wk: int):
"""
Get epiweek integer
"""
season_first_year = int(season.split("/")[0])
season_second_year = int(season.split("/")[1])
# Week 31 is season_wk 01
week = 30 + season_wk
first_year_weeks = pymmwr.mmwr_weeks_in_year(season_first_year)
epiweek_year = season_first_year
if week > first_year_weeks:
week -= first_year_weeks
epiweek_year = season_second_year
return epiweek_year * 100 + week
def epiweek_to_model_week(epiweek: int) -> int:
"""
Convert epiweek to model week starting at 20xx40 and ending at
20xx19/20xx20
"""
if np.isnan(epiweek):
# We consider this as the sign of no onset and assign the last bin
return 34
epiweek = int(epiweek)
season = epiweek_to_season(epiweek)
nweeks = pymmwr.mmwr_weeks_in_year(season)
week = epiweek % 100
if week >= 40 and week <= nweeks:
return epiweek - ((season * 100) + 40)
elif (nweeks == 52 and week <= 21) or (nweeks == 53 and week <= 20):
return week + (nweeks - 40)
elif week >= 20:
warnings.warn(f"Epiweek {epiweek} is greater than the models' range")
return week + (nweeks - 40)
else:
raise Exception(f"Epiweek {epiweek} outside the desired range")
