def check_current(ds: DataSource, config: QCConfig) -> ResultLog:
"""
Check the current published results
"""
logger.info("check current")
log = ResultLog()
df = ds.current
publish_date = 20200330
logger.error(f" [date is hard-coded to {publish_date}]")
# setup run settings equivalent to publish date at 5PM
s = str(publish_date)
y, m, d = int(s[0:4]), int(s[4:6]), int(s[6:8])
publish_timestamp = udatetime.naivedatetime_as_eastern(
datetime(y, m, d, 12 + 5))
ds._target_date = publish_timestamp
df["targetDate"] = publish_date
df["targetDateEt"] = publish_timestamp
df["lastCheckEt"] = df["targetDateEt"]
df["phase"] = "publish"
for row in df.itertuples():
checks.total(row, log)
checks.last_update(row, log)
checks.positives_rate(row, log)
checks.death_rate(row, log)
checks.pendings_rate(row, log)
df_history = ds.history[ds.history.state == row.state]
checks.increasing_values(row, df_history, log)
checks.expected_positive_increase(row, df_history, log, "current",
config)
df_county_rollup = ds.county_rollup[ds.county_rollup.state ==
row.state]
if not df_county_rollup.empty:
checks.counties_rollup_to_state(row, df_county_rollup, log)
return log
def check_working(ds: DataSource, config: QCConfig) -> ResultLog:
"""
Check unpublished results in the working google sheet
https://docs.google.com/spreadsheets/d/1MvvbHfnjF67GnYUDJJiNYUmGco5KQ9PW0ZRnEP9ndlU/edit#gid=1777138528
"""
logger.info("check working")
log = ResultLog()
# targetDate is the date that the dev sheet is currently working on.
# phase is what part of their process they are in.
# targetDateEt is the time that should be used on any 'staleness' checks
d, phase = checks.current_time_and_phase()
ds._target_date = d
df = ds.working
df["targetDate"] = d.year * 10000 + d.month * 100 + d.day
df["targetDateEt"] = d
df["phase"] = phase
logger.info(f"Running with target date = {d} and phase = {phase}")
# *** WHEN YOU CHANGE A CHECK THAT IMPACTS WORKING, MAKE SURE TO UPDATE THE EXCEL TRACKING DOCUMENT ***
for row in df.itertuples():
try:
checks.total(row, log)
#checks.total_tests(row, log)
checks.last_update(row, log)
checks.last_checked(row, log)
checks.checkers_initials(row, log)
checks.positives_rate(row, log)
checks.death_rate(row, log)
checks.less_recovered_than_positive(row, log)
checks.pendings_rate(row, log)
df_history = ds.history[ds.history.state == row.state]
checks.increasing_values(row, df_history, log)
checks.expected_positive_increase(row, df_history, log, "working",
config)
df_county_rollup = ds.county_rollup[ds.county_rollup.state ==
row.state]
if not df_county_rollup.empty:
checks.counties_rollup_to_state(row, df_county_rollup, log)
except Exception as ex:
logger.exception(ex)
log.error(row.state, f"{ex}")
# run loop at end, insted of during run
if config.plot_models and config.save_results:
for row in df.itertuples():
try:
forecast = load_forecast_hd5(config.results_dir, row.state,
row.targetDate)
if forecast is None:
logger.warning(
f"Fould not load forecast for {row.state}/{row.targetDate}"
)
else:
plot_to_file(forecast, f"{config.images_dir}/working",
checks.FIT_THRESHOLDS)
except Exception as ex:
logger.exception(ex)
log.error(row.state, f"{ex}")
return log
