def interconnector_power_flow(time_series: TimeSeries,
network_region: str) -> str:
"""Get interconnector region flows using materialized view"""
___query = """
select
time_bucket_gapfill(INTERVAL '5 minutes', bs.trading_interval) as trading_interval,
bs.network_region,
case when max(bs.net_interchange) < 0 then
max(bs.net_interchange)
else 0
end as imports,
case when max(bs.net_interchange) > 0 then
max(bs.net_interchange)
else 0
end as exports
from balancing_summary bs
where
bs.network_id = '{network_id}' and
bs.network_region= '{region}' and
bs.trading_interval <= '{date_end}' and
bs.trading_interval >= '{date_start}'
group by 1, 2
order by trading_interval desc;
""".format(
network_id=time_series.network.code,
region=network_region,
date_start=time_series.get_range().start,
date_end=time_series.get_range().end,
)
return dedent(___query)
def emission_factor_region_query(
time_series: TimeSeries,
network_region_code: Optional[str] = None) -> str:
__query = """
select
f.trading_interval at time zone '{timezone}' as ti,
f.network_region,
avg(f.emissions_per_mw) * 2
from mv_region_emissions_45d f
where
f.network_id='{network_id}' and
{network_region_query}
f.trading_interval <= '{date_max}' and
f.trading_interval >= '{date_min}'
group by 1, 2
order by 1 asc;
"""
network_region_query = ""
if network_region_code:
network_region_query = f"f.network_region='{network_region_code}' and"
date_range = time_series.get_range()
query = dedent(
__query.format(
network_region_query=network_region_query,
network_id=time_series.network.code,
trunc=time_series.interval.trunc,
date_max=date_range.end,
date_min=date_range.start,
timezone=time_series.network.timezone_database,
))
return query
def energy_facility_query(time_series: TimeSeries,
facility_codes: List[str]) -> str:
"""
Get Energy for a list of facility codes
"""
__query = """
select
date_trunc('{trunc}', t.trading_day at time zone '{timezone}') as trading_day,
t.facility_code,
sum(t.energy) as fueltech_energy,
sum(t.market_value) as fueltech_market_value,
sum(t.emissions) as fueltech_emissions
from at_facility_daily t
where
t.trading_day <= '{date_max}' and
t.trading_day >= '{date_min}' and
t.facility_code in ({facility_codes_parsed})
group by 1, 2
order by
trading_day desc;
"""
date_range = time_series.get_range()
query = dedent(
__query.format(
facility_codes_parsed=duid_in_case(facility_codes),
trunc=time_series.interval.trunc,
date_max=date_range.end,
date_min=date_range.start,
timezone=time_series.network.timezone_database,
))
return query
def network_fueltech_demand_query(time_series: TimeSeries) -> str:
__query = """
select
f.fueltech_id,
round(sum(fs.eoi_quantity) / 1000, 2) as energy,
sum(bs.demand_total) as demand
from facility_scada fs
left join balancing_summary bs on bs.trading_interval = fs.trading_interval and bs.network_id = fs.network_id
left join facility f on fs.facility_code = f.code
join fueltech ft on f.fueltech_id = ft.code
where
fs.trading_interval >= '{date_min}'
and fs.trading_interval < '{date_max}'
and fs.network_id = '{network_id}'
and f.dispatch_type = 'GENERATOR'
group by 1;
"""
date_range = time_series.get_range()
date_min: datetime = date_range.end - timedelta(days=1)
query = dedent(
__query.format(
network_id=time_series.network.code,
trunc=time_series.interval.trunc,
date_max=date_range.end,
date_min=date_min,
timezone=time_series.network.timezone_database,
))
return query
def demand_network_region_query(time_series: TimeSeries,
network_region: str | None,
networks: list[NetworkSchema] = []) -> str:
"""Get the network demand energy and market_value"""
if not networks:
networks = [time_series.network]
if time_series.network not in networks:
networks.append(time_series.network)
___query = """
select
date_trunc('{trunc}', trading_day) as trading_day,
network_id,
{network_region_select}
round(sum(demand_energy), 4),
round(sum(demand_market_value), 4)
from at_network_demand
where
{network_query}
{network_region}
trading_day >= '{date_min}'::date and
trading_day <= '{date_max}'::date
group by 1,2 {group_by}
order by
1 asc
"""
network_region_query = ""
network_region_select = f"'{time_series.network.code}' as network_region,"
group_by = ""
if network_region:
network_region_query = f"network_region='{network_region}' and"
network_region_select = "network_region,"
group_by = ",3"
date_range = time_series.get_range()
networks_list = networks_to_in(networks)
network_query = "network_id IN ({}) and ".format(networks_list)
query = dedent(
___query.format(
trunc=time_series.interval.trunc,
date_min=date_range.start.date(),
date_max=date_range.end.date(),
network_id=time_series.network.code,
network_region=network_region_query,
network_region_select=network_region_select,
group_by=group_by,
network_query=network_query,
))
return query
def energy_network_fueltech_query(
time_series: TimeSeries,
network_region: Optional[str] = None,
networks_query: Optional[List[NetworkSchema]] = None,
coalesce_with: Optional[int] = 0,
) -> str:
"""
Get Energy for a network or network + region
based on a year
"""
if not networks_query:
networks_query = [time_series.network]
if time_series.network not in networks_query:
networks_query.append(time_series.network)
__query = """
select
date_trunc('{trunc}', t.trading_day),
t.fueltech_id,
coalesce(sum(t.energy) / 1000, {coalesce_with}) as fueltech_energy,
coalesce(sum(t.market_value), {coalesce_with}) as fueltech_market_value,
coalesce(sum(t.emissions), {coalesce_with}) as fueltech_emissions
from at_facility_daily t
left join facility f on t.facility_code = f.code
where
t.trading_day <= '{date_max}'::date and
t.trading_day >= '{date_min}'::date and
t.fueltech_id not in ('imports', 'exports', 'interconnector') and
{network_query}
{network_region_query}
1=1
group by 1, 2
order by 1 desc;
"""
network_region_query = ""
date_range = time_series.get_range()
if network_region:
network_region_query = f"f.network_region='{network_region}' and"
networks_list = networks_to_in(networks_query)
network_query = "t.network_id IN ({}) and ".format(networks_list)
query = dedent(
__query.format(
trunc=date_range.interval.trunc,
date_min=date_range.start.date(),
date_max=date_range.end.date(),
network_query=network_query,
network_region_query=network_region_query,
coalesce_with=coalesce_with,
))
return query
def price_network_query(
time_series: TimeSeries,
group_field: str = "bs.network_id",
network_region: Optional[str] = None,
networks_query: Optional[List[NetworkSchema]] = None,
) -> str:
if not networks_query:
networks_query = [time_series.network]
if time_series.network not in networks_query:
networks_query.append(time_series.network)
__query = """
select
time_bucket_gapfill('{trunc}', bs.trading_interval) as trading_interval,
{group_field},
avg(bs.price) as price
from balancing_summary bs
where
bs.trading_interval <= '{date_max}' and
bs.trading_interval >= '{date_min}' and
{network_query}
{network_region_query}
1=1
group by 1, 2
order by 1 desc
"""
timezone = time_series.network.timezone_database
network_region_query = ""
if network_region:
network_region_query = f"bs.network_region='{network_region}' and "
group_field = "bs.network_region"
network_query = "bs.network_id IN ({}) and ".format(
networks_to_in(networks_query))
if len(networks_query) > 1:
group_field = "'AU'"
date_max = time_series.get_range().end
date_min = time_series.get_range().start
query = dedent(
__query.format(
network_query=network_query,
trunc=time_series.interval.interval_sql,
network_region_query=network_region_query,
timezone=timezone,
date_max=date_max,
date_min=date_min,
group_field=group_field,
))
return query
def network_demand_query(
time_series: TimeSeries,
network_region: Optional[str] = None,
networks_query: Optional[List[NetworkSchema]] = None,
) -> str:
if not networks_query:
networks_query = [time_series.network]
if time_series.network not in networks_query:
networks_query.append(time_series.network)
__query = """
select
trading_interval at time zone '{timezone}',
network_id,
max(demand_total) as demand
from balancing_summary bs
where
bs.trading_interval <= '{date_max}' and
bs.trading_interval >= '{date_min}' and
{network_query}
{network_region_query}
1=1
group by
1, {groups_additional}
order by 1 desc;
"""
group_keys = ["network_id"]
network_region_query = ""
if network_region:
group_keys.append("network_region")
network_region_query = f"bs.network_region = '{network_region}' and "
groups_additional = ", ".join(group_keys)
network_query = "bs.network_id IN ({}) and ".format(
networks_to_in(networks_query))
date_max = time_series.get_range().end
date_min = time_series.get_range().start
query = __query.format(
timezone=time_series.network.timezone_database,
date_max=date_max,
date_min=date_min,
network_id=time_series.network.code,
network_query=network_query,
network_region_query=network_region_query,
groups_additional=groups_additional,
)
return dedent(query)
def energy_network_interconnector_emissions_query(
time_series: TimeSeries,
network_region: Optional[str] = None,
networks_query: Optional[List[NetworkSchema]] = None,
) -> str:
"""
Get emissions for a network or network + region
based on a year
"""
if not networks_query:
networks_query = [time_series.network]
if time_series.network not in networks_query:
networks_query.append(time_series.network)
__query = """
select
t.trading_interval at time zone '{timezone}' as trading_interval,
t.flow_from,
t.flow_to,
t.flow_energy as energy,
t.flow_from_emissions,
t.flow_to_emissions
from vw_region_flow_emissions t
where
t.trading_interval <= '{date_max}' and
t.trading_interval >= '{date_min}' and
{network_region_query}
1=1
order by 1 desc
"""
timezone = time_series.network.timezone_database
network_region_query = ""
date_range = time_series.get_range()
if network_region:
network_region_query = f"""
(t.flow_from='{network_region}' or t.flow_to='{network_region}') and
"""
query = dedent(
__query.format(
timezone=timezone,
# trunc=date_range.interval.trunc,
date_min=date_range.start,
date_max=date_range.end,
network_region_query=network_region_query,
)
)
return query
def get_date_range(network: NetworkSchema) -> DatetimeRange:
date_range = get_scada_range(network=NetworkNEM)
time_series = TimeSeries(
start=date_range.start,
end=date_range.end,
interval=human_to_interval("1d"),
period=human_to_period("all"),
network=network,
)
return time_series.get_range()
def energy_network_flow_query(
time_series: TimeSeries,
network_region: str,
networks_query: Optional[List[NetworkSchema]] = None,
) -> str:
"""
Get emissions for a network or network + region
based on a year
"""
if not networks_query:
networks_query = [time_series.network]
if time_series.network not in networks_query:
networks_query.append(time_series.network)
__query = """
select
date_trunc('{trunc}', t.trading_interval) as trading_interval,
sum(t.imports_energy),
sum(t.exports_energy),
abs(sum(t.imports_market_value_rrp)),
abs(sum(t.exports_market_value_rrp))
from (
select
ei.trading_interval,
ei.imports_energy,
ei.exports_energy,
ei.imports_market_value,
ei.exports_market_value,
ei.imports_market_value_rrp,
ei.exports_market_value_rrp
from mv_interchange_energy_nem_region ei
where
ei.trading_interval <= '{date_max}'
and ei.trading_interval >= '{date_min}'
and ei.network_region='{network_region}'
) as t
group by 1
order by 1 desc
"""
date_range = time_series.get_range()
query = dedent(
__query.format(
network_region=network_region,
trunc=date_range.interval.trunc,
date_min=date_range.start,
date_max=date_range.end,
))
return query
def interconnector_flow_network_regions_query(
time_series: TimeSeries, network_region: Optional[str] = None) -> str:
""" """
__query = """
select
fs.trading_interval at time zone '{timezone}' as trading_interval,
f.network_region || '->' || f.interconnector_region_to as flow_region,
f.network_region,
f.interconnector_region_to,
sum(fs.generated) as flow_power
from facility_scada fs
left join facility f on fs.facility_code = f.code
where
f.interconnector is True
and f.network_id='{network_id}'
and fs.trading_interval <= '{date_end}'
and fs.trading_interval >= '{date_start}'
{region_query}
group by 1, 2, 3, 4
order by
1 desc,
2 asc
"""
region_query = ""
if network_region:
region_query = f"and f.network_region='{network_region}'"
query = __query.format(
timezone=time_series.network.timezone_database,
network_id=time_series.network.code,
region_query=region_query,
date_start=time_series.get_range().start,
date_end=time_series.get_range().end,
)
return dedent(query)
def test_schema_timeseries(
ts: TimeSeries,
start_expected: Union[datetime, date],
end_expected: Union[datetime, date],
interval_expected: str,
length_expected: int,
) -> None:
subject_daterange = ts.get_range()
assert str(
subject_daterange.start) == str(start_expected), "Start string matches"
assert subject_daterange.start == start_expected, "Start matches"
assert str(
subject_daterange.end) == str(end_expected), "End string matches"
assert subject_daterange.end == end_expected, "End matches"
assert subject_daterange.trunc == interval_expected, "Interval matches"
def power_facility_query(
time_series: TimeSeries,
facility_codes: List[str],
) -> str:
__query = """
select
t.trading_interval at time zone '{timezone}',
coalesce(avg(t.facility_power), 0),
t.facility_code
from (
select
time_bucket_gapfill('{trunc}', fs.trading_interval) AS trading_interval,
coalesce(
avg(fs.generated), 0
) as facility_power,
fs.facility_code
from facility_scada fs
join facility f on fs.facility_code = f.code
where
fs.trading_interval <= '{date_max}' and
fs.trading_interval > '{date_min}' and
fs.facility_code in ({facility_codes_parsed})
group by 1, 3
) as t
group by 1, 3
order by 1 desc
"""
date_range = time_series.get_range()
query = __query.format(
facility_codes_parsed=duid_in_case(facility_codes),
trunc=time_series.interval.interval_sql,
period=time_series.period.period_sql,
timezone=time_series.network.timezone_database,
date_max=date_range.end,
date_min=date_range.start,
)
return query
def network_region_price_query(time_series: TimeSeries) -> str:
__query = """
select
time_bucket('{trunc}', bs.trading_interval) as trading_interval,
bs.network_id,
bs.network_region,
coalesce(avg(bs.price), avg(bs.price_dispatch)) as price
from balancing_summary bs
where
bs.trading_interval >= '{date_min}'
and bs.trading_interval <= '{date_max}'
and bs.network_id = '{network_id}'
{network_regions_query}
group by 1, 2, 3;
"""
date_range = time_series.get_range()
date_min: datetime = date_range.end - timedelta(days=1)
network_regions_query = ""
if time_series.network.regions:
network_regions: str = ",".join(
[f"'{i.code}'" for i in time_series.network.regions])
network_regions_query = f"and bs.network_region IN ({network_regions})"
query = dedent(
__query.format(
network_id=time_series.network.code,
trunc=time_series.interval.interval_human,
date_max=date_range.end,
date_min=date_min,
network_regions_query=network_regions_query,
))
return query
def emission_network_fueltech_query(
time_series: TimeSeries,
network_region: Optional[str] = None,
networks_query: Optional[List[NetworkSchema]] = None,
) -> str:
"""Query emission stats for each network and fueltech"""
__query = """
select
time_bucket_gapfill('{trunc}', fs.trading_interval) AS trading_interval,
ft.code as fueltech_code,
case
when sum(fs.generated) > 0 then
sum(fs.generated) / {intervals_per_hour} * max(f.emissions_factor_co2)
else 0
end as emissions,
coalesce(max(fs.generated), 0) as fueltech_power
from facility_scada fs
join facility f on fs.facility_code = f.code
join fueltech ft on f.fueltech_id = ft.code
where
fs.is_forecast is False and
f.fueltech_id is not null and
{network_query}
{network_region_query}
fs.trading_interval <= '{date_max}' and
fs.trading_interval >= '{date_min}'
{fueltech_filter}
group by 1, f.code, 2
"""
network_region_query: str = ""
fueltech_filter: str = ""
timezone: str = time_series.network.timezone_database
fueltechs_excluded = [
"exports", "imports", "interconnector", "solar_rooftop",
"solar_utility", "wind"
]
if network_region:
network_region_query = f"f.network_region='{network_region}' and "
network_query = f"f.network_id ='{time_series.network.code}' and"
date_max = time_series.get_range().end
date_min = time_series.get_range().start
fueltechs_exclude = ", ".join("'{}'".format(i) for i in fueltechs_excluded)
query = dedent(
__query.format(
network_query=network_query,
trunc=time_series.interval.interval_sql,
network_region_query=network_region_query,
timezone=timezone,
date_max=date_max,
date_min=date_min,
fueltech_filter=fueltech_filter,
fueltechs_exclude=fueltechs_exclude,
intervals_per_hour=time_series.network.intervals_per_hour,
))
return query
def energy_network_interconnector_emissions_query(
time_series: TimeSeries,
network_region: Optional[str] = None,
networks_query: Optional[List[NetworkSchema]] = None,
) -> str:
"""
Get emissions for a network or network + region
based on a year
"""
if not networks_query:
networks_query = [time_series.network]
if time_series.network not in networks_query:
networks_query.append(time_series.network)
__query = """
select
date_trunc('{trunc}', t.trading_interval at time zone '{timezone}') as trading_interval,
sum(t.imports_energy) / 1000,
sum(t.exports_energy) / 1000,
abs(sum(t.emissions_imports)),
abs(sum(t.emissions_exports)),
sum(t.market_value_imports) as market_value_imports,
sum(t.market_value_exports) as market_value_exports
from (
select
time_bucket_gapfill('5 min', t.trading_interval) as trading_interval,
t.network_id,
t.network_region,
coalesce(t.energy_imports, 0) as imports_energy,
coalesce(t.energy_exports, 0) as exports_energy,
coalesce(t.emissions_imports, 0) as emissions_imports,
coalesce(t.emissions_exports, 0) as emissions_exports,
coalesce(t.market_value_imports, 0) as market_value_imports,
coalesce(t.market_value_exports, 0) as market_value_exports
from at_network_flows t
where
t.trading_interval <= '{date_max}' and
t.trading_interval >= '{date_min}' and
t.network_id = '{network_id}' and
{network_region_query}
) as t
group by 1
order by 1 desc
"""
timezone = time_series.network.timezone_database
network_region_query = ""
date_range = time_series.get_range()
if network_region:
network_region_query = f"""
t.network_region = '{network_region}'
"""
query = dedent(
__query.format(
timezone=timezone,
trunc=date_range.interval.trunc,
network_id=time_series.network.code,
date_min=date_range.start,
date_max=date_range.end,
network_region_query=network_region_query,
))
return query
def energy_network_fueltech_query(
time_series: TimeSeries,
network_region: Optional[str] = None,
networks_query: Optional[List[NetworkSchema]] = None,
) -> str:
"""
Get Energy for a network or network + region
based on a year
"""
if not networks_query:
networks_query = [time_series.network]
if time_series.network not in networks_query:
networks_query.append(time_series.network)
if time_series.interval.interval > 1440:
__query = """
select
date_trunc('{trunc}', t.trading_day) as trading_month,
t.fueltech_id,
coalesce(sum(t.fueltech_energy) / 1000 , 0) as fueltech_energy,
coalesce(sum(t.fueltech_market_value), 0) as fueltech_market_value,
coalesce(sum(t.fueltech_emissions), 0) as fueltech_emissions
from
(select
time_bucket_gapfill('1 day', t.ti_day_aest) as trading_day,
t.fueltech_id,
sum(t.energy) as fueltech_energy,
sum(t.market_value) as fueltech_market_value,
sum(t.emissions) as fueltech_emissions
from mv_facility_all t
where
t.ti_day_aest <= '{date_max}' and
t.ti_day_aest >= '{date_min}' and
t.fueltech_id not in ('imports', 'exports') and
{network_query}
{network_region_query}
1=1
group by 1, 2) as t
group by 1, 2
order by
1 desc;
"""
else:
__query = """
select
t.ti_{trunc_name} as trading_day,
t.fueltech_id,
coalesce(sum(t.energy) / 1000, 0) as fueltech_energy,
coalesce(sum(t.market_value), 0) as fueltech_market_value,
coalesce(sum(t.emissions), 0) as fueltech_emissions
from mv_facility_all t
where
t.trading_interval <= '{date_max}' and
t.trading_interval >= '{date_min}' and
t.fueltech_id not in ('imports', 'exports') and
{network_query}
{network_region_query}
1=1
group by 1, 2
order by
trading_day desc;
"""
network_region_query = ""
date_range = time_series.get_range()
if network_region:
network_region_query = f"t.network_region='{network_region}' and"
networks_list = networks_to_in(networks_query)
network_query = "t.network_id IN ({}) and ".format(networks_list)
trunc_name = "{}_{}".format(
time_series.interval.trunc, time_series.network.timezone_database
).lower()
query = dedent(
__query.format(
trunc=date_range.interval.trunc,
trunc_name=trunc_name,
date_min=date_range.start,
date_max=date_range.end,
network_query=network_query,
network_region_query=network_region_query,
)
)
return query
def power_network_rooftop_query(
time_series: TimeSeries,
network_region: Optional[str] = None,
networks_query: Optional[List[NetworkSchema]] = None,
forecast: bool = False,
) -> str:
"""Query power stats"""
if not networks_query:
networks_query = [time_series.network]
if time_series.network not in networks_query:
networks_query.append(time_series.network)
__query = """
select
time_bucket_gapfill('30 minutes', fs.trading_interval) AS trading_interval,
ft.code as fueltech_code,
{agg_func}(fs.generated) as facility_power
from facility_scada fs
join facility f on fs.facility_code = f.code
join fueltech ft on f.fueltech_id = ft.code
where
{forecast_query}
f.fueltech_id = 'solar_rooftop' and
{network_query}
{network_region_query}
fs.trading_interval <= '{date_max}' and
fs.trading_interval >= '{date_min}'
group by 1, 2
order by 1 desc
"""
network_region_query: str = ""
wem_apvi_case: str = ""
agg_func = "sum"
timezone: str = time_series.network.timezone_database
forecast_query = f"fs.is_forecast is {forecast} and"
if network_region:
network_region_query = f"f.network_region='{network_region}' and "
if NetworkWEM in networks_query:
# silly single case we'll refactor out
# APVI network is used to provide rooftop for WEM so we require it
# in country-wide totals
wem_apvi_case = "or (f.network_id='APVI' and f.network_region='WEM')"
agg_func = "max"
network_query = "(f.network_id IN ({}) {}) and ".format(
networks_to_in(networks_query), wem_apvi_case)
date_max = time_series.get_range().end
date_min = time_series.get_range().start
if forecast:
# @TODO work out what in get_range is mashing this
date_min = time_series.start + timedelta(minutes=30)
date_max = date_min + timedelta(hours=3)
query = dedent(
__query.format(
network_query=network_query,
network_region_query=network_region_query,
timezone=timezone,
date_max=date_max,
date_min=date_min,
forecast_query=forecast_query,
agg_func=agg_func,
))
return query
def power_network_fueltech_query(
time_series: TimeSeries,
network_region: Optional[str] = None,
networks_query: Optional[List[NetworkSchema]] = None,
) -> str:
"""Query power stats"""
if not networks_query:
networks_query = [time_series.network]
if time_series.network not in networks_query:
networks_query.append(time_series.network)
__query = """
select
time_bucket_gapfill('{trunc}', fs.trading_interval) AS trading_interval,
ft.code as fueltech_code,
coalesce(sum(fs.generated), 0) as fueltech_power
from facility_scada fs
join facility f on fs.facility_code = f.code
join fueltech ft on f.fueltech_id = ft.code
where
fs.is_forecast is False and
f.fueltech_id is not null and
f.fueltech_id not in ({fueltechs_exclude}) and
{network_query}
{network_region_query}
fs.trading_interval <= '{date_max}' and
fs.trading_interval >= '{date_min}'
{fueltech_filter}
group by 1, 2
"""
network_region_query: str = ""
fueltech_filter: str = ""
wem_apvi_case: str = ""
timezone: str = time_series.network.timezone_database
fueltechs_excluded = ["exports", "imports", "interconnector"]
if NetworkNEM in networks_query:
fueltechs_excluded.append("solar_rooftop")
if network_region:
network_region_query = f"f.network_region='{network_region}' and "
if NetworkWEM in networks_query:
# silly single case we'll refactor out
# APVI network is used to provide rooftop for WEM so we require it
# in country-wide totals
wem_apvi_case = "or (f.network_id='APVI' and f.network_region='WEM')"
network_query = "(f.network_id IN ({}) {}) and ".format(
networks_to_in(networks_query), wem_apvi_case)
date_max = time_series.get_range().end
date_min = time_series.get_range().start
fueltechs_exclude = ", ".join("'{}'".format(i) for i in fueltechs_excluded)
query = dedent(
__query.format(
network_query=network_query,
trunc=time_series.interval.interval_sql,
network_region_query=network_region_query,
timezone=timezone,
date_max=date_max,
date_min=date_min,
fueltech_filter=fueltech_filter,
wem_apvi_case=wem_apvi_case,
fueltechs_exclude=fueltechs_exclude,
))
return query
def weather_observation_query(time_series: TimeSeries,
station_codes: List[str]) -> str:
if time_series.interval.interval >= 1440:
# @TODO replace with mv
__query = """
select
date_trunc('{trunc}', t.observation_time at time zone '{tz}') as observation_month,
t.station_id,
avg(t.temp_avg),
min(t.temp_min),
max(t.temp_max)
from
(
select
time_bucket_gapfill('1 day', observation_time) as observation_time,
fs.station_id,
case
when avg(fs.temp_air) is not null
then avg(fs.temp_air)
when max(fs.temp_max) is not null and max(fs.temp_min) is not null
then ((max(fs.temp_max) + min(fs.temp_min)) / 2)
else NULL
end as temp_avg,
case when min(fs.temp_min) is not null
then min(fs.temp_min)
else min(fs.temp_air)
end as temp_min,
case when max(fs.temp_max) is not null
then max(fs.temp_max)
else max(fs.temp_air)
end as temp_max
from bom_observation fs
where
fs.station_id in ({station_codes}) and
fs.observation_time <= '{date_end}' and
fs.observation_time >= '{date_start}'
group by 1, 2
) as t
group by 1, 2;
""".format(
trunc=time_series.interval.trunc,
tz=time_series.network.timezone_database,
station_codes=",".join(["'{}'".format(i) for i in station_codes]),
date_start=time_series.get_range().start,
date_end=time_series.get_range().end,
)
else:
__query = """
select
fs.observation_time at time zone '{tz}' as ot,
fs.station_id as station_id,
avg(fs.temp_air) as temp_air,
case when min(fs.temp_min) is not null
then min(fs.temp_min)
else min(fs.temp_air)
end as temp_min,
case when max(fs.temp_max) is not null
then max(fs.temp_max)
else max(fs.temp_air)
end as temp_max
from bom_observation fs
where
fs.station_id in ({station_codes}) and
fs.observation_time <= '{date_end}' and
fs.observation_time >= '{date_start}'
group by 1, 2;
""".format(
tz=time_series.network.timezone_database,
station_codes=",".join(["'{}'".format(i) for i in station_codes]),
date_start=time_series.get_range().start,
date_end=time_series.get_range().end,
)
return dedent(__query)