def get_weather_source(site, use_cz2010=False):
''' Finds most relevant WeatherSource given project site.
Parameters
----------
site : eemeter.structures.ZIPCodeSite
Site to match to weather source data.
use_cz2010 : boolean, default False
Indicates whether or not to use CZ2010 mapping.
Returns
-------
weather_source : eemeter.weather.ISDWeatherSource or None
Closest data-validated weather source in the same climate zone as
project ZIP code, if available. If use_cz2010 is set, returns
the ISDWeatherSource corresponding with the cz2010 station mapping.
If no station can be found, returns None.
'''
zipcode = site.zipcode
if use_cz2010:
station = zipcode_to_cz2010_station(zipcode)
else:
station = zipcode_to_usaf_station(zipcode)
if station is None:
logger.error(
"Could not find ISD station for zipcode {}."
.format(zipcode)
)
return None
logger.debug(
"Mapped ZIP code {} to ISD station {}"
.format(zipcode, station)
)
try:
weather_source = ISDWeatherSource(station)
except ValueError:
logger.error(
"Could not create ISDWeatherSource for station {}."
.format(station)
)
return None
logger.debug("Created ISDWeatherSource using station {}".format(station))
return weather_source
def get_weather_source(project):
''' Finds most relevant WeatherSource given project site.
Parameters
----------
project : eemeter.structures.Project
Project for which to find weather source data.
Returns
-------
weather_source : eemeter.weather.ISDWeatherSource
Closest data-validated weather source in the same climate zone as
project ZIP code, if available.
'''
zipcode = project.site.zipcode
station = zipcode_to_usaf_station(zipcode)
if station is None:
logger.error(
"Could not find ISD station for zipcode {}."
.format(zipcode)
)
return None
logger.info(
"Mapped ZIP code {} to ISD station {}"
.format(zipcode, station)
)
try:
weather_source = ISDWeatherSource(station)
except ValueError:
logger.error(
"Could not create ISDWeatherSource for station {}."
.format(station)
)
return None
logger.info("Created ISDWeatherSource using station {}".format(station))
return weather_source
def get_single_thermostat(thermostat_id, zipcode, equipment_type,
utc_offset, interval_data_filename):
""" Load a single thermostat directly from an interval data file.
Parameters
----------
thermostat_id : str
A unique identifier for the thermostat.
zipcode : str
The zipcode of the thermostat, e.g. `"01234"`.
equipment_type : str
The equipment type of the thermostat.
utc_offset : str
A string representing the UTC offset of the interval data, e.g. `"-0700"`.
Could also be `"Z"` (UTC), or just `"+7"` (equivalent to `"+0700"`),
or any other timezone format recognized by the library
method dateutil.parser.parse.
interval_data_filename : str
The path to the CSV in which the interval data is stored.
Returns
-------
thermostat : thermostat.Thermostat
The loaded thermostat object.
"""
df = pd.read_csv(interval_data_filename)
heating, cooling, aux_emerg = _get_equipment_type(equipment_type)
# load indices
dates = pd.to_datetime(df["date"])
daily_index = pd.DatetimeIndex(start=dates[0], periods = dates.shape[0], freq="D")
hourly_index = pd.DatetimeIndex(start=dates[0], periods = dates.shape[0] * 24, freq="H")
hourly_index_utc = pd.DatetimeIndex(start=dates[0], periods = dates.shape[0] * 24, freq="H", tz=pytz.UTC)
# raise an error if dates are not aligned
if not all(dates == daily_index):
message("Dates provided for thermostat_id={} may contain some "
"which are out of order, missing, or duplicated.".format(thermostat_id))
raise ValueError(message)
# load hourly time series values
temp_in = pd.Series(_get_hourly_block(df, "temp_in"), hourly_index)
if heating:
heating_setpoint = pd.Series(_get_hourly_block(df, "heating_setpoint"), hourly_index)
else:
heating_setpoint = None
if cooling:
cooling_setpoint = pd.Series(_get_hourly_block(df, "cooling_setpoint"), hourly_index)
else:
cooling_setpoint = None
if aux_emerg:
auxiliary_heat_runtime = pd.Series(_get_hourly_block(df, "auxiliary_heat_runtime"), hourly_index)
emergency_heat_runtime = pd.Series(_get_hourly_block(df, "emergency_heat_runtime"), hourly_index)
else:
auxiliary_heat_runtime = None
emergency_heat_runtime = None
# load outdoor temperatures
station = zipcode_to_usaf_station(zipcode)
if station is None:
message = "Could not locate a valid source of outdoor temperature " \
"data for ZIP code {}".format(zipcode)
raise ValueError(message)
ws_hourly = ISDWeatherSource(station)
utc_offset = dateutil.parser.parse("2000-01-01T00:00:00" + utc_offset).tzinfo.utcoffset(None)
temp_out = ws_hourly.indexed_temperatures(hourly_index_utc - utc_offset, "degF")
temp_out.index = hourly_index
# load daily time series values
if cooling:
cool_runtime = pd.Series(df["cool_runtime"].values, daily_index)
else:
cool_runtime = None
if heating:
heat_runtime = pd.Series(df["heat_runtime"].values, daily_index)
else:
heat_runtime = None
# create thermostat instance
thermostat = Thermostat(
thermostat_id,
equipment_type,
zipcode,
station,
temp_in,
temp_out,
cooling_setpoint,
heating_setpoint,
cool_runtime,
heat_runtime,
auxiliary_heat_runtime,
emergency_heat_runtime
)
return thermostat
def get_single_thermostat(thermostat_id, zipcode, equipment_type, utc_offset,
interval_data_filename):
""" Load a single thermostat directly from an interval data file.
Parameters
----------
thermostat_id : str
A unique identifier for the thermostat.
zipcode : str
The zipcode of the thermostat, e.g. `"01234"`.
equipment_type : str
The equipment type of the thermostat.
utc_offset : str
A string representing the UTC offset of the interval data, e.g. `"-0700"`.
Could also be `"Z"` (UTC), or just `"+7"` (equivalent to `"+0700"`),
or any other timezone format recognized by the library
method dateutil.parser.parse.
interval_data_filename : str
The path to the CSV in which the interval data is stored.
Returns
-------
thermostat : thermostat.Thermostat
The loaded thermostat object.
"""
df = pd.read_csv(interval_data_filename)
heating, cooling, aux_emerg = _get_equipment_type(equipment_type)
# load indices
dates = pd.to_datetime(df["date"])
daily_index = pd.DatetimeIndex(start=dates[0],
periods=dates.shape[0],
freq="D")
hourly_index = pd.DatetimeIndex(start=dates[0],
periods=dates.shape[0] * 24,
freq="H")
hourly_index_utc = pd.DatetimeIndex(start=dates[0],
periods=dates.shape[0] * 24,
freq="H",
tz=pytz.UTC)
# raise an error if dates are not aligned
if not all(dates == daily_index):
message("Dates provided for thermostat_id={} may contain some "
"which are out of order, missing, or duplicated.".format(
thermostat_id))
raise ValueError(message)
# load hourly time series values
temp_in = pd.Series(_get_hourly_block(df, "temp_in"), hourly_index)
if heating:
heating_setpoint = pd.Series(_get_hourly_block(df, "heating_setpoint"),
hourly_index)
else:
heating_setpoint = None
if cooling:
cooling_setpoint = pd.Series(_get_hourly_block(df, "cooling_setpoint"),
hourly_index)
else:
cooling_setpoint = None
if aux_emerg:
auxiliary_heat_runtime = pd.Series(
_get_hourly_block(df, "auxiliary_heat_runtime"), hourly_index)
emergency_heat_runtime = pd.Series(
_get_hourly_block(df, "emergency_heat_runtime"), hourly_index)
else:
auxiliary_heat_runtime = None
emergency_heat_runtime = None
# load outdoor temperatures
station = zipcode_to_usaf_station(zipcode)
if station is None:
message = "Could not locate a valid source of outdoor temperature " \
"data for ZIP code {}".format(zipcode)
raise ValueError(message)
ws_hourly = ISDWeatherSource(station)
utc_offset = dateutil.parser.parse("2000-01-01T00:00:00" +
utc_offset).tzinfo.utcoffset(None)
temp_out = ws_hourly.indexed_temperatures(hourly_index_utc - utc_offset,
"degF")
temp_out.index = hourly_index
# load daily time series values
if cooling:
cool_runtime = pd.Series(df["cool_runtime"].values, daily_index)
else:
cool_runtime = None
if heating:
heat_runtime = pd.Series(df["heat_runtime"].values, daily_index)
else:
heat_runtime = None
# create thermostat instance
thermostat = Thermostat(thermostat_id, equipment_type, zipcode, station,
temp_in, temp_out, cooling_setpoint,
heating_setpoint, cool_runtime, heat_runtime,
auxiliary_heat_runtime, emergency_heat_runtime)
return thermostat
def test_zipcode_to_usaf_station():
assert zipcode_to_usaf_station('82440') == '726700'
assert zipcode_to_usaf_station('94403') == '745090'
def test_zipcode_to_usaf_station():
assert zipcode_to_usaf_station('82440') == '726700'
assert zipcode_to_usaf_station('94403') == '994041'