def __init__(self, air_temperature, rel_humidity, rad_temperature=None,
wind_speed=None, comfort_parameter=None):
"""Initialize a UTCI comfort object from DataCollections of UTCI inputs.
Args:
air_temperature: Data Collection of air temperature values in Celcius.
rel_humidity: Data Collection of relative humidity values in % or a
single relative humdity value to be used for the whole analysis.
rad_temperature: Data Collection of mean radiant temperature (MRT)
values in degrees Celcius or a single MRT value to be used for the whole
analysis. If None, this will be the same as the air_temperature.
wind_speed: Data Collection of meteorological wind speed values in m/s
(measured 10 m above the ground) or a single wind speed value to be
used for the whole analysis. If None, this will default to a very
low wind speed of 0.1 m/s.
comfort_parameter: Optional UTCIParameter object to specify parameters under
which conditions are considered acceptable. If None, default will
assume comfort thresholds consistent with those used by meterologists
to categorize outdoor conditions.
"""
# set up the object using air temperature as a base
self._check_datacoll(air_temperature, Temperature, 'C', 'air_temperature')
self._input_collections = [air_temperature]
self._calc_length = len(air_temperature.values)
self._base_collection = air_temperature
# check required inputs
self._air_temperature = air_temperature.values
self._rel_humidity = self._check_input(
rel_humidity, RelativeHumidity, '%', 'rel_humidity')
# check inputs with defaults
if rad_temperature is not None:
self._rad_temperature = self._check_input(
rad_temperature, Temperature, 'C', 'rad_temperature')
else:
self._rad_temperature = self._air_temperature
if wind_speed is not None:
self._wind_speed = self._check_input(
wind_speed, Speed, 'm/s', 'air_speed')
else:
self._wind_speed = [0.1] * self.calc_length
# check that all input data collections are aligned.
BaseCollection.are_collections_aligned(self._input_collections)
# check comfort parameters
if comfort_parameter is None:
self._comfort_par = UTCIParameter()
else:
assert isinstance(comfort_parameter, UTCIParameter), 'comfort_parameter '\
'must be a UTCIParameter object. Got {}'.format(type(comfort_parameter))
self._comfort_par = comfort_parameter
# compute UTCI
self._calculate_utci()
def __init__(self,
air_temperature,
rel_humidity,
rad_temperature=None,
wind_speed=None,
comfort_parameter=None):
"""Initialize a UTCI comfort object from DataCollections of UTCI inputs.
"""
# set up the object using air temperature as a base
self._check_datacoll(air_temperature, Temperature, 'C',
'air_temperature')
self._input_collections = [air_temperature]
self._calc_length = len(air_temperature.values)
self._base_collection = air_temperature
# check required inputs
self._air_temperature = air_temperature.values
self._rel_humidity = self._check_input(rel_humidity, RelativeHumidity,
'%', 'rel_humidity')
# check inputs with defaults
if rad_temperature is not None:
self._rad_temperature = self._check_input(rad_temperature,
Temperature, 'C',
'rad_temperature')
else:
self._rad_temperature = self._air_temperature
if wind_speed is not None:
self._wind_speed = self._check_input(wind_speed, Speed, 'm/s',
'air_speed')
else:
self._wind_speed = [0.1] * self.calc_length
# check that all input data collections are aligned.
BaseCollection.are_collections_aligned(self._input_collections)
# check comfort parameters
if comfort_parameter is None:
self._comfort_par = UTCIParameter()
else:
assert isinstance(comfort_parameter, UTCIParameter), 'comfort_parameter '\
'must be a UTCIParameter object. Got {}'.format(type(comfort_parameter))
self._comfort_par = comfort_parameter
# compute UTCI
self._calculate_utci()
def from_air_and_rad_temp(cls, outdoor_temperature, air_temperature,
rad_temperature=None, air_speed=None,
comfort_parameter=None):
"""Initalize an Adaptive Comfort object from air and radiant temperature."""
if rad_temperature is None:
to = air_temperature
else:
to = BaseCollection.compute_function_aligned(
t_operative, [air_temperature, rad_temperature],
OperativeTemperature(), 'C')
return cls(outdoor_temperature, to, air_speed, comfort_parameter)
def test_init_incorrect():
"""Test the init methods for base collections with incorrect inputs."""
a_per = AnalysisPeriod(6, 21, 12, 6, 21, 13)
dt1, dt2 = DateTime(6, 21, 12), DateTime(6, 21, 13)
v1, v2 = 20, 25
avg = (v1 + v2) / 2
dc1 = BaseCollection(Header(Temperature(), 'C', a_per), [v1, v2],
[dt1, dt2])
dc1 = BaseCollection(Header(Temperature(), 'C', a_per), [v1, v2],
(dt1, dt2))
dc1 = BaseCollection(Header(Temperature(), 'C', a_per), [v1, v2],
xrange(2))
assert dc1.average == avg
with pytest.raises(Exception):
dc1 = BaseCollection(Header(Temperature(), 'C', a_per), [v1, v2], 'te')
with pytest.raises(Exception):
dc1 = BaseCollection(Header(Temperature(), 'C', a_per), [v1, v2], {
'1': 1,
'2': 2
})
def test_init():
"""Test the init methods for base collections."""
a_per = AnalysisPeriod(6, 21, 12, 6, 21, 13)
dt1, dt2 = DateTime(6, 21, 12), DateTime(6, 21, 13)
v1, v2 = 20, 25
avg = (v1 + v2) / 2
# Setup data collection
dc1 = BaseCollection(Header(Temperature(), 'C', a_per), [v1, v2],
[dt1, dt2])
assert dc1.datetimes == (dt1, dt2)
assert dc1.values == (v1, v2)
assert dc1.average == avg
str(dc1) # Test the string representation of the collection
str(dc1.header) # Test the string representation of the header
def __init__(self,
air_temperature,
rel_humidity,
rad_temperature=None,
air_speed=None,
met_rate=None,
clo_value=None,
external_work=None,
comfort_parameter=None):
"""Initialize a PMV comfort object from DataCollections of PMV inputs.
Args:
air_temperature: Data Collection of air temperature values in Celcius.
rel_humidity: Data Collection of relative humidity values in % or a
single relative humdity value to be used for the whole analysis.
rad_temperature: Data Collection of mean radiant temperature (MRT)
values in degrees Celcius or a single MRT value to be used for the whole
analysis. If None, this will be the same as the air_temperature.
air_speed: Data Collection of air speed values in m/s or a single
air_speed value to be used for the whole analysis. If None, this
will default to 0.1 m/s.
met_rate: Data Collection of metabolic rate in met or a single
metabolic rate value to be used for the whole analysis. If None,
default is set to 1.1 met (for seated, typing).
clo_value: Data Collection of clothing values rate in clo or a single
clothing value to be used for the whole analysis. If None, default is
set to 0.7 clo (for long sleeve shirt and pants).
external_work: Data Collection of external work in met or a single
external work value to be used for the whole analysis. If None,
default is set to 0 met.
comfort_parameter: Optional PMVParameter object to specify parameters under
which conditions are considered acceptable. If None, default will
assume a PPD threshold of 10%, no absolute humidity constraints
and a still air threshold of 0.1 m/s.
"""
# set up the object using air temperature as a base
self._check_datacoll(air_temperature, Temperature, 'C',
'air_temperature')
self._input_collections = [air_temperature]
self._calc_length = len(air_temperature.values)
self._base_collection = air_temperature
# check and set required inputs
self._air_temperature = air_temperature.values
self._rel_humidity = self._check_input(rel_humidity, RelativeHumidity,
'%', 'rel_humidity')
# check parameters with defaults
if rad_temperature is not None:
self._rad_temperature = self._check_input(rad_temperature,
Temperature, 'C',
'rad_temperature')
else:
self._rad_temperature = self._air_temperature
if air_speed is not None:
self._air_speed = self._check_input(air_speed, Speed, 'm/s',
'air_speed')
else:
self._air_speed = [0.1] * self.calc_length
if met_rate is not None:
self._met_rate = self._check_input(met_rate, MetabolicRate, 'met',
'met_rate')
else:
self._met_rate = [1.1] * self.calc_length
if clo_value is not None:
self._clo_value = self._check_input(clo_value, ClothingInsulation,
'clo', 'clo_value')
else:
self._clo_value = [0.7] * self.calc_length
if external_work is not None:
self._external_work = self._check_input(external_work,
MetabolicRate, 'met',
'external_work')
else:
self._external_work = [0.] * self.calc_length
# check that all input data collections are aligned.
BaseCollection.are_collections_aligned(self._input_collections)
# check comfort parameters
if comfort_parameter is None:
self._comfort_par = PMVParameter()
else:
assert isinstance(comfort_parameter, PMVParameter), 'comfort_parameter '\
'must be a PMVParameter object. Got {}'.format(type(comfort_parameter))
self._comfort_par = comfort_parameter
# value to track whether humidity ratio has been computed
self._hr_calculated = False
self._hr_comfort_required = True
if self.comfort_parameter.humid_ratio_lower == 0 and \
self.comfort_parameter.humid_ratio_upper == 1:
self._hr_comfort_required = False
# calculate PMV
self._calculate_pmv()
def __init__(self,
air_temperature,
rel_humidity,
rad_temperature=None,
air_speed=None,
met_rate=None,
clo_value=None,
external_work=None,
comfort_parameter=None):
"""Initialize a PMV comfort object from DataCollections of PMV inputs.
"""
# set up the object using air temperature as a base
self._check_datacoll(air_temperature, Temperature, 'C',
'air_temperature')
self._input_collections = [air_temperature]
self._calc_length = len(air_temperature.values)
self._base_collection = air_temperature
# check and set required inputs
self._air_temperature = air_temperature.values
self._rel_humidity = self._check_input(rel_humidity, RelativeHumidity,
'%', 'rel_humidity')
# check parameters with defaults
if rad_temperature is not None:
self._rad_temperature = self._check_input(rad_temperature,
Temperature, 'C',
'rad_temperature')
else:
self._rad_temperature = self._air_temperature
if air_speed is not None:
self._air_speed = self._check_input(air_speed, Speed, 'm/s',
'air_speed')
else:
self._air_speed = [0.1] * self.calc_length
if met_rate is not None:
self._met_rate = self._check_input(met_rate, MetabolicRate, 'met',
'met_rate')
else:
self._met_rate = [1.1] * self.calc_length
if clo_value is not None:
self._clo_value = self._check_input(clo_value, ClothingInsulation,
'clo', 'clo_value')
else:
self._clo_value = [0.7] * self.calc_length
if external_work is not None:
self._external_work = self._check_input(external_work,
MetabolicRate, 'met',
'external_work')
else:
self._external_work = [0.] * self.calc_length
# check that all input data collections are aligned.
BaseCollection.are_collections_aligned(self._input_collections)
# check comfort parameters
if comfort_parameter is None:
self._comfort_par = PMVParameter()
else:
assert isinstance(comfort_parameter, PMVParameter), 'comfort_parameter '\
'must be a PMVParameter object. Got {}'.format(type(comfort_parameter))
self._comfort_par = comfort_parameter
# value to track whether humidity ratio has been computed
self._hr_calculated = False
self._hr_comfort_required = True
if self.comfort_parameter.humid_ratio_lower == 0 and \
self.comfort_parameter.humid_ratio_upper == 1:
self._hr_comfort_required = False
# calculate PMV
self._calculate_pmv()