# coding=utf-8
"""Object for calculating PMV comfort from DataCollections."""
from __future__ import division
from ..pmv import predicted_mean_vote, predicted_mean_vote_no_set
from ..parameter.pmv import PMVParameter
from .base import ComfortCollection
from .solarcal import OutdoorSolarCal
from ladybug._datacollectionbase import BaseCollection
from ladybug.psychrometrics import humid_ratio_from_db_rh
from ladybug.datatype.temperature import Temperature, MeanRadiantTemperature, \
StandardEffectiveTemperature, AirTemperature, OperativeTemperature
from ladybug.datatype.fraction import Fraction, RelativeHumidity, HumidityRatio, \
PercentagePeopleDissatisfied
from ladybug.datatype.speed import Speed, AirSpeed
from ladybug.datatype.energyflux import MetabolicRate, EnergyFlux
from ladybug.datatype.rvalue import ClothingInsulation, RValue
from ladybug.datatype.thermalcondition import PredictedMeanVote, \
ThermalComfort, ThermalCondition, DiscomfortReason
from ladybug.datatype.temperaturedelta import AirTemperatureDelta
from ladybug.datatype.power import Power
try:
from itertools import izip as zip # python 2
except ImportError:
pass
class _PMVnoSET(ComfortCollection):
"""PMV comfort DataCollection object.
This class will not output Standard Effective Temperature (SET), meaning that
the SET model will only be used for conditions where the air speed exceeds the
still air threshold (usually 0.1 m/s). As such, for conditions below this
threshold, the runtime will be roughly 1/10th that of the full PMV collection.
Args:
air_temperature: Data Collection of air temperature values in Celsius.
rel_humidity: Data Collection of relative humidity values in % or a
single relative humidity value to be used for the whole analysis.
rad_temperature: Data Collection of mean radiant temperature (MRT)
values in degrees Celsius 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 level 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.
Properties:
* air_temperature
* rad_temperature
* air_speed
* rel_humidity
* met_rate
* clo_value
* external_work
* comfort_parameter
* predicted_mean_vote
* percentage_people_dissatisfied
* operative_temperature
* is_comfortable
* thermal_condition
* discomfort_reason
* percent_comfortable
* percent_uncomfortable
* percent_neutral
* percent_hot
* percent_cold
* percent_dry
* percent_humid
* humidity_ratio
* adjusted_air_temperature
* cooling_effect
* heat_loss_conduction
* heat_loss_sweating
* heat_loss_latent_respiration
* heat_loss_dry_respiration
* heat_loss_radiation
* heat_loss_convection
"""
_model = 'Predicted Mean Vote'
__slots__ = ('_air_temperature', '_rel_humidity', '_rad_temperature', '_air_speed',
'_met_rate', '_clo_value', '_external_work', '_comfort_par',
'_hr_calculated', '_hr_comfort_required', '_humidity_ratio',
'_pmv', '_ppd', '_is_comfortable', '_thermal_condition',
'_discomfort_reason', '_ta_adj', '_cooling_effect',
'_heat_loss_conduction', '_heat_loss_sweating',
'_heat_loss_latent_respiration', '_heat_loss_dry_respiration',
'_heat_loss_radiation', '_heat_loss_convection',
'_air_temperature_coll', '_rel_humidity_coll',
'_rad_temperature_coll', '_air_speed_coll',
'_met_rate_coll', '_clo_value_coll', '_external_work_coll',
'_humidity_ratio_coll', '_pmv_coll', '_ppd_coll',
'_is_comfortable_coll', '_thermal_condition_coll',
'_discomfort_reason_coll', '_ta_adj_coll', '_cooling_effect_coll',
'_hl_conduction_coll', '_hl_sweating_coll',
'_hl_latent_respiration_coll', '_hl_dry_respiration_coll',
'_hl_radiation_coll', '_hl_convection_coll', '_to', '_to_coll')
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, Fraction, '%', '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, EnergyFlux, '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, RValue, '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, EnergyFlux, '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()
@classmethod
def from_epw(cls, epw, include_wind=True, include_sun=True, met_rate=None,
clo_value=None, external_work=None, pmv_parameter=None):
"""Get a PMV comfort object from the conditions within an EPW file.
Args:
epw: A ladybug EPW object from which the PMV object will be created.
include_wind: Set to True to include the EPW wind speed in the calculation.
Setting to False will assume a condition that is shielded from wind
where the human experiences a very low wind speed of 0.1 m/s. If
included, the wind speed at ground level will be assumed to be 2/3
times the meteorological wind speed in the EPW (usually at 10 meters).
This follows the standard assumed for UTCI. (Default: True to
include wind).
include_sun: Set to True to include the mean radiant temperature (MRT) delta
from both shortwave solar falling directly on people and long wave
radiant exchange with the sky. Setting to False will assume a shaded
condition with MRT being equal to the EPW dry bulb temperature. When
set to True, this calculation will assume no surrounding shade context,
standing human geometry, and a solar horizontal angle relative to
front of person (SHARP) of 135 degrees. A SHARP of 135 essentially
assumes that a person typically faces their side or back to the
sun to avoid glare. (Default: True to include sun).
met_rate: Data Collection of metabolic rate in met or a single
metabolic rate value to be used for the whole analysis. Default: 2.4 met
(walking at 1 m/s, which is the same assumption used in UTCI).
clo_value: Data Collection of clothing values rate in clo or a single
clothing value to be used for the whole analysis. Default: 0.7 clo
(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. Default: 0 met.
pmv_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.
Returns:
An object with data collections of the PMV results as properties.
Usage:
.. code-block:: python
from ladybug.epw import EPW
from ladybug_comfort.collection.pmv import PMV
epw_file_path = './tests/epw/chicago.epw'
epw = EPW(epw_file_path)
pmv = PMV.from_epw(epw, include_wind=True, include_sun=True)
# 12 values for the average SET in each month
print(pmv.standard_effective_temperature.average_monthly_per_hour().values)
"""
# get wind input
if include_wind is True:
wind_speed = epw.wind_speed.duplicate()
for i, spd in enumerate(wind_speed):
wind_speed[i] = spd * (2 / 3) # 2/3 is the conversion used by UTCI
else:
wind_speed = 0.1
# get the mrt input
if include_sun is True:
solarcal_obj = OutdoorSolarCal(epw.location, epw.direct_normal_radiation,
epw.diffuse_horizontal_radiation,
epw.horizontal_infrared_radiation_intensity,
epw.dry_bulb_temperature)
mrt = solarcal_obj.mean_radiant_temperature
else:
mrt = epw.dry_bulb_temperature
# check the met input
met_rate = 2.4 if met_rate is None else met_rate
# return the comfort object
return cls(epw.dry_bulb_temperature, epw.relative_humidity, mrt, wind_speed,
met_rate, clo_value, external_work, pmv_parameter)
def _calculate_humidity_ratio(self):
"""Compute the humidity ratio at each step of the Data Collection."""
self._humidity_ratio = [humid_ratio_from_db_rh(db, rh) for db, rh in zip(
self._air_temperature, self._rel_humidity)]
self._hr_calculated = True
def _calculate_pmv(self):
"""Compute PMV for each step of the Data Collection."""
# perform HR calculation if necessary
if self._hr_comfort_required is True:
self._calculate_humidity_ratio()
# perform the PMV calculation
self._setup_list_attributes()
for ta, tr, vel, rh, met, clo, wme, i in \
zip(self._air_temperature, self._rad_temperature,
self._air_speed, self._rel_humidity,
self._met_rate, self._clo_value,
self._external_work, range(self._calc_length)):
result = predicted_mean_vote_no_set(ta, tr, vel, rh, met, clo, wme,
self._comfort_par.still_air_threshold)
self._append_results_to_lists(result)
self._assess_comfort(result, i)
def _setup_list_attributes(self):
"""Set empty lists for all data collection attributes on this object."""
self._pmv = []
self._ppd = []
self._to = []
self._is_comfortable = []
self._thermal_condition = []
self._discomfort_reason = []
self._ta_adj = []
self._cooling_effect = []
self._heat_loss_conduction = []
self._heat_loss_sweating = []
self._heat_loss_latent_respiration = []
self._heat_loss_dry_respiration = []
self._heat_loss_radiation = []
self._heat_loss_convection = []
def _append_results_to_lists(self, result):
"""Append PMV results from a dictionary to this object's lists."""
self._pmv.append(result['pmv'])
self._ppd.append(result['ppd'])
self._ta_adj.append(result['ta_adj'])
self._cooling_effect.append(result['ce'])
self._heat_loss_conduction.append(result['heat_loss']['cond'])
self._heat_loss_sweating.append(result['heat_loss']['sweat'])
self._heat_loss_latent_respiration.append(result['heat_loss']['res_l'])
self._heat_loss_dry_respiration.append(result['heat_loss']['res_s'])
self._heat_loss_radiation.append(result['heat_loss']['rad'])
self._heat_loss_convection.append(result['heat_loss']['conv'])
def _assess_comfort(self, result, i):
"""Append determine whether conditions are acceptable from a result dict."""
condit = self._comfort_par.thermal_condition(result['pmv'], result['ppd'])
if self._hr_comfort_required is True:
hr = self._humidity_ratio[i]
comf = self._comfort_par.is_comfortable(result['ppd'], hr)
reason = self._comfort_par.discomfort_reason(
result['pmv'], result['ppd'], hr)
else:
comf = self._comfort_par.is_comfortable(result['ppd'])
reason = self._comfort_par.discomfort_reason(
result['pmv'], result['ppd'])
self._is_comfortable.append(comf)
self._thermal_condition.append(condit)
self._discomfort_reason.append(reason)
@property
def air_temperature(self):
"""Data Collection of air temperature values in degrees C."""
return self._get_coll('_air_temperature_coll', self._air_temperature,
AirTemperature, 'C')
@property
def rad_temperature(self):
"""Data Collection of mean radiant temperature (MRT) values in degrees C."""
return self._get_coll('_rad_temperature_coll', self._rad_temperature,
MeanRadiantTemperature, 'C')
@property
def air_speed(self):
"""Data Collection of air speed values in m/s."""
return self._get_coll('_air_speed_coll', self._air_speed,
AirSpeed, 'm/s')
@property
def rel_humidity(self):
"""Data Collection of relative humidity values in %."""
return self._get_coll('_rel_humidity_coll', self._rel_humidity,
RelativeHumidity, '%')
@property
def met_rate(self):
"""Data Collection of metabolic rate in met.
* 1 met = Metabolic rate of a resting seated person
* 1.2 met = Metabolic rate of a standing person
* 2 met = Metabolic rate of a walking person
"""
return self._get_coll('_met_rate_coll', self._met_rate,
MetabolicRate, 'met')
@property
def clo_value(self):
"""Data Collection of clothing level of the human subject in clo.
* 1 clo = Three-piece suit
* 0.5 clo = Shorts + T-shirt
* 0 clo = No clothing
"""
return self._get_coll('_clo_value_coll', self._clo_value,
ClothingInsulation, 'clo')
@property
def external_work(self):
"""Data Collection of the work done by the human subject in met."""
return self._get_coll('_external_work_coll', self._external_work,
MetabolicRate, 'met')
@property
def comfort_parameter(self):
"""PMV comfort parameters that are assigned to this object."""
return self._comfort_par.duplicate() # duplicate since ppd_thresh is setable
@property
def predicted_mean_vote(self):
"""Data Collection of predicted mean vote (PMV) for the input conditions.
PMV is a seven-point scale from cold (-3) to hot (+3) that was used in comfort
surveys of P.O. Fanger.
Each interger value of the scale indicates the following:
* -3 = Cold
* -2 = Cool
* -1 = Slightly Cool
* 0 = Neutral
* +1 = Slightly Warm
* +2 = Warm
* +3 = Hot
"""
return self._get_coll('_pmv_coll', self._pmv, PredictedMeanVote, 'PMV')
@property
def percentage_people_dissatisfied(self):
"""Data Collection of percentage of people dissatisfied (PPD) for the input conditions.
Specifically, this is defined by the percent of people who would have
a PMV beyond acceptable thresholds (typically <-0.5 and >+0.5).
Note that, with the PMV model, the best possible PPD achievable is 5%
and most standards aim to have a PPD below 10%.
"""
return self._get_coll('_ppd_coll', self._ppd, PercentagePeopleDissatisfied, '%')
@property
def operative_temperature(self):
"""Data Collection of operative temperature in degrees C."""
if len(self._to) == 0:
self._to = [(ta + tr) / 2 for ta, tr in
zip(self._air_temperature, self._rad_temperature)]
return self._get_coll('_to_coll', self._to, OperativeTemperature, 'C')
@property
def is_comfortable(self):
"""Data Collection of integers noting whether the input conditions are
acceptable according to the assigned comfort_parameter.
Values are one of the following:
* 0 = uncomfortable
* 1 = comfortable
"""
return self._get_coll('_is_comfortable_coll', self._is_comfortable,
ThermalComfort, 'condition')
@property
def thermal_condition(self):
"""Data Collection of integers noting the thermal status of a subject
according to the assigned comfort_parameter.
Values are one of the following:
* -1 = cold
* 0 = netural
* +1 = hot
"""
return self._get_coll('_thermal_condition_coll', self._thermal_condition,
ThermalCondition, 'condition')
@property
def discomfort_reason(self):
"""Data Collection of integers noting the reason for discomfort
according to the assigned comfort_parameter.
Values are one of the following:
* -2 = too dry
* -1 = too cold
* 0 = comfortable
* +1 = too hot
* +2 = too humid
"""
return self._get_coll('_discomfort_reason_coll', self._discomfort_reason,
DiscomfortReason, 'condition')
@property
def percent_comfortable(self):
"""The percent of time comfortable given by the assigned comfort_parameter."""
return (sum(self._is_comfortable) / self._calc_length) * 100
@property
def percent_uncomfortable(self):
"""The percent of time uncomfortable given by the assigned comfort_parameter."""
return 100 - self.percent_comfortable
@property
def percent_neutral(self):
"""The percent of time that the thermal_condition is neutral."""
_vals = [1 for x in self._thermal_condition if x == 0]
return (sum(_vals) / self._calc_length) * 100
@property
def percent_cold(self):
"""The percent of time that the thermal_condition is cold."""
_vals = [1 for x in self._thermal_condition if x == -1]
return (sum(_vals) / self._calc_length) * 100
@property
def percent_hot(self):
"""The percent of time that the thermal_condition is hot."""
_vals = [1 for x in self._thermal_condition if x == 1]
return (sum(_vals) / self._calc_length) * 100
@property
def percent_dry(self):
"""The percent of time that the thermal_condition neutral but it is too dry."""
_vals = [1 for x in self._discomfort_reason if x == -2]
return (sum(_vals) / self._calc_length) * 100
@property
def percent_humid(self):
"""The percent of time that the thermal_condition neutral but it is too humid."""
_vals = [1 for x in self._discomfort_reason if x == 2]
return (sum(_vals) / self._calc_length) * 100
@property
def humidity_ratio(self):
"""Data Collection of humidity ratio for the dry bulb and relative humidity."""
if self._hr_calculated is False:
self._calculate_humidity_ratio()
return self._get_coll('_humidity_ratio_coll', self._humidity_ratio,
HumidityRatio, 'fraction')
@property
def adjusted_air_temperature(self):
"""Data Collection of air temperatures that have been adjusted by the SET model
to account for the effect of air speed [C].
"""
return self._get_coll('_ta_adj_coll', self._ta_adj,
AirTemperature('Adjusted Air Temperature'), 'C')
@property
def cooling_effect(self):
"""Data Collection of the cooling effect of the air speed in degrees Celsius.
This is the difference between the air temperature and the
adjusted air temperature [C].
"""
return self._get_coll('_cooling_effect_coll', self._cooling_effect,
AirTemperatureDelta('Cooling Effect'), 'dC')
@property
def heat_loss_conduction(self):
"""Data Collection of heat loss by conduction in [W]."""
return self._get_coll('_hl_conduction_coll', self._heat_loss_conduction,
Power('Heat Loss From Conduction'), 'W')
@property
def heat_loss_sweating(self):
"""Data Collection of heat loss by sweating in [W]."""
return self._get_coll('_hl_sweating_coll', self._heat_loss_sweating,
Power('Heat Loss From Sweating'), 'W')
@property
def heat_loss_latent_respiration(self):
"""Data Collection of heat loss by latent respiration in [W]."""
return self._get_coll(
'_hl_latent_respiration_coll', self._heat_loss_latent_respiration,
Power('Heat Loss From Latent Respiration'), 'W')
@property
def heat_loss_dry_respiration(self):
"""Data Collection of heat loss by dry respiration in [W]."""
return self._get_coll(
'_hl_dry_respiration_coll', self._heat_loss_dry_respiration,
Power('Heat Loss From Dry Respiration'), 'W')
@property
def heat_loss_radiation(self):
"""Data Collection of heat loss by radiation in [W]."""
return self._get_coll('_hl_radiation_coll', self._heat_loss_radiation,
Power('Heat Loss From Radiation'), 'W')
@property
def heat_loss_convection(self):
"""Data Collection of heat loss by convection in [W]."""
return self._get_coll('_hl_convection_coll', self._heat_loss_convection,
Power('Heat Loss From Convection'), 'W')
[docs]class PMV(_PMVnoSET):
"""PMV comfort DataCollection object.
Args:
air_temperature: Data Collection of air temperature values in Celsius.
rel_humidity: Data Collection of relative humidity values in % or a
single relative humidity value to be used for the whole analysis.
rad_temperature: Data Collection of mean radiant temperature (MRT)
values in degrees Celsius 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 level 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.
Properties:
* air_temperature
* rad_temperature
* air_speed
* rel_humidity
* met_rate
* clo_value
* external_work
* comfort_parameter
* predicted_mean_vote
* percentage_people_dissatisfied
* operative_temperature
* standard_effective_temperature
* is_comfortable
* thermal_condition
* discomfort_reason
* percent_comfortable
* percent_uncomfortable
* percent_neutral
* percent_hot
* percent_cold
* percent_dry
* percent_humid
* humidity_ratio
* adjusted_air_temperature
* cooling_effect
* heat_loss_conduction
* heat_loss_sweating
* heat_loss_latent_respiration
* heat_loss_dry_respiration
* heat_loss_radiation
* heat_loss_convection
"""
__slots__ = ('_set', '_set_coll')
def _calculate_pmv(self):
"""Compute PMV for each step of the Data Collection."""
# perform HR calculation if necessary
if self._hr_comfort_required is True:
self._calculate_humidity_ratio()
# perform the PMV calculation
self._setup_list_attributes()
self._set = []
for ta, tr, vel, rh, met, clo, wme, i in \
zip(self._air_temperature, self._rad_temperature,
self._air_speed, self._rel_humidity,
self._met_rate, self._clo_value,
self._external_work, range(self._calc_length)):
result = predicted_mean_vote(ta, tr, vel, rh, met, clo, wme,
self._comfort_par.still_air_threshold)
self._append_results_to_lists(result)
self._set.append(result['set'])
self._assess_comfort(result, i)
@property
def standard_effective_temperature(self):
"""Data Collection of standard effective temperature (SET) for the input conditions.
These temperatures describe what the given input conditions "feel like" in
relation to a standard environment of 50% relative humidity, <0.1 m/s average
air speed, and mean radiant temperature equal to average air temperature, in
which the total heat loss from the skin of an imaginary occupant with an activity
level of 1.0 met and a clothing level of 0.6 clo is the same as that from a
person in the actual environment.
"""
return self._get_coll('_set_coll', self._set,
StandardEffectiveTemperature, 'C')