import math
import warnings
from typing import NamedTuple
import numpy as np
from pythermalcomfort.psychrometrics import p_sat, t_o
from pythermalcomfort.shared_functions import valid_range
warnings.simplefilter("always")
def transpose_sharp_altitude(sharp, altitude):
altitude_new = math.degrees(
math.asin(
math.sin(math.radians(abs(sharp - 90))) * math.cos(math.radians(altitude))
)
)
sharp = math.degrees(
math.atan(math.sin(math.radians(sharp)) * math.tan(math.radians(90 - altitude)))
)
sol_altitude = altitude_new
return round(sharp, 3), round(sol_altitude, 3)
def check_standard_compliance(standard, **kwargs):
params = dict()
params["standard"] = standard
for key, value in kwargs.items():
params[key] = value
if params["standard"] == "ankle_draft":
for key, value in params.items():
if key == "met" and value > 1.3:
warnings.warn(
"The ankle draft model is only valid for met <= 1.3",
UserWarning,
)
if key == "clo" and value > 0.7:
warnings.warn(
"The ankle draft model is only valid for clo <= 0.7",
UserWarning,
)
elif params["standard"] == "ashrae": # based on table 7.3.4 ashrae 55 2020
for key, value in params.items():
if key in ["tdb", "tr"]:
if key == "tdb":
parameter = "dry-bulb"
else:
parameter = "mean radiant"
if value > 40 or value < 10:
warnings.warn(
f"ASHRAE {parameter} temperature applicability limits between"
" 10 and 40 °C",
UserWarning,
)
if key in ["v", "vr"] and (value > 2 or value < 0):
warnings.warn(
"ASHRAE air speed applicability limits between 0 and 2 m/s",
UserWarning,
)
if key == "met" and (value > 4 or value < 1):
warnings.warn(
"ASHRAE met applicability limits between 1.0 and 4.0 met",
UserWarning,
)
if key == "clo" and (value > 1.5 or value < 0):
warnings.warn(
"ASHRAE clo applicability limits between 0.0 and 1.5 clo",
UserWarning,
)
if key == "v_limited" and value > 0.2:
raise ValueError(
"This equation is only applicable for air speed lower than 0.2 m/s"
)
elif params["standard"] == "iso": # based on ISO 7730:2005 page 3
for key, value in params.items():
if key == "tdb" and (value > 30 or value < 10):
warnings.warn(
"ISO air temperature applicability limits between 10 and 30 °C",
UserWarning,
)
if key == "tr" and (value > 40 or value < 10):
warnings.warn(
"ISO mean radiant temperature applicability limits between 10 and"
" 40 °C",
UserWarning,
)
if key in ["v", "vr"] and (value > 1 or value < 0):
warnings.warn(
"ISO air speed applicability limits between 0 and 1 m/s",
UserWarning,
)
if key == "met" and (value > 4 or value < 0.8):
warnings.warn(
"ISO met applicability limits between 0.8 and 4.0 met",
UserWarning,
)
if key == "clo" and (value > 2 or value < 0):
warnings.warn(
"ISO clo applicability limits between 0.0 and 2 clo",
UserWarning,
)
def check_standard_compliance_array(standard, **kwargs):
default_kwargs = {"airspeed_control": True}
params = {**default_kwargs, **kwargs}
if standard == "ashrae": # based on table 7.3.4 ashrae 55 2020
tdb_valid = valid_range(params["tdb"], (10.0, 40.0))
tr_valid = valid_range(params["tr"], (10.0, 40.0))
v_valid = valid_range(params["v"], (0.0, 2.0))
if not params["airspeed_control"]:
v_valid = np.where(
(params["v"] > 0.8) & (params["clo"] < 0.7) & (params["met"] < 1.3),
np.nan,
v_valid,
)
to = t_o(params["tdb"], params["tr"], params["v"])
v_limit = 50.49 - 4.4047 * to + 0.096425 * to * to
v_valid = np.where(
(23 < to)
& (to < 25.5)
& (params["v"] > v_limit)
& (params["clo"] < 0.7)
& (params["met"] < 1.3),
np.nan,
v_valid,
)
v_valid = np.where(
(to <= 23)
& (params["v"] > 0.2)
& (params["clo"] < 0.7)
& (params["met"] < 1.3),
np.nan,
v_valid,
)
if "met" in params.keys():
met_valid = valid_range(params["met"], (1.0, 4.0))
clo_valid = valid_range(params["clo"], (0.0, 1.5))
return tdb_valid, tr_valid, v_valid, met_valid, clo_valid
else:
return tdb_valid, tr_valid, v_valid
if standard == "7933": # based on ISO 7933:2004 Annex A
tdb_valid = valid_range(params["tdb"], (15.0, 50.0))
p_a_valid = valid_range(params["p_a"], (0, 4.5))
tr_valid = valid_range(params["tr"], (0.0, 60.0))
v_valid = valid_range(params["v"], (0.0, 3))
met_valid = valid_range(params["met"], (100, 450))
clo_valid = valid_range(params["clo"], (0.1, 1))
return tdb_valid, tr_valid, v_valid, p_a_valid, met_valid, clo_valid
if standard == "fan_heatwaves":
tdb_valid = valid_range(params["tdb"], (20.0, 50.0))
tr_valid = valid_range(params["tr"], (20.0, 50.0))
v_valid = valid_range(params["v"], (0.1, 4.5))
rh_valid = valid_range(params["rh"], (0, 100))
met_valid = valid_range(params["met"], (0.7, 2))
clo_valid = valid_range(params["clo"], (0.0, 1))
return tdb_valid, tr_valid, v_valid, rh_valid, met_valid, clo_valid
if standard == "iso": # based on ISO 7730:2005 page 3
tdb_valid = valid_range(params["tdb"], (10.0, 30.0))
tr_valid = valid_range(params["tr"], (10.0, 40.0))
v_valid = valid_range(params["v"], (0.0, 1.0))
met_valid = valid_range(params["met"], (0.8, 4.0))
clo_valid = valid_range(params["clo"], (0.0, 2))
return tdb_valid, tr_valid, v_valid, met_valid, clo_valid
[docs]def body_surface_area(weight, height, formula="dubois"):
"""Returns the body surface area in square meters.
Parameters
----------
weight : float
body weight, [kg]
height : float
height, [m]
formula : str, optional,
formula used to calculate the body surface area. default="dubois"
Choose a name from "dubois", "takahira", "fujimoto", or "kurazumi".
Returns
-------
body_surface_area : float
body surface area, [m2]
"""
if formula == "dubois":
return 0.202 * (weight**0.425) * (height**0.725)
elif formula == "takahira":
return 0.2042 * (weight**0.425) * (height**0.725)
elif formula == "fujimoto":
return 0.1882 * (weight**0.444) * (height**0.663)
elif formula == "kurazumi":
return 0.2440 * (weight**0.383) * (height**0.693)
else:
raise ValueError(
f"This {formula} to calculate the body_surface_area does not exists."
)
[docs]def f_svv(w, h, d):
"""Calculates the sky-vault view fraction.
Parameters
----------
w : float
width of the window, [m]
h : float
height of the window, [m]
d : float
distance between the occupant and the window, [m]
Returns
-------
f_svv : float
sky-vault view fraction ranges between 0 and 1
"""
return (
math.degrees(math.atan(h / (2 * d)))
* math.degrees(math.atan(w / (2 * d)))
/ 16200
)
[docs]def v_relative(v, met):
"""Estimates the relative air speed which combines the average air speed of
the space plus the relative air speed caused by the body movement. Vag is assumed to
be 0 for metabolic rates equal and lower than 1 met and otherwise equal to
Vag = 0.3 (M – 1) (m/s)
Parameters
----------
v : float, int, or array-like
air speed measured by the sensor, [m/s]
met : float
metabolic rate, [met]
Returns
-------
vr : float, int, or array-like
relative air speed, [m/s]
"""
return np.where(met > 1, np.around(v + 0.3 * (met - 1), 3), v)
[docs]def clo_dynamic(clo, met, standard="ASHRAE"):
"""Estimates the dynamic clothing insulation of a moving occupant. The activity as
well as the air speed modify the insulation characteristics of the clothing and the
adjacent air layer. Consequently, the ISO 7730 states that the clothing insulation
shall be corrected [2]_. The ASHRAE 55 Standard corrects for the effect
of the body movement for met equal or higher than 1.2 met using the equation
clo = Icl × (0.6 + 0.4/met)
Parameters
----------
clo : float, int, or array-like
clothing insulation, [clo]
met : float, int, or array-like
metabolic rate, [met]
standard: str (default="ASHRAE")
- If "ASHRAE", uses Equation provided in Section 5.2.2.2 of ASHRAE 55 2020
Returns
-------
clo : float, int, or array-like
dynamic clothing insulation, [clo]
"""
standard = standard.lower()
if standard not in ["ashrae", "iso"]:
raise ValueError(
"only the ISO 7730 and ASHRAE 55 2020 models have been implemented"
)
if standard == "ashrae":
return np.where(met > 1.2, np.around(clo * (0.6 + 0.4 / met), 3), clo)
else:
return np.where(met > 1, np.around(clo * (0.6 + 0.4 / met), 3), clo)
[docs]def running_mean_outdoor_temperature(temp_array, alpha=0.8, units="SI"):
"""Estimates the running mean temperature also known as prevailing mean
outdoor temperature.
Parameters
----------
temp_array: list
array containing the mean daily temperature in descending order (i.e. from
newest/yesterday to oldest) :math:`[t_{day-1}, t_{day-2}, ... ,
t_{day-n}]`.
Where :math:`t_{day-1}` is yesterday's daily mean temperature. The EN
16798-1 2019 [3]_ states that n should be equal to 7
alpha : float
constant between 0 and 1. The EN 16798-1 2019 [3]_ recommends a value of 0.8,
while the ASHRAE 55 2020 recommends to choose values between 0.9 and 0.6,
corresponding to a slow- and fast- response running mean, respectively.
Adaptive comfort theory suggests that a slow-response running mean (alpha =
0.9) could be more appropriate for climates in which synoptic-scale (day-to-
day) temperature dynamics are relatively minor, such as the humid tropics.
units: str default="SI"
select the SI (International System of Units) or the IP (Imperial Units) system.
Returns
-------
t_rm : float
running mean outdoor temperature
"""
if units.lower() == "ip":
for ix, x in enumerate(temp_array):
temp_array[ix] = units_converter(tdb=temp_array[ix])[0]
coeff = [alpha**ix for ix, x in enumerate(temp_array)]
t_rm = sum([a * b for a, b in zip(coeff, temp_array)]) / sum(coeff)
if units.lower() == "ip":
t_rm = units_converter(tmp=t_rm, from_units="si")[0]
return round(t_rm, 1)
[docs]def units_converter(from_units="ip", **kwargs):
"""Converts IP values to SI units.
Parameters
----------
from_units: str
specify system to convert from
**kwargs : [t, v]
Returns
-------
converted values in SI units
"""
results = list()
if from_units == "ip":
for key, value in kwargs.items():
if "tmp" in key or key == "tr" or key == "tdb":
results.append((value - 32) * 5 / 9)
if key in ["v", "vr", "vel"]:
results.append(value / 3.281)
if key == "area":
results.append(value / 10.764)
if key == "pressure":
results.append(value * 101325)
elif from_units == "si":
for key, value in kwargs.items():
if "tmp" in key or key == "tr" or key == "tdb":
results.append((value * 9 / 5) + 32)
if key in ["v", "vr", "vel"]:
results.append(value * 3.281)
if key == "area":
results.append(value * 10.764)
if key == "pressure":
results.append(value / 101325)
return results
def mapping(value, map_dictionary, right=True):
"""Maps a temperature array to stress categories.
Parameters
----------
value : float, array-like
Temperature to map.
map_dictionary: dict
Dictionary used to map the values
right: bool, optional
Indicating whether the intervals include the right or the left bin edge.
Returns
-------
Stress category for each input temperature.
"""
bins = np.array(list(map_dictionary.keys()))
words = np.append(np.array(list(map_dictionary.values())), "unknown")
return words[np.digitize(value, bins, right=right)]
#: Met values of typical tasks.
met_typical_tasks = {
"Sleeping": 0.7,
"Reclining": 0.8,
"Seated, quiet": 1.0,
"Reading, seated": 1.0,
"Writing": 1.0,
"Typing": 1.1,
"Standing, relaxed": 1.2,
"Filing, seated": 1.2,
"Flying aircraft, routine": 1.2,
"Filing, standing": 1.4,
"Driving a car": 1.5,
"Walking about": 1.7,
"Cooking": 1.8,
"Table sawing": 1.8,
"Walking 2mph (3.2kmh)": 2.0,
"Lifting/packing": 2.1,
"Seated, heavy limb movement": 2.2,
"Light machine work": 2.2,
"Flying aircraft, combat": 2.4,
"Walking 3mph (4.8kmh)": 2.6,
"House cleaning": 2.7,
"Driving, heavy vehicle": 3.2,
"Dancing": 3.4,
"Calisthenics": 3.5,
"Walking 4mph (6.4kmh)": 3.8,
"Tennis": 3.8,
"Heavy machine work": 4.0,
"Handling 100lb (45 kg) bags": 4.0,
"Pick and shovel work": 4.4,
"Basketball": 6.3,
"Wrestling": 7.8,
}
#: Total clothing insulation of typical ensembles.
clo_typical_ensembles = {
"Walking shorts, short-sleeve shirt": 0.36,
"Typical summer indoor clothing": 0.5,
"Knee-length skirt, short-sleeve shirt, sandals, underwear": 0.54,
"Trousers, short-sleeve shirt, socks, shoes, underwear": 0.57,
"Trousers, long-sleeve shirt": 0.61,
"Knee-length skirt, long-sleeve shirt, full slip": 0.67,
"Sweat pants, long-sleeve sweatshirt": 0.74,
"Jacket, Trousers, long-sleeve shirt": 0.96,
"Typical winter indoor clothing": 1.0,
}
#: Clo values of individual clothing elements. To calculate the total clothing insulation you need to add these values together.
clo_individual_garments = {
"Metal chair": 0.00,
"Bra": 0.01,
"Wooden stool": 0.01,
"Ankle socks": 0.02,
"Shoes or sandals": 0.02,
"Slippers": 0.03,
"Panty hose": 0.02,
"Calf length socks": 0.03,
"Women's underwear": 0.03,
"Men's underwear": 0.04,
"Knee socks (thick)": 0.06,
"Short shorts": 0.06,
"Walking shorts": 0.08,
"T-shirt": 0.08,
"Standard office chair": 0.10,
"Executive chair": 0.15,
"Boots": 0.1,
"Sleeveless scoop-neck blouse": 0.12,
"Half slip": 0.14,
"Long underwear bottoms": 0.15,
"Full slip": 0.16,
"Short-sleeve knit shirt": 0.17,
"Sleeveless vest (thin)": 0.1,
"Sleeveless vest (thick)": 0.17,
"Sleeveless short gown (thin)": 0.18,
"Short-sleeve dress shirt": 0.19,
"Sleeveless long gown (thin)": 0.2,
"Long underwear top": 0.2,
"Thick skirt": 0.23,
"Long-sleeve dress shirt": 0.25,
"Long-sleeve flannel shirt": 0.34,
"Long-sleeve sweat shirt": 0.34,
"Short-sleeve hospital gown": 0.31,
"Short-sleeve short robe (thin)": 0.34,
"Short-sleeve pajamas": 0.42,
"Long-sleeve long gown": 0.46,
"Long-sleeve short wrap robe (thick)": 0.48,
"Long-sleeve pajamas (thick)": 0.57,
"Long-sleeve long wrap robe (thick)": 0.69,
"Thin trousers": 0.15,
"Thick trousers": 0.24,
"Sweatpants": 0.28,
"Overalls": 0.30,
"Coveralls": 0.49,
"Thin skirt": 0.14,
"Long-sleeve shirt dress (thin)": 0.33,
"Long-sleeve shirt dress (thick)": 0.47,
"Short-sleeve shirt dress": 0.29,
"Sleeveless, scoop-neck shirt (thin)": 0.23,
"Sleeveless, scoop-neck shirt (thick)": 0.27,
"Long sleeve shirt (thin)": 0.25,
"Long sleeve shirt (thick)": 0.36,
"Single-breasted coat (thin)": 0.36,
"Single-breasted coat (thick)": 0.44,
"Double-breasted coat (thin)": 0.42,
"Double-breasted coat (thick)": 0.48,
}
#: This dictionary contains the reflection coefficients, Fr, for different special materials
f_r_garments = {
"Cotton with aluminium paint": 0.42,
"Viscose with glossy aluminium foil": 0.19,
"Aramid (Kevlar) with glossy aluminium foil": 0.14,
"Wool with glossy aluminium foil": 0.12,
"Cotton with glossy aluminium foil": 0.04,
"Viscose vacuum metallized with aluminium": 0.06,
"Aramid vacuum metallized with aluminium": 0.04,
"Wool vacuum metallized with aluminium": 0.05,
"Cotton vacuum metallized with aluminium": 0.05,
"Glass fiber vacuum metallized with aluminium": 0.07,
}
class DefaultSkinTemperature(NamedTuple):
"""Default skin temperature in degree Celsius for 17 local body parts
The data comes from Hui Zhang's experiments
https://escholarship.org/uc/item/3f4599hx"""
head: float = 35.3
neck: float = 35.6
chest: float = 35.1
back: float = 35.3
pelvis: float = 35.3
left_shoulder: float = 34.2
left_arm: float = 34.6
left_hand: float = 34.4
right_shoulder: float = 34.2
right_arm: float = 34.6
right_hand: float = 34.4
left_thigh: float = 34.3
left_leg: float = 32.8
left_foot: float = 33.3
right_thigh: float = 34.3
right_leg: float = 32.8
right_foot: float = 33.3