Source code for pythermalcomfort.models.clo_tout
from __future__ import annotations
from typing import Literal
import numpy as np
from pythermalcomfort.classes_input import CloTOutInputs
from pythermalcomfort.classes_return import CloTOut
from pythermalcomfort.utilities import Units, units_converter
[docs]
def clo_tout(
tout: float | list[float],
units: Literal["SI", "IP"] = Units.SI.value,
) -> CloTOut:
"""Calculate representative clothing insulation Icl based on outdoor air temperature
at 06:00 a.m. [Schiavon2013]_.
Parameters
----------
tout : float or list of floats
Outdoor air temperature at 06:00 a.m., default in [°C] or [°F] if `units` = 'IP'.
units : str, optional
Select the SI (International System of Units) or the IP (Imperial Units) system.
Supported values are 'SI' and 'IP'. Defaults to 'SI'.
Returns
-------
CloTOut
A dataclass containing the representative clothing insulation Icl. See :py:class:`~pythermalcomfort.classes_return.CloTOut` for more details.
To access the `clo_tout` value, use the `clo_tout` attribute of the returned `CloTOut` instance, e.g., `result.clo_tout`.
Raises
------
TypeError
If `tout` is not a float, int, NumPy array, or a list of floats or integers.
ValueError
If an invalid unit is provided or non-numeric elements are found in `tout`.
Notes
-----
.. note::
The ASHRAE 55 2020 states that it is acceptable to determine the clothing
insulation Icl using this equation in mechanically conditioned buildings [55ASHRAE2023]_.
.. note::
Limitations:
- This equation may not be accurate for extreme temperature ranges.
Examples
--------
.. code-block:: python
from pythermalcomfort.models import clo_tout
result = clo_tout(tout=27)
print(result.clo_tout) # 0.46
result = clo_tout(tout=[27, 25])
print(result.clo_tout) # array([0.46, 0.47])
"""
# Validate inputs using the CloTOutInputs class
CloTOutInputs(
tout=tout,
units=units,
)
# Convert tout to NumPy array for vectorized operations
tout = np.asarray(tout)
# Convert units if necessary
if units.upper() == Units.IP.value:
tout = units_converter(tmp=tout)[0]
clo = np.where(tout < 26, np.power(10, -0.1635 - 0.0066 * tout), 0.46)
clo = np.where(tout < 5, 0.818 - 0.0364 * tout, clo)
clo = np.where(tout < -5, 1, clo)
return CloTOut(clo_tout=np.around(clo, 2))