Source code for pythermalcomfort.models.pmv_ppd_iso

from __future__ import annotations

import numpy as np

from pythermalcomfort.classes_input import PMVPPDInputs
from pythermalcomfort.classes_return import PMVPPD
from pythermalcomfort.models._pmv_ppd_optimized import _pmv_ppd_optimized
from pythermalcomfort.shared_functions import mapping, valid_range
from pythermalcomfort.utilities import (
    Models,
    Units,
    units_converter,
)


[docs] def pmv_ppd_iso( tdb: float | list[float], tr: float | list[float], vr: float | list[float], rh: float | list[float], met: float | list[float], clo: float | list[float], wme: float | list[float] = 0, model: str = Models.iso_7730_2005.value, units: str = Units.SI.value, limit_inputs: bool = True, round_output: bool = True, ) -> PMVPPD: """Return Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD) calculated in accordance with the ISO 7730. The ISO uses the same formulation of the PMV as published by Fanger [Fanger1970]_. Parameters ---------- tdb : float or list of floats Dry bulb air temperature, [°C] in [°F] if `units` = 'IP' tr : float or list of floats Mean radiant temperature, [°C] in [°F] if `units` = 'IP' vr : float or list of floats Relative air speed, [m/s] in [fps] if `units` = 'IP' .. note:: vr is the relative air speed caused by body movement and not the air speed measured by the air speed sensor. The relative air speed is the sum of the average air speed measured by the sensor plus the activity-generated air speed (Vag). Where Vag is the activity-generated air speed caused by motion of individual body parts. vr can be calculated using the function :py:meth:`pythermalcomfort.utilities.v_relative`. rh : float or list of floats Relative humidity, [%]. met : float or list of floats Metabolic rate, [met]. clo : float or list of floats Clothing insulation, [clo]. .. note:: this is the basic insulation also known as the intrinsic clothing insulation value of the clothing ensemble (`I`:sub:`cl,r`), this is the thermal insulation from the skin surface to the outer clothing surface, including enclosed air layers, under actual environmental conditions. This value is not the total insulation (`I`:sub:`T,r`). The dynamic clothing insulation, clo, can be calculated using the function :py:meth:`pythermalcomfort.utilities.clo_dynamic_iso`. wme : float or list of floats, optional External work, [met]. Defaults to 0. model : str, optional Select the model you want to use to calculate the PMV. Currently, the only option available is "7730-2005". 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'. limit_inputs : bool, optional If True, limits the inputs to the standard applicability limits. Defaults to True. .. note:: By default, if the inputs are outside the standard applicability limits the function returns nan. If False returns pmv and ppd values even if input values are outside the applicability limits of the model. The ISO 7730 2005 limits are 10 < tdb [°C] < 30, 10 < tr [°C] < 40, 0 < vr [m/s] < 1, 0.8 < met [met] < 4, 0 < clo [clo] < 2, and -2 < PMV < 2. round_output : bool, optional If True, rounds output value. If False, it does not round it. Defaults to True. Returns ------- PMVPPD A dataclass containing the Predicted Mean Vote and Predicted Percentage of Dissatisfied. See :py:class:`~pythermalcomfort.classes_return.PMVPPD` for more details. To access the `pmv`, `ppd`, `tsv` values, use the corresponding attributes of the returned `PMVPPD` instance, e.g., `result.pmv`. Examples -------- .. code-block:: python from pythermalcomfort.models import pmv_ppd_iso from pythermalcomfort.utilities import v_relative tdb = 25 tr = 25 rh = 50 v = 0.1 met = 1.4 clo_dynamic = 0.5 # calculate relative air speed v_r = v_relative(v=v, met=met) results = pmv_ppd_iso( tdb=tdb, tr=tr, vr=v_r, rh=rh, met=met, clo=clo_dynamic, model="7730-2005", ) print(results.pmv) # 0.17 print(results.ppd) # 5.6 result = pmv_ppd_iso( tdb=[22, 25], tr=25, vr=0.1, rh=50, met=1.4, clo=0.5, model="7730-2005", ) print(result.pmv) # [-0. 0.41] print(result.ppd) # [5. 8.5] """ # Validate inputs using the PMVPPDInputs class PMVPPDInputs( tdb=tdb, tr=tr, vr=vr, rh=rh, met=met, clo=clo, wme=wme, units=units, limit_inputs=limit_inputs, ) tdb = np.asarray(tdb) tr = np.asarray(tr) rh = np.asarray(rh) vr = np.asarray(vr) met = np.asarray(met) clo = np.asarray(clo) wme = np.asarray(wme) if units.upper() == Units.IP.value: tdb, tr, vr = units_converter(tdb=tdb, tr=tr, v=vr) model = model.lower() if model not in [Models.iso_7730_2005.value]: raise ValueError( "PMV calculations can only be performed in compliance with ISO 7730-2005", ) pmv = _pmv_ppd_optimized(tdb, tr, vr, rh, met, clo, wme) ppd_array = 100.0 - 95.0 * np.exp( -0.03353 * pmv**4.0 - 0.2179 * pmv**2.0, ) # Checks that inputs are within the bounds accepted by the model if not return nan if limit_inputs: # ISO 7730-2005 page 3 applicability limits tdb_valid = valid_range(tdb, (10.0, 30.0)) tr_valid = valid_range(tr, (10.0, 40.0)) v_valid = valid_range(vr, (0.0, 1.0)) met_valid = valid_range(met, (0.8, 4.0)) clo_valid = valid_range(clo, (0.0, 2.0)) pmv_valid = valid_range(pmv, (-2, 2)) all_valid = ~( np.isnan(tdb_valid) | np.isnan(tr_valid) | np.isnan(v_valid) | np.isnan(met_valid) | np.isnan(clo_valid) | np.isnan(pmv_valid) ) pmv = np.where(all_valid, pmv, np.nan) ppd_array = np.where(all_valid, ppd_array, np.nan) if round_output: pmv = np.round(pmv, 2) ppd_array = np.round(ppd_array, 1) thermal_sensation = { -2.5: "Cold", -1.5: "Cool", -0.5: "Slightly Cool", 0.5: "Neutral", 1.5: "Slightly Warm", 2.5: "Warm", 10: "Hot", } return PMVPPD( pmv=pmv, ppd=ppd_array, tsv=mapping(pmv, thermal_sensation, right=False), )