### Install Dependencies

Source: https://federicotartarini.github.io/jsthermalcomfort/contributing.html

Installs project dependencies. Run this before starting development.

```bash
npm ci
```

--------------------------------

### Install project dependencies

Source: https://federicotartarini.github.io/jsthermalcomfort/contributing.html

Install all necessary dependencies for the jsthermalcomfort project before running tests or other development commands.

```bash
npm install
```

--------------------------------

### Install JSThermalComfort with npm

Source: https://federicotartarini.github.io/jsthermalcomfort/installation.html

Use this command to install the JSThermalComfort package locally in your project.

```bash
npm install jsthermalcomfort
```

--------------------------------

### Calculate Adaptive Thermal Comfort (IP Units)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

This example demonstrates calculating adaptive thermal comfort using the IP (Imperial Units) system. The function accepts temperature and air speed in IP units.

```javascript
import { adaptive_ashrae } from "jsthermalcomfort/models";
// For users who want to use the IP system
const results = adaptive_ashrae(77, 77, 68, 0.3, 'IP');
console.log(results);
// {tmp_cmf: 75.2, tmp_cmf_80_low: 68.9, tmp_cmf_80_up: 81.5,
//  tmp_cmf_90_low: 70.7, tmp_cmf_90_up: 79.7, acceptability_80: true,
//  acceptability_90: true}
```

--------------------------------

### JSDoc for New Thermal Comfort Model

Source: https://federicotartarini.github.io/jsthermalcomfort/contributing.html

Example of JSDoc comments required for a new thermal comfort model. Ensure to use @public, @memberof models, and provide clear @param and @returns descriptions.

```javascript
/**
 * @public
 * @memberof models
 * @name my_new_model
 * @description Calculates a new thermal comfort index.
 *
 * @param {number} tdb Dry bulb air temperature [°C]
 * @param {number} rh Relative humidity [%]
 * @returns {number} The calculated index value.
 */
export function my_new_model(tdb, rh) {
  // your implementation here
}
```

--------------------------------

### Import JSThermalComfort from CDN (ESM)

Source: https://federicotartarini.github.io/jsthermalcomfort/installation.html

Import the library directly from a CDN for use in projects without local installation. Ensure your environment supports ES Modules.

```javascript
import { models, utilities, pschymetrics } from "https://cdn.jsdelivr.net/npm/jsthermalcomfort/lib/esm/index.js"
```

--------------------------------

### Get Clo Value for Typical Ensemble

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/clo.html

Retrieves the standard Clo value for a specified typical clothing ensemble. Use this function to quickly get insulation values for common outfits.

```typescript
const result = clo_typical_ensembles("Trousers, long-sleeve shirt"); // returns 0.61
```

--------------------------------

### Instantiate JOS3 Model

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Create an instance of the JOS3 class. Optional body parameters like height, weight, age, and sex can be provided.

```python
from thermalcomfort.jos3 import JOS3

X = JOS3(height=1.7, weight=70, age=30, sex='male', bmr_equation='harris-benedict', bsa_equation='dubois')

```

--------------------------------

### Run Tests

Source: https://federicotartarini.github.io/jsthermalcomfort/contributing.html

Executes the project's test suite. Ensure all tests pass before submitting a Pull Request.

```bash
npm test
```

--------------------------------

### Calculate Adaptive Comfort (IP Units)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates adaptive thermal comfort using IP units. Ensure running mean temperature is within the model's applicability limits.

```javascript
// for users who wants to use the IP system
const results = adaptive_en(77, 77, 68, 0.3, 'IP');
console.log(results); // {tmp_cmf: 77.7, acceptability_cat_i: true, acceptability_cat_ii: true, ... }
```

--------------------------------

### Calculate Predicted Heat Strain (PHS)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates the Predicted Heat Strain (PHS) index using the jsthermalcomfort library. Ensure the 'jsthermalcomfort' library is imported before use. This example demonstrates a typical usage with standing posture.

```javascript
import { phs } from "jsthermalcomfort";
const results = phs(40, 40, 0.3, 33.85, 2.5, 0.5, "standing");
console.log(results); // {t_re: 37.5, d_lim_loss_50: 480, d_lim_loss_95: 480, d_lim_t_re: 480, sweat_loss_g: 5847.0, sweat_rate_watt: 252.1, ...}
```

--------------------------------

### Update project documentation

Source: https://federicotartarini.github.io/jsthermalcomfort/contributing.html

Generate or update project documentation, typically before committing documentation changes.

```bash
npm run docs
```

--------------------------------

### Format code with Prettier

Source: https://federicotartarini.github.io/jsthermalcomfort/contributing.html

Run Prettier to automatically format your code according to project standards.

```bash
npm run format
```

--------------------------------

### Import JSThermalComfort in Website (Module Script)

Source: https://federicotartarini.github.io/jsthermalcomfort/installation.html

Include the JSThermalComfort library in your website by importing it within a script tag marked as type="module".

```html
<script type="module">
  import { models, utilities, pschymetrics } from "https://cdn.jsdelivr.net/npm/jsthermalcomfort/lib/esm/index.js"
</script>
```

--------------------------------

### Stage all changes for commit

Source: https://federicotartarini.github.io/jsthermalcomfort/contributing.html

Stage all modified files in the current directory for the next commit.

```bash
git add .
```

--------------------------------

### Run project tests

Source: https://federicotartarini.github.io/jsthermalcomfort/contributing.html

Execute all project tests using Jest to ensure code quality and functionality.

```bash
npm run test
```

--------------------------------

### Push Changes and Tags

Source: https://federicotartarini.github.io/jsthermalcomfort/contributing.html

After bumping the version, push the commit and tags to the remote repository to trigger the release workflow.

```bash
git push && git push --tags
```

--------------------------------

### Clone the jsthermalcomfort repository

Source: https://federicotartarini.github.io/jsthermalcomfort/contributing.html

Clone your fork of the jsthermalcomfort repository locally to begin development.

```bash
git clone git@github.com:FedericoTartarini/jsthermalcomfort.git
```

--------------------------------

### Access Model Outputs

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Access simulation results such as local and mean skin temperature, core temperature, and skin wettedness using getter methods or the dict_results() method.

```python
results = X.dict_results()
t_skin_mean = X.t_skin_mean
t_skin_local = X.t_skin
t_core_local = X.t_core
```

--------------------------------

### Create a new local development branch

Source: https://federicotartarini.github.io/jsthermalcomfort/contributing.html

Create a new branch for your bug fix or feature development. Follow the specified naming conventions for new branches.

```bash
git checkout -b name-of-your-bugfix-or-feature
```

--------------------------------

### Convert Results to CSV

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Convert the model's simulation results into a CSV file using the to_csv method.

```python
X.to_csv('results.csv')
```

--------------------------------

### Set Part-Specific Environmental Conditions

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Demonstrates setting different environmental conditions for specific body parts. The input must be a 17-element list, dictionary, or numpy array corresponding to the defined body parts.

```python
X.tdb = [25.0] * 17 # Example for all body parts
X.tr = {'head': 23.0, 'chest': 22.0} # Example for specific parts
```

--------------------------------

### Calculate PMV with ATHB

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates the PMV value using the Adaptive Thermal Heat Balance (ATHB) framework. Ensure all required parameters are provided.

```javascript
const tdb = 25;
const tr = 25;
const vr = 0.1;
const rh = 50;
const met = 1.1;
const t_running_mean = 20;

const athb_result = athb(tdb, tr, rh, met, t_running_mean);
console.log(athb_result); // Output: {athb_pmv: 0.2}
```

--------------------------------

### Calculate Standard Effective Temperature (SET)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates the Standard Effective Temperature (SET) using provided environmental and personal parameters. Ensure all required parameters are passed in the correct order.

```javascript
const set = set_tmp(25, 25, 0.1, 50, 1.2, 0.5); // returns {set: 24.3}
```

--------------------------------

### Register New Model in Index

Source: https://federicotartarini.github.io/jsthermalcomfort/contributing.html

Import and export your new model function in `src/models/index.js` to make it available in the library.

```javascript
import { my_new_model } from "./my_new_model.js";

export default {
  // ... existing models
  my_new_model,
};
```

--------------------------------

### Set Environmental Conditions

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Set environmental conditions using setter methods. For uniform conditions, use simple variables. For part-specific conditions, provide a 17-element list, dictionary, or numpy array.

```python
X.tdb = 25.0  # Air temperature
X.tr = 23.0  # Mean radiant temperature
X.v = 0.1  # Air velocity
```

--------------------------------

### Push branch to GitHub

Source: https://federicotartarini.github.io/jsthermalcomfort/contributing.html

Push your local development branch to your GitHub fork to share your changes.

```bash
git push origin name-of-your-bugfix-or-feature
```

--------------------------------

### Calculate Adaptive Comfort (SI Units)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates adaptive thermal comfort using SI units. Ensure running mean temperature is within the model's applicability limits.

```javascript
const results = adaptive_en(25, 25, 20, 0.1);
console.log(results); // {tmp_cmf: 25.4, acceptability_cat_i: true, acceptability_cat_ii: true, ... }
console.log(results.acceptability_cat_i); // true
// The conditions you entered are considered to comply with Category I
```

--------------------------------

### Calculate Saturation Vapor Pressure (p_sat)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/psychrometrics.html

Calculates the vapor pressure of water at a given air temperature in Celsius. Returns pressure in Pascals.

```typescript
p_sat(tdb: number): number
```

--------------------------------

### Adaptive Comfort with Running Mean Temperature Out of Bounds

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Demonstrates the function's behavior when the running mean temperature is outside the standard applicability limits (10°C to 30°C). The function returns NaN for comfort temperature in such cases.

```javascript
const results = adaptive_en(25, 25, 9, 0.1);
console.log(results); // {tmp_cmf: NaN, acceptability_cat_i: true, acceptability_cat_ii: true, ... }
// The adaptive thermal comfort model can only be used
// if the running mean temperature is between 10 °C and 30 °C
```

--------------------------------

### Calculate PMV and PPD with ASHRAE 55

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Use this function to calculate PMV and PPD based on ASHRAE 55 standards. It applies a cooling effect before PMV computation, which can lower results compared to the ISO equation when elevated air speed is present. Ensure inputs are within the specified ASHRAE 55 ranges if `limit_inputs` is true.

```javascript
const r = pmv_ppd_ashrae(25, 25, 0.1, 50, 1.2, 0.5);
console.log(r.pmv); // 0.08
console.log(r.ppd); // 5.1
```

--------------------------------

### Calculate Saturation Vapor Pressure in Torr (p_sat_torr)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/psychrometrics.html

Estimates the saturation vapor pressure in torr based on the dry bulb air temperature in Celsius.

```typescript
p_sat_torr(tdb: number): number
```

--------------------------------

### AT_SCHEMA

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates the Apparent Temperature (AT), which adjusts the dry bulb temperature based on humidity and optionally solar radiation to represent perceived temperature.

```APIDOC
## AT_SCHEMA

### Description
Calculates the Apparent Temperature (AT). The AT is defined as the temperature at the reference humidity level producing the same amount of discomfort as that experienced under the current ambient temperature, humidity, and solar radiation. It includes the chilling effect of the wind at lower temperatures.

### Parameters
* `tdb` (number) - dry bulb air temperature, [°C]
* `rh` (number) - relative humidity, [%]
* `v` (number) - wind speed 10m above ground level, [m/s]
* `q` ((number | undefined)?) - Net radiation absorbed per unit area of body surface [W/m2]
* `kwargs` (object?) - other parameters
  * `kwargs.round` (boolean, default `true`) - if True rounds output value, if False it does not round it

### Returns
`AtResult` : set containing results for the model

### Example
```javascript
const result = at(25, 30, 0.1);
console.log(result); // {at: 24.1}
```
```

--------------------------------

### Bump Package Version

Source: https://federicotartarini.github.io/jsthermalcomfort/contributing.html

Use npm to increment the package version. Choose the appropriate command for patch, minor, major, or exact version bumps.

```bash
npm version patch
```

```bash
npm version minor
```

```bash
npm version major
```

```bash
npm version 1.2.3
```

--------------------------------

### Calculate Cooling Effect (IP Units)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates the Cooling Effect (CE) using IP units. The 'IP' string must be passed as the last argument to specify the unit system.

```javascript
const CE_IP = cooling_effect(77, 77, 1.64, 50, 1, 0.6, "IP");
console.log(CE_IP); // Output: {ce: 3.74}
```

--------------------------------

### clo_dynamic

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/utilities_functions.html

Estimates the dynamic clothing insulation, adjusting for activity and air speed based on specified standards.

```APIDOC
## clo_dynamic(clo: number, met: number, standard: ("ASHRAE" | "ISO"))

### Description
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** (number) - clothing insulation, [clo]
* **met** (number) - metabolic rate, [met]
* **standard** (("ASHRAE" | "ISO") = "ASHRAE") - If "ASHRAE", uses Equation provided in Section 5.2.2.2 of ASHRAE 55 2020

### Returns
`number` : dunamic clothing insulation, [clo]
```

--------------------------------

### Saturation Vapor Pressure (p_sat)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/psychrometrics.html

Calculates the vapor pressure of water at a given air temperature.

```APIDOC
## p_sat(tdb: number): number

### Description
Calculates vapour pressure of water at different temperatures.

### Parameters
#### Path Parameters
- **tdb** (number) - Required - air temperature, [°C]

### Returns
`number` : vapour pressure of water, [Pa]
```

--------------------------------

### pmv_ppd_iso

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates PMV and PPD according to ISO 7730. It delegates to the `pmv_ppd` function with a fixed standard of 'ISO'. The function includes input validation based on ISO 7730's stricter ranges when `limit_inputs` is true.

```APIDOC
## pmv_ppd_iso

### Description
Calculates Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD) in accordance with ISO 7730. This function uses Fanger's original PMV formulation and applies stricter input limits.

### Parameters

*   **tdb** (number) - Dry-bulb air temperature [°C or °F].
*   **tr** (number) - Mean radiant temperature [°C or °F].
*   **vr** (number) - Relative air speed [m/s or fps].
*   **rh** (number) - Relative humidity [%].
*   **met** (number) - Metabolic rate [met].
*   **clo** (number) - Clothing insulation [clo].
*   **wme** (number, optional, default `0`) - External work [met].
*   **kwargs** (Object, optional, default `{}`)
    *   **kwargs.units** (`"SI"` | `"IP"`, optional, default `'SI'`) - Unit system.
    *   **kwargs.limit_inputs** (boolean, optional, default `true`) - If true, returns NaN for out-of-range inputs.
    *   **kwargs.round_output** (boolean, optional, default `true`) - If true, rounds PMV to 2 decimal places and PPD to 1.

### Returns
`PmvPpdIso` - An object containing PMV and PPD values.

### Example
```javascript
const r = pmv_ppd_iso(25, 25, 0.1, 50, 1.2, 0.5);
console.log(r.pmv); // 0.08
console.log(r.ppd); // 5.1
```
```

--------------------------------

### Calculate Normal Effective Temperature (NET)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates the Normal Effective Temperature (NET) using dry bulb temperature, relative humidity, and wind speed. Rounds the output by default.

```javascript
const result = net(37, 100, 0.1);
console.log(result); // -> {net: 37}
```

--------------------------------

### Calculate Wet Bulb Temperature (t_wb)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/psychrometrics.html

Calculates the wet-bulb temperature in Celsius using the Stull equation. Requires dry bulb air temperature and relative humidity.

```typescript
t_wb(tdb: number, rh: number): number
```

--------------------------------

### Wet Bulb Temperature (t_wb)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/psychrometrics.html

Calculates the wet-bulb temperature using the Stull equation.

```APIDOC
## t_wb(tdb: number, rh: number): number

### Description
Calculates the wet-bulb temperature using the Stull equation [6].

### Parameters
#### Path Parameters
- **tdb** (number) - Required - air temperature, [°C]
- **rh** (number) - Required - relative humidity, [%]

### Returns
`number` : wet-bulb temperature, [°C]
```

--------------------------------

### Calculate UTCI with IP units

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates the Universal Thermal Climate Index (UTCI) using IP units. Ensure inputs are within standard applicability limits for accurate results.

```javascript
console.log(utci(77, 77, 3.28, 50, 'ip')) // will print 76.4
```

--------------------------------

### f_svv

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/utilities_functions.html

Calculates the sky-vault view fraction.

```APIDOC
## f_svv(w: number, h: number, d: number)

### Description
Calculates the sky-vault view fraction

### Parameters
* **w** (number) - width of the window, [m]
* **h** (number) - height of the window, [m]
* **d** (number) - distance between the occupant and the window, [m]

### Returns
`number` : sky-vault view faction ranges between 0 and 1
```

--------------------------------

### Update Model Display Name in Documentation

Source: https://federicotartarini.github.io/jsthermalcomfort/contributing.html

Add a mapping for your new model in `docs_theme/index.js` to set a human-readable title in the generated documentation.

```javascript
const displayNameMap = {
  // ... existing mappings
  my_new_model: "My New Premium Model (MNPM)",
};
```

--------------------------------

### Calculate Cooling Effect (SI Units)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates the Cooling Effect (CE) using SI units. Ensure all parameters are provided in their respective SI units.

```javascript
const CE = cooling_effect(25, 25, 0.3, 50, 1.2, 0.5);
console.log(CE); // Output: {ce: 1.64}
```

--------------------------------

### PMV_SCHEMA

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates the Predicted Mean Vote (PMV) based on various thermal comfort parameters and standards.

```APIDOC
## PMV_SCHEMA

### Description
Returns Predicted Mean Vote (PMV) calculated in accordance with main thermal comfort Standards. The PMV is an index that predicts the mean value of the thermal sensation votes of a large group of people on a sensation scale expressed from –3 to +3.

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Method
None (This is a function/schema definition)

### Endpoint
None (This is a function/schema definition)

### Parameters
- **tdb** (number) - dry bulb air temperature, default in [°C] in [°F] if `units` = 'IP'
- **tr** (number) - mean radiant temperature, default in [°C] in [°F] if `units` = 'IP'
- **vr** (number) - relative air speed, default in [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).
- **rh** (number) - relative humidity, [%]
- **met** (number) - metabolic rate. Note: 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. 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).
- **clo** (number) - clothing insulation
- **wme** (number, optional, default=0) - external work
- **standard** (string, optional, default="ISO") - comfort standard used for calculation. Can be either "ISO" or "ASHRAE".
- **kwargs** (PmvKwargs) - additional arguments

### Returns
`{pmv: number}` : result - Object containing the Predicted Mean Vote.

### Request Example
```javascript
const tdb = 25;
const tr = 25;
const rh = 50;
const v = 0.1;
const met = 1.4;
const clo = 0.5;

// calculate relative air speed
const v_r = v_relative(v, met);
// calculate dynamic clothing
const clo_d = clo_dynamic(clo, met);

const results = pmv(tdb, tr, v_r, rh, met, clo_d);
console.log(results); // 0.06
```

### Response Example
```json
{
  "pmv": 0.06
}
```
```

--------------------------------

### Calculate Adaptive Predicted Mean Vote (aPMV)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

This snippet demonstrates how to use the a_pmv function to calculate the Adaptive Predicted Mean Vote. Ensure all required parameters are provided with correct units.

```javascript
const tdb = 24,
const tr = 30,
const vr = 0.22,
const rh = 50,
const met = 1.4,
const clo = 0.5,
const a_coefficient = 0.293,
const wme = undefined,

const result = a_pmv(tdb, tr, vr, rh, met, clo, a_coefficient, wme);
console.log(result) //output { a_pmv: 0.48 }
```

--------------------------------

### Saturation Vapor Pressure in Torr

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/psychrometrics.html

Estimates the saturation vapor pressure in torr.

```APIDOC
## p_sat_torr(tdb: number): number

### Description
Estimates the saturation vapour pressure in [torr].

### Parameters
#### Path Parameters
- **tdb** (number) - Required - dry bulb air temperature [C]

### Returns
`number` : saturation vapour pressure [torr]
```

--------------------------------

### clo_typical_ensembles

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/clo.html

Calculates the total clothing insulation (Clo) for a given set of typical clothing ensembles.

```APIDOC
## clo_typical_ensembles

### Description
Calculates the total clothing insulation (Clo) for a given set of typical clothing ensembles.

### Method
N/A (Function call)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters
* `ensembles` ((`"Walking shorts, short-sleeve shirt"` | `"Typical summer indoor clothing"` | `"Knee-length skirt, short-sleeve shirt, sandals, underwear"` | `"Trousers, long-sleeve shirt"` | `"Knee-length skirt, long-sleeve shirt, full slip"` | `"Sweat pants, long-sleeve sweatshirt"` | `"Jacket, Trousers, long-sleeve shirt"` | `"Typical winter indoor clothing"`)) - Typical ensembles. One of:
    * "Walking shorts, short-sleeve shirt"
    * "Typical summer indoor clothing"
    * "Knee-length skirt, short-sleeve shirt, sandals, underwear"
    * "Trousers, short-sleeve shirt, socks, shoes, underwear"
    * "Trousers, long-sleeve shirt"
    * "Knee-length skirt, long-sleeve shirt, full slip"
    * "Sweat pants, long-sleeve sweatshirt"
    * "Jacket, Trousers, long-sleeve shirt"
    * "Typical winter indoor clothing"

### Returns
`number` : Clothing insulation of the given ensembles

### Example
```javascript
const result = clo_typical_ensembles("Trousers, long-sleeve shirt"); // returns 0.61
```
```

--------------------------------

### Adaptive Thermal Comfort with Low Running Mean Temperature

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

When the running mean outdoor temperature is below 10°C, the adaptive thermal comfort model returns NaN values, indicating the conditions are outside its applicability limits.

```javascript
import { adaptive_ashrae } from "jsthermalcomfort/models";
const results = adaptive_ashrae(25, 25, 9, 0.1);
console.log(results);
// {tmp_cmf: NaN, tmp_cmf_80_low: NaN, ...}
// The adaptive thermal comfort model can only be used
// if the running mean temperature is higher than 10°C
```

--------------------------------

### Calculate PMV and PPD using ISO 7730

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates PMV and PPD based on ISO 7730 standards. The function delegates to pmv_ppd with the standard fixed to 'ISO'. Input limits are enforced by default, returning NaN for out-of-range values.

```javascript
const r = pmv_ppd_iso(25, 25, 0.1, 50, 1.2, 0.5);
console.log(r.pmv); // 0.08
console.log(r.ppd); // 5.1
```

--------------------------------

### Calculate Predicted Mean Vote (PMV)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates the Predicted Mean Vote using thermal comfort parameters. Requires helper functions `v_relative` and `clo_dynamic` for accurate calculations, especially when dealing with air speed and clothing insulation adjustments based on metabolic rate.

```javascript
const tdb = 25;
const tr = 25;
const rh = 50;
const v = 0.1;
const met = 1.4;
const clo = 0.5;

// calculate relative air speed
const v_r = v_relative(v, met);
// calculate dynamic clothing
const clo_d = clo_dynamic(clo, met);

const results = pmv(tdb, tr, v_r, rh, met, clo_d);
console.log(results); // 0.06
```

--------------------------------

### PMV_PPD_SCHEMA

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD) according to ISO or ASHRAE comfort standards.

```APIDOC
## PMV_PPD_SCHEMA

### Description
Returns Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD) calculated in accordance with main thermal comfort Standards. The PMV is an index that predicts the mean value of the thermal sensation votes of a large group of people on a sensation scale expressed from –3 to +3.

### Parameters
* `tdb` (number) - dry bulb air temperature, default in [°C] in [°F] if `units` = 'IP'
* `tr` (number) - mean radiant temperature, default in [°C] in [°F] if `units` = 'IP'
* `vr` (number) - relative air speed, default in [m/s] in [fps] if `units` = 'IP'
* `rh` (number) - relative humidity, [%]
* `met` (number) - metabolic rate
* `clo` (number) - clothing insulation
* `wme` (number, default `0`) - external work
* `standard` ((`"ISO"` | `"ASHRAE"`), default `"ISO"`) - comfort standard used for calculation
* `kwargs` (Pmv_ppdKwargs) - additional arguments

### Returns
`Pmv_ppdReturns` : Result of pmv and ppd

### Example
```javascript
const tdb = 25;
const tr = 25;
const rh = 50;
const v = 0.1;
const met = 1.4;
const clo = 0.5;
// Calculate relative air speed
const v_r = v_relative(v, met);
// Calculate dynamic clothing
const clo_d = clo_dynamic(clo, met);
const results = pmv_ppd(tdb, tr, v_r, rh, met, clo_d);
console.log(results); // Output: { pmv: 0.06, ppd: 5.1 }
console.log(results.pmv); // Output: -0.06
```
```

--------------------------------

### A_PMV_SCHEMA

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates the Adaptive Predicted Mean Vote (aPMV) based on environmental and personal factors. This model accounts for cultural, climatic, social, psychological, and behavioral adaptations affecting thermal comfort.

```APIDOC
## A_PMV_SCHEMA

### Description
Returns Adaptive Predicted Mean Vote (aPMV) [25]. This index was developed by Yao, R. et al. (2009). The model takes into account factors such as culture, climate, social, psychological and behavioral adaptations, which have an impact on the senses used to detect thermal comfort. This model uses an adaptive coefficient (λ) representing the adaptive factors that affect the sense of thermal comfort.
This is a version that supports scalar arguments.

### Parameters
- **tdb** (number) - Dry bulb air temperature, default in [°C] in [°F] if `units` = 'IP'
- **tr** (number) - Mean radiant temperature, default in [°C] in [°F] if `units` = 'IP'
- **vr** (number) - Relative air speed, default in [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 v_relative in utilities.js.
- **rh** (number) - Relative humidity, [%]
- **met** (number) - Metabolic rate, [met]
- **clo** (number) - Clothing insulation, [clo]
  Note: 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) The dynamic clothing insulation, clo, can be calculated using the function clo_dynamic in utilities.js.
- **a_coefficient** (number) - Adaptive coefficient
- **wme** (number = 0) - External work
- **kwargs** (A_pmvKwargs) - additional arguments

### Returns
`APmvResult` : set containing results for the model

### Example
```javascript
const tdb = 24,
const tr = 30,
const vr = 0.22,
const rh = 50,
const met = 1.4,
const clo = 0.5,
const a_coefficient = 0.293,
const wme = undefined,

const result = a_pmv(tdb, tr, vr, rh, met, clo, a_coefficient, wme);
console.log(result) //output { a_pmv: 0.48 }
```
```

--------------------------------

### Calculate Apparent Temperature (AT)

Source: https://federicotartarini.github.io/jsthermalcomfort/documentation/models.html

Calculates the Apparent Temperature (AT), which adjusts dry bulb temperature based on relative humidity and solar radiation. Use this for a more accurate perception of ambient temperature.

```javascript
const result = at(25, 30, 0.1);
console.log(result); // {at: 24.1}
```