heatindex 0.0.1

Tools for Calculating Heat Stress

Heatindex

Tools for Calculating Heat Stress

This package currently provides a single function, heatindex, which is an implementation of the simpler and faster heat index introduced by Lu et al. (2025). This simpler and faster implementation matches the values of the heat index from Steadman (1979) and Lu and Romps (2022) for air temperatures above 300 K (27 C, 80 F) and with only minor differences at lower temperatures.

Installation

The recommended way to install heatindex is by using pip, the Python package installer.

Recommended

Open your terminal or command prompt and run the following command:

pip install heatindex

This will download and install the latest stable version of heatindex from the Python Package Index (PyPI).

Manual

Alternatively, clone the repository and install it locally:

git clone https://github.com/romps/heatindex
cd heatindex/python
./prepare_package.sh
pip install .

The source code for this package is located in heatindex/cpp. Running prepare_package.sh creates hard links in heatindex/python/src to the source files.

Usage and examples

The heatindex function takes two arguments: air temperature (Ta) in Kelvin and relative humidity (RH) on a scale from 0 to 1, and returns the heat index in Kelvin. Note that the relative humidity is defined with respect to saturation over liquid water for air temperatures over 273.16 K and with respect to saturation over ice for air temperatures lower than 273.16 K.

For example:

>>> import heatindex as hi
>>> hi.heatindex(310,0.5)
318.62255317071686

Note: The precision of the underlying root solver is set to 1e-8, so the output is reliable up to the seventh decimal place.

The heatindex function is vectorized using NumPy, enabling efficient element-wise computations. For example, when Ta and RH are lists of three elements, the result is a Numpy array of length 3:

>>> Ta = [310,311,312]
>>> RH = [0,0.5,1]
>>> hi.heatindex(Ta,RH)
array([305.55495303, 324.54442932, 368.60533913])

If one argument is an array and the other a scalar, NumPy broadcasting applies:

>>> Ta = [310,311,312]
>>> RH = 1
>>> hi.heatindex(Ta,RH)
array([359.90632483, 364.20412564, 368.60533913])

When both Ta and RH are arrays (or matrices), they must have identical shapes:

>>> Ta = [[310,311],[312,313]]
>>> RH = [[0,1],[0,1]]
>>> hi.heatindex(Ta,RH)
array([[305.55495303, 364.20412564],
       [307.05336139, 373.11024873]])

Authors

• Yi-Chuan Lu - Creator - [e-mail] - ORCID: 0000-0003-3659-1474
• David M. Romps - Creator, Maintainer - [e-mail] - ORCID: 0000-0001-7649-5175

Citation

To cite package heatindex in publications use:

Lu, Y.-C. and Romps, D.M., 2025. heatindex: Tools for Calculating Heat Stress. https://heatindex.org.

A BibTeX entry for LaTeX users is

 @Manual{heatindex2025,
  title = {heatindex: Tools for Calculating Heat Stress},
  author = {Yi-Chuan Lu and David M. Romps},
  year = {2025},
  note = {Python package version 0.0.1},
  url = {https://heatindex.org},
 }

References

1. Lu et al., "Simpler and faster: an improved heat index," in review (2025).
2. Steadman, R.G., 1979. The assessment of sultriness. Part I: A temperature-humidity index based on human physiology and clothing science. Journal of Applied Meteorology and Climatology, 18(7), pp.861-873.
3. Lu, Y.-C. and Romps, D.M., 2022. Extending the heat index. Journal of Applied Meteorology and Climatology, 61(10), pp.1367-1383.