Could it be possible to update more Thermal Comfort Indices in the new version of Ladybug Tools?

Dear @chris @djordje and Ladybug team, I’d like to ask you if it’s possible to re-add in the new ladybug version component “Thermal Indices” the following indices previously available in the component “Thermal Comfort Indices”:

ASV (actual sensation vote)

ATshade (apparent temperature shade)

CWC (Canada’s Wind Chill Index)

DI (Thom Discomfort Index)


NET (Net Effective Temperature)

Out_SET* (Outdoor Standard Effective Temperature)

PHS (Predicted Heat Strain)

THI (Temperature Humidity Index)

TS (Thermal Sensation Index)

Even if some of these indices are not very used, in my paper Redirecting I described them as being part of Ladybug Tools, so it would be nice to restore them if someone is interested in using them.

Moreover, is the actual PET the classic one or the update of 2018 described in Redirecting ? If it’s the case, I strongly recommend adding the “PET classic” index to the Thermal Indices component, to allow model comparison.

Finally, it could be really amazing if other promising thermal comfort indices such as GOCI (Redirecting), STI (, PT** (The perceived temperature – a versatile index for the assessment of the human thermal environment. Part A: scientific basics | SpringerLink) and mPET ( ; The potential of a modified physiologically equivalent temperature (mPET) based on local thermal comfort perception in hot and humid regions | SpringerLink ) could be added as stand-alone components.

Cit. “It is therefore extremely important that software developers add in their tools as many promising indices/models as possible, to encourage researchers in using them and, therefore, to contribute to the production of new comparative studies to implement data on their suitability for application in human biometeorological studies

Many thanks for considering this proposition!
Best regards,

Hi @MatteoFBC ,

Your description of these indices as part of Ladybug Tools is still correct. It’s just that, because many of these indices are not really used in contemporary practice (as you said) and they have more value to researchers, we have kept them on the Software Development Kit (SDK) layer of the software rather than having Grasshopper component for them. But you can see most of the indices that you listed in our SDK docs here:

And you can see the source code for the models here on the GitHub:

Granted, there are are still 3 models that we have to add from the Legacy plugin and we have some open issues for them here:

But having all of these models on the SDK layer means that someone could easily create their own component for any of these models with a couple of lines of Python inside a GHPython component. It also obviously means that anyone using that ladybug-comfort Python package in another development environment can use the models.

The fact that we removed the need to expose everything on Grasshopper components also means that we can easily add those other comfort models that you mentioned on the SDK layer without overwhelming people who are just getting into thermal comfort modeling and just need to know the 4 most common ones models to use in practice. So, if you open issues on the ladybug-comfort GitHub for each of those models, we can add them eventually. Or better yet, if you send a PR to that repository with code for these models, I would be happy to review it and merge it into the code base.

Lastly to answer this:

I am pretty sure that it’s the updated one and you can see a discussion about the source code that we worked from here. I know the implementation of PET in Legacy had some bugs in it related to the reference environment and the way in which the human subject’s metabolic rate in met was translated into Watts above basal metabolism. So we can add PET classic but we should make sure that the implementation has these issues fixed.

Hi and thanks for your answer!

I created an issue for each promising model that is not included in the SDK yet.

I’m not very proficient in coding but for mPET it seems that a Python script already exists:

If I will find something more useful than the actual paper for the ones that proposes complex equations, I will update the links on github