imageless-annual-glare
Run an annual glare study for a Honeybee model to compute hourly Daylight Glare Probability (DGP) for each sensor in a model's sensor grids.
This recipe uses the image-less glare method developed by Nathaniel Jones to estimate glare at each sensor. More information on this method can be found here.
The resulting DGP is used to compute Glare Autonomy (GA), which is the percentage of occupied time that a view is free of glare.
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Release files for pollination-imageless-annual-glare 0.1.8
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Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pollination_imageless_annual_glare-0.1.8.tar.gz | 147.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pollination_imageless_annual_glare-0.1.8-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 158.5 kB
Release files / pollination_imageless_annual_glare-0.1.8.tar.gz
| Download URL | pollination_imageless_annual_glare-0.1.8.tar.gz |
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| Size | 147.0 kB |
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Release files / pollination_imageless_annual_glare-0.1.8-py2.py3-none-any.whl
| Download URL | pollination_imageless_annual_glare-0.1.8-py2.py3-none-any.whl |
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| Size | 11.5 kB |
| Tags | Python 2 Python 3 |
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