C002 -- Speeding up Annual Daylighting Simulation Using NumPy

Multi-phase simulation methods have dramatically sped up the calculation of climate-based daylighting metrics(CBDMs). This advance enables modern green building standards like LEED, WELL, and EN 17037 to require annual daylighting calculations at a fine resolution across a building’s floorplate. However, as parallel ray tracing increases in speed, the matrix multiplication step in multi-phase methods has emerged as a bottleneck to delivering fast simulation results.

This paper describes a new calculation method for annual daylighting simulation based on vectorization. Vectorization allows a computer to perform simple operations on large amounts of data simultaneously. We use the NumPy library in Python to vectorize multiple steps in the calculation of spatial daylight autonomy (sDA) and annual renderings for glare as example CBDMs. We also show that NumPy can manipulate large high dynamic range (HDR) images.