Replication Data for: A Deep-Learning Based Incidence Operator for Adjustable and Solver-Agnostic Modelling of Adaptive Façades

This dataset contains the files: <br>
- code: All Python files to replicate result data, figure and table generation. <br>
- data/raw: The training data including all investigated feature sets as well as the target. The training data for the incidence operator (y) were generated using the Grasshopper file and the plugins presented in the study (<a href="https://doi.org/10.18419/opus-17170">https://doi.org/10.18419/opus-17170</a>). For the feature matrix X1, a uniform grid of 11 tint states between [0% and 100%] was generated. The 10,000 zenith and azimuth angles per discrete tint state are determined using the Fibonacci distribution. The feature sets X2,X3,X4 are derived from X1 as described in the paper. Additionally, this folder contains the Grasshopper file with all information about the investigated parametric design. <br>
- data/results: The Optuna study results for all feature sets.<br>
- figures: The result figures within the paper.<br>