12 ML

Download an ONNX wind-prediction model from HuggingFace for the Wind Predictor component. Yel 2.0 is public; Esen 1.0 and Poyraz 1.0 need a HuggingFace token. All are 8-channel Wind Predictor models. (Yel 1.0 is a different architecture — the GAN image model used by GAN Predict via its API — and cannot be loaded here.) Models cache in ~/Eddy3D/Models/ and are reused on subsequent runs (a model already downloaded to the old ~/SUS_LAB/ folder is moved over, not re-fetched).

Predict a pedestrian wind-speed field from buildings using the Eddy3D GAN (no CFD run). Sends the geometry to the GAN API and returns wind speeds + a colored result mesh.

Run ONNX wind-field prediction end-to-end. Computes SDF, building height, Zrelative, U/Uref, direction features from geometry, assembles the 8-channel input tensor, runs ONNX inference, and outputs predicted wind speeds. Supports legacy 1ch (U), 2ch (U + k) and new 4ch (U + k + Uroof + kroof) models.

Calculate Pedestrian Wind Comfort using predicted wind fields from the ONNX model.

Compute and export wind dataset features from analysis points and building geometry.

Read processed CSV datasets back into Grasshopper. Supports mag_U and all spatial features.

Resample direction-specific wind-magnitude fields onto a new point grid (nearest-neighbour average, with direction-specific rotation). Prepares grids for GAN applications.

Export the solved MRT field as a machine-learning dataset: one row per sensor per hour with spatial features, hourly climate drivers and the MRT/UTCI targets.