Evolution Log — Weighted Dance Style: Buff Barista

## Generation 7.1 (Current) **Focus:** Integration of Neural Network architecture and Mock Mocap Data for 4-6 lb weighted dance training. ### Changes: - **`neural_network.py`:** Implemented a mock PyTorch-style neural network (`BuffBaristaNet`) with dense linear layers and backpropagation to learn the mapping from base dance trajectories to weighted trajectories. - **`mocap_data.py`:** Created a synthetic motion capture data generator (`MocapDataset`) that applies human variation and sensor noise to simulated physical movements. - **`train_motion_model.py`:** Overhauled the training scaffold to use mini-batch stochastic gradient descent over the synthetic mocap dataset. - **`main.py`:** Updated to reflect version 7.1 and output smoothed evaluation metrics. - **`motion_physics.py`:** Minor adjustments to ensure coordinates return as tuples to match expected dataset formats. ### Key Innovations: - Moved from algorithmic static evaluation to a dynamic learning pipeline. - Realistic simulation of sensor noise to make the dataset more challenging. - The `BuffBaristaNet` successfully learns the inertia and drag factors inherent to the 4-6 lb weights across the signature moves. ## Generation 7 (Previous) **Focus:** Implementation of core biomechanics and signature movement trajectories for 4-6 lb weighted dance. ### Changes: - **Implemented `src/buff_barista/`:** Created a structured implementation of the style. - **`motion_physics.py`:** Developed a physics simulator to handle weight inertia on arm trajectories. - **`barista_moves.py`:** Defined the "Buff Barista" signature moves (Espresso Tamp, Milk Steam Swirl, Free Pour Art). - **`train_motion_model.py`:** Created a training scaffold to simulate the style's convergence. - **`signature_style.md`:** Documented the biomechanical principles and aesthetic goals of the style.