CloudLabs Transform Matrices vs SPICENet Visualization

This situation provides a Cartesian plane where you can draw polygons with up to five sides, which will be represented by matrices. You will be able to configure a transformation matrix in order to operate the matrix that represents the polygon, and then observe the transformation applied to the original polygon.

SpiceNet is an educational and research-oriented simulation app for exploring SPICEnet, a self-organizing neural model for learning relationships between sensory inputs. Run simulations from generated data or import your own CSV file, adjust network and data parameters, and inspect the results through scatter plots, line charts, histograms, tuning curves, and heatmaps. The app also includes a theory section explaining the SPICEnet model and a benchmark tool for comparing standard Swift computation with Apple’s Accelerate framework. Features: - Run SPICEnet simulations from random data - Import CSV files and select columns for analysis - Adjust neurons, learning rate, initialization range, data count, transformation type, and chunk size - Visualize simulation output with multiple chart types - View explanatory SPICEnet theory content - Run local performance benchmarks - Export benchmark results as a PDF All simulations and file processing run locally on the device. Academic context: SpiceNet was developed by Omar Ashour as part of a bachelor thesis under the supervision of Prof. Dr.-Ing. Cristian Axenie at Technische Hochschule Nürnberg Georg Simon Ohm.