Presented are results of two numerical experiments: the whole chloroplast genome chaos game representation of Cannabis sativa and the comparison of two state-of-the-art neural network architectures applied to the neural style transfer problem. A brief explanation of the chaos game representation is given followed by results illustrating that the whole chloroplast genome has global structure. An explication of neural style transfer and the ResNet and FractalNet neural network architectures is then given followed by results when both networks are trained to learn the underlying feature representation of an image of Cannabis sativa. Finally, the artistic motivation of these numerical experiments is presented in the context of the genotype-phenotype distinction.