Adding DMD capabilities #23
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dreamer2368
requested changes
Jul 1, 2025
| fd = None | ||
| fd_oper = None | ||
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| def __init__(self, dim, high_order_terms, rand_functions, nt, config): |
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Based on the usage shown below, high_order_terms and rand_functions can be parsed from config and need not be passed as input arguments. Can we parse them from config and reduce the number of input arguments?
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They could be. But updating the workflow maintains the original structure of defining trainers/latent space/latent physics. Can update it your way through if necessary!
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| # Updating the dynamics callback to account for the higher order terms and other non linear functions from the .yml file. | ||
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| latent_dynamics = ld_dict[ld_type](latent_space.n_z, config['latent_dynamics'][ld_type]['higher_order_terms'], config['latent_dynamics'][ld_type]['extra_functions'], physics.nt, config['latent_dynamics']) |
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As I mentioned above, high_order_terms and rand_functions can be parsed from config and need not be passed as input arguments. That way we wouldn't have to change this line.
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Adding EDMD implementation to the latent space dynamics. Updated codebase allows user to choose standard/extended DMD through the .yml file.