def test_inverse_model_v1(model_minimal_pkl):
nemf.inverse_model(model_minimal_pkl)
def test_inverse_model_v2(model_npzd_osci_pkl):
nemf.inverse_model(model_npzd_osci_pkl)
def test_inverse_model_v5(model_npzd_stable_refed_pkl):
nemf.inverse_model(model_npzd_stable_refed_pkl)
def test_inverse_model_v4(model_npzd_osci_refed_pkl):
nemf.inverse_model(model_npzd_osci_refed_pkl)
def test_inverse_model_v3(model_npzd_stable_pkl):
nemf.inverse_model(model_npzd_stable_pkl)
def inverse_pickler(path,name,method): model = load_model(path) model = nemf.inverse_model(model,method=method) write_pickle(model,name)
# NPZD Example # import the module import nemf # provide the path of model/system configuration model_path = 'example_files/NPZD/NPZD_model.yml' ref_data_path = 'example_files/NPZD/NPZD_ref_oscillating.csv' # load the model configuration model_config = nemf.model_class(model_path, ref_data_path) # visualise the model configuration to check for errors nemf.interaction_graph(model_config) # for a simple time evolution of the model call: output_dict = nemf.forward_model(model_config) # the results of the time evolution can be visualized with: nemf.output_summary(output_dict) # if the model shall be fitted as well call: model = nemf.inverse_model(model_config) # to plot the results: nemf.output_summary(model) # writes optimized model to file model.export_to_yaml(path='optimized_model.yml')