dyngpt.inferrer.inferring_dynamics

dyngpt.inferrer.inferring_dynamics(observed_data, config_infer, gene_names=[], true_params=[], synthetic_flag=0, new_model=False, synthetic_data=[])

Infer the underlying dynamic parameters of a state transition network from observed data.

Args:

observed_data (numpy.ndarray): The observed dataset containing state counts. config_infer (Namespace): Configuration object containing inference parameters. gene_names (list, optional): List of gene names corresponding to the observed data. Defaults to []. true_params (list, optional): List of true parameter values for validation. Defaults to []. synthetic_flag (int, optional): Flag indicating whether synthetic data is used (1) or not (0). Defaults to 0. new_model (bool, optional): Whether to initialize a new model or use a pre-trained model. Defaults to False. synthetic_data (list, optional): Synthetic dataset for model validation, if applicable. Defaults to [].

Returns:

dict: Contains the inferred parameters, loss values, KL divergence values, and other evaluation metrics.