twinfer.simulation.gillespie_simulations.run_simulation

twinfer.simulation.gillespie_simulations.run_simulation(update_propensities, update_matrix, pop0, time_points, n_cells=1000, promoter_indices=None, pop0_mat=None)[source]

Simulates the dynamics of a population of cells using the Gillespie algorithm.

Parameters:

update_propensities (callable): A function to compute the propensities for reactions. update_matrix (numpy.ndarray): The stoichiometry matrix defining the system’s reactions. pop0 (numpy.ndarray): Initial population vector for all species (shape: [n_species]). time_points (numpy.ndarray): Array of time points at which to sample the population. n_cells (int, optional): Number of cells to simulate. Defaults to 1000.

Returns:
numpy.ndarray: A 3D array containing the simulated population data.

Shape: [n_species, len(time_points), n_cells].

Notes:

  • The function uses a JIT-compiled helper function gillespie_simulation_all_cells for efficient simulation.

  • Warnings are printed for cells that encounter issues during simulation:

    • Cell stuck due to zero propensities for too long.