def main(): x2_history = BooleanTimeSeries([0], [True], 0.5) x2_history.label = 'x2' x2_history.style = '-r' x1_input = BooleanTimeSeries([0, 0.5, 1, 1.5, 2, 2.5, 3], [False], 3) x1_input.label = 'x1' x1_input.style = '-b' delay_parameters = [0.3] end_time = 3 my_bde_solver = \ BDESolver(my_forcing_input_model, delay_parameters, [x2_history], [x1_input]) my_bde_solver.solve(end_time) my_bde_solver.show_result()
def main(): x1_history = BooleanTimeSeries([0, 1.5], [True, False], 2) x2_history = BooleanTimeSeries([0, 1], [True, False], 2) x1_history.label = "x1" x1_history.style = "-r" x2_history.label = "x2" x2_history.style = "-b" delay_parameters = [1, 0.5] end_time = 6 my_bde_solver = BDESolver(my_two_variable_model, delay_parameters, [x1_history, x2_history]) my_bde_solver.solve(end_time) my_bde_solver.show_result() my_bde_solver.print_result()
# Plot the history BooleanTimeSeries.plot_many([hist_m, hist_ft]) plt.xlabel("Time (hours)") plt.legend() plt.show() # The model uses a forcing input for light light_t = [0] + list(range(6, 120, 12)) light_y = [] for t in light_t: light_y.append(6 <= t % 24 < 18) light_bts = BooleanTimeSeries(light_t, light_y, 118) light_bts.label = "light" light_bts.style = "-g" # Plot light light_bts.plot() plt.show() # Plot light and the histories BooleanTimeSeries.plot_many([hist_m, hist_ft, light_bts]) plt.show() # Define the model equations def neurospora_eqns(z, forced_inputs): m = 0 ft = 1