protocol = 1 solve_start, solve_end, solve_timestep, stimulus_magnitude, stimulus_duration, stimulus_period, stimulus_start_time = ms.get_protocol_details( protocol) solve_timestep = 0.1 num_solves = 5 params_file = "gary_decker_params.txt" traces_file = "gary_decker_traces.txt" seed = 2 npr.seed(seed) model_number = 8 # Decker dog original_gs, g_parameters = ms.get_original_params(model_number) original_gs = np.array(original_gs) print original_gs, "\n" lower_bounds = 0.5 * original_gs upper_bounds = 2.0 * original_gs times = np.arange(solve_start, solve_end + solve_timestep, solve_timestep) ap = ap_simulator.APSimulator() ap.DefineStimulus(stimulus_magnitude, stimulus_duration, stimulus_period, stimulus_start_time) ap.DefineSolveTimes(solve_start, solve_end, solve_timestep) ap.DefineModel(model_number) ap.SetNumberOfSolves(num_solves)
expt_dir = "/home/rossj/Documents/roche_data/2017-01_data/170123_2_2" traces_dir = expt_dir + '/traces' output_dir = expt_dir + '/output' trace_number = 65 AP = np.loadtxt(traces_dir + '/{}.csv'.format(trace_number), delimiter=',') expt_times = AP[:, 0] expt_trace = AP[:, 1] fig = plt.figure() ax = fig.add_subplot(111) ax.grid() ax.plot(expt_times, expt_trace, color='red') model = 7 original_gs, g_parameters = ms.get_original_params(model) # list, list #original_gs[0] *= 4 solve_start = expt_times[0] solve_end = expt_times[-1] solve_timestep = expt_times[1] - expt_times[0] data_clamp_on = 50 data_clamp_off = 52 num_solves = 100 stimulus_magnitude, stimulus_duration, stimulus_period, stimulus_start_time = 0, 1, 1000, 0 # need to make sure these are always same as in C++ protocol # might have to change it to have protocols hard-coded into Python instead of C++