def __str__(self): # # Plot marginals # for item in self.p.params: # plot.marginal_plot(item, path=self.working_path) # # # Plot joints # for item in self.p.margin_ax: # plot.plot_joint(self, self.p.params[item[0]], self.p.params[item[1]]) # fullplot print(("Reconstructed likelihood shape before plot: ", self.likelihood.shape)) plot.fullplot(self) return "Plot Done!\n" \ "(fitted_sigma, fit_err, relative_deviation, acc, sharper, broader)\n" + str(self.analyse_result())\ + "\n KLD: " + str(self.KL)
inference.run_sim(multi_comp, noise_sigma) inference.run_evaluation() # Do statistics for the current inference Ra_stat[i, 0], Ra_stat[i, 1], Ra_stat[i, 2], Ra_stat[ i, 3], Ra_stat[4], Ra_stat[5] = stat(Ra) gpas_stat[i, 0], gpas_stat[i, 1], gpas_stat[i, 2], gpas_stat[ i, 3], gpas_stat[4], gpas_stat[5] = stat(gpas) cm_stat[i, 0], cm_stat[i, 1], cm_stat[i, 2], cm_stat[ i, 3], cm_stat[4], cm_stat[5] = stat(cm) # Plot some single joint distribution if i == num_of_iter - 1: print(inference) fullplot(inference) plot_joint(inference, Ra, gpas) plot_joint(inference, Ra, cm) plot_joint(inference, cm, gpas) print("\n\n") runningTime = (time.time() - startTime) / 60 lasted = "The Ra-gpas-cm ball-and-stick simulation was running for %f minutes\n" % runningTime configuration = "--\n" setup1 = 'Multi compartment simulation; White noise sigma=7; ramp stimulus; Ra parameter; dt=0.1\n' setup2 = 'Multi compartment simulation; White noise sigma=7; ramp stimulus; gpas parameter; dt=0.1\n' setup3 = 'Multi compartment simulation; White noise sigma=7; ramp stimulus; cm parameter; dt=0.1\n' header1 = "Number of simulations: " + str( num_of_iter) + '\n' + setup1 + configuration + lasted header2 = "Number of simulations: " + str(
if __name__ == "__main__": # load_statistics(50, ["Ra", "cm", "gpas"], "/Users/Dani/TDK/parameter_estim/stim_protocol2/ramp/loglikelihood", # "/Users/Dani/TDK/parameter_estim/stim_protocol2/ramp") cm = np.loadtxt( "/Users/Dani/TDK/parameter_estim/stim_protocol2/zap/100/loglikelihood/cm(0).txt", dtype=str) gpas = np.loadtxt( "/Users/Dani/TDK/parameter_estim/stim_protocol2/zap/100/loglikelihood/gpas(0).txt", dtype=str) Ra = np.loadtxt( "/Users/Dani/TDK/parameter_estim/stim_protocol2/zap/100/loglikelihood/Ra(0).txt", dtype=str) ll = np.loadtxt( "/Users/Dani/TDK/parameter_estim/stim_protocol2/zap/100/loglikelihood/loglikelihood(0).txt" ) inf = load_inference( ll, "/Users/Dani/TDK/parameter_estim/stim_protocol2/zap/100", Ra, cm, gpas) inf.run_evaluation() print(inf) from module.plot import fullplot, plot_joint plot_joint(inf, inf.p.params[0], inf.p.params[1]) plot_joint(inf, inf.p.params[0], inf.p.params[2]) plot_joint(inf, inf.p.params[1], inf.p.params[2]) fullplot(inf)