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)