def info_all():
spec_data = Bayesian.fisher_decomposition(
fisher_matrix, 'All', opt_model.models, 'isen')
fig = plt.figure(figsize=tall)
fig = opt_model.plot_fisher_data(spec_data, fig=fig)
fig.set_size_inches(tall)
fig.tight_layout()
return fig
def info_sphere():
''' Fisher information about the sphere
'''
spec_data = Bayesian.fisher_decomposition(
fisher_matrix, 'Sphere', opt_model.models, 'eos')
fig = plt.figure(figsize=tall)
fig = opt_model.plot_fisher_data(spec_data, fig=fig)
fig.tight_layout()
return fig
def info_gun():
''' Fisher information about the gun experiment
'''
spec_data = Bayesian.fisher_decomposition(
fisher_matrix, 'Gun', opt_model.models, 'eos')
fig = plt.figure(figsize=tall)
fig = opt_model.plot_fisher_data(spec_data, fig=fig)
fig.set_size_inches(tall)
fig.tight_layout()
return fig
def test_fisher_matrix(self):
"""Tests if the fisher information matrix can be generated correctly
"""
bayes = Bayesian(simulations=[(self.sim1, self.exp1),
(self.sim2, self.exp2)],
model=self.eos_model)
fisher = bayes.get_fisher_matrix(simid=1)
n_model = bayes.shape()[1]
self.assertIsInstance(fisher, np.ndarray)
self.assertEqual(fisher.shape, (n_model, n_model))
data = bayes.fisher_decomposition(fisher)
bayes.plot_fisher_data(data)
plt.show()
fig1.savefig(out_dir+'scipy2016_figure1'+figtype, dpi=1000)
# Figure 1
fig1 = plt.figure(figsize=square)
f1ax1 = fig1.gca()
eos_model.prior.plot(axis=f1ax1, style='--b')
eos_true.plot(axis=f1ax1, style='-.g')
f1ax1.legend(['Prior EOS',
'True EOS'])
fig1.tight_layout()
fig1.savefig(out_dir+'scipy2016_figure1eos'+figtype, dpi=1000)
# Figure 5
fisher = analysis.get_fisher_matrix(simid=0, sens_calc=True)
spec_data = analysis.fisher_decomposition(fisher)
fig5 = analysis.plot_fisher_data(spec_data)
fig5.set_size_inches(tall)
fig5.tight_layout()
fig5.savefig(out_dir+'scipy2016_figure5'+figtype, dpi=1000)
# Figure 2
fisher = analysis.get_fisher_matrix(simid=1, sens_calc=True)
spec_data = analysis.fisher_decomposition(fisher)
fig2 = analysis.plot_fisher_data(spec_data)
fig2.axes[1].axvline(s_data_s[1])
fig2.axes[1].annotate(r'$v_{CJ}$',
xy=(s_data_s[1],0),