def get_sim(sim_name):
"""
Returns the simulator object for a given simulator name.
"""
if sim_name == 'lv':
return misc.get_simulator('lotka_volterra')
elif sim_name == 'hh':
return misc.get_simulator('hodgkin_huxley')
else:
return misc.get_simulator(sim_name)
def plot_results(sim_name):
"""
Plots all results for a given simulator and kind of error.
"""
global sim
sim = misc.get_simulator(translate_sim_name(sim_name))
# gaussian
err_gauss = get_err_gaussian(sim_name)
err_gauss = max(err_gauss, 0.0)
# NDE
all_err_nde = []
all_n_sims_nde = []
for exp_desc in ed.parse(
util.io.load_txt('exps/{0}_nl.txt'.format(sim_name))):
all_err_nde.append(get_err_nde(exp_desc))
all_n_sims_nde.append(exp_desc.inf.n_samples)
all_err_snl = None
all_n_sims_snl = None
for exp_desc in ed.parse(
util.io.load_txt('exps/{0}_seq.txt'.format(sim_name))):
# SNL
if isinstance(exp_desc.inf, ed.SNL_Descriptor):
all_err_snl = get_err_snl(exp_desc)
all_n_sims_snl = [(i + 1) * exp_desc.inf.n_samples
for i in xrange(exp_desc.inf.n_rounds)]
matplotlib.rc('text', usetex=True)
matplotlib.rc('font', size=16)
all_n_sims = np.concatenate([all_n_sims_nde, all_n_sims_snl])
min_n_sims = np.min(all_n_sims)
max_n_sims = np.max(all_n_sims)
fig, ax = plt.subplots(1, 1)
ax.semilogx(all_n_sims_nde,
np.sqrt(all_err_nde),
's:',
color='b',
label='NL')
ax.semilogx(all_n_sims_snl,
np.sqrt(all_err_snl),
'o:',
color='r',
label='SNL')
ax.axhline(np.sqrt(err_gauss), linestyle='--', color='k', label='Gaussian')
ax.set_xlabel('Number of simulations (log scale)')
ax.set_ylabel('MMD')
ax.set_xlim([min_n_sims * 10**(-0.2), max_n_sims * 10**0.2])
ax.set_ylim([-0.1 if sim_name == 'gauss' else 0.0, ax.get_ylim()[1]])
ax.legend(fontsize=14,
loc='upper right' if sim_name == 'gauss' else 'lower right')
plt.show()
def __init__(self, exp_desc):
"""
:param exp_desc: an experiment descriptor object
"""
assert isinstance(exp_desc, ed.ExperimentDescriptor)
self.exp_desc = exp_desc
self.exp_dir = os.path.join(misc.get_root(), 'experiments', exp_desc.get_dir())
self.sim = misc.get_simulator(exp_desc.sim)
